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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthesis, microstructure and micro-mechanical characterization of metal (Nb, Ti) – MAX phase (Ti 2 AlC) nanolaminates

We utilize elevated temperature physical vapor deposition (PVD) techniques to design metal/MAX multilayered nanocomposite thin films with alternating nanoscale metallic (Nb, Ti) and MAX phase (Ti 2 AlC) layer thicknesses. These metal/MAX nanolaminate architectures attempt to exploit a unique hierarchical topology – as interfaces between the layers are expected to be in direct competition with the internal interfaces within the MAX layers, to drive their tunable macroscopic mechanical behavior. Two metal/MAX nanolaminates – Nb/Ti 2 AlC and Ti/Ti 2 AlC – were deposited. The Nb/Ti 2 AlC metal/MAX system showed highly diffused layer interfaces with distinct Ti – rich and Nb–Al – rich layers, with the presence of MAX phase alongside TiC and other Ti–Al and Nb–Al intermetallic phases. The Nb/Ti 2 AlC system possessed a layered architecture, though the MAX phases were not found to be continuously present in each alternating layer. The second Ti/Ti 2 AlC system showed a non-lamellar nanocomposite microstructure and the formation of mixed Ti n+1 AlC n phases (a mix of n = 1, 2), and no indication of layering. Diffusion occurring between the metal/MAX layers in both cases, likely due to the elevated temperatures during the deposition process, is speculated as the likely cause of these resultant microstructures. The mechanical properties of both systems were evaluated using micromechanical (nanoindentation and micro-pillar compression) techniques, which demonstrated high strengths for both systems (Nb system: yield and instability strengths of 4.88 ± 0.1 GPa and 5.57 ± 0.03 GPa, Ti system: yield and instability strength of 5.61 ± 0.28 GPa and 6.21 ± 0.25 GPa). In conclusion, this work highlights the promising mechanical properties of metal/MAX multilayered depositions and summarizes the challenges in PVD synthesis of metal/MAX multilayered nanolaminates.

MAX phase↗
DOE OSTI2026

Calculating shock Hugoniot and isentropes using multiphase equation of state tables and application to shock and release of diamond ablators in inertial confinement fusion implosions

Advances in shock and ramp compression techniques now allow experimental access to unprecedented extreme conditions of pressure and temperature, providing a means to test theoretical models. Here, we describe a simple methodology to compute multi-phase shock Hugoniot and isentropes using multiphase equation of state tables. We treat explicitly the phase coexistence along the phase boundary to reveal the evolution of the sample as it undergoes the phase transformation in adiabatic conditions. We illustrate the method by calculating the predicted shock and shock-and-release behavior of diamond at conditions relevant for the initial stage of inertial confinement fusion implosions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

LaSDI: Parametric Latent Space Dynamics Identification

Enabling fast and accurate physical simulations with data has become an important area of computational physics to aid in inverse problems, design-optimization, uncertainty quantification, and other various decision-making applications. This paper presents a data-driven framework for parametric latent space dynamics identification procedure that enables fast and accurate simulations. The parametric model is achieved by building a set of local latent space model and designing an interaction among them. An individual local latent space dynamics model achieves accurate solution in a trust region. By letting the set of trust region to cover the whole parameter space, our model shows an increase in accuracy with an increase in training data. Herein we introduce two different types of interaction mechanisms, i.e., point-wise and region-based approach. Both linear and nonlinear data compression techniques are used. We illustrate the framework of Latent Space Dynamics Identification (LaSDI) enable a fast and accurate solution process on various partial differential equations, i.e., Burgers’ equations, radial advection problem, and nonlinear heat conduction problem, achieving 0 (100)x speed-up and 0 (1)% relative error with respect to the corresponding full order models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Reduced order models for thermal radiative transfer problems based on moment equations and data-driven approximations of the Eddington tensor

Here a new group of structure and asymptotic preserving reduced-order models (ROMs) for multidimensional nonlinear thermal radiative transfer (TRT) problems is presented. They are formulated by means of the nonlinear projective approach and data compression techniques. The nonlinear projection is applied to the Boltzmann transport equation (BTE) to derive a hierarchy of low-order moment equations. Approximation of the Eddington tensor that provides exact closure for the system of moment equations is found with projection-based data-driven methodologies. These include the (i) proper orthogonal decomposition (POD), (ii) dynamic mode decomposition (DMD) and (iii) a variant of the DMD. A parameterization is derived for this ROM for the temperature of radiation incoming to the problem domain (the radiation drive temperature). This parameterization is informed from results of a dimensionless study of the TRT problem. Analysis of the ROMs is performed on the classical Fleck-Cummings TRT multigroup test problem in 2D geometry with a radiation-driven Marshak wave. Numerical results are presented to demonstrate the performance of these ROMs for the simulation of evolving radiation and heat waves. Results show these models to be sufficiently accurate for practical computations with rather low-rank representations of the Eddington tensor. As the rank of the approximation is increased, the errors of solutions generated by the ROMs gradually decreases.

