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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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Strategies for solving the excited-state self-consistent-field problem for highly excited and multiply ionized states

The dynamics of molecules exposed to intense x-ray radiation involve a large number of multiply ionized and highly excited electronic configurations. To model these dynamics a reliable and efficient electronic structure model is imperative. Employing the Hartree-Fock-Slater electronic structure model in combination with the maximum overlap method, we quantify the associated convergence failures when calculating electronic states of carbon monoxide with multiple vacancies in the core and valence levels. Here, we characterize these cases and describe strategies to overcome the convergence problems. The described techniques not only eliminate all convergence issues for CO but also result in a significant reduction of convergence failures for simulations of the x-ray-induced multiple ionization dynamics of the phenol molecule.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Medium Voltage Energy Hub Based on Multilevel Cascaded H Bridge-Dual Active Bridge Back-to-Back Converter for Power Distribution Feeders Interconnection and Multiple Simultaneous Grid Services

This paper presents a medium voltage energy hub based on a modular design of a multilevel cascaded H bridge (CHB)-dual active bridge (DAB) converter. The energy hub composed of the two CHB-DAB modules with a back-to-back topology can be utilized as a grid interconnection component between distribution feeders. The energy hub can provide multiple simultaneous grid services such as voltage regulation, power factor correction, as well as active power flow control between the connected feeders, contributing to grid flexibility, efficiency, reliability, and resilience. Circuit structure and control schemes for the energy hub including both local controllers for each converter and outer loop controllers are proposed to enable simultaneous grid services with coordination to prevent the overloading of the hub. To validate the performance of the hub, the hub system is interconnected between two IEEE 4-bus feeders and provides voltage regulation for both feeders, while controlling active power flow between them. The system and the feeders are implemented in Real-Time Digital Simulator (RTDS) for real-time simulation verification.

Choi, Jongchan↗
DOE OSTI2016

SU-G-BRB-06: Commissioning and Evaluation of EPID-Based in Vivo Dosimetry Software Using a Tissue-Maximum Ratio Approach

Purpose: To commission and evaluate an in vivo EPID-based transit dosimetry software (EPIgray, DOSIsoft, Cachan, France) using simple fields and TG119-based IMRT treatment plans. Methods: EPIgray was commissioned on a Truebeam based on finite tissue-maximum ratio (fTMR) measurements with solid water blocks of thicknesses between 0 and 37 cm. Field sizes varied from 2×2 to 20×20 cm{sup 2}. Subsequently, treatment plans of single and opposed beams with field sizes between 4×4 and 15×15 cm{sup 2} as well as IMRT plans were measured to evaluate the dose reconstruction accuracy. Single field dose predictions were made for anterior-posterior and lateral beams. IMRT plans were created based on TG119 recommendations. The reconstructed dose was compared to the planned dose for selected points at isocenter and away from isocenter. Results: For single square fields, the dose in EPIgray was reconstructed within 3% accuracy at isocenter relative to the planned dose. Similarly, the relative deviation of the total dose was accurately reconstructed within 3% for all IMRT plans with points placed inside a high dose region near the isocenter. Predictions became less accurate than 5% when the evaluation point was outside the majority of IMRT beam segments. Additionally, points 5 cm or more away from the isocenter or within an avoidance structure were predicted less reliably. Conclusion: EPIgray formalism accuracy is adequate for an efficient error detection system. It provides immediate intra-fractional feedback on the delivery of treatment plans without affecting the treatment beam. Besides the EPID, no additional hardware is required, which makes it accessible to all clinics. The software evaluates point dose measurements to verify treatment plan delivery and patient positioning within 5% accuracy, depending on the placement of evaluation points. EPIgray is not intended to replace patient-specific quality assurance but should be utilized as an additional layer of safety for continuous patient treatment verification. This research is supported by DOSIsoft.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Decoding crystallography from high-resolution electron imaging and diffraction datasets with deep learning

