Publications

The term photonic wire laser is now widely used for lasers with transverse dimensions much smaller than the wavelength. As a result, a large fraction of the mode propagates outside the solid core. Here, we propose and demonstrate a scheme to form a coupled cavity by taking advantage of this unique feature of photonic wire lasers. In this scheme, we used quantum cascade lasers with antenna-coupled third-order distributed feedback grating as the platform. Inspired by the chemistry of hybridization, our scheme phase-locks multiple such lasers by π coupling. With the coupled-cavity laser, we demonstrated several performance metrics that are important for various applications in sensing and imaging: a continuous electrical tuning of ~10 GHz at ~3.8 THz (fractional tuning of ~0.26%), a good level of output power (~50–90 mW of continuous-wave power) and tight beam patterns (~100 of beam divergence).

A late-injection strategy is typically adopted in stratified-charge direct injection spark ignition (DISI) engines to improve combustion stability for lean operation, but this may induce wall wetting on the piston surface and result in high soot emissions. E30 fuel, i.e., gasoline with 30% ethanol, is a potential alternative fuel that can offer a high Research Octane Number. However, the relatively high ethanol content increases the heat of vaporization, potentially exacerbating wall-wetting issues in DISI engines. In this study, the Refractive Index Matching (RIM) technique is used to measure fuel wall films in the piston bowl. The RIM implementation uses a novel LED illumination, integrated in the piston assembly and providing side illumination of the piston-bowl window. This RIM diagnostics in combination with high-speed imaging was used to investigate the impact of coolant temperature on the characteristics of wall wetting and combustion in an optical DISI engine fueled with E30. The experiments reveal that the smoke emissions increase drastically from 0.068 FSN to 1.14 FSN when the coolant temperature is reduced from 90 °C to 45 °C. Consistent with this finding, natural flame luminosity imaging reveals elevated soot incandescence with a reduction of the coolant temperature, indicative of pool fires. The RIM diagnostics show that a lower coolant temperature also leads to increased fuel film thickness, area, and volume, explaining the onset of pool fires and smoke.

As batteries become more prevalent in grid energy storage applications, the controllers that decide when to charge and discharge become critical to maximizing their utilization. Controller design for these applications is based on models that mathematically represent the physical dynamics and constraints of batteries. Unrepresented dynamics in these models can lead to suboptimal control. Our goal is to examine the state-of-the-art with respect to the models used in optimal control of battery energy storage systems (BESSs). This review helps engineers navigate the range of available design choices and helps researchers by identifying gaps in the state-of-the-art. BESS models can be classified by physical domain: state-of-charge (SoC), temperature, and degradation. SoC models can be further classified by the units they use to define capacity: electrical energy, electrical charge, and chemical concentration. Most energy based SoC models are linear, with variations in ways of representing efficiency and the limits on power. The charge based SoC models include many variations of equivalent circuits for predicting battery string voltage. SoC models based on chemical concentrations use material properties and physical parameters in the cell design to predict battery voltage and charge capacity. Temperature is modeled through a combination of heat generation and heat transfer. Heat is generated through changes in entropy, overpotential losses, and resistive heating. Heat is transferred through conduction, radiation, and convection. Variations in thermal models are based on which generation and transfer mechanisms are represented and the number and physical significance of finite elements in the model. Modeling battery degradation can be done empirically or based on underlying physical mechanisms. Empirical stress factor models isolate the impacts of time, current, SoC, temperature, and depth-of-discharge (DoD) on battery state-of-health (SoH). Through a few simplifying assumptions, these stress factors can be represented using regularization norms. Physical degradation models can further be classified into models of side-reactions and those of material fatigue. This article demonstrates the importance of model selection to optimal control by providing several example controller designs. Simpler models may overestimate or underestimate the capabilities of the battery system. Adding details can improve accuracy at the expense of model complexity, and computation time. Our analysis identifies six gaps: deficiency of real-world data in control literature, lack of understanding in how to balance modeling detail with the number of representative cells, underdeveloped model uncertainty based risk-averse and robust control of BESS, underdevelopment of nonlinear energy based SoC models, lack of hysteresis in voltage models used for control, lack of entropy heating and cooling in thermal modeling, and deficiency of knowledge in what combination of empirical degradation stress factors is most accurate. These gaps are opportunities for future research.

Various versions of deep borehole nuclear waste disposal have been proposed in the past in which effective sealing of a borehole after waste emplacement is generally required. In a high temperature disposal mode, the sealing function will be fulfilled by melting the ambient granitic rock with waste decay heat or an external heating source, creating a melt that will encapsulate waste containers or plug a portion of the borehole above a stack of the containers. However, there are certain drawbacks associated with natural materials, such as high melting temperatures, inefficient consolidation, slow crystallization kinetics, the resulting sealing materials generally being porous with low mechanical strength, insufficient adhesion to waste container surface, and lack of flexibility for engineering controls. In this study, we showed that natural granitic materials can be purposefully engineered through chemical modifications to enhance the sealing capability of the materials for deep borehole disposal. The present work systematically explores the effect of chemical modification and crystallinity (amorphous vs. crystalline) on the melting and crystallization processes of a granitic rock system. The approach can be applied to modify granites excavated from different geological sites. Several engineered granitic materials have been explored which possess significantly lower processing and densification temperatures than natural granites. Those new materials consolidate more efficiently by viscous flow and accelerated recrystallization without compromising their mechanical integrity and properties.

This chapter considers the collection of sparse samples in electron microscopy, either by modification of the sampling methods utilized on existing microscopes, or with new microscope concepts that are specifically designed and optimized for collection of sparse samples. It explores potential embodiments of a multi-beam compressive sensing electron microscope. Sparse measurement matrices offer an advantage of efficient image recovery, since each iteration of the process becomes a simple multiplication by a sparse matrix. Electron microscopy is well suited to compressed or sparse sampling due to the difficulty of building electron microscopes that can accurately record more than one electron signal at a time. Sparse sampling in electron microscopy has been considered for dose reduction, improving three-dimensional reconstructions and accelerating data acquisition. For sparse sampling, variations of scanning transmission electron microscopy (STEM) are typically used. In STEM, the electron probe is scanned across the specimen, and the detector measurement is recorded as a function of probe location.

Understanding fluid flow and transport in shale is of great importance to the development of unconventional hydrocarbon reservoirs and nuclear waste repositories. Tracer techniques have proven to be a useful tool for gaining such understanding. Shale is characterized by the presence of nanometer-sized pores and the resulting extremely low permeability. Chemical species confined in nanopores could behave drastically differently from those in a bulk system and the interaction of these species with pore surfaces is much enhanced due to a high surface/fluid volume ratio, both of which could potentially affect tracer migration and chromatographic differentiation in shale. Nanoconfinement manifests the discrete nature of fluid molecules in transport, therefore enhancing mass-dependent isotope fractionations. All these effects combined lead to a distinct set of tracer signatures that may not be observed in a conventional hydrocarbon reservoir or highly permeable groundwater aquifer system. These signatures can be used to delineate flow regimes, trace fluid sources, and quantify the rate and extent of a physical/chemical process. Such signatures can be used for the evaluation of cap rock structural integrity, the postclosure monitoring of a geologic repository, or the detection of a possible contamination in a water aquifer by a shale oil/gas extraction.

The goal of this work is to build model credibility of a structural dynamics model by comparing simulated responses to measured responses in random vibration environments, with limited knowledge of the true test input. Oftentimes off-axis excitations can be introduced during single axis vibration testing in the laboratory due to shaker or test fixture dynamics and interface variation. Model credibility cannot be improved by comparing predicted responses to measured responses with unknown excitation profiles. In the absence of sufficient time domain response measurements, the true multi-degree-of-freedom input cannot be exactly characterized for a fair comparison between the model and experiment. Methods exist, however, to estimate multi-degree-of-freedom (MDOF) inputs required to replicate field test data in the laboratory Ross et al.: 6-DOF Shaker Test Input Derivation from Field Test. In: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, Bethel (2017). This work focuses on utilizing one of these methods to approximately characterize the off-axis excitation present during laboratory random vibration testing. The method selects a sub-set of the experimental output spectral density matrix, in combination with the system transmissibility matrix, to estimate the input spectral density matrix required to drive the selected measurement responses. Using the estimated multi-degree-of-freedom input generated from this method, the error between simulated predictions and measured responses was significantly reduced across the frequency range of interest, compared to the error computed between experimental data to simulated responses generated assuming single axis excitation.

Multi-degree of freedom testing is growing in popularity and in practice. This is largely due to its inherent benefits in producing realistic stresses that the test article observes in its working environment and the efficiency of testing all axes at one time instead of individually. However, deriving and applying the “correct” inputs to a test has been a challenge. This paper explores a recently developed theory into deriving rigid body accelerations as an input to a test article through sub-structuring techniques. The theory develops a transformation matrix that separates the complete system dynamics into two sub-structures, the test article and next level assembly. The transformation does this by segregating the test article’s fixed base modal coordinates and the next level assembly’s free modal coordinates. This transformation provides insight into the damage that the test article acquires from its excited fixed base shapes and how to properly excite the test article by observing the next level assembly’s rigid body motion. This paper examines using next level assembly’s rigid body motion as a direct input in a multi-degree of freedom test to excite the test article’s fixed base shapes in the same way as the working environment.

Contact in structures with mechanical interfaces has the ability to significantly influence the system dynamics, such that the energy dissipation and resonant frequencies vary as a function of the response amplitude. Finite element analysis is commonly used to study the physics of such problems, particularly when examining the local behavior at the interfaces. These high fidelity, nonlinear models are computationally expensive to run with time-stepping solvers due to their large mesh densities at the interface, and because of the high expense required to update the tangent operators. Hurty/Craig-Bampton substructuring and interface reduction techniques are commonly utilized to reduce computation time for jointed structures. In the past, these methods have only been applied to substructures rigidly attached to one another, resulting in a linear model. The present work explores the performance of a particular interface reduction technique (system-level characteristic constraint modes) on a nonlinear model with node-to-node contact for a benchmark structure consisting of two c-shape beams bolted together at each end.

3D scanning laser Doppler vibrometry (LDV) systems are well known for modal testing of articles whose excited dynamic properties are time-invariant over the duration of all scans. However, several potential test situations can arise in which the modal parameters of a given article will change over the course of a typical LDV scan. One such instance is considered in this work, in which the internal state of a thermal battery changes at different rates over its activation lifetime. These changes substantially alter its dynamic properties as a function of time. Due to the extreme external temperatures of the battery, non-contact LDV was the preferred method of response measurement. However, scanning such an object is not optimal due to the non-simultaneous nature of the scanning LDV when capturing a full set of data. Nonetheless, by carefully considering the test configuration, hardware and software setup, as well as data acquisition and processing methods it was possible to utilize a scanning LDV system to collect sufficient information to provide a measure of the time varying dynamic characteristics of the test article. This work will demonstrate the techniques used, the acquired results and discuss the technical issues encountered.

Finite element models are regularly used in many disciplines to predict dynamic behavior of a structure under certain loads and subject to various boundary conditions, in particular when analytical models cannot be used due to geometric complexity. One such example is a structure with an entrained fluid cavity. To assist an experimental study of the acoustoelastic effect, numerical studies of an enclosed cylinder were performed to design the test hardware. With a system that demonstrates acoustoelastic coupling, it was then desired to make changes to decouple the structure from the fluid by making changes to either the fluid or the structure. In this paper, simulation is used to apply various changes and observe the effects on the structural response to choose an effective decoupling approach for the experimental study.

