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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

IC Project: w19_hossfault “Modelling of stick-slip behavior in sheared granular fault gouge & nonlinear elasticity behavior in cracked solid”

Low frequency earthquakes, non-volcanic tremor, and acoustic emissions are examples of weak seismic signals that may help detect major seismic events, i.e., earthquakes. In a laboratory setting, in which stick-slip events are simulated, acoustic emissions are detected far from the stick-slip events. In both, field and laboratory scale cases, the acoustic emission signals are sourced or detected in a volume remote from the volume that spawns the earthquake. Therefore, it is relevant to establish the causal relationship between signals detected on passive, remote monitors and the dynamics of the elastic structures that launch important seismic events. The work conducted under this IC allocation allowed us to utilize a numerical model that let us follow this causality, i.e., examine and connect the dynamics in a granular system (fault gouge), to signals detected on passive remote monitors. It was demonstrated that stress chains are key in the dynamics of granular systems and that their evolution is the source of the acoustic emission.

58 GEOSCIENCES↗
DOE OSTI2026

Elastic and resonance structures of the nucleon from the hadronic tensor in lattice QCD: Implications for neutrino-nucleon scattering and hadron physics

We compute the Euclidean hadronic tensor from charge density operators and extract elastic and resonance structures by employing exponential fits to the four-point function correlator, as well as a Bayesian reconstruction inverse algorithm to obtain the corresponding spectral density for qualitative comparison. We present the determination of the nucleon’s Sachs electric form factor using the hadronic tensor formalism and verify that it is consistent with that from the conventional three-point function calculation. Beyond the elastic peak, we observe a structure located approximately 0.5–0.7 GeV above the nucleon mass in the Bayesian reconstruction. This structure is interpreted as a mixture of the Roper resonance [𝑁⁡(1440)], and states with both positive and negative parities in this mass region, as well as multihadron states. Assuming the observed structure is dominated by 𝐽 𝑃 = 1/2 ± states, we extract the transition electric form factor 𝐺$^*_𝐸$⁡(𝑄 2 ) and the corresponding longitudinal helicity amplitude 𝑆 1/2 ⁡(𝑄 2 ), and compare them with those determined from the CLAS experimental data of nucleon-to-Roper transition. Although fitting to the four-point correlation function or using the inverse algorithm does not resolve individual resonances, it nevertheless enables the determination of total inclusive lepton–nucleon scattering cross sections in appropriate energy bins. This lattice QCD calculation presents the first major step toward studying the inclusive 𝑁 → 𝑋 contributions within the hadronic tensor formalism.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Understanding the Elastic, Plastic, and Damage Features in Fracturing of Self-reinforced Thermoplastic Composites via Non-destructive Digital Imaging Correlation

This work demonstrated the utilization of non-destructive Digital Imaging Correlation (DIC) method to characterize the elastic, plastic, and damage features during the Mode I intra-laminar fracturing process of self-reinforced thermoplastic composites by using a self-reinforced polypropylene (PP) composite as an example. The DIC results clearly showed the development of huge plastic zone (PZ) and non-negligible Fracture Process Zone (FPZ) in front of the notch tip during the fracturing process, and the geometries and sizes of the foregoing zones at the peak load were further quantified. Such an interesting fracturing behavior of self-reinforced thermoplastic composites is way different from brittle materials (e.g., glass, acrylic, etc.), ductile materials (e.g., aluminum, steel, etc.), and even quasi-brittle materials (e.g., concrete, nanoparticle-reinforced composites, tough ceramics, wood, cement, carbon/glass fiber-reinforced polymers, etc.). Thus, understanding the elastic, plastic, and damage features is the first step before better characterizing the material fracture properties of self-reinforced thermoplastic composites through new analytical methods and computational modeling. These efforts are of utmost importance for wide applications of self-reinforced thermoplastic composites in various engineering fields in the future.

Lightweight Composites, Self-reinforced Thermoplas↗
DOE OSTI2021

Estimation of the orientation of stress in the Earth’s crust without earthquake or borehole data

Abstract Mechanical stress acting in the Earth’s crust is a fundamental property that is important for a wide range of scientific and engineering applications. The orientation of maximum horizontal compressive stress can be estimated by inverting earthquake source mechanisms and measured directly from borehole-based measurements, but large regions of the continents have few or no observations. Here we present an approach to determine the orientation of maximum horizontal compressive stress by measuring stress-induced anisotropy of nonlinear susceptibility, which is the derivative of elastic modulus with respect to strain. Laboratory and Earth experiments show that nonlinear susceptibility is azimuthally dependent in an anisotropic stress field and is maximum in the orientation of maximum horizontal compressive stress. We observe this behavior in the Earth—in Oklahoma and New Mexico, U.S.A, where maximum nonlinear susceptibility coincides with the orientation of maximum horizontal compressive stress measured using traditional methods. Our measurements use empirical Green’s functions and solid-earth tides and can be applied at different temporal and spatial scales.

