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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Effective Forces Between Colloidal Particles

Colloidal suspensions have proven to be excellent model systems for the study of condensed matter and its phase behavior. Many of the properties of colloidal suspensions can be investigated with a systematic variation of the characteristics of the systems and, in addition, the energy, length and time scales associated with them allow for experimental probing of otherwise inaccessible regimes. The latter property also makes colloidal systems vulnerable to external influences such as gravity. Experiments performed in micro-ravity by Chaikin and Russell have been invaluable in extracting the true behavior of the systems without an external field. Weitz and Pusey intend to use mixtures of colloidal particles with additives such as polymers to induce aggregation and form weak, tenuous, highly disordered fractal structures that would be stable in the absence of gravitational forces. When dispersed in a polarizable medium, colloidal particles can ionize, emitting counterions into the solution. The standard interaction potential in these charged colloidal suspensions was first obtained by Derjaguin, Landau, Verwey and Overbeek. The DLVO potential is obtained in the mean-field linearized Poisson-Boltzmann approximation and thus has limited applicability. For more precise calculations, we have used ab initio density functional theory. In our model, colloidal particles are charged hard spheres, the counterions are described by a continuum density field and the solvent is treated as a homogeneous medium with a specified dielectric constant. We calculate the effective forces between charged colloidal particles by integrating over the solvent and counterion degrees of freedom, taking into account the direct interactions between the particles as well as particle-counterion, counterion-counterion Coulomb, counterion entropic and correlation contributions. We obtain the effective interaction potential between charged colloidal particles in different configurations. We evaluate two- and three-body forces in the bulk as well as study the influence of soft walls. We qualitatively explain the effects of the walls on the forces and demonstrate that many-body effects are negligible in our system. With adjustments in the parameters, the DLVO pair-potential can describe the results quantitatively. Besides electrostatic interactions, entropic depletion effects that arise from (hard-core) exclusion play an important role in determining the behavior of multi-component colloidal suspensions. A standard theory for depletion forces is due to Asakura and Oosawa and is based on the ideal gas approximation. To go beyond this approximation, we have studied entropic forces in molecular dynamics simulations of systems of hard spheres (the effects of the solvent have been ignored). The effective depletion forces for these systems can be found either from equilibrium distribution functions or from direct momentum transfer calculations. Our results obtained by either method show qualitative differences from the Asakura-Oosawa forces, indicating a longer range, higher value at contact and most importantly a more complicated structure, comprising of several maxima and minima. Our calculations include the determination of effective forces between two spheres, a hard sphere and a wall, and the behavior of a hard sphere near a step-edge and a corner. We also demonstrate that such entropic forces do not necessarily satisfy pairwise additivity.

Tehver, Riina↗
DOE OSTI2023

Chemistry and Dynamics of Supercritical Carbon Dioxide and Methane in the Slit Pores of Layered Silicates

In the mid 2010s, high-pressure diffraction and spectroscopic tools opened a window into the molecular-scale behavior of fluids at the conditions of many CO 2 sequestration and shale/tight gas reservoirs - conditions where CO 2 and CH 4 are present as variably wet supercritical fluids. Integrating high-pressure spectroscopy and diffraction with molecular modeling has revealed much about the ways that supercritical CO 2 and CH 4 behave in reservoir components, particularly in the slit-shaped micro- and meso-pores of layered silicates (phyllosilicates) abundant in caprocks and shales. This Account summarizes how supercritical CO 2 and CH 4 behave in the slit pores of swelling phyllosilicates as functions of the H 2 O activity, framework structural features, and charge-balancing cation properties at 90 bar and 323 K – conditions similar to a reservoir at ~1 km depth. Slit pores containing cations with large radii, low hydration energy, and large polarizability readily interact with CO 2 , allowing CO 2 and H 2 O to adsorb and co-exist in these interlayer pores over a wide range of fluid humidities. In contrast, cations with small radii, high hydration energy, and low polarizability weakly interact with CO 2 leading to reduced CO 2 uptake and a tendency to exclude CO 2 from interlayers when H 2 O is abundant. The reorientation dynamics of confined CO 2 depends on the interlayer pore height, which is strongly influenced by the cation properties, framework properties, and fluid humidity. The silicate structural framework also influences CO 2 uptake and behavior - for example, smectites with increasing F-for-OH substitution in the framework take up greater quantities of CO 2 . Reactions that trap CO 2 in carbonate phases have been observed in thin H 2 O films near smectite surfaces, including a dissolution-reprecipitation mechanism when the edge surface area is high and an ion exchange-precipitation mechanism when the interlayer cation can form a highly insoluble carbonate. In contrast, supercritical CH 4 does not readily associate with cations, does not react with smectites, and is only incorporated into interlayer slit mesopores when (i) the pore has a $z$-dimension large enough to accommodate CH 4 , (ii) the smectite has low charge and (iii) the H 2 O activity is low. In conclusion, the adsorption and displacement of CH 4 by CO 2 and vice-versa have been studied on the molecular scale in one shale, but opportunities remain to examine behavioral details in this more complicated, slit-pore inclusive system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Stellar Echo Imaging of Exoplanets