42 ENGINEERING↗
DOE OSTI2025

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗
DOE OSTI2025

Neural architecture codesign for fast physics applications

We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method employs neural architecture search and network compression in a two-stage approach to discover hardware efficient models. This approach consists of a global search stage that explores a wide range of architectures while considering hardware constraints, followed by a local search stage that fine-tunes and compresses the most promising candidates. We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. We synthesize the optimal models to high level synthesis code for FPGA deployment with the hls4ml library. Additionally, our hierarchical search space provides greater flexibility in optimization, which can easily extend to other tasks and domains. We demonstrate this with two case studies: Bragg peak finding in materials science and jet classification in high energy physics, achieving models with improved accuracy, smaller latencies, or reduced resource utilization relative to the baseline models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Demonstration of a quantum-classical coprocessing protocol for simulating nuclear reactions

Quantum computers hold great promise for exact simulations of nuclear dynamical processes (e.g., scattering and reactions), which are paramount to the study of nuclear matter at the limit of stability and in the formation of chemical elements in stars. However, quantum simulations of the unitary (real) time dynamics of fermionic many-body systems require a currently prohibitive number of reliable and long-lived qubits. Here we propose a co-processing algorithm for the simulation of real-time dynamics in which the time evolution of the spatial coordinates is carried out on a classical processor, while the evolution of the spin degrees of freedom is carried out on quantum hardware. We demonstrate this hybrid scheme with the simulation of two neutrons scattering at the Lawrence Berkeley National Laboratory's Advanced Quantum Testbed. After implementing error mitigation strategies to improve the accuracy of the algorithm in addition to a combination of circuit compression techniques and tomography as methods to elucidate the onset of decoherence, our results validate the principle of the proposed co-processing scheme. A generalization of this present scheme will open the way for (real-time) path integral simulations of nuclear scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Latent Space Dynamics Identification

LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. It allows a fast and accurate solution process, which is useful for multi-query decision making applications, such as design optimization and uncertainty quantification. The performance of the LaSDI framework is demonstrated on four different problems, i.e., 1D and 2D Burgers equations, nonlinear heat conduction, and radial advection problems. Both linear and nonlinear compression techniques, such as neural network and proper orthogonal decomposition, are used to form a latent space. A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.

Fries, William↗
DOE OSTI2023

Data-Driven Smoothers for Extreme-Scale Computing

Patch-based relaxation refers to a family of methods for solving linear systems which partitions the matrix into smaller pieces often corresponding to groups of adjacent degrees of freedom residing within patches of the computational domain. The two most common families of patch-based methods are block-Jacobi and Schwarz methods, where the former typically corresponds to non-overlapping domains and the later implies some overlap. We focus on cases where each patch consists of the degrees of freedom on a finite element method mesh cell. Patch methods often capture complex local physics much more effectively than simpler point-smoothers such as Jacobi; however, forming, inverting, and applying each patch can be prohibitively expensive in terms of both storage and computation time. To this end, we propose several approaches for performing analysis on these patches and constructing a reduced representation. The compression techniques rely on either matrix norm comparisons or unsupervised learning via a clustering approach. We illustrate how it is frequently possible to retain/factor less than 5% of all patches and still develop a method that converges only a little slower than when all patches are stored/factored.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Oak Ridge National Laboratory Thermoplastic Composite Joining of Pultruded Continuous Fiber Spars for Multi-Functional Battery Enclosure

Oak Ridge National Laboratory (ORNL) worked with DowAksa Industry to investigate the potential of using PA66 material to produce larger composite parts, transcending the limitations of traditional presses. The project aimed to develop a suitable material for printing battery boxes using Nylon 66 infused with 40 wt.% carbon fiber, compatible with the ORNL Additive Manufacturing and Compression Molding (AM-CM) system. However, even with extensive work, it was concluded that the material is not compatible with the AMCM process and suitable for joining using compression technique. Main reason for the incompatibility were found to be very high crystallinity of the PA66 grade chosen for this work. To improve printability, a modifier (proprietary) was added to decrease crystallinity, but this led to reduced thermal stability and adhesion issues.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Viscosity Measurements in Extreme Conditions

