This report describes testing conducted related to the development of a “hydrostatic power takeoff” (HPTO) system for a wave energy converter. Tests were conducted with an experimental electric motor rig to provide preliminary results and de-risk future testing. Efficiency mapping tests were conducted as well as hardware-in-the-loop (HIL) testing. The results of the efficiency mapping tests provide good insight into how to systematically perform efficiency mapping tests. The HIL testing indicates good overall performance of the system and provides a stepping stone towards more complete system tests in the future.
Variational quantum algorithms are a class of techniques intended to be used on near-term quantum computers. The goal of these algorithms is to perform large quantum computations by breaking the problem down into a large number of shallow quantum circuits, complemented by classical optimization and feedback between each circuit execution. One path for improving the performance of these algorithms is to enhance the classical optimization technique. Given the relative ease and abundance of classical computing resources, there is ample opportunity to do so. In this work, we introduce the idea of learning surrogate models for variational circuits using a few experimental measurements, and then performing parameter optimization using these models as opposed to the original data. We demonstrate this idea using a surrogate model based on kernel approximations, through which we reconstruct local patches of variational cost functions using batches of noisy quantum circuit results. Through application to the quantum approximate optimization algorithm and preparation of ground states for molecules, we demonstrate the superiority of surrogate-based optimization over commonly used optimization techniques for variational algorithms.
Under high-cycle fatigue conditions, a fatigue crack in nanocrystalline Pt was observed to undergo healing. The healing appears to occur by cold welding, facilitated by grain boundary migration, and also by local closure stresses. The healing may help explain several observations: role of air (or vacuum) on fatigue life, impeded subsurface fatigue cracking, apparent flaw healing in sub-critical cycling of ceramics, the existence of a fatigue threshold, and the role of vacuum on the fatigue threshold.
High-conductivity solid electrolytes, such as the Na superionic conductor, NaSICON, are poised to play an increasingly important role in safe, reliable battery-based energy storage, enabling advanced sodium-based batteries. Coupled demands of increased current density (≥0.1 A cm-2) and low-temperature (<200 °C) operation, combined with increased discharge times for long-duration storage (>12 h), challenge the limitations of solid electrolytes. Here, we explore the penetration of molten sodium into NaSICON at high current densities. Previous studies of β″-alumina proposed that Poiseuille pressure-driven cracking (mode I) and recombination of ions and electrons within the solid electrolyte (mode II) are the two main mechanisms for Na penetration, but a comprehensive study of Na penetration in NaSICON is necessary, particularly at high current density. To further understand these modes, this work employs unidirectional galvanostatic testing of Na|NaSICON|Na symmetric cells at 0.1 A cm-2 over 23 h at 110 °C. While galvanostatic testing shows a relatively constant yet increasingly noisy voltage profile, electrochemical impedance spectroscopy (EIS) reveals a significant decrease in cell impedance correlated with significant sodium penetration, as observed in scanning electron microscopy (SEM). Further SEM analysis of sodium accumulation within NaSICON suggests that mode II failure may be far more prevalent than previously considered. Further, these findings suggest that total (dis)charge density (mAh cm-2), as opposed to current density (mA cm-2), may be a more critical parameter when examining solid electrolyte failure, highlighting the challenge of achieving long discharge times in batteries using solid electrolytes. Together, these results provide a better understanding of the limitations of NaSICON solid electrolytes under high current and emphasize the need for improved electrode-electrolyte interfaces.
This presentation is on the Molybdenum (Mo) sleeve experiments at the Sandia Critical Experiments Facility. The Institut de Radioprotection et de Sûreté Nucléaire (IRSN) performed the preliminary design of the experiment. IRSN performed the final nuclear design of the experiment. Sandia performed the detailed design of the experiment to make it work in the critical assembly and Sandia also oversaw the fabrication and installation of the hardware. The slides include cutaway and overall views and a look into the results.
This lecture is on the design of a Uranium Dioxide-Beryllium Oxide UO2-BeO Critical Experiment at Sandia. This presentation provides background info on the Annular Core Research Reactor (ACRR). Additionally, this presentation shows experimental and alternative designs and concludes with a sensitivity analysis.