While machine learning has been making enormous strides in many technical areas, it is still massively underused in transmission electron microscopy. To address this, a convolutional neural network model was developed for reliable classification of crystal structures from small numbers of electron images and diffraction patterns with no preferred orientation. Diffraction data containing 571,340 individual crystals divided among seven families, 32 genera, and 230 space groups were used to train the network. Despite the highly imbalanced dataset, the network narrows down the space groups to the top two with over 70% confidence in the worst case and up to 95% in the common cases. As examples, we benchmarked against alloys to two-dimensional materials to cross-validate our deep-learning model against high-resolution transmission electron images and diffraction patterns. We present this result both as a research tool and deep-learning application for diffraction analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological N-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). The power of control variates stems from utilizing inexpensive but highly correlated surrogates of the statistics one wishes to measure. The stronger the correlation between the surrogate and the statistic of interest, the larger the variance reduction delivered by the method. We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements offer a factor of 5-10 improvement in the measurement error compared with the raw measurements. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Doping-Dependent Nodal Fermi Velocity in Bi-2212 Revealed by High-Resolution ARPES

The improved resolution of laser-based angle-resolved photoemission spectroscopy (ARPES) allows reliable access to fine structures in the spectrum. We present a systematic, doping-dependent study of a recently discovered low-energy kink in the nodal dispersion of Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+{delta}} (Bi-2212), which demonstrates the ubiquity and robustness of this kink in underdoped Bi-2212. The renormalization of the nodal velocity due to this kink becomes stronger with underdoping, revealing that the nodal Fermi velocity is non-universal, in contrast to assumed phenomenology. This is used together with laser-ARPES measurements of the gap velocity, v{sub 2}, to resolve discrepancies with thermal conductivity measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Gap Analysis to Support Modeling the Long-Term Degradation of Used Nuclear Fuel Canisters

Welded stainless steel canisters are being used worldwide for dry storage of used nuclear fuel (UNF) assemblies, and the number of canisters in use is steadily increasing. In support of work currently being pursued at Pacific Northwest National Laboratory to understand the atmospheric corrosion behavior of spent fuel dry storage systems, a gap analysis is underway to assess the state of knowledge for modeling of the long-term degradation of a UNF canister. The fundamental aim of this work is to inform research and development (R&D) efforts to establish a sound technical basis to support the extended dry storage of UNF for 100+ years. The analysis is considering all major components of the atmosphere corrosion degradation processes, ranging from contaminant sources and climatic interactions to regional conditions of particle transport and deposition, to microscale effects leading to stress corrosion cracking. The results of this gap analysis will be used to define the R&D pathway to develop an integrated multi-scale atmospheric corrosion modeling capability for UNF in dry storage canisters that can support the safe and reliable performance of these structures for more than 100 years.

Nuclear Fuel Canisters↗
DOE OSTI2016

Effect of Irradiation on Strengthening of a Model Fe-9Cr Oxide Dispersion Strengthened Alloy

The growing energy demand will increasingly call upon advanced nuclear reactors to supply safe and reliable energy worldwide. However, structural and cladding materials in these reactors will be subject to extreme conditions of up to a few hundred displacements per atom (dpa) at temperatures as high as 600 deg. C. Oxide dispersion strengthened (ODS) alloys are leading candidates for these components because their dispersion of Y-Ti-O nanoclusters provides high strength at elevated temperatures and dimensional stability under irradiation. But recent work has suggested that the oxides are unstable under irradiation, which has serious implications on mechanical performance. Thus, the objective of this work is to understand the change in strengthening mechanisms of an Fe-9Cr ODS alloy under irradiation. We use two approaches to assess strengthening of a proton-irradiated and neutron-irradiated Fe-9Cr ODS. First, nanoindentation directly measures changes in yield strength. Second, microstructure measurements are passed through models of two strengthening mechanisms. Results of these two approaches are compared to infer the strengthening mechanisms in the irradiated ODS alloy. A model Fe-9Cr ODS steel was irradiated to 3 dpa at 500 deg. C using either 2.0 MeV protons or a fast neutron spectrum. Both irradiation types induced the formation of dislocation loops and voids. Both proton and neutron irradiation resulted in dissolution of oxide nanoclusters, though neutron irradiation led to much more extensive oxide nano-cluster dissolution. The irradiated microstructure was used to predict irradiation hardening by considering both the precipitation strengthening and solid solution strengthening mechanisms. Due to more extensive oxide nano-cluster dissolution under neutron irradiation, the solid solution strengthening mechanism must be considered in order for the predicted change in yield strength to be comparable to that measured by nanoindentation. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2026