Acoustoelastic coupling occurs when a hollow structure’s in-vacuo mode aligns with an acoustic mode of the internal cavity. The impact of this coupling on the total dynamic response of the structure can be quite severe depending on the similarity of the modal frequencies and shapes. Typically, acoustoelastic coupling is not a design feature, but rather an unfortunate result that must be remedied as modal tests are often used to correlate or validate finite element models of the uncoupled structure. Here, however, a test structure is intentionally designed such that multiple structural and acoustic modes are well-aligned, resulting in a coupled system that allows for an experimental investigation. Coupling in the system is first identified using a measure termed the magnification factor and the structural-acoustic interaction for a target mode is then measured. Modifications to the system demonstrate the dependency of the coupling with respect to changes in the mode shape and frequency proximity. This includes an investigation of several practical techniques used to decouple the system by altering the internal acoustic cavity, as well as the structure itself. Furthermore, acoustic absorption material effectively decoupled the structure while structural modifications, in their current form, proved unsuccessful. The most effective acoustic absorption method consisted of randomly distributing typical household paper towels in the acoustic cavity; a method that introduces negligible mass to the structural system with the additional advantages of being inexpensive and readily available.

Time-resolved particle image velocimetry was conducted at 40 kHz using a pulse-burst laser in the supersonic wake of a wall-mounted hemisphere. Velocity fields suggest a recirculation region with two lobes, in which flow moves away from the wall near the centerline and recirculates back toward the hemisphere off the centerline, contrary to transonic configurations. Spatio-temporal cross-correlations and conditional ensemble averages relate the characteristic behavior of the unsteady shock motion to the flapping of the shear layer. At Mach 1.5, oblique shocks develop, associated with vortical structures in the shear layer and convect downstream in tandem; a weak periodicity is observed. Shock motion at Mach 2.0 appears somewhat different, wherein multiple weak disturbances propagate from shear-layer turbulent structures to form an oblique shock that ripples as these vortices pass by. Bifurcated shock feet coalesce and break apart without evident periodicity. Power spectra show a preferred frequency of shear-layer flapping and shock motion for Mach 1.5, but at Mach 2.0, a weak preferred frequency at the same Strouhal number of 0.32 is found only for oblique shock motion and not shear-layer unsteadiness.

Understanding and quantifying the relative importance of premixed and non-premixed reaction zones within turbulent partially premixed flames is an important issue for multi-regime combustion. In the present work, the recently-developed method of gradient-free regime identification (GFRI) is applied to instantaneous 1D Raman/Rayleigh measurements of temperature and major species from two turbulent lifted methane/air flames. Local premixed and non-premixed reaction zones are identified using criteria based on the mixture fraction, the chemical explosive mode, and the heat release rate, the latter two being calculated from an approximation of the full thermochemical state of each measured sample. A chemical mode (CM) zero-crossing is a previously documented marker for a premixed reaction zone. Results from the lifted flames show strong correlations among the mixture fraction at the CM zero-crossing, the magnitude of the change in CM at the zero-crossing, and the local heat release rate at the CM zero-crossing compared to the maximum heat release rate. The trends are confirmed through a comparable analysis of numerical simulations of two laminar triple flames. These newly documented trends are associated with the transition from dominantly premixed flame structures to dominantly non-premixed flames structures. The methods introduced for assessing the relative importance of local premixed and non-premixed reactions zones have potential for application to a broad range of turbulent flames.

International nuclear safeguards inspectors are tasked with verifying that nuclear materials in facilities around the world are not misused or diverted from peaceful purposes. They must conduct detailed inspections in complex, information-rich environments, but there has been relatively little research into the cognitive aspects of their jobs. We posit that the speed and accuracy of the inspectors can be supported and improved by designing the materials they take into the field such that the information is optimized to meet their cognitive needs. Many in-field inspection activities involve comparing inventory or shipping records to other records or to physical items inside of a nuclear facility. The organization and presentation of the records that the inspectors bring into the field with them could have a substantial impact on the ease or difficulty of these comparison tasks. In this paper, we present a series of mock inspection activities in which we manipulated the formatting of the inspectors’ records. We used behavioral and eye tracking metrics to assess the impact of the different types of formatting on the participants’ performance on the inspection tasks. The results of these experiments show that matching the presentation of the records to the cognitive demands of the task led to substantially faster task completion.

Here, we apply density functional theory (DFT) to investigate rare-earth metal organic frameworks (RE-MOFs), RE12(μ3-OH)16(C8O6H4)8(C8O6H5)4 (RE = Y, Eu, Tb, Yb), and characterize the level of theory needed to accurately predict structural and electronic properties in MOF materials with 4f-electrons. A two-step calculation approach of geometry optimization with spin-restricted DFT and large core potential (LCPs), and detailed electronic structures with spin-unrestricted DFT with a full valence potential + Hubbard U correction is investigated. Spin-restricted DFT with LCPs resulted in good agreement between experimental lattice parameters and optimized geometries, while a full valence potential is necessary for accurate representation of the electronic structure. The electronic structure of Eu-DOBDC MOF indicated a strong dependence on the treatment of highly localized 4f-electrons and spin polarization, as well as variation within a range of Hubbard corrections (U = 1-9 eV). For Hubbard corrected spin-unrestricted calculations, a U value of 1-4 eV maintains the non-metallic character of the band gap with slight deviations in f-orbital energetics. When compared with experimentally reported results, the importance of the full valence calculation and the Hubbard correction in correctly predicting the electronic structure is highlighted.

In its simplest implementation, patent-protected AeroMINE consists of two opposing foils, where a low-pressure zone is generated between them. The low pressure draws fluid through orifices in the foil surfaces from plenums inside the foils. The inner plenums are connected to ambient pressure. If an internal turbine-generator is placed in the path of the flow to the plenums, energy can be extracted. The fluid transports the energy through the plenums, and the turbine-generator can be located at ground level, inside a controlled environment for easy access and to avoid inclement weather conditions or harsh environments. This contained internal turbine-generator has the only moving parts in the system, isolated from people, birds and other wildlife. AeroMINEs could be used in distributed-wind energy settings, where the stationary foil pairs are located on warehouse rooftops, for example. Flow created by several such foil pairs could be combined to drive a common turbine-generator.

The degradation of a chemical warfare agent simulant using a catalytically active Zr-based metal-organic framework (MOF) as a function of different solvent systems was investigated. Complementary molecular modelling studies indicate that the differences in the degradation rates are related to the increasing size in the nucleophile, which hinders the rotation of the product molecule during degradation. Methanol was identified as an appropriate solvent for non-Aqueous degradation applications and demonstrated to support the MOF-based destruction of both sarin and soman.

Developers of optical systems are seeking lighter, cheaper, and rapidly-developed systems. Design, fabrication, and testing a 10x dual-focus telescope is presented utilizing additive manufacturing, active alignment, and image correction algorithms.

Controlling microscopic morphology of energetic materials is of significant interest for the improvement of their performance and production consistency. As an important insensitive high explosive material, triaminotrinitrobenzene (TATB) has attracted tremendous research effort for military grade explosives and propellants. In this study, a new, rapid and inexpensive synthesis method for monodispersed TATB microparticles based on micelle-confined precipitation was developed. Surfactant with proper hydrophilic-lipophilic balance value was found to be critical to the success of this synthesis. The morphology of the TATB microparticles can be tuned between quasi-spherical and faceted by controlling the speed of recrystallization.

Abstract not provided.

Observation of vibrational properties of phyllosilicate edges via a combined molecular modeling and experimental approach was performed. Deuterium exchange was utilized to isolate edge vibrational modes from their internal counterparts. The appearance of a specific peak within the broader D2O band indicates the presence of deuteration on the edge surface, and this peak is confirmed with the simulated spectra. These results are the first to unambiguously identify spectroscopic features of phyllosilicate edge sites.

The performances of five commercial anion exchange membranes are compared in aqueous soluble organic redox flow batteries (RFBs) containing the TEMPO and methyl viologen (MV) redox pair. Capacities between RFBs with different membranes are found to vary by >50% of theoretical after 100 cycles. This capacity loss is attributed to crossover of TEMPO and MV across the membrane and is dominated by either diffusion, migration, or electroosmotic drag, depending on the membrane. Counterintuitively, the worst performing membranes display the lowest diffusion coefficients for TEMPO and MV, instead seeing high crossover fluxes due to electroosmotic drag. This trend is rationalized in terms of the ion exchange capacity and water content of these membranes. Decreasing these values in an effort to minimize diffusion of the redox-active species while the RFB rests can inadvertently exacerbate conditions for electroosmotic drag when theRFBoperates.Using fundamental membrane properties, it is demonstrated that the relative magnitude of crossover and capacity loss during RFB operation may be understood.

Multiple fastener reduced-order models and fitting strategies are used on a multiaxial dataset and these models are further evaluated using a high-fidelity analysis model to demonstrate how well these strategies predict load-displacement behavior and failure. Two common reduced-order modeling approaches, the plug and spot weld, are calibrated, assessed, and compared to a more intensive approach – a “two-block” plug calibrated to multiple datasets. An optimization analysis workflow leveraging a genetic algorithm was exercised on a set of quasistatic test data where fasteners were pulled at angles from 0° to 90° in 15° increments to obtain material parameters for a fastener model that best capture the load-displacement behavior of the chosen datasets. The one-block plug is calibrated just to the tension data, the spot weld is calibrated to the tension (0°) and shear (90°), and the two-block plug is calibrated to all data available (0°-90°). These calibrations are further assessed by incorporating these models and modeling approaches into a high-fidelity analysis model of the test setup and comparing the load-displacement predictions to the raw test data.

Austenitic stainless steels (Fe-Cr-Ni) are resistant to hydrogen embrittlement but have not been studied using molecular dynamics simulations due to the lack of an Fe-Cr-Ni-H interatomic potential. Herein we describe our recent progress towards molecular dynamics studies of hydrogen effects in Fe-Cr-Ni stainless steels. We first describe our Fe-Cr-Ni-H interatomic potential and demonstrate its characteristics relevant to mechanical properties. We then demonstrate that our potential can be used in molecular dynamics simulations to derive Arrhenius equation of hydrogen diffusion and to reveal twinning and phase transformation deformation mechanisms in stainless steels.

We offer an explanation for how dendrite growth can be inhibited when Li metal pouch cells are subjected to external loads, even for cells using soft, thin separators. We develop a contact mechanics model for tracking Li surface and sub-surface stresses where electrodes have realistically (micron-scale) rough surfaces. Existing models examine a single, micron-scale Li metal protrusion under a fixed local current density that presses more or less conformally against a separator or stiff electrolyte. At the larger, sub-mm scales studied here, contact between the Li metal and the separator is heterogeneous and far from conformal for surfaces with realistic roughness: the load is carried at just the tallest asperities, where stresses reach tens of MPa, while most of the Li surface feels no force at all. Yet, dendrite growth is suppressed over the entire Li surface. To explain this dendrite suppression, our electrochemical/mechanics model suggests that Li avoids plating at the tips of growing Li dendrites if there is sufficient local stress; that local contact stresses there may be high enough to close separator pores so that incremental Li+ ions plate elsewhere; and that creep ensures that Li protrusions are gradually flattened. These mechanisms cannot be captured by single-dendrite-scale analyses.

