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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

On Current-Squared Flows and ModMax Theories

We show that the recently introduced ModMax theory of electrodynamics and its Born-Infeld-like generalization are related by a flow equation driven by a quadratic combination of stress-energy tensors. The operator associated to this flow is a 4d 4 d analogue of the T\overline{T} T T ¯ deformation in two dimensions. This result generalizes the observation that the ordinary Born-Infeld Lagrangian is related to the free Maxwell theory by a current-squared flow. As in that case, we show that no analogous relationship holds in any other dimension besides d=4 d = 4 . We also demonstrate that the \mathcal{N}=1 𝒩 = 1 supersymmetric version of the ModMax-Born-Infeld theory obeys a related supercurrent-squared flow which is formulated directly in \mathcal{N} = 1 𝒩 = 1 superspace.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A Proposed Common Model of Multi-phase Strength and Equation of State for a Tri-laboratory Collaboration (Working Draft 1.1)

The proposed simple common model for multiphase strength and EoS (CMMP) is meant to be sufficiently simple that each of the collaborating labs can share in a common starting point. Another objective is to start with relatively simple assumptions, which will not necessarily capture details of the physical processes, and incrementally add complexity in order to identify the minimal-needed technical detail. Through this co-evolution of model and experiment, we will better learn the importance of various theoretical approximations and where to invest future resources in experiment and model development. This simple framework is based on pressure and temperature equilibrium of all co-existing phases combined with deviatoric stress averaging through a volume fraction weighted ow stress and a volume fraction weighted shear modulus. Implementations of the framework based on equilibrium phase fractions (i.e. instantaneous kinetic rate) and for finite rate transition kinetics are proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Novel effects of grain size and ion implantation on grain boundary segregation in ion irradiated austenitic steel

Nuclear reactor environments are extreme in nature due to the combination of exposure to corrosive coolant, mechanical stresses, and neutron irradiation damage. This combination of environments can lead to irradiation induced/assisted precipitation, segregation, and embrittlement coupled with enhanced creep and stress corrosion cracking. While nanostructured materials are of interest in a variety of applications due to their unique properties including high mechanical strength, for nuclear applications nanostructured materials have the added benefit of irradiation resistance due to the high volume density of sinks for irradiation-induced defects. In this study, we show unique radiation-induced segregation (RIS) behavior in nanocrystalline 304 stainless steel (SS304). Typical RIS in austenitic steels includes Ni enrichment and Cr depletion within the grain boundaries. In nanostructured SS304 this RIS is reduced. Furthermore, interestingly, some grain boundaries in the nanocrystalline SS304 in this study were found to be enriched in Cr after Fe 2+ ion irradiation at 500 °C up to 50 displacements per atom (dpa). To understand this unique observation, lattice-based atomic kinetic Monte Carlo simulations were performed to investigate the effects of grain size, thermal segregation, as well as injected interstitials (introduced as Fe self-ions). The results indicate that the Cr enrichment at grain boundaries may be caused by combined effects of grain size, self-ion injection and preferential Cr diffusion via the interstitial mechanism. In conclusion, the findings also suggest a possible difference in RIS between ion and neutron irradiations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An Initial Look at the Magnetic Design of a 150 mm Aperture High-Temperature Superconducting Magnet With a Dipole Field of 8 to 10 T

High-temperature superconducting REBa 2 Cu 3 O 7-$x$ (rebco) conductors have the potential to generate a high magnetic field over a broad temperature range. The corresponding accelerator magnet technology, still in its infancy, can be attractive for future energy-frontier particle colliders such as a multi-TeV muon collider. To help develop the technology, we explore the requirements and potential characteristics of a rebco magnet, operating at 4.2 or 20 K, with a dipole field of 8-10 T in a clear aperture of 150 mm. We use the canted cos $\theta$ magnet configuration to reduce the electromagnetic stresses on the conductors. We present the resulting dipole fields, field gradients for combined-function cases, conductor stresses, magnet dimensions and conductor lengths. We also discuss the conductor performance that is required to achieve the target dipole field at 4.2 and 20 K. In conclusion, the information can provide useful input to the development of rebco magnet and conductor technology for collider-ring magnets in a muon collider.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Plant genotype and rhizobia strain combinations strongly influence the transcriptome under heavy metal stress conditions in Medicago truncatula