VO2 has shown great promise for sensors, smart windows, and energy storage devices, because of its drastic semiconductor-to-metal transition (SMT) near 340 K coupled with a structural transition. To push its application toward room-temperature, effective transition temperature (Tc) tuning in VO2 is desired. In this study, tailorable SMT characteristics in VO2 films have been achieved by the electrochemical intercalation of foreign ions (e.g., Li ions). By controlling the relative potential with respect to Li/Li+ during the intercalation process, Tc of VO2 can be effectively and systematically tuned in the window from 326.7 to 340.8 K. The effective Tc tuning could be attributed to the observed strain and lattice distortion and the change of the charge carrier density in VO2 introduced by the intercalation process. This demonstration opens up a new approach in tuning the VO2 phase transition toward room-temperature device applications and enables future real-time phase change property tuning.
This presentation provides information on the experiments to measure the effect of Tantalum (Ta) on critical systems. This talk presents details on the Sandia Critical Experiments Program with the Seven Percent Critical Experiment (7uPCX) and the Burnup Credit Critical Experiment (BUCCX). The presentation highlights motivations, experiment design, and evaluations and publications.
Uncertainties in an output of interest that depends on the solution of a complex system (e.g., of partial differential equations with random inputs) are often, if not nearly ubiquitously, determined in practice using Monte Carlo (MC) estimation. While simple to implement, MC estimation fails to provide reliable information about statistical quantities (such as the expected value of the output of interest) in application settings such as climate modeling, for which obtaining a single realization of the output of interest is a costly endeavor. Specifically, the dilemma encountered is that many samples of the output of interest have to be collected in order to obtain an MC estimator that has sufficient accuracy - so many, in fact, that the available computational budget is not large enough to effect the number of samples needed. To circumvent this dilemma, we consider using multifidelity Monte Carlo (MFMC) estimation which leverages the use of less costly and less accurate surrogate models (such as coarser grids, reduced-order models, simplified physics, and/or interpolants) to achieve, for the same computational budget, higher accuracy compared to that obtained by an MC estimator - or, looking at it another way, an MFMC estimator obtains the same accuracy as the MC estimator at lower computational cost. The key to the efficacy of MFMC estimation is the fact that most of the required computational budget is loaded onto the less costly surrogate models so that very few samples are taken of the more expensive model of interest. We first provide a more detailed discussion about the need to consider an alternative to MC estimation for uncertainty quantification. Subsequently, we present a review, in an abstract setting, of the MFMC approach along with its application to three climate-related benchmark problems as a proof-of-concept exercise. Copyright:
The automated kinetics workflow code, KinBot, was used to explore and characterize the regions of the C7H7 potential energy surface that are relevant to combustion environments and especially soot inception. We first explored the lowest-energy region, which includes the benzyl, fulvenallene + H, and cyclopentadienyl + acetylene entry points. We then expanded the model to include two higher-energy entry points, vinylpropargyl + acetylene and vinylacetylene + propargyl. The automated search was able to uncover the pathways from the literature. In addition, three important new routes were discovered: a lower-energy pathway connecting benzyl with vinylcyclopentadienyl, a decomposition mechanism from benzyl that results in side-chain hydrogen atom loss to produce fulvenallene + H, and shorter and lower energy routes to the dimethylene-cyclopentenyl intermediates. We systematically reduced the extended model to a chemically relevant domain composed of 63 wells, 10 bimolecular products, 87 barriers, and 1 barrierless channel and constructed a master equation using the CCSD(T)-F12a/cc-pVTZ//ωB97X-D/6-311++G(d,p) level of theory to provide rate coefficients for chemical modeling. Our calculated rate coefficients show excellent agreement with measured ones. We also simulated concentration profiles and calculated branching fractions from the important entry points to provide an interpretation of this important chemical landscape.