Dichroic coatings have been developed for high transmission at 527 nm and high reflection at 1054 nm for laser operations in the nanosecond pulse regime. The coatings consist of HfO2 and SiO2 layers deposited with e-beam evaporation, and laser-induced damage thresholds as high as 12.5 J/cm2 were measured at 532 nm with 3.5 ns pulses (22.5 degrees angle of incidence, in S-polarization). However, laser damage measurements at the single wavelength of 532 nm do not adequately characterize the laser damage resistance of these coatings, since they were designed to operate at dual wavelengths simultaneously. This became apparent after one of the coatings damaged prematurely at a lower fluence in the beam train, which inspired further investigations. To gain a more complete understanding of the laser damage resistance, results of a dual-wavelength laser damage test performed at both 532 nm and 1064 nm are presented.

Abstract not provided.

Spectral linewidths are used to assess a variety of physical properties, even as spectral overlap makes quantitative extraction difficult owing to uncertainty. Uncertainty, in turn, can be minimized with the choice of appropriate experimental conditions used in spectral collection. In response, we assess the experimental factors dictating uncertainty in the quantification of linewidth from a Raman experiment highlighting the comparative influence of (1) spectral resolution, (2) signal to noise, and (3) relative peak intensity (RPI) of the overlapping peaks. Practically, Raman spectra of SiGe thin films were obtained experimentally and simulated virtually under a variety of conditions. RPI is found to be the most impactful parameter in specifying linewidth followed by the spectral resolution and signal to noise. While developed for Raman experiments, the results are generally applicable to spectroscopic linewidth studies illuminating the experimental trade-offs inherent in quantification.

Microtubules are stiff biopolymers that self-assemble via the addition of GTP-tubulin (αβ-dimer bound to GTP), but hydrolysis of GTP- to GDP-tubulin within the tubules destabilizes them toward catastrophically-fast depolymerization. The molecular mechanisms and features of the individual tubulin proteins that drive such behavior are still not well-understood. Using molecular dynamics simulations of whole microtubules built from a coarse-grained model of tubulin, we demonstrate how conformational shape changes (i.e., deformations) in subunits that frustrate tubulin-tubulin binding within microtubules drive depolymerization of stiff tubules via unpeeling "ram's horns" consistent with experiments. We calculate the sensitivity of these behaviors to the length scales and strengths of binding attractions and varying degrees of binding frustration driven by subunit shape change, and demonstrate that the dynamic instability and mechanical properties of microtubules can be produced based on either balanced or imbalanced strengths of lateral and vertical binding attractions. Finally, we show how catastrophic depolymerization can be interrupted by small regions of the microtubule containing undeformed dimers, corresponding to incomplete lattice hydrolysis. The results demonstrate a mechanism by which microtubule rescue can occur.

This paper investigates the application of a method to find the cost function or the weight matrices to be used in model predictive control (MPC) such that the MPC has the same performance as a predesigned linear controller in state-feedback form when constraints are not active. This is potentially useful when a successful linear controller already exists and it is necessary to incorporate the constraint-handling capabilities of MPC. This is the case for a wave energy converter (WEC), where the maximum power transfer law is well-understood. In addition to solutions based on numerical optimization, a simple analytical solution is also derived for cases with a short prediction horizon. These methods are applied for the control of an empirically-based WEC model. The results show that the MPC can be successfully tuned to follow an existing linear control law and to comply with both input and state constraints, such as actuator force and actuator stroke.

Cross Reality (XR) immersive environments offer challenges and opportunities in designing for cognitive aspects (e.g. learning, memory, attention, etc.) of information design and interactions. Information design is a multidisciplinary endeavor involving data science, communication science, cognitive science, media, and technology. In the present paper the holodeck metaphor is extended to illustrate how information design practices and some of the qualities of this imaginary computationally augmented environment (a.k.a. the holodeck) may be achieved in XR environments to support information-rich storytelling and real life, face-to-face, and virtual collaborative interactions. The Simulation Experience Design Framework & Method is introduced to organize challenges and opportunities in the design of information for XR. The notion of carefully blending both real and virtual spaces to achieve total immersion is discussed as the reader moves through the elements of the cyclical framework. A solution space leveraging cognitive science, information design, and transmedia learning highlights key challenges facing contemporary XR designers. Challenges include but are not limited to interleaving information, technology, and media into the human storytelling process, and supporting narratives in a way that is memorable, robust, and extendable.

This paper describes the fissile mass and concentration necessary for a critical event to occur outside containers disposed in a bedded salt repository. The criticality limits are based on modeling mixtures of water, salt, dolomite, concrete, rust, and fissile material using a neutron/photon transport computational code. Several idealized depositional configurations of fissile material in the host rock are analyzed: homogeneous spheres and heterogeneous arrangements of plate fractures in regular arrays. Deposition of large masses and concentrations are required for criticality to occur for low enriched 235U enrichment. Homogeneous mixtures with deposition in all the porosity are more reactive at high enrichments of 235U and 239Pu. However, unlike typical engineered systems, heterogeneous configurations can be more reactive than homogeneous systems at high enrichment when deposition occurs in only a portion of the porosity and the total porosity is small, because the relationship between the porosity of the fractures and matrix also strongly influences the results.

Supercritical CO2 (sCO2) power cycles find potential application with a variety of heat sources including nuclear, concentrated solar (CSP), coal, natural gas, and waste heat sources, and consequently cover a wide range of scales. Most studies to date have focused on the performance of sCO2 power cycles, while economic analyses have been less prevalent, due in large part to the relative scarcity of reliable cost estimates for sCO2 power cycle components. Further, the accuracy of existing sCO2 techno-economic analyses suffer from a small sample set of vendor-based component costs for any given study. Improved accuracy of sCO2 component cost estimation is desired to enable a shift in focus from plant efficiency to economics as a driver for commercialization of sCO2 technology. This study reports on sCO2 component cost scaling relationships that have been developed collaboratively from an aggregate set of vendor quotes, cost estimates, and published literature. As one of the world’s largest supporters of sCO2 research and development, the Department of Energy (DOE) National Laboratories have access to a considerable pool of vendor component costs that span multiple applications specific to each National Laboratory’s mission, including fossil-fueled sCO2 applications at the National Energy Technology Laboratory (NETL), CSP at the National Renewable Energy Laboratory (NREL), and CSP, nuclear, and distributed energy sources at Sandia National Laboratories (SNL). The resulting cost correlations are relevant to sCO2 components in all these applications, and for scales ranging from 5-750 MWe. This work builds upon prior work at SNL, in which sCO2 component cost models were developed for CSP applications ranging from 1-100 MWe in size. Similar to the earlier SNL efforts, vendor confidentiality has been maintained throughout this collaboration and in the published results. Cost models for each component were correlated from 4-24 individual quotes from multiple vendors, although the individual cost data points are proprietary and not shown. Cost models are reported for radial and axial turbines, integrally-geared and barrel-style centrifugal compressors, high temperature and low temperature recuperators, dry sCO2 coolers, and primary heat exchangers for coal and natural gas fuel sources. These models are applicable to sCO2-specific components used in a variety of sCO2 cycle configurations, and include incremental cost factors for advanced, high temperature materials for relevant components. Non-sCO2-specific costs for motors, gearboxes, and generators have been included to allow cycle designers to explore the cost implications of various turbomachinery configurations. Finally, the uncertainty associated with these component cost models is quantified by using AACE International-style class ratings for vendor estimates, combined with component cost correlation statistics.

Compact heat exchangers for supercritical CO2 (sCO2) service are often designed with external, semi-circular headers. Their design is governed by the ASME Boiler & Pressure Vessel Code (BPVC) whose equations were typically derived by following Castigliano’s Theorems. However, there are no known validation experiments to support their claims of pressure rating or burst pressure predictions nor is there much information about how and where failures occur. This work includes high pressure bursting of three semicircular header prototypes for the validation of three aspects: (1) burst pressure predictions from the BPVC, (2) strain predictions from Finite Element Analysis (FEA), and (3) deformation from FEA. The header prototypes were designed with geometry and weld specifications from the BPVC Section VIII Division 1, a design pressure typical of sCO2 service of 3,900 psi (26.9 MPa), and were built with 316 SS. Repeating the test in triplicate allows for greater confidence in the experimental results and enables data averaging. Burst pressure predictions are compared with experimental results for accuracy assessment. The prototypes are analyzed to understand their failure mechanism and locations. Experimental strain and deformation measurements were obtained optically with Digital Image Correlation (DIC). This technique allows strain to be measured in two dimensions and even allows for deformation measurements, all without contacting the prototype. Eight cameras are used for full coverage of both headers on the prototypes. The rich data from this technique are an excellent validation source for FEA strain and deformation predictions. Experimental data and simulation predictions are compared to assess simulation accuracy.

Probabilistic simulations of the post-closure performance of a generic deep geologic repository for commercial spent nuclear fuel in shale host rock provide a test case for comparing sensitivity analysis methods available in Geologic Disposal Safety Assessment (GDSA) Framework, the U.S. Department of Energy's state-of-the-art toolkit for repository performance assessment. Simulations assume a thick low-permeability shale with aquifers (potential paths to the biosphere) above and below the host rock. Multi-physics simulations on the 7-million-cell grid are run in a high-performance computing environment with PFLOTRAN. Epistemic uncertain inputs include properties of the engineered and natural systems. The output variables of interest, maximum I-129 concentrations (independent of time) at observation points in the aquifers, vary over several orders of magnitude. Variance-based global sensitivity analyses (i.e., calculations of sensitivity indices) conducted with Dakota use polynomial chaos expansion (PCE) and Gaussian process (GP) surrogate models. Results of analyses conducted with raw output concentrations and with log-transformed output concentrations are compared. Using log-transformed concentrations results in larger sensitivity indices for more influential input variables, smaller sensitivity indices for less influential input variables, and more consistent values for sensitivity indices between methods (PCE and GP) and between analyses repeated with samples of different sizes.

The U.S. Department of Energy is conducting research and development on generic concepts for disposal of spent nuclear fuel and high-level radioactive waste in multiple lithologies, including salt, crystalline (granite/metamorphic), and argillaceous (clay/shale) host rock. These investigations benefit greatly from international experience gained in disposal programs in many countries around the world. The focus of this study is the post-closure degradation and radionuclide-release rates for tristructural-isotropic (TRISO) coated particle spent fuels for various generic geologic repository environments.1,2,3 The TRISO particle coatings provide safety features during and after reactor operations, with the SiC layer representing the primary barrier. Three mechanisms that may lead to release of radionuclides from the TRISO particles are: (1) helium pressure buildup4 that may eventually rupture the SiC layer, (2) diffusive transport through the layers (solid-state diffusion in reactor, aqueous diffusion in porous media at repository conditions), and (3) corrosion5 of the layers in groundwater/brine. For TRISO particles in a graphite fuel element, the degradation in an oxidizing geologic repository was concluded to be directly dependent on the oxidative corrosion rate of the graphite matrix4, which was analyzed as much slower than SiC layer corrosion processes. However, accumulated physical damage to the graphite fuel element may decrease its post-closure barrier capability more rapidly. Our initial performance model focuses on the TRISO particles and includes SiC failure from pressure increase via alpha-decay helium, as exacerbated by SiC layer corrosion5. This corrosion mechanism is found to be much faster than solid-state diffusion at repository temperatures but includes no benefit of protection by the other outer layers, which may prolong lifetime. Our current model enhancements include constraining the material properties of the layers for porous media diffusion analyses. In addition to evaluating the SiC layer porosity structure, this work focuses on the pyrolytic carbon layers (inner/outer-IPyC/OPyC) layers, and the graphite compact, which are to be analyzed with the SiC layer in two modes: (a) intact SiC barrier until corrosion failure and (b) SiC with porous media transport. Our detailed performance analyses will consider these processes together with uncertainties in the properties of the layers to assess radionuclide release from TRISO particles and their graphite compacts.