Heavy metals such as cadmium (Cd) and mercury (Hg) pose significant threats to plant health and food safety as they are absorbed from the environment. Legumes are generally considered sensitive to heavy metals but possess standing genetic variation for accumulation and tolerance to toxic ions. We conducted a transcriptomic analysis on hydroponically and soil grown Medicago truncatula plants to investigate gene expression responses to Cd and Hg exposure in roots, leaves, and nodules. By using plant genotypes with varying metal tolerance or accumulation levels, we observed distinct clustering of gene ontologies, indicating tissue-specific, genotype-specific, and metal-specific gene expression patterns. Considering the symbiotic relationship between legumes and nitrogen-fixing bacteria, we further examined plant phenotypes and transcriptomes of plant genotypes with contrasting Hg accumulation levels and inoculated them with high or low Hg-tolerant Sinorhizobium medicae strains that have presence-absence variation for a mercury reductase (Mer) operon. Host plants inoculated with the Hg-tolerant rhizobia strain possessing a Mer operon exhibited less reduction in nodule number and plant biomass. A smaller reduction in iron (Fe) distribution in nodules after Hg stress was measured using X-ray Fluorescence (XRF) imaging. Dual transcriptome (host plant and bacteria) analysis of nodules revealed a remarkable decrease in the number of differentially expressed genes (DEGs) and clustering of gene ontologies in plants inoculated with the Hg-tolerant rhizobia strain, including symbiosis related genes. This finding suggests that the Hg-tolerant rhizobia strain has the potential to mitigate Hg stress in host plants. Furthermore, we observed genotype by-genotype interactions between the high Hg accumulating plant genotype and the Hg-tolerant rhizobia strain. These findings provide insights into enhancing plant resilience in contaminated environments through optimizing legume-rhizobia interactions for heavy metal tolerance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Stress relaxation cracking susceptibility evaluation in 347H stainless steel welds

Abstract Stress relaxation cracking (SRC) has been reported as a dominant failure mechanism for 347H stainless steel welds at elevated service temperatures, occurring in either the heat-affected zone (HAZ) or fusion zone (FZ). In this study, SRC susceptibility of physically simulated HAZ and cross-welded E347-347H stainless steel welds was studied using a four-step accelerated SRC test with a thermomechanical physical simulator. The stress and temperature range studied represents weld-induced residual stress at 150–600 MPa and post-weld heat treatment temperatures between 800 and 1050 °C. For all temperature conditions, the cross-welded samples failed at a lower critical stress threshold than the simulated HAZ. A finite element model of a 50.8-mm-thick single-V groove weld was used to generate the residual stress maps induced by a 40-pass welding procedure, which in combination with the experimental threshold stress map predicted potential SRC failure locations. Postmortem microstructural evaluations were performed to identify contributing characteristics to SRC. It was found that HAZ samples exhibited a combination of creep void development, secondary cracks with intergranular fracture near grain boundary carbides, and eutectic phases. FZ samples showed brittle fracture with cracks propagating along straight, non-tortuous interdendritic grain boundaries.

42 ENGINEERING↗
DOE OSTI2025

Combining four-point bending and corrosion to map stress-dependent corrosion susceptibility of 316H stainless steel in FLiNaK

Understanding the effect of stress on the corrosion of steels in molten salts is important for material screening and safety assessment of molten salt reactors. We present a method that combines four-point bending with corrosion testing, enabling the mapping of corrosion susceptibility as a function of local stress from a single specimen. Guided by finite element analysis, a four-point bending setup was used to bend a 316H stainless-steel bar under controlled elastic stress during a 100-hour exposure in FLiNaK at 700 °C. Post-exposure characterization using scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed a pronounced correlation between stress and corrosion. Regions under tensile stress exhibited significantly deeper attack depths and greater chromium depletion along grain boundaries, whereas compressive zones showed shallower corrosion cracks. The stress effect is attributed to stress concentration under tensile loading, which promotes chromium dissolution and crack propagation. This technique can be readily applied to other structural alloys, enabling quantitative measurement of corrosion susceptibility as a function of local stress.