All stars exhibit intensity fluctuations over several timescales, from nanoseconds to years. These intensity fluctuations echo off bodies and structures in the star system. We posit that it is possible to take advantage of these echoes to detect, and possibly image, Earth-scale exoplanets. Unlike direct imaging techniques, temporal measurements do not require fringe tracking, maintaining an optically-perfect baseline, or utilizing ultra-contrast coronagraphs. Unlike transit or radial velocity techniques, stellar echo detection is not constrained to any specific orbital inclination. Current results suggest that existing and emerging technology can already enable stellar echo techniques at flare stars, such as Proxima Centauri, including detection, spectroscopic interrogation, and possibly even continent-level imaging of exoplanets in a variety of orbits. Detection of Earth-like planets around Sun-like stars appears to be extremely challenging, but cannot be fully quantified without additional data on micro- and millisecond-scale intensity fluctuations of the Sun. We consider survey missions in the mold of Kepler and place preliminary constraints on the feasibility of producing 3D tomographic maps of other structures in star systems, such as accretion disks. In this report we discuss the theory, limitations, models, and future opportunities for stellar echo imaging.

stellar↗
NASA NTRSDate not supplied

On the Equivalence of Gas and Liquid Leak Flow Rates for Application to Propulsion and Propellant Transfer Systems

The equivalence of leak rates for gas flow and liquid flow through an arbitrary small leak size in pressurized systems has been investigated theoretically and experimentally. Measurements were taken for gaseous helium (GHe) rates and water flow issuing from the same leak configuration. The predictions for the correlation of GHe leak rates to water leak rates have been satisfactorily compared with present test data and those of other investigators over a wide range leak flow rates (many orders of magnitude) corresponding to a wide range of leak sizes (0.1 m to 0.1 mm). The results show that at extremely small leak sizes (sub-micron range), the effects of Knudsen number in the free molecular regime (rarefied gases) become important. By a proper scaling procedure, the measured flow rate for water could be applied to equivalent propellant leaks in flight operations. In the present tests the micro-channel range of the leak size is satisfactorily simulated by repeatable precision set needle position valve. Test results show that in general the theoretical model predicts the data reasonably well for GHe flow rates in the range of 0.001 to 1 sccs. Outside this range of GHe flow rates some adjustments (improvements) to the analytical model are required along with further testing.

Max Kandula↗
NASA NTRS2014

TBS (Trabecular Bone Score) Expands Understanding of Spaceflight Effects on the Lumbar Spine of Long-Duration Astronauts