Finite element models can be used to model and predict the hysteresis and energy dissipation exhibited by nonlinear joints in structures. As a result of the nonlinearity, the frequency and damping of a mode is dependent on excitation amplitude, and when the modes remain uncoupled, quasi-static modal analysis has been shown to efficiently predict this behavior. However, in some cases the modes have been observed to couple such that the frequency and damping of one mode is dependent on the amplitude of other modes. To model the interactions between modes, one must integrate the dynamic equations in time, which is several orders of magnitude more expensive than quasi-static analysis. This work explores an alternative where quasi-static forces are applied in the shapes of two or more modes of vibration simultaneously, and the resulting load–displacement curves are used to deduce the effect of other modes on the effective frequency and damping of the mode in question. This methodology is demonstrated on a simple 2D cantilever beam structure with a single bolted joint which exhibits micro-slip nonlinearity over a range of vibration amplitudes. The predicted frequency and damping are compared with those extracted from a few expensive dynamic simulations of the structure, showing that the quasi-static approach produces reasonable albeit highly conservative bounds on the observed dynamics. This framework is also demonstrated on a 3D structure where dynamic simulations are infeasible.
Kustas, Andrew K.; Mann, James B.; Trumble, Kevin P.; Chandrasekar, Srinivasan
Soft magnetic Fe-Si alloys (electrical steels) possess exceptional functional properties such as high permeability, low coercivity, and low core loss, which generally improve with increasing Si content in the alloy. However, Fe-Si alloys containing > 3.5 wt% Si are also characterized by prohibitively low workability and poor ductility that have prevented their efficient commercial production in sheet form by rolling. This has limited their use for improving efficiency of motors and transformers. In this study, hybrid cutting-extrusion (HCE) is used as a single-step thermomechanical processing method to produce continuous Fe-Si alloy sheet with high Si compositions of 4 wt% to 6.5 wt%. HCE sheet is shown to have a homogeneous annealed grain structure and simple-shear crystallographic textures. By controlling the HCE deformation path, varied crystallographic shear textures are created in the sheet. Quasi-static magnetic properties of the HCE sheet are evaluated to decouple the effects of sheet texture and Si composition on resultant permeability and coercivity properties. The results suggest that HCE, with suitable process scaling, is a viable route for production of high-Si content electrical steel sheet for next-generation motors and transformers.
Here this study investigates improving the efficacy of an energy harvesting absorber's ability to control a structure under vortex-induced vibrations, base excitation, and a combination of the two by including mechanical amplitude stoppers. The nonlinear reduced-order model is developed through modifying trilinear spring models to represent the impact forces, a modified van der Pol oscillator to represent the forcing due to the vortex-induced vibrations and using the Euler-Lagrange principle to express the equations of motion. It is seen that a soft stopper stiffness and a 5mm gap performs the most effectively of increasing the power generated from the absorber while still greatly reducing the primary structure's amplitude. By changing the stopper's location towards the middle of the energy harvesting absorber, the large effects of the impact forces are reduced and improves the efficacy of medium and hard stopper stiffnesses to generate near the amount of power the soft stopper does, while greatly improving the control of the primary structure. When the system is under combined loadings, the large oscillations of the synchronization region cause the effective configuration to be that of a 27.5 mm gap with soft stiffnesses. The results shows that medium stiffness stoppers with small gaps generate large aperiodic regions due to the high impact force. When the oscillations are close to the stoppers, the beating phenomenon is observed and is not overpowered by the vibro-impact force.
Understanding the formation of H2CO3 in water from CO2 is important in environmental and industrial processes. Although numerous investigations have studied this reaction, the conversion of CO2 to H2CO3 in nanopores, and how it differs from that in bulk water, has not been understood. We use ReaxFF metadynamics molecular simulations to demonstrate striking differences in the free energy of CO2 conversion to H2CO3 in bulk and nanoconfined aqueous environments. We find that nanoconfinement not only reduces the energy barrier but also reverses the reaction from endothermic in bulk water to exothermic in nanoconfined water. Also, charged intermediates are observed more often under nanoconfinement than in bulk water. Stronger solvation and more favorable proton transfer with increasing nanoconfinement enhance the thermodynamics and kinetics of the reaction. Here our results provide a detailed mechanistic understanding of an important step in the carbonation process, which depends intricately on confinement, surface chemistry, and CO2 concentration.