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗
DOE OSTI2015

Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions

A description is given of new tools to facilitate model building and refinement into electron cryo-microscopy reconstructions. The recent rapid development of single-particle electron cryo-microscopy (cryo-EM) now allows structures to be solved by this method at resolutions close to 3 Å. Here, a number of tools to facilitate the interpretation of EM reconstructions with stereochemically reasonable all-atom models are described. The BALBES database has been repurposed as a tool for identifying protein folds from density maps. Modifications to Coot, including new Jiggle Fit and morphing tools and improved handling of nucleic acids, enhance its functionality for interpreting EM maps. REFMAC has been modified for optimal fitting of atomic models into EM maps. As external structural information can enhance the reliability of the derived atomic models, stabilize refinement and reduce overfitting, ProSMART has been extended to generate interatomic distance restraints from nucleic acid reference structures, and a new tool, LIBG, has been developed to generate nucleic acid base-pair and parallel-plane restraints. Furthermore, restraint generation has been integrated with visualization and editing in Coot, and these restraints have been applied to both real-space refinement in Coot and reciprocal-space refinement in REFMAC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Molten Salt Corrosion Tests of Additively Manufactured Stainless Steel 316H

Molten salt reactors (MSRs) have drawn considerable interest due to their favorable safety features, high thermal efficiency, and compatibility with different fuel cycles. Yet, the success of MSRs hinges critically on the performance of structural materials to be used in these aggressive molten salt environments, where corrosion and material compatibility remain primary challenges to long-term reliability. Additively manufactured (AM) nuclear structural materials prompt the use of novel geometries and compositions to enhance material performance and reduce costs of constructing MSRs. The rapid solidification conditions inherent to AM processing impart distinctive microstructural features, including cellular sub-structures, dislocation densities, residual stress, and oxide inclusions, which can influence material performance in MSR components. While the mechanical properties of AM stainless steels have been widely studied, their corrosion behavior, particularly in molten salt environments, has received far less attention. Addressing these needs, the Advanced Materials and Manufacturing Technologies (AMMT) program provides a framework for systematically evaluating how unique microstructures produced by AM processes influence the performance of these materials in these demanding environments and for developing reproducible testing workflows that can support future code qualification efforts and standards development. Bridging this knowledge gap is essential for assessing the viability of AM alloys in MSRs and informing qualification strategies. A further challenge is the absence of standardized protocols for molten salt corrosion testing. Accordingly, this report provides an account of the corrosion evaluation of AM 316H stainless steel in NaCl 2 -MgCl 2 molten salt at 550 °C, with exposure times of 100 and 500 hours. It documents the experimental procedures implemented under the AMMT program, including salt preparation, exposure protocols, and post-test characterization methods, to establish reproducibility and transparency. Importantly, the study examines AM 316H samples in the as-fabricated condition, directly reflecting the surface state most relevant to engineering applications, and compares their behavior to machine-cut surfaces. Overall, preliminary evaluations have noted that surface conditions (e.g. morphology, contamination, etc.) have a noticeable impact on the corrosion resiliency. The impact of the corrosion is difficult to detect at 100h, unless, in the case of AM 316H, the specimen surface is decontaminated. After 500 h, as-fabricated surfaces of AM and wrought 316H display evidence of general versus preferential corrosion attack, respectively. Both AM and wrought 316H machine-cut surfaces exhibit a continuous Cr depletion zone, evident of general corrosion. While the estimated extent of corrosion appears within the same order of magnitude regardless of the surface condition, it is apparent that more predictable behavior is observed on machine-cut surfaces. Nonetheless, further investigation is necessary to fully elucidate the corrosion mechanism under these conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2013

Comparison of API & IEC Standards for Offshore Wind Turbine Applications in the U.S. Atlantic Ocean: Phase II - March 9, 2009 - September 9, 2009

