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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2026

HDSense: An efficient method for ranking observable sensitivity

Identifying which observables most effectively constrain model parameters can be computationally prohibitive when considering full likelihoods of many correlated observables. This is especially important for, e.g., hadronization models, where high precision is required to interpret the results of collider experiments. We introduce the High-Dimensional Sensitivity (HDSense) score, a computationally efficient metric for ranking observable sets using only one-dimensional histograms. Derived by profiling over unknown correlations in the Fisher information framework, the score balances total information content against redundancy between observables. We apply HDSense to rank a set observables in terms of their constraining power with respect to five parameters of the Lund string model of hadronization implemented in Pythia using simulated leptonic collider events at the $Z$ pole. Validation against machine-learning--based full-likelihood approximations demonstrates that HDSense successfully identifies near-optimal observable subsets. The framework naturally handles data from multiple experiments with different acceptances and incorporates detector effects. While demonstrated on hadronization models, the methodology applies broadly to generic parameter estimation problems where correlations are unknown or difficult to model.

Assi, Benoît [Cincinnati U.] (ORCID:00000003092433↗
DOE OSTI2023

Interface Coating Design for Dynamic Voltage Stability of Solid‐State Batteries

Abstract Intrinsic or interface thermodynamic voltage windows of solid electrolytes are often narrower than the operational voltage range needed by a full battery, thus various interface decomposition reactions can happen in a practical solid‐state battery. Experimentally, it is found that a proper battery design utilizing the reactions can lead to a dynamic evolution from interface instability to stability, giving the so‐called dynamic voltage stability for advanced battery performance. Here, first the state‐of‐the‐art understanding is articulated about how the dynamic voltage stability should be interpreted in physical picture and treated in computation, emphasizing the potential importance of nonequilibrium reaction pathways. The constrained ensemble computational approach is further applied across most types of solid‐state electrolytes to systematically evaluate and compare their dynamic stability voltage windows in response to the mechanical constriction effect. High‐throughput calculations are used to search for coating materials for different interfaces between sulfide, halide, and oxide electrolytes and typical cathode materials with enhanced dynamic voltage stability. A comparison with experiment is given to highlight the value of these computational predictions.

Wang, Yichao↗
DOE OSTI2020

Computationally Efficient Decompositions of Oblique Projection Matrices

Oblique projection matrices arise in problems in weighted least squares, signal processing, and optimization. While these matrices can be potentially very large, their low-rank structure can be exploited for efficient computation. Here, we propose fast and scalable algorithms for computing their eigendecomposition and singular value decomposition (SVD). Numerical experiments that compare our proposed approaches to existing methods, including randomized SVD, are presented. In addition, we test their accuracy on linear systems from equality constrained optimization problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Plasma Science and Innovation Center (PSI-Center) at Washington, Wisconsin, and Utah State, ARRA Supplement

The objective of the Plasma Science and Innovation Center (PSI-Center) is to develop and deploy computational models that simulate conditions in smaller, concept-exploration plasma experiments. The PSIC group at the University of Wisconsin-Madison, led by Prof. Carl Sovinec, uses and enhances the Non-Ideal Magnetohydrodynamics with Rotation, Open Discussion (NIMROD) code, to simulate macroscopic plasma dynamics in a number of magnetic confinement configurations. These numerical simulations provide information on how magnetic fields and plasma flows evolve over all three spatial dimensions, which supplements the limited access of diagnostics in plasma experiments. The information gained from simulation helps explain how plasma evolves. It is also used to engineer more effective plasma confinement systems, reducing the need for building many experiments to cover the physical parameter space. The ultimate benefit is a more cost-effective approach to the development of fusion energy for peaceful power production. The supplemental funds provided by the American Recovery and Reinvestment Act of 2009 were used to purchase computer components that were assembled into a 48-core system with 256 Gb of shared memory. The system was engineered and constructed by the group's system administrator at the time, Anthony Hammond. It was successfully used by then graduate student, Dr. John O'Bryan, for computing magnetic relaxation dynamics that occur during experimental tests of non-inductive startup in the Pegasus Toroidal Experiment (pegasus.ep.wisc.edu). Dr. O'Bryan's simulations provided the first detailed explanation of how the driven helical filament of electrical current evolves into a toroidal tokamak-like plasma configuration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Development of Non Destructive Assay Approach for Characterization of Spent Fuel Debris at Fukushima - 18543