Bone loss due to long‐duration spaceflight has been characterized by both DXA and QCT serial scans. It is unclear if these spaceflight‐induced changes in bone mineral density (BMD) and structure result in increased fracture incidence. NASA astronauts currently fly 5 to 6‐month missions on the International Space Station (ISS) and at least one 12‐month mission is planned. While NASA has measured areal BMD (by DXA) and volumetric BMD (by QCT) and has estimated hip strength (by finite element models of QCT data, no method has yet been used to examine bone micro‐architecture from lumbar spine (LS). DXA scans are routinely performed pre‐ and postflight on all ISS astronauts to follow BMD changes associated with spaceflight. Trabecular Bone Score (TBS) is a relatively new method that measures grey‐scale‐level texture information extracted from LS DXA images and correlates with 3D parameters of bone micro‐architecture. We evaluated the ability of LS TBS to discriminate changes in astronauts who have flown on ISS missions and to determine if TBS can provide additional information compared to DXA. Methods: Lumbar Spine (L1‐4) DXA scans from 51 astronauts (mean age, 47 +/- 4 yrs) were divided into 3 groups based on the exercise regimens performed onboard the ISS. "Pre‐ARED" (exercise using a load‐limited resistive exercise device, <300 lb), "ARED" (exercise with a high‐load resistive exercise device, up to 600 lb) and "Bisphos+ARED" group (ARED exercise and a 70‐mg alendronate tablet once a week before and during flight, starting 17 days before launch). DXA scans were performed and analyzed on a Hologic Discovery W using the same technician for the pre‐ and post‐flight scans. LSC for the LS in our laboratory is 0.025 g/sq. cm. TBS was performed at the Mercy Hospital, Cincinnati, Ohio on a similar Hologic computer. Data were analyzed using a paired, 2‐tailed Student's t‐test for the difference between pre‐ and postflight means. Percent change and % change per month are noted. Interpretation: Our data suggest that: TBS and DXA both detected significant decrements in the LS in these pre‐ ARED astronauts, not unexpected given the insufficient loads provided by this early exercise device. TBS did not detect significant changes in the ARED or Bisphos+ARED groups while DXA did detect significant changes in the ARED astronauts. These findings suggest that DXA and TBS are detecting independent effects of bone loss interventions tested in ISS astronauts in space, which may be due to distinct effects of interventions on mineral content of separate cortical vs. trabecular bone. Conclusion: TBS, in conjunction with DXA BMD, may provide additional insight into the nature of changes (or lack thereof) in the microstructure of trabecular bone and the areal BMD of vertebral bodies.

Smith, Scott A.↗
NASA NTRS2020

Environmental factors driving spatial heterogeneity in desert halophile microbial communities

Spatial heterogeneity in microbial communities is observed in all-natural ecosystems and can stem from both adaptations to local environmental conditions as well as stochastic processes. Extremophile microbial communities inhabiting evaporitic halite nodules (salt rocks) in the Atacama Desert, Chile, are a good model ecosystem for investigating factors leading to microbiome heterogeneity, due to their diverse taxonomic composition and the spatial segregation of individual nodules. We investigated the abiotic factors governing microbiome composition across different spatial scales, allowing for insight into the factors that govern halite colonization from regional desert-wide scales to micro-scales within individual nodules. We found that water availability and community drift account for microbiome assembly differently at different distance scales, with higher rates of cell dispersion at the smaller scales resulting in a more homogenous composition. This trend likely applies to other endoliths, and to non desert communities, where dispersion between communities is limited. At the intra-nodule scales, a light availability gradient was most important in determining the distribution of microbial taxa despite intermixing by water displacement via capillary action.

microbiome extremophile, desert, heterogeneity, Me↗
DOE OSTI2021

An FEM-Based Peridynamic Model for Failure Analysis of Unidirectional Fiber-Reinforced Laminates

To predict the mixed damage modes of unidirectional fiber-reinforced polymer (FRP) laminates under dynamic loading, an FEM-based peridynamic model is introduced in this paper. Based on its geometric structure and material composition, a long fiber lamina is considered a transversely isotropic medium as a result of homogenization at the meso-scale. The laminated structure is modeled by stacking surface mesh layers with arbitrary fiber angles along the thickness direction. The peridynamic bonds between Gauss points connect the separated elements. These bonds are classified as inner-layer bonds and inter-layer bonds. To represent the anisotropy of a laminate, the micro-elastic modulus of the inner-layer and inter-layer bonds is calculated from the anisotropic engineering material constants separately. To capture complex failure behaviors of laminate structures, an empirical damage model is proposed for the tension/ compression breakage of peridynamic bonds. This damage model can control the in-plane and delamination failure process. Finally, benchmark tests are conducted to validate the elastic response of laminates under dynamic loading. In terms of damage analysis, the proposed model can capture the complex damage modes and resistive force of laminate structures.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Trifluoroacetic Acid from Degradation of HCFCs and HFCs: A Three-Dimensional Modeling Study