Two surrogate models are under development to rapidly emulate the effects of the Fuel Matrix Degradation (FMD) model in GDSA Framework. One is a polynomial regression surrogate with linear and quadratic fits, and the other is a k-Nearest Neighbors regressor (kNNr) method that operates on a lookup table. Direct coupling of the FMD model to GDSA Framework is too computationally expensive. Preliminary results indicate these surrogate models will enable GDSA Framework to rapidly simulate spent fuel dissolution for each individual breached spent fuel waste package in a probabilistic repository simulation. This capability will allow uncertainties in spent fuel dissolution to be propagated and sensitivities in FMD inputs to be quantified and ranked against other inputs.

Bedded salt contains interfaces between the host salt and other in situ materials such as clay seams, or different materials such as anhydrite or polyhalite in contact with the salt. These inhomogeneities are thought to have first-order effects on the closure of nearby drifts and potential roof collapses. Despite their importance, characterizations of the peak shear strength and residual shear strength of interfaces in salt are extremely rare in the published literature. This paper presents results from laboratory experiments designed to measure the mechanical behavior of a bedding interface or clay seam as it is sheared. The series of laboratory direct shear tests reported in this paper were performed on several samples of materials from the Permian Basin in New Mexico. These tests were conducted at several normal and shear loads up to the expected in situ pre-mining stress conditions. Tests were performed on samples with a halite/clay contact, a halite/anhydrite contact, a halite/polyhalite contact, and on plain salt samples without an interface for comparison. Intact shear strength values were determined for all of the test samples along with residual values for the majority of the tests. The test results indicated only a minor variation in shear strength, at a given normal stress, across all samples. This result was surprising because sliding along clay seams is regularly observed in the underground, suggesting the clay seam interfaces should be weaker than plain salt. Post-test inspections of these samples noted that salt crystals were intrinsic to the structure of the seam, which probably increased the shear strength as compared to a more typical clay seam.

The fluid injection into the subsurface perturbs the states of pore pressure and stress on the pre-existing faults, potentially causing earthquakes. In the multiphase flow system, the contrast of fluid and rock properties between different structures produces the changes in pressure gradients and subsequently stress fields. Assuming two-phase fluid flow (gas-water system) and poroelasticity, we simulate the three-layered formation including a basement fault, in which injection-induced pressure encounters the fault directly given injection scenarios. The single-phase poroelasticity model with the same setting is also conducted to evaluate the multiphase flow effects on poroelastic response of the fault to gas injection. Sensitivity tests are performed by varying the fault permeability. The presence of gaseous phase reduces the pressure buildup within the highly gas-saturated region, causing less Coulomb stress changes, whereas capillarity increases the pore pressure within the gas-water mixed region. Even though the gaseous plume does not approach the fault, the poroelastic stressing can affect the fault stability, potentially the earthquake occurrence.

The reaction network of the simplest Criegee intermediate (CI) CH2OO has been studied experimentally during the ozonolysis of ethylene. The results provide valuable information about plasma- and ozone-assisted combustion processes and atmospheric aerosol formation. A network of CI reactions was identified, which can be described best by the sequential addition of CI with ethylene, water, formic acid, and other molecules containing hydroxy, aldehyde, and hydroperoxy functional groups. Species resulting from as many as four sequential CI addition reactions were observed, and these species are highly oxygenated oligomers that are known components of secondary organic aerosols in the atmosphere. Insights into these reaction pathways were obtained from a near-atmospheric pressure jet-stirred reactor coupled to a high-resolution molecular-beam mass spectrometer. The mass spectrometer employs single-photon ionization with synchrotron-generated, tunable vacuum-ultraviolet radiation to minimize fragmentation via near-threshold ionization and to observe mass-selected photoionization efficiency (PIE) curves. Species identification is supported by comparison of the mass-selected, experimentally observed photo-ionization thresholds with theoretical calculations for the ionization energies. A variety of multi-functional peroxide species are identified, including hydroxymethyl hydroperoxide (HOCH2OOH), hydroperoxymethyl formate (HOOCH2OCHO), methoxymethyl hydroperoxide (CH3OCH2OOH), ethoxymethyl hydroperoxide (C2H5OCH2OOH), 2-hydroxyethyl hydroperoxide (HOC2H4OOH), dihydroperoxy methane (HOOCH2OOH), and 1-hydroperoxypropan-2-one [CH3C(O)CH2OOH]. A semi-quantitative analysis of the signal intensities as a function of successive CI additions and temperature provides mechanistic insights and valuable information for future modeling work of the associated energy conversion processes and atmospheric chemistry. This work provides further evidence that the CI is a key intermediate in the formation of oligomeric species via the formation of hydroperoxides.

Atmospheric tracer transport is a computationally demanding component of the atmospheric dynamical core of weather and climate simulations. Simulations typically have tens to hundreds of tracers. A tracer field is required to preserve several properties, including mass, shape, and tracer consistency. To improve computational efficiency, it is common to apply different spatial and temporal discretizations to the tracer transport equations than to the dynamical equations. Using different discretizations increases the difficulty of preserving properties. This paper provides a unified framework to analyze the property preservation problem and classes of algorithms to solve it. We examine the primary problem and a safety problem; describe three classes of algorithms to solve these; introduce new algorithms in two of these classes; make connections among the algorithms; analyze each algorithm in terms of correctness, bound on its solution magnitude, and its communication efficiency; and study numerical results. A new algorithm, QLT, has the smallest communication volume, and in an important case it redistributes mass approximately locally. These algorithms are only very loosely coupled to the underlying discretizations of the dynamical and tracer transport equations and thus are broadly and efficiently applicable. In addition, they may be applied to remap problems in applications other than tracer transport.

The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. We employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We find a difference in species abundance within a 130 m radius of the center of the test site.

In this work we investigate the Orowan hypothesis, that decreases in surface energy due to surface adsorbates lead directly to lowered fracture toughness, at an atomic/molecular level. We employ a Lennard-Jones system with a slit crack and an infiltrating fluid, nominally with gold-water properties, and explore steric effects by varying the soft radius of fluid particles and the influence of surface energy/hydrophobicity via the solid–fluid binding energy. Using previously developed methods, we employ the J-integral to quantify the sensitivity of fracture toughness to the influence of the fluid on the crack tip, and exploit dimensionless scaling to discover universal trends in behavior.

We use dielectric metasurfaces made from direct bandgap semiconductors to generate high-harmonics and nonlinear mixing simultaneously, without the need of phase matching. Inclusion of broken-symmetry designs and quantum heterostructures can lead to even higher efficiencies.

Novel multilayered FeSiCrB-Fe x N (x = 2-4) metallic glass composites were fabricated using spark plasma sintering of FeSiCrB amorphous ribbons (Metglas 2605SA3 alloy) and Fe x N (x = 2-4) powder. Crystalline Fe x N can serve as a high magnetic moment, high electrical resistance binder, and lamination material in the consolidation of amorphous and nanocrystalline ribbons, mitigating eddy currents while boosting magnetic performance and stacking factor in both wound and stacked soft magnetic cores. Stacking factors of nearly 100% can be achieved in an amorphous ribbon/iron nitride composite. FeSiCrB-Fe x N multilayered metallic glass composites prepared by spark plasma sintering have the potential to serve as a next-generation soft magnetic material in power electronics and electrical machines.

Aqueous dissolution of silicate materials exhibits complex temporal evolution and rich pattern formations. Mechanistic understanding of this process is critical for the development of a predictive model for a long-term performance assessment of silicate glass as a waste form for high-level radioactive waste disposal. Here we provide a summary of a recently developed nonlinear dynamic model for silicate material degradation in an aqueous environment. This model is based on a simple self-organizational mechanism: dissolution of silica framework of a material is catalyzed by cations released from material degradation, which in turn accelerate the release of cations. This model provides a systematical prediction of the key features observed in silicate glass dissolution, including the occurrence of a sharp corrosion front, oscillatory dissolution, multiple stages of the alteration process, wavy dissolution fronts, growth rings, incoherent bandings of alteration products, and corrosion pitting. This work provides a new perspective for understanding silicate material degradation and evaluating the long-term performance of these materials as a waste form for radioactive waste disposal.

Over the last 13 years, at Sandia National Laboratories we have applied the belief/plausibility measure from evidence theory to estimate the uncertainty for numerous safety and security issues for nuclear weapons. For such issues we have significant epistemic uncertainty and are unable to assign probability distributions. We have developed and applied custom software to implement the belief/plausibility measure of uncertainty. For safety issues we perform a quantitative evaluation, and for security issues (e.g., terrorist acts) we use linguistic variables (fuzzy sets) combined with approximate reasoning. We perform the following steps: Train Subject Matter Experts (SMEs) on assignment of evidence Work with SMEs to identify the concern(s): the top-level variable(s) Work with SMEs to identify lower-level variable and functional relationship(s) to the top-level variable(s) Then the SMEs gather their State of Knowledge (SOK) and assign evidence to the lower-level variables. Using this information, we evaluate the variables using custom software and produce an estimate for the top-level variable(s) including uncertainty. We have extended the Kaplan-Garrick risk triplet approach for risk to use the belief/plausibility measure of uncertainty.

Exascale computing demands high bandwidth and low latency I/O on the computing edge. Object storage systems can provide higher bandwidth and lower latencies than tape archive. File transfer nodes present a single point of mediation through which data moving between these storage systems must pass. By increasing the performance of erasure coding, stripes can be subdivided into large numbers of shards. This paper’s contribution is a prototype nearline disk object storage system based on Ceph. We show that using general purpose graphical processing units (GPGPU) for erasure coding on file transfer nodes is effective when using a large number of shards. We describe an architecture for nearline disk archive storage for use with high performance computing (HPC) and demonstrate the performance with benchmarking results. We compare the benchmark performance of our design with the IntelR⃝ Storage Acceleration Library (ISA-L) CPU based erasure coding libraries using the native Ceph erasure coding feature.

