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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

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

SRAM-Based Digital Arbiter PUF

The increased use of Field Programmable Gate Arrays (FPGAs) in critical systems brings new challenges in securing the diversely programmable fabric from cyber-attacks. FPGAs are an inexpensive, efficient, and flexible alternative to Application Specific Integrated Circuits (ASICs), which are becoming increasingly expensive and impractical for low volume manufacturing as technology nodes continue to shrink. Unfortunately, FPGAs are not designed for high security applications, and their high-flexibility lends itself to low security and vulnerability to malicious attacks. Similar to securing an ASIC’s functionality, FPGA programmers can exploit the inherent randomness introduced into hardware structures during fabrication for security applications. Physically Unclonable Functions (PUFs) are one such solution that uses the die specific variability in hardware fabrication for both secret key generation and verification. PUFs strive to be random, unique, and reliable. Throughout recent years many PUF structures have been presented to try and maximize these three design constraints, reliability being the most difficult of the three to achieve. This thesis presents a new PUF structure that combines two elementary PUF concepts (a bi-stable SRAM PUF and a delay-based arbiter PUF) to create a PUF with increased reliability, while maintaining both random and unique qualities. Properties of the new PUF will be discussed as well as the various design modifications that can be made to tweak the desired performance and overhead.

97 MATHEMATICS AND COMPUTING↗

Conditional Generative Adversarial Networks for Solving Heat Transfer Problems

Generative Adversarial Networks (GANs) have been used as a deep learning approach to solving physics and engineering problems. Using deep learning for these problems is attractive in that reasonably accurate models can be inferred from only raw data, eliminating the need to define the exact physical equations governing a problem. We expand on previous work using GANs to generate steady-state solutions to the two-dimensional heat equation. Using a basic conditional GAN (cGAN), we generate accurate solutions for rectangular domains conditioned on four edge boundary conditions (MAE < 0.5%). For finding steady-state solutions over arbitrary two-dimensional domains (not constrained to rectangles), we use a cGAN designed for image-to-image translation. We train this GAN on various types of geometric domains (circles, squares, triangles, shapes with one circular or rectangular hole), achieving accurate results on test data made up of geometries similar to those in training (MAE < 1%). For both of these GANs, we experiment with different loss function terms, showing that a term using the gradients of solution images significantly improves the basic cGAN but not the image-to-image GAN. Lastly, we show that the image-to-image GAN performs poorly when applied to two-dimensional geometries that vary in structure from training data (MAE < 8% for shapes with multiple holes or different shaped holes). This demonstrates the cGAN's lack of generalizability. While the cGAN is an accurate and computationally efficient method when trained and tested on similarly structured data, it is a much less reliable method when applied to data that is slightly different in structure from the training data.

97 MATHEMATICS AND COMPUTING↗

Nanosecond rf-Power Switch for Gyrotron-Driven Millimeter-Wave Accelerators

The development of alternative mm-wave high-gradient, >200 MV/m, accelerating structures offers a promising path to reduce the cost and footprint of future TeV-scale linear colliders, as well as linacs for industrial, medical, and security applications. The major factor limiting accelerating gradient is vacuum rf breakdown. The probability of such breakdowns increases with pulse length. For reliable operation, millimeter-wave structures require nanoseconds-long pulses at the megawatt level. This power is available from gyrotrons, which have a minimum pulse length on the order of microseconds. To create shorter pulses and to reliably detect rf breakdowns, we developed the following devices: a laser-based rf switch capable of selecting 10 ns long pulses out of the microseconds long gyrotron pulses, thus enabling the use of the gyrotrons as power sources for mm-wave high-gradient linacs, and a shot-to-shot sub-THz spectrometer with high-frequency resolution, capable of detecting pulse shortening due to rf breakdowns. We will describe the principle of operation of these devices and their achieved parameters. Here, we also report on the experimental demonstration of these devices with the high-power gyrotron at the Massachusetts Institute of Technology. In the experiments, we demonstrate nanosecond rf power modulation, shot-to-shot measurements of the pulse spectra, and detection of rf breakdowns.

43 PARTICLE ACCELERATORS↗

Probabilistic Modeling of Landfill Subsidence Introduced by Buried Structure Collapse - 13229

The long-term reliability of land disposal facility final cover systems - and therefore the overall waste containment - depends on the distortions imposed on these systems by differential settlement/subsidence. The evaluation of differential settlement is challenging because of the heterogeneity of the waste mass and buried structure placement. Deterministic approaches to long-term final cover settlement prediction are not able to capture the spatial variability in the waste mass and sub-grade properties, especially discontinuous inclusions, which control differential settlement. An alternative is to use a probabilistic model to capture the non-uniform collapse of cover soils and buried structures and the subsequent effect of that collapse on the final cover system. Both techniques are applied to the problem of two side-by-side waste trenches with collapsible voids. The results show how this analytical technique can be used to connect a metric of final cover performance (inundation area) to the susceptibility of the sub-grade to collapse and the effective thickness of the cover soils. This approach allows designers to specify cover thickness, reinforcement, and slope to meet the demands imposed by the settlement of the underlying waste trenches. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessing the reliability of the NIST library during routine GC-MS analyses: Structure and spectral data corroboration for 5,5-diphenyl-1,3-dioxolan-4-one during a recent OPCW proficiency test

In the field of analytical chemistry, it is the nature of the available instrumentation that makes a specific technique uniquely suited for answering a specific challenge. Often times, instruments equipped with ultrasensitive array of detectors and state-of-the-art separation components have served to highlight their invaluable role in the field. Nonetheless, it is their ultimate ability to predict the structure of an unknown material on the basis of mass spectral data that exponentially magnifies their value. Their efficacy in achieving this prediction is largely based on the size of their internal mass spectral library that conveniently can be accessed by using the software. The library can thus exhaustively correlate an unknown compound's mass spectrum to known compounds in a database and provide the analytical chemist with a probable structure for the unknown analyte. During routine analysis, it is customary that after the appropriate collection of the compound's mass spectrum, the next step involves its comparison with a compound in the instrument's National Institute of Standards and Technology (NIST) library.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