Trifluoroacetic acid (TFA; CF3COOH) is produced by the degradation of the halocarbon replacements HFC-134a, HCFC-124, and HCFC-123. The formation of TFA occurs by HFC/HCFC reacting with OH to yield CF3COX (X = F or CI), followed by in-cloud hydrolysis of CF3COX to form TFA. The TFA formed in the clouds may be reevaporated but is finally deposited onto the surface by washout or dry deposition. Concern has been expressed about the possible long-term accumulation of TFA in certain aquatic environments, pointing to the need to obtain information on the concentrations of TFA in rainwater over scales ranging from local to continental. Based on projected concentrations for HFC-134a, HCFC-124, and HCFC-123 of 80, 10, and 1 pptv in the year 2010, mass conservation arguments imply an annually averaged global concentration of 0.16 micro g/L if washout were the only removal mechanism for TFA. We present 3-D simulations of the HFC/HCFC precursors of TFA that include the rates of formation and deposition of TFA based on assumed future emissions. An established (GISS/Harvard/ UCI) but coarse-resolution (8 deg latitude by 10 deg longitude) chemical transport model was used. The annually averaged rainwater concentration of 0.12 micro g/L (global) was calculated for the year 2010, when both washout and dry deposition are included as the loss mechanism for TFA from the atmosphere. For some large regions in midnorthern latitudes, values are larger, 0.15-0.20 micro g/L. The highest monthly averaged rainwater concentrations of TFA for northern midlatitudes were calculated for the month of July, corresponding to 0.3-0.45 micro g/L in parts of North America and Europe. Recent laboratory experiments have suggested that a substantial amount of vibrationally excited CF3CHFO is produced in the degradation of HFC-134a, decreasing the yield of TFA from this compound by 60%. This decrease would reduce the calculated amounts of TFA in rainwater in the year 2010 by 26%, for the same projected concentrations of precursors.

Kotamarthi, V. R.↗
NASA NTRS1998

Trifluoroacetic Acid from Degradation of HCFCs and HFCs: A Three-Dimensional Modeling Study

Trifluoroacetic acid (TFA; CF3 COOH) is produced by the degradation of the halocarbon replacements HFC-134a, HCFC-124, and HCFC-123. The formation of TFA occurs by HFC/HCFC reacting with OH to yield CF3COX (X = F or CI), followed by in-cloud hydrolysis of CF to form TFA. The TFA formed in the clouds may be reevaporated but is finally deposited onto the surface by washout or dry deposition. Concern has been expressed about the possible long-term accumulation of TFA in certain aquatic environments, pointing to the need to obtain information on the concentrations of TFA in rainwater over scales ranging from local to continental. Based on projected concentrations for HFC-134a, HCFC-124, and HCFC-123 of 80, 10, and 1 pptv in the year 2010, mass conservation arguments imply an annually averaged global concentration of 0.16 micro g/L if washout were the only removal mechanism for TFA. We present 3-D simulations of the HFC/HCFC precursors of TFA that include the rates of formation and deposition of TFA based on assumed future emissions. An established (GISS[Harvard/ UCI) but coarse-resolution (8 deg latitude by 10 deg longitude) chemical transport model was used. The annually averaged rainwater concentration of 0.12 micro g/L (global) was calculated for the year 2010, when both washout and dry deposition are included as the loss mechanism for TFA from the atmosphere. For some large regions in midnorthern latitudes, values are larger. 0.15-0.20 micro g/L. The highest monthly averaged rainwater concentrations of TFA for northern midlatitudes were calculated for the month of July, corresponding to 0.3 - 0.45 micro g/L in parts of North America and Europe. Recent laboratory experiments have suggested that a substantial amount of vibrationally excited CF3CHFO is produced in the degradation of HFC-134a, decreasing the yield of TFA from this compound by 60%. This decrease would reduce the calculated amounts of TFA in rainwater in the year 2010 by 26%, for the same projected concentrations of precursors.

Kotamarthi, V. R.↗
DOE OSTI2025

If We Build Them, They Will Run: Automated HPC Apps Deployment and Profiling with eBPF in Cloud

The high performance computing (HPC) community is in a period of transition. The rise of AI/ML coupled with a changing landscape of resources deems portability a new metric of performance, and methods to move between on-premises and cloud environments and assess compatibility are paramount. Here we design and test a strategy for bridging the gap between traditional HPC and Kubernetes environments – first containerizing applications, providing automated orchestration to run studies, and packaging the setup with automated means to assess performance using low overhead eXtended Berkeley Packet Filter (eBPF) programs. We first assess different designs for eBPF collection, demonstrating a tradeoff between number of programs deployed on a node and overhead added. We develop 5 low overhead eBPF programs that combine with streaming ML models to assess CPU, futex, TCP, shared memory, and file access across four different builds of an HPC application for CPU and GPU. We use eBPF data to generate insights into the possible underlying etiology of scaling issues. We then assess compatibility of a well-known benchmark, HPCG, across matrices of micro-architectures and optimization levels (217 containers across 24 instance types and over 7500 runs). We provide to the community 30 applications to deploy in our automated setup and perform a scaling study from 4 to a maximum of 256 nodes for both CPU and GPU applications. Finally, we use our gained knowledge about performance to generate compatibility artifacts that are used by a newly developed Kubernetes controller to intelligently select instance type based on optimizing a figure of merit. Along with insights to scaling in this environment with a collection of applications and templates to work from, we provide an overall strategy for approaching HPC application deployment and image selection based on compatibility in cloud.