58 GEOSCIENCES↗
DOE OSTI2026

Atomistic modeling of lanthanide diffusion in refractory body-centered cubic molybdenum

Lanthanide fission products can strongly interact with candidate cladding alloys, but their transport properties in refractory metals remain poorly understood. Here, in this work, we investigate the atomic-scale diffusion behavior of La, Ce, Pr, and Nd in body-centered cubic (bcc) molybdenum, a potential candidate for advanced nuclear cladding. Self-consistent mean-field transport modeling is performed to evaluate the fission product transport and vacancy mobility, informed by first-principles and nudged elastic band calculations of vacancy formation energies, migration barriers, and solute–vacancy binding characteristics. Compared with bcc Fe, lanthanide solutes in bcc Mo exhibit slower tracer diffusion due to higher vacancy formation and migration energies. Furthermore, the calculations reveal that the influence of fission products on migration barriers in bcc Mo are not as extensive in range compared to bcc Fe. Among the studied lanthanides, La exhibits the strongest vacancy binding while also being the fastest diffuser in Mo. These findings highlight how refractory bcc alloys can reduce fission product infiltration, offering valuable insight into the development of durable cladding systems for advanced reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Electronic Band Structure of a Superconducting Nickelate Probed by the Seebeck Coefficient in the Disordered Limit

Superconducting nickelates are a new family of strongly correlated electron materials with a phase diagram closely resembling that of superconducting cuprates. While analogy with the cuprates is natural, very little is known about the metallic state of the nickelates, making these comparisons difficult. We probe the electronic dispersion of thin-film superconducting five-layer ( n = 5 ) and metallic three-layer ( n = 3 ) nickelates by measuring the Seebeck coefficient S . We find a temperature-independent and negative S / T for both n = 5 and n = 3 nickelates. These results are in stark contrast to the strongly temperature-dependent S / T measured at similar electron filling in the cuprate La 1.36 Nd 0.4 Sr 0.24 CuO 4 . The electronic structure calculated from density-functional theory can reproduce the temperature dependence, sign, and amplitude of S / T in the nickelates using Boltzmann transport theory. This demonstrates that the electronic structure obtained from first-principles calculations provides a reliable description of the fermiology of superconducting nickelates and suggests that, despite indications of strong electronic correlations, there are well-defined quasiparticles in the metallic state. Finally, we explain the differences in the Seebeck coefficient between nickelates and cuprates as originating in strong dissimilarities in impurity concentrations. Our study demonstrates that the high elastic scattering limit of the Seebeck coefficient reflects only the underlying band structure of a metal, analogous to the high magnetic field limit of the Hall coefficient. This opens a new avenue for Seebeck measurements to probe the electronic band structures of relatively disordered quantum materials. Published by the American Physical Society 2024

Grissonnanche, G. (ORCID:0000000251153125)↗
DOE OSTI2024

Constraints on directionality effect of nuclear recoils in a liquid argon time projection chamber

The direct search for dark matter in the form of weakly interacting massive particles (WIMP) is performed by detecting nuclear recoils produced in a target material from the WIMP elastic scattering. The experimental identification of the direction of the WIMP-induced nuclear recoils is a crucial asset in this field, as it enables unmistakable modulation signatures for dark matter. The Recoil Directionality (ReD) experiment was designed to probe for such directional sensitivity in argon dual-phase time projection chambers (TPC), that are widely considered for current and future direct dark matter searches. The TPC of ReD was irradiated with neutrons at the INFN Laboratori Nazionali del Sud. Data were taken with nuclear recoils of known directions and kinetic energy of 72 keV, which is within the range of interest for WIMP-induced signals in argon. The direction-dependent liquid argon charge recombination model by Cataudella et al. was adopted and a likelihood statistical analysis was performed, which gave no indications of significant dependence of the detector response to the recoil direction. The aspect ratio R of the initial ionization cloud is $R < 1.072$ with 90 % confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A new approach to model geomaterials with heterogeneous properties in thermo-hydro-mechanical coupled problems