Fukushima is considering options for decommissioning the damaged reactor. One of the technical challenges is the accurate characterization of fissile isotopes in the spent fuel debris. This is due to the fissile content, high gamma and neutron emission and uncertainties regarding the fuel burnup and unknown, heterogeneous mixture of materials that may be present. These requirements lead to significant challenges for potential measurement approaches with regard to the requirements for shielding and remote operation that result from plant and operational constraints. Mirion Technologies (MTKK) has been working to perform feasibility and concept design studies for a non-destructive assay (NDA) system that could be used to characterize the fissile content of retrieved samples of fuel debris. The main advantage of using an NDA technique is that the entire volume of the sample is interrogated so the method is not reliant upon assumptions of representativeness of samples retrieved and sent for laboratory analysis. The proposed technique comprises a combination of gamma spectroscopy and combined passive / active neutron interrogation with advanced data analysis algorithms in order to determine the maximum available data on the spent fuel properties and obtain a full radionuclide characterization of each sample. This includes quantification of individual fissile nuclides with validated uncertainties. In this paper we describe the NDA techniques and systems that are proposed, their benefits and limitations, and how they may be implemented into a full-scale system for fuel element debris characterization. We describe the studies that were performed based on experience of real systems and research supplemented with extensive computer modelling work to represent the expected fuel element debris properties. The work benefits from Mirion's extensive global physics and engineering expertise in designing, supplying and operating a wide range of NDA systems for diverse applications and in different challenging physical and operational environments. We describe how the advanced and innovative physics techniques that have resulted from Mirion's collective experience in these areas, can be deployed in an NDA system. The final approach that has been developed provides a means for determining the masses of the individual fissile isotopes with robust uncertainties and capable of implementation into an NDA system that meets the expected requirements for an operational plant. We focus on the techniques that have been developed and describe how they are of wider relevance and interest for projects that include challenges for characterisation of fuel residues. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Prediction Uncertainties beyond the Range of Experience: A Case Study in Inertial Confinement Fusion Implosion Experiments

Scientists often predict physical outcomes, e.g., experimental results, with the assistance of computer codes that, at their best, only coarsely approximate reality. Coarse predictions are challenging in critical part due to the multitude of seemingly arbitrary yet consequential decisions that must be made such as choice of relevant data, calibration of code parameters, and construction of empirical discrepancy forms. In this paper, we present a case study in the context of inertial confinement fusion (ICF) implosion experiments where extrapolative predictions are needed with quantified uncertainties. The purpose of this case study is to reflect relevant statistical methods, as applied to ICF model fitting and prediction, to document the numerous decisions that must be made in the prediction pipeline, to extend a complex example in extrapolation to the uncertainty quantification (UQ) community, and to reflect on the challenges we encountered supporting extrapolations with imperfect models and thereby recommend several future research directions. We conclude with a discussion about the UQ community's role in less than ideal predictive scenarios like our ICF exercise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Several Levels of Theory for Description of Isotope Effects in Ozone: Symmetry Effect and Mass Effect