Computer science↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators

Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered a promising approach to address some challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications are contingent upon their efficient execution on the underlying hardware infrastructure. Specialized Al accelerator hardware systems have recently become available for accelerating Al applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT-2 model, and (iii) an 1,I,M-driven science use case, GenSLM. We present our findings and analyses of the models' performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, and sensitivity to gradient accumulation steps.

Emani, Murali↗
DOE OSTI2025

Multi-scale Interaction Mechanism for Edge-Localized-Mode Suppression in the Tokamak Edge

A central challenge in fusion energy is reconciling the high-confinement mode required for reactor performance with the intense intermittent relaxation events it produces, known as edge-localized modes. These instabilities arise in the steep pressure pedestal at the plasma edge when magnetohydrodynamic thresholds are crossed, inflicting damaging heat loads on reactor components. Here, we show that multiscale interactions between microscopic turbulence and macroscopic magnetohydrodynamic modes provide encouraging prospects for self-organized edge-localized modes regulation. Using direct quantitative measurements of multiscale modes, eddy dynamics, and turbulent flux, we show that small-scale electron drift wave turbulence actively scatters the large-scale peeling-ballooning modes. This scattering decorrelates the pressure and velocity fields of the instability, so arresting its growth. Our modeling and theoretical analysis confirm this suppression mechanism is effective even when conventional linear stability thresholds are exceeded. This work establishes a nonlinear principle for edge-localized modes stability, revealing how ambient micro-turbulence can be leveraged to maintain a macro-stable, high-performance pedestal for future fusion reactors.

experimental nuclear physics↗
DOE OSTI2024

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Macro Scale Independently Homogenized Subcells for Modeling Braided Composites

An analytical method has been developed to analyze the impact response of triaxially braided carbon fiber composites, including the penetration velocity and impact damage patterns. In the analytical model, the triaxial braid architecture is simulated by using four parallel shell elements, each of which is modeled as a laminated composite. Currently, each shell element is considered to be a smeared homogeneous material. The commercial transient dynamic finite element code LS-DYNA is used to conduct the simulations, and a continuum damage mechanics model internal to LS-DYNA is used as the material constitutive model. To determine the stiffness and strength properties required for the constitutive model, a top-down approach for determining the strength properties is merged with a bottom-up approach for determining the stiffness properties. The top-down portion uses global strengths obtained from macro-scale coupon level testing to characterize the material strengths for each subcell. The bottom-up portion uses micro-scale fiber and matrix stiffness properties to characterize the material stiffness for each subcell. Simulations of quasi-static coupon level tests for several representative composites are conducted along with impact simulations.

Blinzler, Brina J.↗
DOE OSTI2022

Bridging the length scales on mechanical property evaluation (Final Report)