Rational design of novel electrolytes with enhanced functionality requires fundamental molecular-level understanding of structure-property relationships. Here we examine the suitability of a range of organic solvents for non-aqueous electrolytes in secondary magnesium batteries using density functional theory (DFT) calculations as well as experimental probes such as cyclic voltammetry and Raman spectroscopy. The solvents considered include ethereal solvents (e.g., glymes) sulfones (e.g., tetramethylene sulfone), and acetonitrile. Computed reduction potentials show that all solvents considered are stable against reduction by Mg metal. Additional computations were carried out to assess the stability of solvents in contact with partially reduced Mg cations (Mg 2+ → Mg + ) formed during cycling (e.g., deposition) by identifying reaction profiles of decomposition pathways. Most solvents, including some proposed for secondary Mg energy storage applications, exhibit decomposition pathways that are surprisingly exergonic. Interestingly, the stability of these solvents is largely dictated by magnitude of the kinetic barrier to decomposition. This insight should be valuable toward rational design of improved Mg electrolytes.

The MPI multithreading model has been historically difficult to optimize; the interface that it provides for threads was designed as a process-level interface. This model has led to implementations that treat function calls as critical regions and protect them with locks to avoid race conditions. We hypothesize that an interface designed specifically for threads can provide superior performance than current approaches and even outperform single-threaded MPI. In this paper, we describe a design for partitioned communication in MPI that we call finepoints. First, we assess the existing communication models for MPI two-sided communication and then introduce finepoints as a hybrid of MPI models that has the best features of each existing MPI communication model. In addition, “partitioned communication” created with finepoints leverages new network hardware features that cannot be exploited with current MPI point-to-point semantics, making this new approach both innovative and useful both now and in the future. To demonstrate the validity of our hypothesis, we implement a finepoints library and show improvements against a state-of-the-art multithreaded optimized Open MPI implementation on a Cray XC40 with an Aries network. Our experiments demonstrate up to a 12 × reduction in wait time for completion of send operations. This new model is shown working on a nuclear reactor physics neutron-transport proxy-application, providing up to 26.1% improvement in communication time and up to 4.8% improvement in runtime over the best performing MPI communication mode, single-threaded MPI.

We use molecular simulations to provide a conceptual understanding of a crystalline-amorphous interface for a candidate negative thermal expansion (NTE) material. Specifically, classical molecular dynamics (MD) simulations were used to investigate the temperature and pressure dependence on structural properties of ZrW2O8. Polarizability of oxygen atoms was included to better account for the electronic charge distribution within the lattice. Constant-pressure simulations of cubic crystalline ZrW2O8 at ambient pressure reveal a slight NTE behavior, characterized by a small structural rearrangement resulting in oxygen sharing between adjacent WO4 tetrahedra. Periodic quantum calculations confirm that the MD-optimized structure is lower in energy than the idealized structure obtained from neutron diffraction experiments. Additionally, simulations of pressure-induced amorphization of ZrW2O8 at 300 K indicate that an amorphous phase forms at pressures greater than 10 GPa, and this phase persists when the pressure is decreased to 1 bar. Simulations were performed on a hybrid model consisting of amorphous ZrW2O8 in direct contact with the cubic crystalline phase. Upon equilibration at 300 K and 1 bar, the crystalline phase remains unchanged beyond a thin layer of disrupted structure at the amorphous interface. Detailed analysis reveals the transition in metal coordination at the interface.

Austenitic stainless steels are used extensively in hydrogen gas containment components due to their known resilience in hydrogen environments. Depending on the conditions, degradation can occur in austenitic stainless steels but typically the materials retain sufficient mechanical properties within such extreme environments. In many hydrogen containment applications, it is necessary or advantageous to join components through welding as it ensures minimal gas leakage, unlike mechanical fittings that can become leak paths that develop over time. Over the years many studies have focused on the mechanical behavior of austenitic stainless steels in hydrogen environments and determined their properties to be sufficient for most applications. However, significantly less data have been generated on austenitic stainless steel welds, which can exhibit more degradation than the base material. In this paper, we assess the trends observed in austenitic stainless steel welds tested in hydrogen. Experiments of welds including tensile and fracture toughness testing are assessed and comparisons to behavior of base metals are discussed.

Uranyl ion, UO22+, and its aqueous complexes with organic and inorganic ligands, are the dominant species for transport of natural occurring uranium at the Earth surface environments. In the nuclear waste management, uranyl ion and its aqueous complexes are expected to be responsible for uranium mobilization in the disposal concepts where spent fuel is disposed in oxidized environments such as unsaturated zones relative to the underground water table. In the natural environments, oxalate, in fully deprotonated form, C2O42-, is ubiquitous, as oxalate is one of the most important degradation products of humic and fulvic acids. Oxalate is known to form aqueous complexes with uranyl ion to facilitate the transport of uranium. However, oxalate also forms solid phases with uranyl ion in certain environments, limiting the movement of uranium. Therefore, the knowledge of the stability constants of aqueous and solid uranyl oxalate complexes is important not only to the understanding of the mobility of uranium in natural environments, but also to the performance assessment of radionuclides in geological repositories for spent nuclear fuel. In this work, we present the stability constants for UO2C2O4(aq) and UO2(C2O4)22- at infinite dilution based on our evaluation of the literature data over a wide range of ionic strengths up to 9.5 mol•kg-1. We also obtain the solubility constants at infinite dilution for the following solid uranyl oxalates, UO2C2O4•3H2O and UO2C2O4•H2O, based on the solubility data in a wide range of ionic strengths up to 11 mol•kg-1. In our evaluation, we use the computer code EQ3/6 Version 8.0a. The model developed by us is expected to enable researchers to accurately assess the role of oxalate in mobilization/immobilization of uranium under various conditions including those in geological repositories.

Many optical systems are used for specific tasks such as classification. Of these systems, the majority are designed to maximize image quality for human observers; however, machine learning classification algorithms do not require the same data representation used by humans. In this work we investigate compressive optical systems optimized for a specific machine sensing task. Two compressive optical architectures are examined: An array of prisms and neutral density filters where each prism and neutral density filter pair realizes one datum from an optimized compressive sensing matrix, and another architecture using conventional optics to image the aperture onto the detector, a prism array to divide the aperture, and a pixelated attenuation mask in the intermediate image plane. We discuss the design, simulation, and tradeoffs of these compressive imaging systems built for compressed classification of the MNSIT data set. To evaluate the tradeoffs of the two architectures, we present radiometric and raytrace models for each system. Additionally, we investigate the impact of system aberrations on classification accuracy of the system. We compare the performance of these systems over a range of compression. Classification performance, radiometric throughput, and optical design manufacturability are discussed.

Many optical systems are used for specific tasks such as classification. Of these systems, the majority are designed to maximize image quality for human observers; however, machine learning classification algorithms do not require the same data representation used by humans. In this work we investigate compressive optical systems optimized for a specific machine sensing task. Two compressive optical architectures are examined: An array of prisms and neutral density filters where each prism and neutral density filter pair realizes one datum from an optimized compressive sensing matrix, and another architecture using conventional optics to image the aperture onto the detector, a prism array to divide the aperture, and a pixelated attenuation mask in the intermediate image plane. We discuss the design, simulation, and tradeoffs of these compressive imaging systems built for compressed classification of the MNSIT data set. To evaluate the tradeoffs of the two architectures, we present radiometric and raytrace models for each system. Additionally, we investigate the impact of system aberrations on classification accuracy of the system. We compare the performance of these systems over a range of compression. Classification performance, radiometric throughput, and optical design manufacturability are discussed.

We analytically model single-, two-, and three-wires above ground to determine the decay lengths of common and differential modes induced by an E1 high-altitude electromagnetic pulse (HEMP) excitation. Decay length information is pivotal to determine whether any two nodes in the power grid may be treated as uncoupled. We employ a frequency-domain method based on transmission line theory named ATLOG — Analytic Transmission Line Over Ground to model infinitely long and finite single wires, as well as solve the eigenvalue problem of a single-, two-, and three-wire system. Our calculations show that a single, semi-infinite power line can be approximated by a 10 km section of line and that the second electrical reflection for all line lengths longer than the decay length are below half the rated operating voltage. Furthermore, our results show that the differential mode propagates longer distances than the common mode in two-and three-wire systems, and this should be taken into account when performing damage assessment from HEMP excitation. This analysis is a significant step toward simplifying the modeling of practical continental grid lengths, yet maintaining accuracy, a result of enormous impact.

Additive manufacturing (AM) offers the potential for increased design flexibility in the low volume production of complex engineering components for hydrogen service. However the suitability of AM materials for such extreme service environments remains to be evaluated. This work examines the effects of internal and external hydrogen on AM type 304L austenitic stainless steels fabricated via directed-energy deposition (DED) and powder bed fusion (PBF) processes. Under ambient test conditions, AM materials with minimal manufacturing defects exhibit excellent combinations of tensile strength, tensile ductility, and fatigue resistance. To probe the effects of extreme hydrogen environments on the AM materials, tensile and fatigue tests were performed after thermalprecharging in high pressure gaseous hydrogen (internal H) or in high pressure gaseous hydrogen (external H). Hydrogen appears to have a comparable influence on the AM 304L as in wrought materials, although the micromechanisms of tensile fracture and fatigue crack growth appear distinct. Specifically, microstructural characterization implicates the unique solidification microstructure of AM materials in the propagation of cracks under conditions of tensile fracture with hydrogen. These results highlight the need to establish comprehensive microstructure-property relationships for AM materials to ensure their suitability for use in extreme hydrogen environments.

High-quality image products in an X-Ray Phase Contrast Imaging (XPCI) system can be produced with proper system hardware and data acquisition. However, it may be possible to further increase the quality of the image products by addressing subtleties and imperfections in both hardware and the data acquisition process. Noting that addressing these issues entirely in hardware and data acquisition may not be practical, a more prudent approach is to determine the balance of how the apparatus may reasonably be improved and what can be accomplished with image post-processing techniques. Given a proper signal model for XPCI data, image processing techniques can be developed to compensate for many of the image quality degradations associated with higher-order hardware and data acquisition imperfections. However, processing techniques also have limitations and cannot entirely compensate for sub-par hardware or inaccurate data acquisition practices. Understanding system and image processing technique limitations enables balancing between hardware, data acquisition, and image post-processing. In this paper, we present some of the higher-order image degradation effects we have found associated with subtle imperfections in both hardware and data acquisition. We also discuss and demonstrate how a combination of hardware, data acquisition processes, and image processing techniques can increase the quality of XPCI image products. Finally, we assess the requirements for high-quality XPCI images and propose reasonable system hardware modifications and the limits of certain image processing techniques.

It is well-known that a slotted resonant cavity with high-quality factor exhibits interior electromagnetic (EM) fields that may be even larger than the external field. The authors aim to reduce the cavity’s EM fields and quality factor over a frequency band analytically, numerically, and experimentally by introducing microwave absorbing materials in the cavity. A perturbation model approach was developed to estimate the quality factor of loaded cavities, which is validated against full-wave simulations and experiments. Results with 78.7 mils (2 mm) thick ECCOSORB-MCS absorber placed on the inside cavity wall above and below the aperture slot (with only 0.026% cavity volume) result in a reduction of shielding effectiveness >19 dB and reductions in quality factor >91%, providing confirmation of the efficacy of this approach.

The flow rates and aerosol transmission properties were evaluated for an engineered microchannel with characteristic dimensions similar to those of stress corrosion cracks (SCCs) capable of forming in dry cask storage systems (DCSS) for spent nuclear fuel. Pressure differentials covering the upper limit of commercially available DCSS were also examined. These preliminary data sets are intended to demonstrate a new capability to characterize SCCs under well-controlled boundary conditions.

