Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016), and Hadgu et al. (2017). The TSPA computing hardware (2014 server cluster -CL2014) and storage system described in Hadgu et al. (2015) were used for the current analysis. One floating license of Gold Sim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The FY18 task included developing an inventory of software used for the Yucca Mountain Project process models and preliminary assessment of status of the software; enhancing security of the cluster and setting a backup system. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.
Statechart modelling notations, with so-called ‘run to completion’ semantics and simulation tools for validation, are popular with engineers for designing systems. However, they do not support formal refinement and they lack formal static verification methods and tools. For example, properties concerning the synchronisation between different parts of a system may be difficult to verify for all scenarios, and impossible to verify at an abstract level before the full details of substates have been added. Event-B, on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible, restricting instantiation and testing to a validation role. In this paper, we introduce a notion of refinement, similar to that of Event-B, into a ‘run to completion’ Statechart modelling notation, and leverage Event-B’s tool support for proof. We describe the pitfalls in translating ‘run to completion’ models into Event-B refinements and suggest a solution. We illustrate the approach using our prototype translation tools and show by example, how a synchronisation property between parallel Statecharts can be automatically proven at an intermediate refinement level.
Random vibration tests have been conducted for over 5 decades using vibration machines which excite a test item in uniaxial motion. With the advent of multi shaker test systems, excitation in multiple axes and/or at multiple locations is feasible. For random vibration testing, both the auto spectrum of the individual controls and the cross spectrum, which defines the relationship between the controls, define the test environment. This is a striking contrast to uniaxial testing where only the control auto spectrum is defined. In a vibration test the energy flow proceeds from drive excitation voltages to control acceleration auto and cross spectral densities and finally, to response auto and cross spectral densities. This paper examines these relationships, which are encoded in the frequency response function. Following the presentation of a complete system diagram, examination of the relationships between the excitation and control spectral density matrices is clarified. It is generally assumed that the control auto spectra are known from field measurements, but the control cross spectra may be unknown or uncertain. Given these constraints, control algorithms often prioritize replication of the field auto spectrum. The system dynamics determine the cross spectrum. The Nearly Independent Drive Algorithm, described herein, is one approach. A further issue in Multi Input Multi Response testing is the link between cross spectrum at one set of locations and auto spectra at a second set of locations. The effect of excitation cross spectra on control auto spectra is one important case, encountered in every test. The effect of control cross spectra on response auto spectra is important since we may desire to adjust control cross spectra to achieve some desired response auto spectra. The relationships between cross spectra at one set of locations and auto spectra at another set of locations is examined with the goal of elucidating the advantages and limitations of using control cross spectra to define response auto spectra.
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.
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.
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.
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.
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.
Power production of the turbines at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at the Texas Tech University’s National Wind Institute Research Center was measured experimentally and simulated for neutral atmospheric boundary layer operating conditions. Two V27 wind turbines were aligned in series with the dominant wind direction, and the upwind turbine was yawed to investigate the impact of wake steering on the downwind turbine. Two conditions were investigated, including that of the leading turbine operating alone and both turbines operating in series. The field measurements include meteorological evaluation tower (MET) data and light detection and ranging (lidar) data. Computations were performed by coupling large eddy simulations (LES) in the three-dimensional, transient code Nalu-Wind with engineering actuator line models of the turbines from OpenFAST. The simulations consist of a coarse precursor without the turbines to set up an atmospheric boundary layer inflow followed by a simulation with refinement near the turbines. Good agreement between simulations and field data are shown. These results demonstrate that Nalu-Wind holds the promise for the prediction of wind plant power and loads for a range of yaw conditions.
Bayesian optimization is an effective surrogate-based optimization method that has been widely used for simulation-based applications. However, the traditional Bayesian optimization (BO) method is only applicable to single-fidelity applications, whereas multiple levels of fidelity exist in reality. In this work, we propose a bi-fidelity known/unknown constrained Bayesian optimization method for design applications. The proposed framework, called sBF-BO-2CoGP, is built on a two-level CoKriging method to predict the objective function. An external binary classifier, which is also another CoKriging model, is used to distinguish between feasible and infeasible regions. The sBF-BO-2CoGP method is demonstrated using a numerical example and a flip-chip application for design optimization to minimize the warpage deformation under thermal loading conditions.
Safety basis analysts throughout the U.S. Department of Energy (DOE) complex rely heavily on the information provided in the DOE Handbook, DOE-HDBK-3010, Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities, to determine radionuclide source terms from postulated accident scenarios. In calculating source terms, analysts tend to use the DOE Handbook's bounding values on airborne release fractions (ARFs) and respirable fractions (RFs) for various categories of insults (representing potential accident release categories). This is typically due to both time constraints and the avoidance of regulatory critique. Unfortunately, these bounding ARFs/RFs represent extremely conservative values. Moreover, they were derived from very limited small-scale bench/laboratory experiments and/or from engineered judgment. Thus, the basis for the data may not be representative of the actual unique accident conditions and configurations being evaluated. The goal of this research is to develop a more accurate and defensible method to determine bounding values for the DOE Handbook using state-of-art multi-physics-based computer codes. This enables us to better understand the fundamental physics and phenomena associated with the types of accidents in the handbook. In this fourth year, we improved existing computational capabilities to better model fragmentation situations to capture small fragments during an impact accident. In addition, we have provided additional new information for various sections of Chapters 4 and 5 of the Handbook on free fall powders and impacts of solids, and have provided the damage ratio simulations for containers (7A drum and standard waste box) for various drops and impact scenarios. Thus, this work provides a low-cost method to establish physics-justified safety bounds by considering specific geometries and conditions that may not have been previously measured and/or are too costly to perform during an experiment.
We study semiconductor hyperbolic metamaterials (SHMs) at the quantum limit experimentally using spectroscopic ellipsometry as well as theoretically using a new microscopic theory. The theory is a combination of microscopic density matrix approach for the material response and Green’s function approach for the propagating electric field. Our approach predicts absorptivity of the full multilayer system and for the first time allows the prediction of in-plane and out-of-plane dielectric functions for every individual layer constructing the SHM as well as effective dielectric functions that can be used to describe a homogenized SHM.