The main objective of this article is to present a new approach to model coupled thermo-hydro-mechanical problems considering geomaterials with heterogeneous properties. This approach has been implemented in the software CODE_BRIGHT and it provides the possibility of considering geomaterials with a spatially correlated heterogeneous field of porosity, following a normal distribution. This spatial correlation can be isotropic or anisotropic. An important feature of this approach is that material properties such as intrinsic permeability, thermal conductivity, diffusivity, retention curve, elastic modulus or cohesion are defined as a function of porosity and, thus, they become heterogeneous with spatial correlation and, eventually, anisotropic. A validation exercise and other basic numerical examples have been carried out to illustrate the possibilities of the proposed approach. The results, which have been compared with a homogeneous case, show that considering heterogeneous fields can be relevant in different modelling problems, especially coupled thermo-hydro-mechanical problems.

42 ENGINEERING↗
DOE OSTI2024

Miniaturized Magnetoelastic Sensor System

This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

On the S-matrix of Ising field theory in two dimensions

We explore the analytic structure of the non-perturbative S-matrix in arguably the simplest family of massive non-integrable quantum field theories: the Ising field theory (IFT) in two dimensions, which may be viewed as the Ising CFT deformed by its two relevant operators, or equivalently, the scaling limit of the Ising model in a magnetic field. Our strategy is that of collider physics: we employ Hamiltonian truncation method (TFFSA) to extract the scattering phase of the lightest particles in the elastic regime, and combine it with S-matrix bootstrap methods based on unitarity and analyticity assumptions to determine the analytic continuation of the 2 → 2 S-matrix element to the complex s-plane. Focusing primarily on the “high temperature” regime in which the IFT interpolates between that of a weakly coupled massive fermion and the E 8 affine Toda theory, we will numerically determine 3-particle amplitudes, follow the evolution of poles and certain resonances of the S-matrix, and exclude the possibility of unknown wide resonances up to reasonably high energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Magnetoelastic properties of multiferroic hexagonal ErMnO 3

Here, the strength and dynamics of magnetoelastic coupling through the paramagnetic (PM) – antiferromagnetic (AFM) – ferrimagnetic (FIM) transitions in multiferroic hexagonal ErMnO 3 have been investigated by Resonant Ultrasound Spectroscopy. Elastic stiffening by up to 2% below the PM – AFM transition at 80 K arises from biquadratic coupling between strain and the magnetic order parameter with relaxation times longer than ~10 -6 s for the response of spins to changes in strain. In contrast with YMnO 3 , the PM – AFM transition in ErMnO 3 is accompanied by a peak in acoustic loss immediately below the Néel point which is interpreted in terms of strain relaxation accompanying ordering of spins of Er 3+ at 4b sites. Changes in the magnetic ordering scheme at the AFM – FIM transition near 3 K are accompanied by elastic softening of ~0.03 %. During poling of the low temperature ferrimagnetic structure round magnetic hysteresis loops, small changes in elastic stiffness which arise due to the contribution of piezomagnetic and/or piezoelectric moduli are detected. Contributions of piezoelectric moduli to acoustic resonance frequencies also permit changes in the configuration of ferroelectric domains to be detected in response both to cycling through this transition and to application of a magnetic field. A peak in acoustic loss in the vicinity of 250 K is attributed to strain-mediated pinning/freezing of some aspect of the domain microstructure with an activation energy of ~0.25–0.3 eV. A return to the original elastic properties on heating to temperatures above ~250 K is interpreted in terms of backswitching of domains to the configuration they had at the start. These observations confirm the existence of subtle variations in magnetoelastic coupling behaviour relating to both the magnetic order parameters and magnetic domain structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Reaction Heterogeneity in LiFePO 4 Agglomerates and the Role of Intercalation-Induced Stress

As an important battery cathode material, reaction distribution in lithium iron phosphate (LiFePO4) has been extensively studied in dispersed particle systems, but remains poorly understood for mesoscopic agglomerates (or secondary particles) that are used in most commercial batteries. Herein, we apply three-dimensional X-ray spectroscopic imaging to characterize the two-phase structure in LiFePO4 secondary particles during electrochemical cycling. (De)lithiated domains are found to not form the commonly assumed core-shell structure but develop highly anisotropic filamentary morphology that is rate independent and symmetric between charging and discharging. Phase-field simulations elucidate that the observed 1D phase growth behavior is not caused by the 1D lithium diffusivity of LiFePO4 but the elastic interaction between primary particles, which gives rise to stronger reaction heterogeneity than dispersed nanoparticles. As a result, uniform lithium (de)intercalation does not occur on the secondary particle surface even at high cycling rates.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Neutron elastic scattering on calcium isotopes from chiral nuclear optical potentials