The essential components of theory for the description of isotope effects in recombination reaction that forms ozone are presented, including the introduction of three reaction pathways for symmetric and asymmetric isotopomers, a brief review of relevant experimental data for singly- and doubly substituted isotopologues, the definitions of ζ-effect and η-effect, and the introduction of isotopic enrichment δ. Two levels of theory are developed to elucidate the role of molecular symmetry, atomic masses, vibrational zero-point energies, and rotational excitations in the recombination process. Here, the issue of symmetry is not trivial, since the important factors, such as 1/2 and 2, appear in seven different places in the formalism. It is demonstrated that if all these effects are taken into account properly, then no anomalous isotope effects emerge. At the next level of theory, a model is considered in which one scattering resonance (sitting right at the top of centrifugal barrier) is introduced per ro-vibrational channel. It is found that this approach is equivalent to statistical treatment with partition functions at the transition state. Accurate calculations using hyper-spherical coordinates show that no isotope effects come from difference in the number of states. In contrast, differences in vibrational and rotational energies lead to significant isotope effects. However, those effects appear to be local, found for the rather extreme values of rotational quantum numbers. They largely cancel when rate coefficients are computed for the thermal distribution of rotational excitations. Although large isotope effects (observed in experiments) are not reproduced here, this level of theory can be used as a foundation for more detailed computational treatment, with accurate information about resonance energies and lifetimes computed and included.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine learning of high dimensional data on a noisy quantum processor

Abstract Quantum kernel methods show promise for accelerating data analysis by efficiently learning relationships between input data points that have been encoded into an exponentially large Hilbert space. While this technique has been used successfully in small-scale experiments on synthetic datasets, the practical challenges of scaling to large circuits on noisy hardware have not been thoroughly addressed. Here, we present our findings from experimentally implementing a quantum kernel classifier on real high-dimensional data taken from the domain of cosmology using Google’s universal quantum processor, Sycamore. We construct a circuit ansatz that preserves kernel magnitudes that typically otherwise vanish due to an exponentially growing Hilbert space, and implement error mitigation specific to the task of computing quantum kernels on near-term hardware. Our experiment utilizes 17 qubits to classify uncompressed 67 dimensional data resulting in classification accuracy on a test set that is comparable to noiseless simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Improving the stability and performance of MagLIF implosions by applying dielectric coatings and increasing applied B z , fuel preheat, and load current

We report two magnetized liner inertial fusion (MagLIF) experiments that produced record thermonuclear D–D neutron yields of 2.11×10 13 and 2.33×10 13 . These yields are about a factor of two higher than previous MagLIF results. The experiments achieved ion temperatures of 3.0 and 3.3 keV and stagnation pressures of 1.6 and 1.3 Gbar. The inferred Lawson parameters were χ=0.2 and 0.1, which are the largest reported for MagLIF. The performance increase used a high-aspect-ratio beryllium liner with a dielectric coating and modest increases in preheat energy (∼2.2 kJ), peak current (18.5 MA), and axial magnetic field (15 T). Three-dimensional HYDRA simulations are consistent with the measured liner dynamics and fusion outputs. These results indicate a pathway to higher-yield MagLIF designs using coated, high-aspect-ratio liners and improved input parameters. Simulations further suggest that adding an ice fuel layer could increase yield by up to a factor of 2.5 by reducing liner convergence, instability feedthrough, and mix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Evaluation of Visualization Heuristics