We have investigated cubic zirconium tungstate (ZrW2O8) using density functional perturbation theory (DFPT), along with experimental characterization to assess and validate computational results. Cubic zirconium tungstate is among the few known materials exhibiting isotropic negative thermal expansion (NTE) over a broad temperature range, including room temperature where it occurs metastably. Isotropic NTE materials are important for technological applications requiring thermal-expansion compensators in composites designed to have overall zero or adjustable thermal expansion. While cubic zirconium tungstate has attracted considerable attention experimentally, a very few computational studies have been dedicated to this well-known NTE material. Therefore, spectroscopic, mechanical and thermodynamic properties have been derived from DFPT calculations. A systematic comparison of the calculated infrared, Raman, and phonon density-of-state spectra has been made with Fourier transform far-/mid-infrared and Raman data collected in this study, as well as with available inelastic neutron scattering measurements. The thermal evolution of the lattice parameter computed within the quasi-harmonic approximation exhibits negative values below the Debye temperature, consistent with the observed negative thermal expansion characteristics of cubic zirconium tungstate, α-ZrW2O8. These results show that this DFPT approach can be used for studying the spectroscopic, mechanical and thermodynamic properties of prospective NTE ceramic waste forms for encapsulation of radionuclides produced during the nuclear fuel cycle.

Pyrolysis of materials at high heat fluxes are less well-studied because the high heat flux regime is not as common to many practical fire applications. The fire behavior of organic materials in such an environment needs further characterization in order to construct models to predict the dynamics in this regime. The test regime is complicated because of the temperatures achieved and the speed at which materials decompose, due to the flux condition. A series of tests has been performed, which exposed a variety of materials to this environment. The resulting imagery from the tests provides some unique insights into the behavior of various materials at these conditions. Furthermore, experimental and processing techniques suggest analytical methods that can be employed to extract quantitative information from pyrolysis experiments.

A variety of energy sources produce intense radiative flux (»100 kW/m2) well beyond those typical of fire environments. Such energy sources include directed energy, nuclear weapons, and propellant fires. Studies of material response to irradiation typically focus on much lower heat flux; characterization of materials at extreme flux is limited. Various common cellulosic and synthetic-polymer materials were exposed to intense irradiation (up to 3 MW/m2) using the Solar Furnace at Sandia National Laboratories. When irradiated, these materials typically pyrolyzed and ignited after a short time (<1 s). The mass loss for each sample was recorded; the topology of the pyrolysis crater was reconstructed using a commercial three-dimensional scanner. The scans spatially resolved the volumetric displacement, mapping this response to the radially varying flux and fluence. These experimental data better characterize material properties and responses, such as the pyrolysis efflux rate, aiding the development of pyrolysis and ignition models at extreme heat flux.

The DOE and industry collaborators have initiated the high burn-up demonstration project to evaluate the effects of drying and long-term dry storage on high burn-up fuel. Fuel was transferred to a dry storage cask, which was then dried using standard industry vacuum-drying techniques and placed on a storage pad to be opened and the fuel examined in 10 years. Helium fill gas samples were collected 5 hours, 5 days, and 12 days after closure. The samples were analyzed for fission gases (⁸⁵Kr) as an indicator of damaged or leaking rods, and then analyzed to determine water content and concentrations of other trace gases. Gamma-ray spectroscopy found no detectible ⁸⁵Kr. Sample water contents proved difficult to measure, requiring heating to desorb water from the inner surface of the sampling bottles. Final results indicated that water in the cask gas phase built up over 12 days to 17,400 ppmv ±10%, equivalent to ∼100 ml of water within the cask gas phase. Trace gases were measured by direct gas mass spectrometry. Carbon dioxide built up over two weeks to 930 ppmv, likely due to breakdown of hydrocarbon contaminants (possibly vacuum pump oil) in the cask. Hydrogen built up to nearly 500 ppmv. and may be attributable to water radiolysis and/or to metal corrosion in the cask.

For long-term storage, spent nuclear fuel (SNF) is placed in dry storage systems, commonly consisting of welded stainless steel canisters enclosed in ventilated overpacks. Choride-induced stress corrosion cracking (CISCC) of these canisters may occur due to the deliquescence of sea-salt aerosols as the canisters cool. Current experimental and modeling efforts to evaluate canister CISCC assume that the deliquescent brines, once formed, persist on the metal surface, without changing chemical or physical properties. Here we present data that show that magnesium chloride rich-brines, which form first as the canisters cool and sea-salts deliquesce, are not stable at elevated temperatures, degassing HCl and converting to solid carbonates and hydroxychloride phases, thus limiting conditions for corrosion. Moreover, once pitting corrosion begins on the metal surface, oxygen reduction in the cathode region surrounding the pits produces hydroxide ions, increasing the pH under some experimental conditions, leads to precipitation of magnesium hydroxychloride hydrates. Because magnesium carbonates and hydroxychloride hydrates are less deliquescent than magnesium chloride, precipitation of these compounds causes a reduction in the brine volume on the metal surface, potentially limiting the extent of corrosion. If taken to completion, such reactions may lead to brine dry-out, and cessation of corrosion.

Sodium-cooled Fast Reactors (SFRs) have an extended operational history that can be leveraged to accelerate the licensing process for modern designs. Sandia National Laboratories has recently reconstituted the United States SFR data from the Centralized Reliability Data Organization (CREDO) into a new modern database called the Sodium System Component Reliability Database (NaSCoRD). NaSCoRD contains a record of 117 pumps, 60 with a sodium working fluid, that have operated in EBR-II, FFTF, and test loops including those operated by both Westinghouse and the Energy Technology Engineering Center. This paper will present sodium pump failure probabilities for various conditions allowable from the U.S. facility CREDO data that has been recovered under NaSCoRD. The current sodium pump reliability estimates will be presented in comparison to estimates provided in historical studies. The impacts of the suggested corrections from an EG&G Idaho report and various prior distributions on these reliability estimates will also be presented.

Sodium-cooled Fast Reactors (SFRs) have an extended operational history that can be leveraged to accelerate the licensing process for modern designs. Sandia National Laboratories has recently reconstituted the United States SFR data from the Centralized Reliability Data Organization (CREDO) into a new modern database called the Sodium System Component Reliability Database (NaSCoRD). NaSCoRD contains a record of 117 pumps, 60 with a sodium working fluid, that have operated in EBR-II, FFTF, and test loops including those operated by both Westinghouse and the Energy Technology Engineering Center. This paper will present sodium pump failure probabilities for various conditions allowable from the U.S. facility CREDO data that has been recovered under NaSCoRD. The current sodium pump reliability estimates will be presented in comparison to estimates provided in historical studies. The impacts of the suggested corrections from an EG&G Idaho report and various prior distributions on these reliability estimates will also be presented.

Radiation transport in stochastic media is a problem found in a multitude of applications, and the need for tools that are capable of thoroughly modeling this type of problem remains. A collection of approximate methods have been developed to produce accurate mean results, but the demand for methods that are capable of quantifying the spread of results caused by the randomness of material mixing remains. In this work, the new stochastic media transport algorithm Conditional Point Sampling is expanded using Embedded Variance Deconvolution such that it can compute the variance caused by material mixing. The accuracy of this approach is assessed for 1D, binary, Markovian-mixed media by comparing results to published benchmark values, and the behavior of the method is numerically studied as a function of user parameters. We demonstrate that this extension of Conditional Point Sampling is able to compute the variance caused by material mixing with accuracy dependent on the accuracy of the conditional probability function used.

Appropriate waste-forms for radioactive materials must isolate the radionuclides from the environment for long time periods. To accomplish this typically requires low waste-form solubility, to minimize radionuclide release to the environment. However, radiation eventually damages most waste-forms, leading to expansion, crumbling, increased exposed surface area, and faster dissolution. We have evaluated the use of a novel class of materials-ZrW2O8, Zr2P2WO12 and related compounds-that contract upon amorphization. The proposed ceramic waste-forms would consist of zoned grains, or sintered ceramics with center-loaded radionuclides and barren shells. Radiation-induced amorphization would result in core shrinkage but would not fracture the shells or overgrowths, maintaining isolation of the radionuclide. We have synthesized these phases and have evaluated their leach rates. Tungsten forms stable aqueous species at neutral to basic conditions, making it a reliable indicator of phase dissolution. ZrW2O8 leaches rapidly, releasing tungstate while Zr is retained as a solid oxide or hydroxide. Tungsten release rates remain elevated over time and are highly sensitive to contact times, suggesting that this material will not be an effective waste-form. Conversely, tungsten release rates from Zr2P2WO12 rapidly drop and are tied to P release rates; we speculate that a low-solubility protective Zr-phosphate leach layer forms, slowing further dissolution.

Post-closure performance assessment (PA) calculations suggest that deep borehole disposal of cesium (Cs)/strontium (Sr) capsules, a U.S. Department of Energy (DOE) waste form (WF), is safe, resulting in no releases to the biosphere over 10,000,000 years when the waste is placed in a 3-5 km deep waste disposal zone. The same is true when a hypothetical breach of a stuck waste package (WP) is assumed to occur at much shallower depths penetrated by through-going fractures. Cs and Sr retardation in the host rock is a key control over movement. Calculated borehole performance would be even stronger if credit was taken for the presence of the WP.

Porphyrins are vital pigments involved in biological energy transduction processes. Their abilities to absorb light, then convert it to energy, have raised the interest of using porphyrin nanoparticles as photosensitizers in photodynamic therapy. A recent study showed that self- assembled porphyrin-silica composite nanoparticles can selectively destroy tumor cells, but detection of the cellular uptake of porphyrin-silica composite nanoparticles was limited to imaging microscopy. Here we developed a novel method to rapidly identify porphyrin-silica composite nanoparticles using Atmospheric Solids Analysis Probe-Mass Spectrometry (ASAP-MS). ASAP-MS can directly analyze complex mixtures without the need for sample preparation. Porphyrin-silica composite nanoparticles were vaporized using heated nitrogen desolvation gas, and their thermo-profiles were examined to identify distinct mass- to-charge (M/Z) signatures. HeLa cells were incubated in growth media containing the nanoparticles, and after sufficient washing to remove residual nanoparticles, the cell suspension was loaded onto the end of ASAP glass capillary probe. Upon heating, HeLa cells were degraded and porphyrin-silica composite nanoparticles were released. Vaporized nanoparticles were ionized and detected by MS. The cellular uptake of porphyrin-silica composite nanoparticles was identified using this ASAP-MS method.

Energy and cost efficient synthesis pathways are important for the production, processing, and recycling of rare earth metals necessary for a range of advanced energy and environmental applications. In this work, we present results of successful in situ liquid cell transmission electron microscopy production and imaging of rare earth element nanostructure synthesis, from aqueous salt solutions, via radiolysis due to exposure to a 200 keV electron beam. Nucleation, growth, and crystallization processes for nanostructures formed in yttrium(iii) nitrate hydrate (Y(NO3)3·4H2O), europium(iii) chloride hydrate (EuCl3·6H2O), and lanthanum(iii) chloride hydrate (LaCl3·7H2O) solutions are discussed. In situ electron diffraction analysis in a closed microfluidic configuration indicated that rare earth metal, salt, and metal oxide structures were synthesized. Real-time imaging of nanostructure formation was compared in closed cell and flow cell configurations. Notably, this work also includes the first known collection of automated crystal orientation mapping data through liquid using a microfluidic transmission electron microscope stage, which permits the deconvolution of amorphous and crystalline features (orientation and interfaces) inside the resulting nanostructures.