We formulate microscopic neutron-nucleus optical potentials from many-body perturbation theory based on chiral two- and three-body forces. The neutron self-energy is first calculated in homogeneous matter to second order in perturbation theory, which gives the central real and imaginary terms of the optical potential. Here, the real spin-orbit term is calculated separately from the density matrix expansion using the same chiral interaction as in the self-energy. Finally, the full neutron-nucleus optical potential is derived within the improved local density approximation utilizing mean-field models consistent with the chiral nuclear force employed. We compare the results of the microscopic calculations to phenomenological models and experimental data up to projectile energies of E = 200 MeV. Experimental elastic differential scattering cross sections and vector analyzing powers are generally well reproduced by the chiral optical potential, but we find that total cross sections are overestimated at high energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗
DOE OSTI2022

Experimental Investigation of Low-Frequency Distributed Acoustic Strain-Rate Responses to Propagating Fractures

Summary Low-frequency distributed acoustic sensing (LF-DAS) responds to strain changes due to far-field fracture propagation. To better understand the LF-DAS response to fracture propagation, we performed laboratory-scale hydraulic fracture experiments with embedded optical strain sensors. The objectives of this research are to generate hydraulic fractures of known geometry, measure the strain response along the embedded fiber-optic cable comparable to LF-DAS measurements, and use the results to inform the interpretation of field-derived LF-DAS data. The experiments were conducted in unconfined transparent cubic blocks with a dimension of 8 in. on each side. The block was made of transparent epoxy to visualize the fracture propagation. Fiber-optic sensing cables were embedded in the block at different distances to the source of injection. We injected dyed water through an injection tubing to generate a transverse, radial fracture along an initial flaw. An optical interrogator recorded the response of offset fiber Bragg grating (FBG) strain sensors normal to the plane of the fracture. The strain data were visualized on a waterfall plot, akin to visualizations of field-derived LF-DAS data. Dimensional analysis was used to scale the laboratory results to field conditions. We compared the evolution of the strain response at the fiber-optic cable, injection pressure, and rate with known fracture geometry. The measured strains were compared with Sneddon’s (1946) linear elastic solution for a penny-shaped crack and found to follow this behavior. The generated radial fractures in transparent media can be modeled with Sneddon’s linear elastic radial fracture model and a Mode I critical stress intensity factor. The LF-DAS characteristic response of a narrowing region of extension surrounded by compression was exhibited as a fracture that approached and intersected the fiber-optic cable. The experimentally derived strain and strain-rate waterfall plots with known fracture geometry, injection rate, and pressure response provide insight in understanding LF-DAS responses in the field. Furthermore, we developed a method to estimate fracture geometry evolution from the fiber-optic strain data and validated the method against the experimental data.

Engineering↗
DOE OSTI2024

Unleashing the power of EFT in neutrino-nucleus scattering

Neutrino physics is advancing into a precision era with the construction of new experiments, particularly in the few GeV energy range. Within this energy range, neutrinos exhibit diverse interactions with nucleons and nuclei. This study delves in particular into neutrino-nucleus quasi-elastic cross sections, taking into account both standard and, for the first time, non-standard interactions, all within the framework of effective field theory (EFT). The main uncertainties in these cross sections stem from uncertainties in the nucleon-level form factors, and from the approximations necessary to solve the nuclear many-body problem. We explore how these uncertainties influence the potential of neutrino experiments to probe new physics introduced by left-handed, right-handed, scalar, pseudoscalar, and tensor interactions. For some of these interactions the cross section is enhanced, making long-baseline experiments an excellent place to search for them. Our results, including tabulated cross sections for all interaction types and all neutrino flavors, can serve as the foundation for such searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Graph neural networks for mechanical property prediction of 2D fiber composites

This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. Hence, training only the isotropic limit properties may not be acceptable. Another aspect is the need to normalize elastic stiffness values for ML, especially when high elastic contrast ratios are encountered between composite phases or in the material set. We introduce a normalization technique based on the mean-field method (MFM) to handle such high contrast ratios and train for the entire stiffness tensor. We show that the proposed GNN approaches exhibit high accuracy and efficiency compared to traditional methods and convolutional neural networks, utilizing unstructured graphs constructed from microstructure topology. Our model successfully predicts the stiffness tensor, peak strength under bulk damage, and brittle fracture initiation strength across diverse microstructure configurations while maintaining high accuracy even for extreme material contrasts and volume fractions. We also present a method to improve prediction accuracy for small dataset sizes using Voronoi partitioning.

Brittle strength↗