Heuristics have been used since the early 1990's in the Human Computer Interaction (HCI) domain, for evaluating user interfaces. Most notably, heuristics developed by Nielsen and Molich (1990) have been used by the HCI community. Forsell and Johansson (2010) used the same methodology as Nielsen and Molich and developed a set of 10 heuristics for information visualization. Currently, neither the information visualization or the visual analytics community has adopted these heuristics. However, several studies have been conducted using heuristics. Hearst et al. (2015) found that using the heuristics for visualizations along with asking questions about the data resulted in complementary results as the questions about the data could compensate for heuristics that were difficult to understand and apply. Heli Väätäjä et al. (2016) found that heuristics related to interaction, veracity, and aesthetics needed to be added to the Forsell and Johansson (2010) set. They also noted that a lack of domain knowledge caused the evaluators issues in conducting a heuristic evaluation. We conducted a controlled experiment to determine what factors might impact the expert evaluators' capability to conduct a heuristic evaluation of a static information visualization. In particular, we wanted to understand how their familiarity with the visualizations and their experience in conducting heuristic evaluations impacted their evaluations of visualizations. We recruited 10 participants who were domain experts in the visualization field each having experience with one of more of the following: user experience design or research, user interface development, and human computer interaction research. We used a heuristic set proposed by Forsell and Johansson. Participants were also asked to complete a demographic survey in which they rated their experience with each visualization type generally, their experience conducting heuristic evaluations, their experience using each visualization type to extract information, and their experience developing and creating each visualization type. The participants were shown a series of 5 common visualizations (Scatterplots, Sunbursts, Tree Maps, Parallel Sets, and Area Graphs) all displaying the VAST 2008 Mini Challenge Two- Migrant Boats data . Participants were given a suggested analytical question related to each visualization to keep in mind as they applied the 10 heuristics to each visualization. They were asked if they could find any usability problems in the visualizations and which heuristic(s) helped them to identify these problems. The participants were asked to rate how relevant each heuristic was for evaluating each visualization along with rating how confident they felt in their ability to apply the heuristic to evaluate each visualization. At the conclusion of the study, participants provided qualitative feedback on the usability issues of each visualization. Additionally, we collected eye tracking data on 6 of the 10 participants. We will be using this data to determine how long participants looked at the various visualizations and what parts of the visualizations they focused on. We had two hypotheses for this empirical evaluation: 1.The Forsell and Johansson heuristics of Orientation and help, Data set reduction, and Prompting are less useful for static visualizations because they require some interaction in order to test completely. 2.Participants that do not have experience with heuristic evaluation will provide lower evaluation scores for the heuristics compared to those that have experience. Related to hypothesis 1, as our study used only static visualizations, interaction-related usability challenges should be harder to identify. This should result in lower usefulness ratings for those heuristics. Preliminary results indicate that participants found it more difficult to apply heuristics to unfamiliar visualizations.

Williams, Ryan G.↗
DOE OSTI2026

How Cloud is Accelerating Research at NREL

This presentation coincides with AWS's announcement of their new Parallel Computing Service (PCS) which allows for easy creation of HPC-style clusters in their AWS cloud computing platform. I helped them beta test this service before it was made generally available in August. AWS asked if we would be interested in discussing our experience with the PCS service, and our experience with HPC workloads in the cloud in general, so this slideshow discusses a brief history of scientific computing at NREL and shares a bit of our experiences and approach to utilizing cloud services for HPC-style workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Na ion dynamics in P2-Na x [Ni 1/3 Ti 2/3 ]O 2 : a combination of quasi-elastic neutron scattering and first-principles molecular dynamics study

In this work, the P2-type layered material Na 2/3 [Ni 1/3 Ti 2/3 ]O 2 was studied as a promising bi-functional electrode material for sodium-ion batteries. To assess the electrochemical performance of this material, we investigated the diffusion mechanism as well as ionic and electronic conductivity with a combination of experimental and computational techniques. The quasi-elastic neutron scattering (QENS) experiments and first-principles molecular dynamics (FPMD) simulations were performed to identify the diffusion mechanism. The QENS data showed that Na ion diffusion can be well described by the Singwi–Sjölander jump diffusion model, where the obtained mean jump length matched the distances between the neighboring edge-share and face-share Na sites. FPMD predicted diffusivity values similar to those from QENS. The computed composition dependence of ionic and electronic conductivity of Na x [Ni 1/3 Ti 2/3 ]O 2 suggested that electronic conductivity changes significantly when x deviates from 2/3 as the redox couple of Ni and Ti is activated, while the change of ionic conductivity with x is relatively small.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Bond Dissociation Energies for Diatomic Molecules Containing 3d Transition Metals: Benchmark Scalar-Relativistic Coupled-Cluster Calculations for 20 Molecules