316H↗
DOE OSTI2020

The Importance of Vane Configuration on Yield Stress Measurements of Cement Slurry

Vane methods combined with direct shear tests are widely applied to measure the yield stress $τ_0$ in concentrated suspensions such as cement slurries. This report reviews three different vanes with different shapes and sizes, and examines the relationship between the yield stress versus the torque and the shear rate versus the angular velocity. This research shows that vanes with conical shapes or reduced height/diameter ratio $(H/D)$ result in larger yield stress values.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Single crystal yield criterion for chromium based on atomistic studies of isolated 1/2[111] screw dislocations

Using the recently developed Bond Order Potential for Cr, we investigate the mobility of isolated 1/2[111] screw dislocations under stress at 0 K. These studies provide the dependence of the critical resolved shear stress (i.e., the Peierls stress) on the orientation of the maximum resolved shear stress plane and on the shear stress perpendicular to the slip direction. Similar studies are made for loading in tension and compression to show that the onset of yielding in Cr single crystals can be described using a combination of the shear stresses parallel and perpendicular to the slip direction. Based on these results, we develop a single crystal yield criterion for Cr that includes all non-Schmid contributions to the Peierls stress. This criterion is used to predict the shape of the yield surface and compare it with the regular Tresca's hexagon arising from the Schmid law. For all directions of uniaxial load, the criterion is used to quantify the character and magnitude of the tension-compression asymmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Residential segregation and outdoor urban moist heat stress disparities in the United States

The combined impact of urbanization-induced warming and drying on large-scale heat stress disparities remains unknown, with multicity studies using satellite-derived land surface temperature as a proxy for these disparities. Here, using high-resolution urban-resolving numerical model simulations for 2014–2018, we find pervasive disparities in all-sky average maximum summertime air temperature and moist heat stress metrics across US cities, with higher outdoor heat stress exposure in poorer and primarily non-white census tracts. Ninety-four percent of the US urban population (228 million) live in cities where heat stress burdens the poor, with heat stress inequities between white and non-white populations strongly associated with residential segregation. Similarly, historically redlined neighborhoods show higher heat stress than their non-redlined counterparts, demonstrating how historical segregation relates to present-day environmental inequalities. Our results provide quantitative estimates of physiologically relevant heat stress disparities at the US national scale and highlight potential biases when using satellites as a proxy for these.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Qualitative and quantitative analysis of neutron irradiation effects in SiC/SiC composites using X-ray computed tomography

Silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC) composites are candidate materials for cladding of light water reactor (LWR) fuels. Loss of fission product gas retention due to the formation of microcrack networks is considered a potential failure mechanism for SiC/SiC-cladded fuels. In this work, a variety of SiC/SiC composite tubes were irradiated with and without an LWR-relevant radial heat flux in the High Flux Isotope Reactor, followed by detailed characterization with X-ray computed tomography (XCT). This first set of XCT data for neutron-irradiated samples confirmed that the internal stresses arising from a combination of temperature gradients and irradiation-induced swelling act as the primary driver for cracking. Consequently, while the observed cracking patterns varied depending on the tube architectures, the sharp edges of relatively large pores were found to be the common stress concentrator. These findings are useful to help improve the design and manufacturing of SiC/SiC fuel claddings for reduced failure probability.

42 ENGINEERING↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2025

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mitigation and Diagnosis of Pin-Hole Formation in Polymer Electrolyte Membrane Fuel Cells

In this work, we implement a calendering technique to flatten stray fibers within the gas diffusion media, thereby mitigating pin-hole formation in the hot-pressed MEAs. We have investigated the influence of calendering on the long-term durability for several types of gas diffusion electrodes (GDEs) using a combined chemical and mechanical accelerated stress test (AST). The calendered MEAs demonstrate an average AST lifetime improvement of 77% relative to the as-fabricated MEAs.