The development of small-scale mechanical testing in combination with microstructural investigation is of great interest to the nuclear materials community for both materials development and monitoring applications. Dramatically reducing the sample sizes to reduce radioactivity and obtaining mechanical properties of irradiated samples is truly intriguing. Moreover, such studies promise a range of benefits including cost reduction, fundamental insight in structure-property relationships, increased statistics on less sample material, and reinvestigation of prior irradiated and tested reactor samples while simultaneously enabling the generation of mechanical test data on ion beam irradiated materials with limited penetration depths. Small scale materials testing on sub-sized samples has been studied for several decades, though it has only been after the development of micro-testing based on Focused Ion Beam (FIB) sample manufacturing in that orders of magnitude smaller samples could really be investigated in a quantitative manner. In recent years, small scale mechanical testing techniques at a number of length scales has been developed for both unirradiated and irradiated (ion and neutron) materials. Technological advances made in this field have enabled ex-situ and in-situ transmission electron microscopy (TEM) and scanning electron microscopy (SEM) examination, thus leading to more accurate measurements as well as additional mechanistic information. A recent review of the benefits of these techniques show that these techniques are at a stage to tackle multi-scale ranges of materials investigations and can be utilized to obtain fundamental science-based understanding of nuclear materials. Considering the tremendous advances made, one can see how small-scale mechanical testing techniques combined with modeling can enable true small scale to bulk scale mechanical property correlations. However, for the engineering community to adapt this approach fully, one needs to demonstrate that a) that these techniques can produce results with high fidelity and reproducibility, b) generate engineering stress-strain data that one can utilize to understand bulk behavior, and c) generate new insight into relevant phenomena fostering the true understanding of radiation damage and microstructure in materials for nuclear applications. It is the objective of this proposal to bridge the length scale between macro- and micro- scale mechanical testing of unirradiated and irradiated materials. This involves the development and demonstration of procedures for multi-scale mechanical testing that enable high fidelity reproducibility of data and the generation bulk property data from small-scale mechanical tests. Through this, the proposal aims to enhance the confidence in the obtained data at the smaller length scales and enhance the insight provided from these techniques for bulk scale applications on both unirradiated and irradiated materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2022

Recommended Direct Simulation Monte Carlo Collision Model Parameters for Reacting Methane Flows

While hydrocarbon combustion and gas-surface interactions have been simulated for a variety of applications in continuum solvers, such processes have been rarely investigated in Direct Simulation Monte Carlo (DSMC). Thus Variable Hard/Soft Sphere (VHS/VSS)collision parameters are not available for most molecules of interest in the decomposition of methane, a significant pyrolysis gas product and potential atmospheric species for Titan re-entries. As these properties are essential for accurate modeling of gas transport and thermochemical effects, a method must be devised to compute them for use in DSMC. In this study, the methodology outlined in Stephani et al is utilized to compute the VHS/VSS parameters by fitting the Ω(1,1)and Ω(2,2) collision integrals [1]. These collision integrals are typically computed from intermolecular potentials and are used in CFD simulations to calculate transport properties such as viscosity, thermal conductivity, and diffusion. This approach ensures consistency between micro-scale collisions and macro-scale transport properties. To produce the necessary collision integrals needed for the fitting routine, we utilize the method described by Laricchiuta et al, where collision integrals are computed based on the constituent particles’ polarizability and effective electron number [2].Preliminary computations of pure-species Ω(1,1)and Ω(2,2)collision integrals produced from the coupled approach of Stephani et al and Laricchiuta et al for methane show good agreement with those computed via available ab-initio Potential Energy Surface Computations, as seen in Figure 1. Above 300K, no more than 12% deviation is observed between the two results over the temperature range of the fitted PES data [3].Current results of this study include full collision-specificVSS transport properties for a complex-species mixture involving major byproducts of pure methane decomposition. Targeted final results will include a comprehensive list of VSS parameters relevant toDSMC simulations of Titan atmospheric entry, based on the reduced kinetic model of Savajano et al [4].

M R Gosma↗
DOE OSTI2026

Advancing Detector R&D for High-Pressure Gaseous Argon TPCs in Precision Neutrino Physics

High-pressure gaseous argon time projection chambers (HPgTPCs) represent an emerging detector paradigm for neutrino physics, combining increased target density with the intrinsic tracking and low thresholds of gaseous detectors. This approach enables detailed reconstruction of exclusive final states, improved particle identification, and sensitivity to low-energy and rare processes — capabilities that are increasingly central to precision oscillation measurements and searches for beyond-the-Standard-Model signatures. This abstract presents an overview of ongoing detector R&D toward high-pressure gaseous argon TPC operation, with emphasis on micro-pattern gas detector (MPGD) charge amplification in argon-based mixtures. We report experimental characterization of triple-GEM structures at pressures relevant for neutrino applications, including studies of multiplication factor scaling, stability, and operational voltage envelopes across gas admixtures. Measurements performed at the TOAD and GORG test stands at Fermilab help define viable amplification and electronics noise regimes in conditions where higher density imposes stricter constraints on signal formation. These results provide essential input to the optimization of high-pressure gaseous argon detectors for future neutrino experiments, including near-detector concepts such as ND-GAr in DUNE Phase II near detector upgrade. More broadly, this program shows how dedicated detector R&D can expand the precision frontier in neutrino physics by enabling complementary reconstruction capabilities beyond conventional detectors.

McConnell, Brenna [Indiana U.] (ORCID:000900041138↗