Benchmark scalar-relativistic coupled-cluster calculations for dissociation energies of the 20 diatomic molecules containing 3d transition metals in the 3dMLBE20 database ( J. Chem. Theory Comput. 2015, 11, 2036) are reported in this paper. Electron correlation and basis set effects are systematically studied. The agreement between theory and experiment is in general satisfactory. For a subset of 16 molecules, the standard deviation between computational and experimental values is 9 kJ/mol with the maximum deviation being 15 kJ/mol. The discrepancies between theory and experiment remain substantial (more than 20 kJ/mol) for VH, CrH, CoH, and FeH. To explore the source of the latter discrepancies, the analysis used to determine the experimental dissociation energies for VH and CrH is revisited. It is shown that, if improved values are used for the heterolytic C–H dissociation energies of di- and trimethylamine involved in the experimental determination, the experimental values for the dissociation energies of VH and CrH are increased by 18 kJ/mol, such that D 0 (VH) = 223 ± 7 kJ/mol and D 0 (CrH) = 204 ± 7 kJ/mol (or D e (VH) = 233 ± 7 kJ/mol and D e (CrH) = 214 ± 7 kJ/mol). Finally, the new experimental values agree quite well with the calculated values, showing the consistency of the computation and the measured reaction thresholds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. Lastly, HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

58 GEOSCIENCES↗
DOE OSTI2022

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC

ynchrotron light sources are routinely used to perform imaging experiments. In this paper, we review the relevant computational stages, identify bottlenecks, and highlight future opportunities to streamline data acquisition for experimental microscopy workflows. We demonstrate our preliminary exploration with an end-to-end scientific workflow on Summit based on micro-computed tomography data. Computational elements include: 1) reconstruction of volumetric image data; 2) denoising with deep neural networks; and 3) non-local means based segmentation and quantitative analysis.

Mcclure, James↗
DOE OSTI2021

Effective Field Theory for jet substructure in heavy ion collisions

I develop an Effective Field Theory (EFT) framework to compute jet substructure observables for heavy ion collision experiments. As an example, I consider dijet events that accompany the formation of a weakly coupled long lived Quark Gluon Plasma (QGP) medium in a heavy ion collision and look at an observable insensitive to jet selection bias: the simultaneous measurement of jet mass along with the transverse momentum imbalance between the jets that are groomed to remove soft radiation. Treating the jet as an open quantum system, I write down a factorization formula within the SCET (Soft Collinear Effective Theory) framework in the forward scattering regime. The physics of the medium is encoded in a universal soft field correlator while the jet-medium interaction is captured by a medium induced jet function. The factorization formula leads to a Lindblad type equation for the evolution of the reduced density matrix of the jet in the Markovian approximation. The solution for this equation allows a resummation of large logarithms that arise due to the final state measurements imposed while simultaneously summing over multiple incoherent interactions of the jet with the medium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Advancing Development and Application of Superalloys

This JOM topic is sponsored by the High Temperature Alloys Committee of TMS and addresses advances in the development and application of superalloys. Each year, the High Temperature Alloys Committee organizes symposia at the TMS and Materials Science and Technology annual meetings. In 2020, two symposia were organized for the TMS annual meeting on February 23–27 in San Diego, CA: Materials Design Approaches & Experiences V, co-sponsored by the Integrated Computational Materials Engineering Committee and Advancing Current and State-of-the-Art Applications of Ni- and Co-base Superalloys, co-sponsored by the Corrosion and Environmental Effects Committee. Later this year, the 14th International Symposium on Superalloys will be held on September 13-17 in Seven Springs, PA. The conference, held every 4 years, convenes members of the superalloy community to discuss recent challenges and discoveries affecting future performance and use of superalloys. The TMS High Temperature Alloys Committee meets at both the TMS Annual Meeting & Exhibition and the annual Materials Science and Technology conference. The meetings are open to anyone interested in high-temperature alloys. This special topic on Advancing Development and Application of Superalloys includes a range of sub-topics including mechanical performance, corrosion resistance, processing and advanced manufacturing techniques, which were submitted by research groups from industry, national laboratories and universities.

36 MATERIALS SCIENCE↗