AMR↗
DOE OSTI2020

Threading–Unthreading Transition of Linear-Ring Polymer Blends in Extensional Flow

Adding small amounts of ring polymers to a matrix of their linear counterparts is known to increase the zero-shear-rate viscosity because of linear-ring threading. Uniaxial extensional rheology measurements show that, unlike its pure linear and ring constituents, the blend exhibits an overshoot in the stress growth coefficient. By combining these measurements with ex-situ small-angle neutron scattering and nonequilibrium molecular dynamics simulations, this overshoot is shown here to be driven by a transient threading–unthreading transition of rings embedded within the linear entanglement network. Prior to unthreading, embedded rings deform affinely with the linear entanglement network and produce a measurably stronger elongation of the linear chains in the blend compared to the pure linear melt. Thus, rings uniquely alter the mechanisms of transient elongation in linear polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Structure and Sulfur: Tuning the Viscoelastic and Surface Properties of Natural Keratin Fibers

Natural keratin fibers, such as wool, possess a complex hierarchical structure that governs their mechanical properties and surface energy. However, the extent to which these characteristics are influenced by combined contributions of structural variations (e.g., fiber diameter, intermediate filament (IF) packing) and chemical composition (e.g., disulfide bond density) remains poorly understood. In this study, we investigate wool fibers from five sheep breeds (Merino, Polwarth, Cheviot, Eider, and Devon) to elucidate how these factors influence viscoelasticity and surface interactions. Using a multimodal approach integrating interfacial and bulk characterization methods, including inverse gas chromatography (IGC), atomic force microscopy-infrared spectroscopy (AFM-IR), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and synchrotron small-angle X-ray scattering (SAXS), we show that the nanometer-thick 18-methyleicosanoic acid (18-MEA) layer is consistently present across all wool types and plays a key role in governing hydrophobicity and surface heterogeneity. A controlled isothermal treatment at 200 °C, designed to cleave disulfide bonds, results in a nearly 40% reduction in specific surface area across all fiber types, accompanied by a significant decrease in tensile strength and 80% reduction in elongation at break for Merino and Devon wool, but limited influence on the mechanical properties of Eider fibers. Furthermore, rate-dependent tensile testing within the elastic regime reveals distinct viscoelastic responses among the fiber types, suggesting that the sulfur-rich protein matrix surrounding IFs and its structure contribute actively to stress partitioning. Altogether, when combined with conclusions from SAXS measurements of IF spacing, our work offers compelling insights into the role of the keratin-associated protein (KAP) matrix in shaping wool fiber mechanics. Differences in mechanical behavior among wool types, despite similar IF spacing or sulfur content, highlight the importance of matrix composition and cross-linking density, suggesting that the molecular architecture of the KAP network may be a dominant factor in determining fiber performance.

X-ray scattering↗
DOE OSTI2022

Effect of microstructure on fatigue crack propagation in additive manufactured nickel-based superalloy Haynes 282: an experiment and crystal plasticity study

Haynes 282 is a γ' precipitation-strengthened nickel-based superalloy known for its exceptional high-temperature creep resistance and excellent fabricability. Recent advancements in powder-bed fusion-based additive manufacturing (PBF-AM) have enabled the fabrication of Haynes 282 with accurate, site-specific control of the grain orientation and morphology at the microscale. This ability opens up new avenues for microstructure design, to improve the material’s fatigue crack resistance and service life. This paper investigates the fatigue crack growth behavior of hybrid microstructure Haynes 282 fabricated via PBF-AM. Previous experiments revealed a higher crack propagation rate in the coarse columnar-grained microstructural regions when compared against fine-grained areas. Here, a strain gradient crystal plasticity model was adapted to study the fracture-related mechanical fields at the crack tip in the two microstructures. The simulation results showed a consistent influence of grain structure and texture on crack propagation, as was seen in the experiment. The model analysis revealed higher crack propagation driving force along crack direction in the coarse-grained sharply textured microstructure and higher driving force for crack kinking in fine-grained more diffusely textured microstructure, which is ascribed to the combined effect of yield stress, hardening rate, texture and grain morphology. The presented modeling approach will facilitate the development of the AM-based accurate microstructure design by deepening the fundamental study in AM-specific microstructure-properties relations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