Radiation-hydrodynamics simulations are critical to the NNSA complex for understanding high energy density physics and for addressing problems in national security science. However, current rad-hydro codes typically do not account for viscosity, which generally leads to large uncertainties in problems involving mixing of materials under shock loading. This report details progress made towards experimental measurements of fluid viscosity at high pressures and temperatures achieved by shock wave compression techniques, as well as complementary material model development and hydrodynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-Peak-Power Long-Wave Infrared Lasers with CO2 Amplifiers

Long-wave infrared (LWIR) picosecond pulses with multi-terawatt peak power have recently become available for advanced high-energy physics and material research. Multi-joule pulse energy is achieved in an LWIR laser system via amplification of a microjoule seed pulse with high-pressure, mixed-isotope CO 2 amplifiers. A chirped-pulse amplification (CPA) scheme is employed in such a laser to reduce the nonlinear interaction between the optical field and the transmissive elements of the system. Presently, a research and development effort is underway towards an even higher LWIR peak power that is required, for instance, for promising particle acceleration schemes. The required boost of the peak power can be achieved by reducing the pulse duration to fractions of a picosecond. For this purpose, the possibility of reducing the gain narrowing in the laser amplifiers and post-compression techniques are being studied. Another direction in research is aimed at the increased throughput (i.e., repetition rate), efficiency, and reliability of LWIR laser systems. The transition from a traditional electric-discharge pumping to an optical pumping scheme for CO 2 amplifiers is expected to improve the robustness of high-peak-power LWIR lasers, making them suitable for broad implementation in scientific laboratory, industrial, and clinical environments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Femtosecond diffraction and dynamic high pressure science

Solid-state material at high pressure is prevalent throughout the Universe, and an understanding of the structure of matter under such extreme conditions, gleaned from x-ray diffraction, has been pursued for the best part of a century. The highest pressures that can be reached to date (2 TPa) in combination with x-ray diffraction diagnosis have been achieved by dynamic compression via laser ablation. The past decade has witnessed remarkable advances in x-ray technologies, with novel x-ray Free-Electron-Lasers (FELs) affording the capacity to produce high quality single-shot diffraction data on timescales below 100 fs. We provide a brief history of the field of dynamic compression, spanning from when the x-ray sources were almost always laser-plasma based, to the current state-of-the art diffraction capabilities provided by FELs. We give an overview of the physics of dynamic compression, diagnostic techniques, and the importance of understanding how the rate of compression influences the final temperatures reached. We provide illustrative examples of experiments performed on FEL facilities that are starting to give insight into how materials deform at ultrahigh strain rates, their phase diagrams, and the types of states that can be reached. We emphasize that there often appear to be differences in the crystalline phases observed between the use of static and dynamic compression techniques. We give our perspective on both the current state of this rapidly evolving field and some glimpses of how we see it developing in the near-to-medium term.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Establishing gold and platinum standards to 1 terapascal using shockless compression

New techniques are advancing the frontier of high-pressure physics beyond 1 terapascal, leading to new discoveries and offering stringent tests for condensed-matter theory and advanced numerical methods. However, the ability to absolutely determine the pressure state remains challenging, and well-calibrated pressure-density reference materials are required. We conducted shockless dynamic compression experiments at the National Ignition Facility and the Z machine to obtain quasi-absolute, high-precision, pressure-density equation-of-state data for gold and platinum. We derived two experimentally constrained pressure standards to terapascal conditions. Establishing accurate experimental determinations of extreme pressure will facilitate better connections between experiments and theory, paving the way toward improving our understanding of material response to these extreme conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)

This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A kinetic model for pure electron plasma compression via the rotating wall technique

An approximate model for pure electron plasma compression is developed for the case where the rotating wall (RW) electric field couples to the ${E}\times{B}$rotation and axial bounce motion of the electrons. The key assumption in the model is that, throughout the compression, the plasma remains in a slowly evolving thermal equilibrium defined by the plasma temperature and angular momentum. Linearized drift kinetic theory is employed to derive an expression for torque exerted by the RW field on the plasma through coupling to the resonant plasma particles, and averaging is used to find the torque that both compresses and heats the plasma. The evolution equations for the angular velocity and temperature of the plasma include the compression and heating from the torque and cooling from cyclotron radiation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