Material extrusion printing of reactive resins and inks present a unique challenge due to the time-dependent nature of the rheological and chemical properties they possess. As a result, careful print optimization or process control is important to obtain consistent, high quality prints via additive manufacturing. We present the design and use of a near-infrared (NIR) flow through cell for in situ chemical monitoring of reactive resins during printing. Differences between in situ and off-line benchtop measurements are presented and highlight the need for in-line monitoring capability. Additionally, in-line extrusion force monitoring and off-line post inspection using machine vision is demonstrated. By combining NIR and extrusion force monitoring, it is possible to follow cure reaction kinetics and viscosity changes during printing. When combined with machine vision, the ability to automatically identify and quantify print artifacts can be incorporated on the printing line to enable real-time, artificial intelligence-assisted quality control of both process and product. Together, these techniques form the building blocks of an optimized closed-loop process control strategy when complex reactive inks must be used to produce printed hardware.
An in situ ion irradiation scanning electron microscope (I3SEM) has been developed, installed, and integrated into the Ion Beam Laboratory at Sandia National Laboratories. The I3SEM facility combines a field emission, variable pressure, scanning electron microscope, a 6 MV tandem accelerator, high flux low energy ion source, an 808 nm-wavelength laser, and multiple stages to control the thermal and mechanical state of the sample observed. The facility advances real-time understanding of materials evolution under combined environments at the mesoscale. As highlighted in multiple examples, this unique combination of tools is optimized for studying mesoscale material response in overlapping extreme environments, allowing for simultaneous ion irradiation, implantation, laser bombardment, conductive heating, cooling, and mechanical deformation.
Schauer, Lucas; Schmidt, Michael J.; Engdahl, Nicholas B.; Pankavich, Stephen D.; Benson, David A.; Bolster, Diogo
Lagrangian particle tracking schemes allow a wide range of flow and transport processes to be simulated accurately, but a major challenge is numerically implementing the inter-particle interactions in an efficient manner. This article develops a multi-dimensional, parallelized domain decomposition (DDC) strategy for mass-Transfer particle tracking (MTPT) methods in which particles exchange mass dynamically. We show that this can be efficiently parallelized by employing large numbers of CPU cores to accelerate run times. In order to validate the approach and our theoretical predictions we focus our efforts on a well-known benchmark problem with pure diffusion, where analytical solutions in any number of dimensions are well established. In this work, we investigate different procedures for "tiling"the domain in two and three dimensions (2-D and 3-D), as this type of formal DDC construction is currently limited to 1-D. An optimal tiling is prescribed based on physical problem parameters and the number of available CPU cores, as each tiling provides distinct results in both accuracy and run time. We further extend the most efficient technique to 3-D for comparison, leading to an analytical discussion of the effect of dimensionality on strategies for implementing DDC schemes. Increasing computational resources (cores) within the DDC method produces a trade-off between inter-node communication and on-node work. For an optimally subdivided diffusion problem, the 2-D parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to around 2700 cores, reducing a 5gh simulation to 8gs, while the 3-D algorithm maintains appreciable speedup up to 1700 cores.
Rare-earth metals (REMs) are crucial for many important industries, such as power generation and storage, in addition to cancer treatment and medical imaging. One promising new REM refinement approach involves mimicking the highly selective and efficient binding of REMs observed in relatively recently discovered proteins. However, realizing any such bioinspired approach requires an understanding of the biological recognition mechanisms. In this report we developed a new classical polarizable force field based on the AMOEBA framework for modeling a lanthanum ion (La3+) interacting with water, acetate, and acetamide, which have been found to coordinate the ion in proteins. The parameters were derived by comparing to high-level ab initio quantum mechanical (QM) calculations that include relativistic effects. The AMOEBA model, with advanced atomic multipoles and electronic polarization, is successful in capturing both the QM distance-dependent La3+–ligand interaction energies and experimental hydration free energy. A new scheme for pairwise polarization damping (POLPAIR) was developed to describe the polarization energy in La3+ interactions with both charged and neutral ligands. Simulations of La3+ in water showed water coordination numbers and ion–water distances consistent with previous experimental and theoretical findings. Water residence time analysis revealed both fast and slow kinetics in water exchange around the ion. This new model will allow investigation of fully solvated lanthanum ion–protein systems using GPU-accelerated dynamics simulations to gain insights on binding selectivity, which may be applied to the design of synthetic analogues.