The Nuclear Energy Systems Laboratory (NESL) Brayton Laboratory at Sandia National Laboratories has been at the forefront of supercritical carbon dioxide (sCO2) power cycle development since 2007 when internal R&D funds were used to investigate the stability of sCO2 as a working fluid for power cycles. Since then, Sandia has been a leader in research and development of sCO2 power cycles through government funded research and by partnering with industry to design and test components necessary for commercialization of sCO2 Brayton cycles. Peregrine Turbine Technologies (PTT) is a small business working to commercialize sCO2 power cycles with their proprietary thermodynamic cycles, heat exchangers, and turbomachinery designs. Under a Small Business Innovation Research (SBIR) program with the United States Air Force Research Laboratory, PTT has designed a novel motorless turbocompressor for sCO2 power cycles. In 2017, Sandia purchased the first sCO2 turbocompressor from PTT and installed it into the 1-MW thermal turbomachinery development platform at Sandia. PTT and Sandia have worked together to experimentally test the turbocompressor to the limits of the development platform (932 F @ 2500 psi). This report will detail the design of the turbomachinery development platform, the novel process used to start the turbomachinery, and the experimental results to date. The report will also look at lessons learned throughout the process of constructing and operating an experimental sCO2 loop.

The design of satellites usually includes the objective of minimizing mass due to high launch costs, which is challenging due to the need to protect sensitive electronics from the space radiation environment by means of radiation shielding. This is further complicated by the need to account for uncertainties, e.g. in manufacturing. There is growing interest in automated design optimization and uncertainty quantification (UQ) techniques to help achieve that objective. Traditional optimization and UQ approaches that rely exclusively on response functions (e.g. dose calculations) can be quite expensive when applied to transport problems. Previously we showed how adjoint-based transport sensitivities used in conjunction with gradient-based optimization algorithms can be quite effective in designing mass-efficient electron and/or proton shields in one- or two-dimensional Cartesian geometries. In this paper we extend that work to UQ and to robust design (i.e. optimization that considers uncertainties) in 2D. This consists primarily of using the sensitivities to geometric changes, originally derived for optimization, within relevant algorithms for UQ and robust design. We perform UQ analyses on previous optimized designs given some assumed manufacturing uncertainties. We also conduct a new optimization exercise that accounts for the same uncertainties. Our results show much improved computational efficiencies over previous approaches.

Optical remote sensing has become a valuable tool in many application spaces because it can be unobtrusive, search large areas efficiently, and is increasingly accessible through commercially available products and systems. In the application space of chemical, biological, radiological, nuclear, and explosives (CBRNE) sensing, optical remote sensing can be an especially valuable tool because it enables data to be collected from a safe standoff distance. Data products and results from remote sensing collections can be combined with results from other methods to offer an integrated understanding of the nature of activities in an area of interest and may be used to inform in-situ verification techniques. This work will overview several independent research efforts focused on developing and leveraging spectral and polarimetric sensing techniques for CBRNE applications, including system development efforts, field deployment campaigns, and data exploitation and analysis results. While this body of work has primarily focused on the application spaces of chemical and underground nuclear explosion detection and characterization, the developed tools and techniques may have applicability to the broader CBRNE domain.

Near-wall turbulence models in Large-Eddy Simulation (LES) typically approximate near-wall behavior using a solution to the mean flow equations. This approach inevitably leads to errors when the modeled flow does not satisfy the assumptions surrounding the use of a mean flow approximation for an unsteady boundary condition. Herein, modern machine learning (ML) techniques are utilized to implement a coordinate frame invariant model of the wall shear stress that is derived specifically for complex flows for which mean near-wall models are known to fail. The model operates on a set of scalar and vector invariants based on data taken from the first LES grid point off the wall. Neural networks were trained and validated on spatially filtered direct numerical simulation (DNS) data. The trained networks were then tested on data to which they were never previously exposed and comparisons of the accuracy of the networks’ predictions of wall-shear stress were made to both a standard mean wall model approach and to the true stress values taken from the DNS data. The ML approach showed considerable improvement in both the accuracy of individual shear stress predictions as well as produced a more accurate distribution of wall shear stress values than did the standard mean wall model. This result held both in regions where the standard mean approach typically performs satisfactorily as well as in regions where it is known to fail, and also in cases where the networks were trained and tested on data taken from the same flow type/region as well as when trained and tested on data from different respective flow topologies.

Tolerance Interval Equivalent Normal (TI-EN) and Superdistribution (SD) sparse-sample uncertainty quantification (UQ) methods are used for conservative estimation of small tail probabilities. These methods are used to estimate the probability of a response laying beyond a specified threshold with limited data. The study focused on sparse-sample regimes ranging from N = 2 to 20 samples, because this is reflective of most experimental and some expensive computational situations. A tail probability magnitude of 10−4 was examined on four different distribution shapes, in order to be relevant for quantification of margins and uncertainty (QMU) problems that arise in risk and reliability analyses. In most cases the UQ methods were found to have optimal performance with a small number of samples, beyond which the performance deteriorated as samples were added. Using this observation, a generalized Jackknife resampling technique was developed to average many smaller subsamples. This improved the performance of the SD and TI-EN methods, specifically when a larger than optimal number of samples were available. A Complete Jackknifing technique, which considered all possible sub-sample combinations, was shown to perform better in most cases than an alternative Bootstrap resampling technique.

PFLOTRAN is well-established in single-phase reactive transport problems, and current research is expanding its visibility and capability in two-phase subsurface problems. A critical part of the development of simulation software is quality assurance (QA). The purpose of the present work is QA testing to verify the correct implementation and accuracy of two-phase flow models in PFLOTRAN. An important early step in QA is to verify the code against exact solutions from the literature. In this work a series of QA tests on models that have known analytical solutions are conducted using PFLOTRAN. In each case the simulated saturation profile is rigorously shown to converge to the exact analytical solution. These results verify the accuracy of PFLOTRAN for use in a wide variety of two-phase modelling problems with a high degree of nonlinearity in the interaction between phase behavior and fluid flow.

It is experimentally observed that multilayer fibre–resin composites can soften and swell significantly when heated above their designed operating temperatures. This swelling is expected to further accelerate the pyrolysis, releasing volatile components which can ignite in an oxygenated environment if exposed to a spark, flame or sufficiently elevated temperature. Here the intumescent behaviour of resin-infused carbon-fibre is investigated. Preliminary experiments and simulations are compared for a carbon-fibre sample radiatively heated on the top side and insulated on the bottom. Simulations consider coupled thermal and porous media flow.

The DOE and industry collaborators have initiated the high burn-up demonstration project to evaluate the effects of drying and long-term dry storage on high burn-up fuel. Fuel was transferred to a dry storage cask, which was then dried using standard industry vacuum-drying techniques and placed on a storage pad to be opened and the fuel examined in 10 years. Helium fill gas samples were collected 5 hours, 5 days, and 12 days after closure. The samples were analyzed for fission gases (85Kr) as an indicator of damaged or leaking rods, and then analyzed to determine water content and concentrations of other trace gases. Gamma-ray spectroscopy found no detectible 85Kr. Sample water contents proved difficult to measure, requiring heating to desorb water from the inner surface of the sampling bottles. Final results indicated that water in the cask gas phase built up over 12 days to 17,400 ppmv ±10%, equivalent to ∼100 ml of water within the cask gas phase. Trace gases were measured by direct gas mass spectrometry. Carbon dioxide built up over two weeks to 930 ppmv, likely due to breakdown of hydrocarbon contaminants (possibly vacuum pump oil) in the cask. Hydrogen built up to nearly 500 ppmv. and may be attributable to water radiolysis and/or to metal corrosion in the cask.

Streamline-based quad meshing algorithms use smooth cross fields to partition surfaces into quadrilateral regions by tracing cross field separatrices. In practice, re-entrant corners and misalignment of singularities lead to small regions and limit cycles, negating some of the benefits a quad layout can provide in quad meshing. We introduce three novel methods to improve on a pipeline for coarse quad partitioning. First, we formulate an efficient method to compute high-quality cross fields on curved surfaces by extending the diffusion generated method from Viertel and Osting (SISC, 2019). Next, we introduce a method for accurately computing the trajectory of streamlines through singular triangles that prevents tangential crossings. Finally, we introduce a robust method to produce coarse quad layouts by simplifying the partitions obtained via naive separatrix tracing. Our methods are tested on a database of 100 objects and the results are analyzed. The algorithm performs well both in terms of efficiency and visual results on the database when compared to state-of-the-art methods.

Previous efforts determined a set of calibrated model parameters for ReynoldsAveraged Navier Stokes (RANS) simulations of a compressible jet in crossflow (JIC) using a k-ɛ turbulence model. These coefficients were derived from Particle Image Velocimetry (PIV) data of a complementary experiment using a limited set of flow conditions. Here, k-ɛ models using conventional (nominal) and calibrated parameters are rigorously validated against PIV data acquired under a much wider variety of JIC cases, including a flight configuration. The results from the simulations using the calibrated model parameters showed considerable improvements over those using the nominal values, even for cases that were not used in defining the calibrated parameters. This improvement is demonstrated using quality metrics defined specifically to test the spatial alignment of the jet core as well as the magnitudes of flow variables on the PIV planes. These results suggest that the calibrated parameters have applicability well outside the specific flow case used in defining them and that with the right model parameters, RANS results can be improved significantly over the nominal.

Exposure to chemicals in everyday life is now more prevalent than ever. Air and water pollution can be delivery mechanisms for toxins, carcinogens, and other chemicals of interest (COI). A compact, multiplexed, chemical sensor with high responsivity and selectivity is desperately needed. We demonstrate the integration of unique Zr-based metal organic frameworks (MOFs) with a plasmonic transducer to demonstrate a nanoscale optical sensor that is both highly sensitive and selective to the presence of COI. MOFs are a product of coordination chemistry where a central ion is surrounded by a group of ligands resulting in a thin-film with nano-to micro-porosity, ultra-high surface area, and precise structural tunability. These properties make MOFs an ideal candidate for gaseous chemical sensing, however, transduction of a signal which probes changes in MOF films has been difficult. Plasmonic sensors have performed well in many sensing environments, but have had limited success detecting gaseous chemical analytes at low levels. This is due, in part, to the volume of molecules required to interact with the functionalized surface and produce a detectable shift in plasmonic resonance frequency. The fusion of a highly porous thin-film layer with an efficient plasmonic transduction platform is investigated and summarized. We will discuss the integration and characterization of the MOF/plasmonic sensor and summarize our results which show, upon exposure to COI, small changes in optical characteristics of the MOF layer are effectively transduced by observing shifts in plasmonic resonance.