The National Renewable Energy Laboratory (NREL) contracted MMI Engineering to conduct Phase II of the Joint Industry Project on Comparison of two design standards for offshore wind turbines (OWTs) in the United States Outer Continental Shelf waters. The two standards were the American Petroleum Institute (API) RP – 2A Recommended Practice for Planning, Designing, and Constructing Fixed Offshore Platforms and the International Electrotechnical Commission (IEC) 61400-3 Design Requirements for Offshore Wind Turbines. In Phase I, two structure types (a monopile and a tripod) were studied at two sites – offshore Texas at 24-m water depth and offshore Massachusetts at 15-m water depth. This study provided insights into the loads imposed on the structures caused by wind and ocean forces, and also provided insights into the strength (capacity) of the structures subject to these loads. The resulting reliability (annual failure probability for ultimate strength) for the two structures at the two sites were generally governed by turbine and blade resonance avoidance for designing the structure, and not by ultimate strength needs to resist extreme loads. The conclusions drawn from Phase I were based on these limited numbers of case studies. This limitation prompted the need to conduct this second phase to study two new designs, the monopile and a jacket (space frame) substructure, at the same site where ultimate strength would likely also influence design and resonance avoidance. The site selected for Phase II was the offshore Massachusetts site, but with a water depth of 25 m (instead of 15 m as in Phase I). This selection permitted the use of the same meteorological and oceanographic (metocean) parameters, with the breaking wave criteria altered as a result of the increased water depth.

17 WIND ENERGY↗
DOE OSTI2014

The effect of classical and quantum dynamics on vibrational frequency shifts of H{sub 2} in clathrate hydrates

Vibrational frequency shifts of H{sub 2} in clathrate hydrates are important to understand the properties and elucidate details of the clathrate structure. Experimental spectra of H{sub 2} in clathrate hydrates have been measured for different clathrate compositions, temperatures, and pressures. In order to establish reliable relationships between the clathrate structure, dynamics, and observed frequencies, calculations of vibrational frequency shifts in different clathrate environments are required. In this study, a combination of classical molecular dynamics simulations, electronic structure calculations, and quantum dynamical simulation is used to calculate relative vibrational frequencies of H{sub 2} in clathrate hydrates. This approach allows us to assess dynamical effects and simulate the change of vibrational frequencies with temperature and pressure. The frequency distributions of the H{sub 2} vibrations in the different clathrate cage types agree favorably with experiment. Also, the simulations demonstrate that H{sub 2} in the 5{sup 12} cage is more sensitive to the details of the environment and to quantum dynamical effects, in particular when the cage is doubly occupied. We show that for the 5{sup 12} cage quantum effects lead to frequency increases and double occupation is unlikely. This is different for the 5{sup 12}6{sup 4} cages for which higher occupation numbers than one H{sub 2} per cage are likely.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Avoidable errors in deposited macromolecular structures: an impediment to efficient data mining

Whereas the vast majority of the more than 85 000 crystal structures of macromolecules currently deposited in the Protein Data Bank are of high quality, some suffer from a variety of imperfections. Although this fact has been pointed out in the past, it is still worth periodic updates so that the metadata obtained by global analysis of the available crystal structures, as well as the utilization of the individual structures for tasks such as drug design, should be based on only the most reliable data. Here, selected abnormal deposited structures have been analysed based on the Bayesian reasoning that the correctness of a model must be judged against both the primary evidence as well as prior knowledge. These structures, as well as information gained from the corresponding publications (if available), have emphasized some of the most prevalent types of common problems. The errors are often perfect illustrations of the nature of human cognition, which is frequently influenced by preconceptions that may lead to fanciful results in the absence of proper validation. Common errors can be traced to negligence and a lack of rigorous verification of the models against electron density, creation of non-parsimonious models, generation of improbable numbers, application of incorrect symmetry, illogical presentation of the results, or violation of the rules of chemistry and physics. Paying more attention to such problems, not only in the final validation stages but during the structure-determination process as well, is necessary not only in order to maintain the highest possible quality of the structural repositories and databases but most of all to provide a solid basis for subsequent studies, including large-scale data-mining projects. For many scientists PDB deposition is a rather infrequent event, so the need for proper training and supervision is emphasized, as well as the need for constant alertness of reason and critical judgment as absolutely necessary safeguarding measures against such problems. Ways of identifying more problematic structures are suggested so that their users may be properly alerted to their possible shortcomings.

model validation↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