Transition metal nitrides (e.g., TiN) have shown tremendous promise in optical metamaterials for nanophotonic devices due to their plasmonic properties comparable to noble metals and superior high temperature stability. Vertically aligned nanocomposites (VANs) offer a great platform for combining two dissimilar functional materials with a one-step deposition technique toward multifunctionality integration and strong structural/property anisotropy. Here, we report a two-phase nanocomposite design combining ferromagnetic CoFe2 nanosheets in the plasmonic TiN matrix as a new hybrid plasmonic metamaterial. The hybrid metamaterials exhibit anisotropic optical and magnetic responses, as well as a pronounced magneto-optical coupling response evidenced by Magneto-optic Kerr Effect measurement, owing to the novel vertically aligned structure. This work demonstrates a new TiN-based metamaterial with anisotropic properties and multifunctionality toward light polarization modulation, optical switching, and integrated optics.
Liu, Renjie; El Berch, John N.; House, Stephen D.; Meil, Samuel W.; Mpourmpakis, Giannis; Porosoff, Marc D.
Reactive separations of CO/CO2 mixtures are a promising pathway to lower the energy requirement of CO2 hydrogenation to chemicals and fuels, with applications in the U.S. Navy’s seawater-to-fuel process. With the CO/CO2 feedstock, a challenge is activating CO to produce heavier hydrocarbons while preventing CO2 methanation, requiring low-temperature Fischer-Tropsch synthesis (FTS) catalysts. In this work, we demonstrate that a Ru–Co single atom alloy (SAA) catalyst produces C5+ hydrocarbons at a rate of 11.7 μmol/s/g-cobalt (hexane basis) in a 50/50 CO/CO2 stream with ≤1% CO2 conversion. The reaction operates at a relatively low temperature (200 °C) and high gas hourly space velocity (GHSV: 84,000 mL/g/h) that is compatible with the upstream reverse water-gas shift reaction. Detailed experiments, catalyst characterizations, and density functional theory (DFT) calculations have been conducted to understand the active phase, the role of the Ru dopant, and catalyst restructuring that occurs at elevated temperatures (>200 °C). Ru dopants are found to promote the reduction of Co species, enabling catalytic activity for CO hydrogenation without pre-reduction, but may not enhance the FTS activity or desired C5+ hydrocarbon selectivity.
Here we examine the utility of the quadratic pseudospectrum for understanding and detecting states that are somewhat localized in position and energy, in particular, in the context of condensed matter physics. Specifically, the quadratic pseudospectrum represents a method for approaching systems with incompatible observables {Aj|1 ≤ j ≤ d} as it minimizes collectively the errors $\parallel$Ajv - λjv$\parallel$ while defining a joint approximate spectrum of incompatible observables. Moreover, we derive an important estimate relating the Clifford and quadratic pseudospectra. Finally, we prove that the quadratic pseudospectrum is local and derive the bounds on the errors that are incurred by truncating the system in the vicinity of where the pseudospectrum is being calculated.