The dynamic model ofWave Energy Converters (WECs) may have nonlinearities due to several reasons such as a nonuniform buoy shape and/or nonlinear power takeoff units. This paper presents the Hamiltonian Surface-Shaping (HSS) approach as a tool for the analysis and design of nonlinear control of WECs. The Hamiltonian represents the stored energy in the system and can be constructed as a function of the WEC's system states, its position, and velocity. The Hamiltonian surface is defined by the energy storage, while the system trajectories are constrained to this surface and determined by the power flows of the applied non-conservative forces. The HSS approach presented in this paper can be used as a tool for the design of nonlinear control systems that are guaranteed to be stable. The optimality of the obtained solutions is not addressed in this paper. The case studies presented here cover regular and irregular waves and demonstrate that a nonlinear control system can result in a multiple fold increase in the harvested energy.

Understanding the viscosity and friction of a fluid under nanoconfinement is the key to nanofluidics research. Existing work on nanochannel flow enhancement has been focused on simple systems with only one to two fluids considered such as water flow in carbon nanotubes, and large slip lengths have been found to be the main factor for the massive flow enhancement. In this study, we use molecular dynamics simulations to study the fluid flow of a ternary mixture of octane-carbon dioxide-water confined within two muscovite and kerogen surfaces. The results indicate that, in a muscovite slit, supercritical CO2 (scCO2) and H2O both enhance the flow of octane due to (i) a decrease in the friction of octane with the muscovite wall because of the formation of thin layers of H2O and scCO2 near the surfaces; and (ii) a reduction in the viscosity of octane in nanoconfinement. Water reduces octane viscosity by weakening the interaction of octane with the muscovite surface, while scCO2 reduces octane viscosity by weakening both octane-octane and octane-surface interactions. In a kerogen slit, water does not play any significant role in changing the friction or viscosity of octane. In contrast, scCO2 reduces both the friction and the viscosity of octane, and the enhancement of octane flow is mainly caused by the reduction of viscosity. Our results highlight the importance of multicomponent interactions in nanoscale fluid transport. The results presented here also have a direct implication in enhanced oil recovery in unconventional reservoirs.

Recently, a Cambrian explosion of a novel, non-volatile memory (NVM) devices known as memristive devices have inspired effort in building hardware neural networks that learn like the brain. Early experimental prototypes built simple perceptrons from nanosynapses, and recently, fully-connected multi-layer perceptron (MLP) learning systems have been realized. However, while backpropagating learning systems pair well with high-precision computer memories and achieve state-of-the-art performances, this typically comes with a massive energy budget. For future Internet of Things/peripheral use cases, system energy footprint will be a major constraint, and emerging NVM devices may fill the gap by sacrificing high bit precision for lower energy. In this paper, we contrast the well-known MLP approach with the extreme learning machine (ELM) or NoProp approach, which uses a large layer of random weights to improve the separability of high-dimensional tasks, and is usually considered inferior in a software context. However, we find that when taking the device non-linearity into account, NoProp manages to equal hardware MLP system in terms of accuracy. While also using a sign-based adaptation of the delta rule for energy-savings, we find that NoProp can learn effectively with four to six 'bits' of device analog capacity, while MLP requires eight-bit capacity with the same rule. This may allow the requirements for memristive devices to be relaxed in the context of online learning. By comparing the energy footprint of these systems for several candidate nanosynapses and realistic peripherals, we confirm that memristive NoProp systems save energy compared with MLP systems. Lastly, we show that ELM/NoProp systems can achieve better generalization abilities than nanosynaptic MLP systems when paired with pre-processing layers (which do not require backpropagated error). Collectively, these advantages make such systems worthy of consideration in future accelerators or embedded hardware.

Patch antennas incorporating a U-shaped slot are well-known to have relatively large (about 30%) impedance bandwidths. This work uses characteristic mode analysis (CMA) to explain the impedance behavior of a classic U-slot patch geometry in terms of coupled mode theory and shows the relevant modes are in-phase and anti-phase coupled modes whose resonant frequencies are governed by coupled mode theory. Additional analysis shows that one uncoupled resonator is the conventional TM01 patch mode and the other is a lumped LC resonator involving the slot and the probe. An equivalent circuit model for the antenna is given wherein element values are extracted from CMA data and which explicitly demonstrates coupling between these two resonators. The circuit model approximately reproduces the impedance locus of the driven simulation. A design methodology based on coupled mode theory and guided by CMA is presented that allows wideband U-slot patch geometries to be designed quickly and efficiently. The methodology is illustrated through example.

Significant testing is required to design and certify primary aircraft structures subject to High Energy Dynamic Impact (HEDI) events; current work under the NASA Advanced Composites Consortium (ACC) HEDI Project seeks to determine the state-of-the-art of dynamic fracture simulations for composite structures in these events. This paper discusses one of three Progressive Damage Analysis (PDA) methods selected for the second phase of the NASA ACC project: peridynamics, through its implementation in EMU. A brief discussion of peridynamic theory is provided, including the effects of nonlinearity and strain rate dependence of the matrix followed by a blind prediction and test-analysis correlation for ballistic impact testing performed for configured skin-stringer panels.

A decentered Zernike overlay is utilized in the design of a field biased off-axis wide field of view reflective imager and the optical performance with this surface type is compared to a conic only solution.

We study an iterative low-rank approximation method for the solution of the steady-state stochastic Navier-Stokes equations with uncertain viscosity. The method is based on linearization schemes using Picard and Newton iterations and stochastic finite element discretizations of the linearized problems. For computing the low-rank approximate solution, we adapt the nonlinear iterations to an inexact and low-rank variant, where the solution of the linear system at each nonlinear step is approximated by a quantity of low rank. This is achieved by using a tensor variant of the GMRES method as a solver for the linear systems. We explore the inexact low-rank nonlinear iteration with a set of benchmark problems, using a model of ow over an obstacle, under various configurations characterizing the statistical features of the uncertain viscosity, and we demonstrate its effectiveness by extensive numerical experiments.

Abstract not provided.

We discuss chemical, structural, and ellipsometry characterization of low temperature epitaxial Si. While low temperature growth is not ideal, we are still able to prepare crystalline Si to cap functional atomic precision devices.

Abstract not provided.

Abstract not provided.

The study of hypersonic flows and their underlying aerothermochemical reactions is particularly important in the design and analysis of vehicles exiting and reentering Earth’s atmosphere. Computational physics codes can be employed to simulate these phenomena; however, code verification of these codes is necessary to certify their credibility. To date, few approaches have been presented for verifying codes that simulate hypersonic flows, especially flows reacting in thermochemical nonequilibrium. In this paper, we present our code-verification techniques for hypersonic reacting flows in thermochemical nonequilibrium, as well as their deployment in the Sandia Parallel Aerodynamics and Reentry Code (SPARC).

We report measurements of a+/− 5 mm toroidal variation of the outer strike point radial position using an array of three identical Langmuir probes distributed at 90° intervals around the torus (90° 180° 270°). The strike point radial location is determined from the profiles of floating potential (Vf) measured by the three 6 mm diameter domed Langmuir probes as the strike point is swept radially on a horizontal tile surface just outside of the upper small angle slot (SAS1) divertor. Based on the three probe measurements, the strike point variation is consistent with previous error field measurements by Schaffer [1,2] and estimates by Luxon [3] which indicated the strike point error could appear as an n = 1 radial variation of 4.5 mm at the outer mid plane and thus could be effectively described with a three point measurement. The results are also consistent with field line tracing calculations using the MAFOT code [4]. The small angle slot (SAS1) divertor performance is particularly sensitive to a misalignment with the divertor plasma since enhanced neutral confinement and recycling in the slot and distribution of neutrals along the slot surfaces are important for achieving divertor detachment at the lowest possible core plasma separatrix density. These strike point measurements are discussed with regard to the slot divertor alignment.

Photovoltaic (PV) power plants and their constituent components, by virtue of their application, are exposed to some of the harshest outdoor terrestrial environments. Most equipment is subject directly to the environment and myriad stresses (micro and macro environment). Other aspects including local site conditions, construction variability and quality, and maintenance practices also influence the likelihood of such hazards. Many discrete components, including PV modules, wires, connectors, wire management devices, combiner boxes, protection devices, inverters, and transformers, make up the PV generation system. While there are abundant data that illustrate PV modules and PV inverters to be the major contributors of PV system failures, the mentioned data illustrate the importance of minimizing failures in the often ignored components such as PV connectors, PV wires (both above and below ground), wire splices, fuses, fuse holders, fuse holder enclosures, and wire management devices. With the exception of PV fuses, these components predominantly use polymeric materials. Therefore, it is crucial to understand the typical materials used in components, degradation processes and mechanisms leading to component failure, and their impact on system performance or failure. It further provides some practical considerations, approaches, and methods in addressing the problems with practical solutions in the design to assure the performance of the PV plant over the intended design lifetime.

Reliable structural health monitoring (SHM) systems can automatically process data, assess structural condition and signal the need for human intervention. There is a significant need for formal SHM technology validation and quantitative performance assessment processes to uniformly and comprehensively support the evolution and adoption of SHM systems. In recent years, the SHM community has made significant advances in its efforts to evolve statistical methods for analyzing data from in-situ sensors. Several statistical approaches have been demonstrated using real data from multiple SHM technologies to produce Probability of Detection (POD) performance measures. Furthermore, limited comparisons of these methods - utilizing different simplification assumptions and data types - have shown them to produce similar POD values. Given these encouraging results, it is important to understand the circumstances under which the data was acquired. Thus far, the statistical analyses have assumed the viability of the data outright and focused on the performance quantification process once acceptable data has been compiled. This paper will address the array of parameters that must be considered when conducting tests to acquire representative SHM data. For some SHM applications, it may not be possible to simulate all environments in one single test. All relevant parameters must be identified and considered by properly merging results from multiple tests. Laboratory tests, for example, may have separate fatigue and environmental response components. Flight tests, which will likely not include statistically-relevant damage detection opportunities, will still play an important role in assessing overall SHM system performance under an aircraft operator's control. One statistical method, the One-Sided Tolerance Interval (OSTI) approach, will be discussed along with the test methods used to acquire the data. Finally, prospects for streamlining the deployment of SHM solutions will be considered by comparing SHM data needs during what is now an introductory phase of SHM usage with future data needs after a substantial database of SHM data and usage history has been compiled.

Femtosecond Laser Electronic Excitation Tagging (FLEET) is used to measure velocity flowfields in the wake of a sharp 7◦ half-angle cone in nitrogen at Mach 8, over freestream Reynolds numbers from 4.3∗106 /m to 13.8∗106 /m. Flow tagging reveals expected wake features such as the separation shear layer and two-dimensional velocity components. Frequency-tripled FLEET has a longer lifetime and is more energy efficient by tenfold compared to 800 nm FLEET. Additionally, FLEET lines written with 267 nm are three times longer and 25% thinner than that written with 800 nm at a 1 µs delay. Two gated detection systems are compared. While the PIMAX 3 ICCD offers variable gating and fewer imaging artifacts than a LaVision IRO coupled to a Photron SA-Z, its slow readout speed renders it ineffective for capturing hypersonic velocity fluctuations. FLEET can be detected to 25 µs following excitation within 10 mm downstream of the model base, but delays greater than 4 µs have deteriorated signal-to-noise and line fit uncertainties greater than 10%. In a hypersonic nitrogen flow, exposures of just several hundred nanoseconds are long enough to produce saturated signals and/or increase the line thickness, thereby adding to measurement uncertainty. Velocity calculated between the first two delays offer the lowest uncertainty (less than 3% of the mean velocity).