In order to better understand the complex pooling and vaporization of a liquid hydrogen spill, Sandia National Laboratories is conducting a highly instrumented, controlled experiment inside their Shock Tube Facility. Simulations were run before the experiment to help with the planning of experimental conditions, including sensor placement and cross wind velocity. This paper describes the modeling used in this planning process and its main conclusions. Sierra Suite’s Fuego, an in-house computational fluid dynamics code, was used to simulate a RANS model of a liquid hydrogen spill with five crosswind velocities: 0.45, 0.89, 1.34, 1.79, and 2.24 m/s. Two pool sizes were considered: a diameter of 0.85 m and a diameter of 1.7. A grid resolution study was completed on the smaller pool size with a 1.34 m/s crosswind. A comparison of the length and height of the plume of flammable hydrogen vaporizing from the pool shows that the plume becomes longer and remains closer to the ground with increasing wind speed. The plume reaches the top of the facility only in the 0.45 m/s case. From these results, we concluded that it will be best for the spacing and location of the concentration sensors to be reconfigured for each wind speed during the experiment.
Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods is that the resulting model requires significantly less data to train. By incorporating physical rules into the machine learning formulation itself, the predictions are expected to be physically plausible. Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets. In this paper, we investigate the possibility of constraining a GP formulation with monotonicity on three different material datasets, where one experimental and two computational datasets are used. The monotonic GP is compared against the regular GP, where a significant reduction in the posterior variance is observed. The monotonic GP is strictly monotonic in the interpolation regime, but in the extrapolation regime, the monotonic effect starts fading away as one goes beyond the training dataset. Imposing monotonicity on the GP comes at a small accuracy cost, compared to the regular GP. The monotonic GP is perhaps most useful in applications where data are scarce and noisy, and monotonicity is supported by strong physical evidence.
Strong gas-mineral interactions or slow adsorption kinetics require a molecular-level understanding of both adsorption and diffusion for these interactions to be properly described in transport models. In this combined molecular simulation and experimental study, noble gas adsorption and mobility is investigated in two naturally abundant zeolites whose pores are similar in size (clinoptilolite) and greater than (mordenite) the gas diameters. Simulated adsorption isotherms obtained from grand canonical Monte Carlo simulations indicate that both zeolites can accommodate even the largest gas (Rn). However, gas mobility in clinoptilolite is significantly hindered at pore-limiting window sites, as seen from molecular dynamics simulations in both bulk and slab zeolite models. Experimental gas adsorption isotherms for clinoptilolite confirm the presence of a kinetic barrier to Xe uptake, resulting in the unusual property of reverse Kr/Xe selectivity. Finally, a kinetic model is used to fit the simulated gas loading profiles, allowing a comparison of trends in gas diffusivity in the zeolite pores.
A fundamental task of radar, beyond merely detecting a target, is to estimate some parameters associated with it. For example, this might include range, direction, velocity, etc. In any case, multiple measurements, often noisy, need to be processed to yield a ‘best estimate’ of the parameter. A common mathematical method for doing so is called “Regression” analysis. The goal is to minimize the expected squared error in the estimate. Even when alternate algorithms are considered, the least s
Nakagawa, Seiji; Kibikas, William M.; Chang, Chun; Kneafsey, Timothy; Dobson, Patrick; Samuel, Abraham; Bruce, Stephen; Kaargeson-Loe, Nils; Bauer, Stephen J.
Marine energy generation technologies such as wave and tidal power have great potential in meeting the need for renewable energy in the years ahead. Yet, many challenges remain associated with marine-based systems because of the corrosive environment. Conventional materials like metals are subject to rapid corrosive breakdown, crippling the lifespan of structures in such environments. Fiber-reinforced polymer composites offer an appealing alternative in their strength and corrosion resistance, but can experience degradation of mechanical properties as a result of moisture absorption. An investigation is conducted to test the application of a technique for micromechanical analysis of composites, known as multicontinuum theory and demonstrated in past works, as a mechanism for predicting the effects of prolonged moisture absorption on the performance of fiber-reinforced composites. Experimental tensile tests are performed on composite coupons with and without prolonged exposure to a salt water solution to obtain stiffness and strength properties. Multicontinuum theory is applied in conjunction with micromechanical modeling to deduce the effects of moisture absorption on the behavior of constituent materials within the composites. The results are consistent with experimental observations when guided by known mechanisms and trends from previous studies, indicating multicontinuum theory as a potentially effective tool in predicting the long-term performance of composites in marine environments.