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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tardigrade-examples V0.1.0

Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.

Allard, Thomas↗
DOE OSTI2026

MATEY

Scalable open-source codebase for developing spatiotemporal foundation models for multiscale multiphysics systems

Zhang, Pei [Oak Ridge National Laboratory] (000000↗
DOE OSTI2025

Prediction of cccDNA dynamics in hepatitis B patients by a combination of serum surrogate markers

Quantification of intrahepatic covalently closed circular DNA (cccDNA) is a key for evaluating an elimination of hepatitis B virus (HBV) in infected patients. However, quantifying cccDNA requires invasive methods such as a liver biopsy, which makes it impractical to access the dynamics of cccDNA in patients. Although HBV RNA and HBV core-related antigens (HBcrAg) have been proposed as surrogate markers for evaluating cccDNA activity, they do not necessarily estimate the amount of cccDNA. Here, we employed a recently developed multiscale mathematical model describing intra- and intercellular viral propagation and applied it in HBV-infected patients under treatment. We developed a model that can predict intracellular HBV dynamics by use of extracellular viral markers, including HBsAg, HBV DNA, and HBcrAg in peripheral blood. Importantly, the model prediction of the amount of cccDNA in patients over time was confirmed to be well correlated with the data for quantified cccDNA by paired liver biopsy. Thus, our method combining classic and emerging surrogate markers enables us to predict the decay dynamics of cccDNA in patients undergoing treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

On the frontiers of coupled extreme environments

Coupled extreme environments pose among the highest demands on materials, stressing the limits of temperature, pressure, electric and magnetic fields, atomic displacement rates, and chemical potentials that can be simultaneously sustained. Here, this issue highlights exciting new materials science methods that will enable rapid progress in what has traditionally been the most difficult materials arena. New opportunities in artificial intelligence, multi-physics simulations capabilities, the use of extreme conditions to synthesize novel materials, and our ability to interrogate materials under relevant conditions provide new avenues to understand and design new materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bridging Multiscale Processes in Earth System Models with Physics-Guided Hierarchical Machine Learning

Focal Area(s): The focal area of this whitepaper is, “Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI driven model/component/parameterization selection).” The ideas and frameworks described herein are deemed site agnostic. As a use case, this group will initially focus on the coupling between land processes, surface/subsurface hydrological processes, coastal processes, and human activities in the U.S. Gulf states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multi-scale Multi-physics Scientific Machine Learning for Water Cycle Extreme Events Identification, Labelling, Representation, and Characterization

Impacts of climate are usually felt through extreme events such as droughts, floods, thunderstorms, windstorms, wildfires, and so on, that are intimately tied to the water cycle. Predicting the frequency and severity of extreme events under climate change remains a significant challenge; meanwhile, the mechanisms and impacts of these extremes are far from well understood. There are several major science challenges: (1) Lack of labelled extreme events data and missing standards in defining extremes; (2) Computational demand of high-resolution ensemble climate modeling; (3) Modeling the multiscale multi-physics hierarchical structure of compound extremes; (4) Lack of understanding of mechanisms of extreme events; (5) Large uncertainty in extreme events impacts on infrastructure; (6) Subjective assessment of weather-related risk from seasonal to multi-decadal time scales and lack of metrics for risk assessment and mitigation control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiscale Patterning from Competing Interactions and Length Scales

We live in an era of complexity marked by impressive new tools powering the scientific method to accelerate discovery, prediction, and control of increasingly complex systems. In common with many disciplines and societal challenges and opportunities, materials and condensed matter sciences are beneficiaries. The volume and fidelity of experimental, computational, and visualization data available, and tools to rapidly interpret them, are remarkable. Conceptual frameworks, including multiscale, multiphysics modeling of this complexity, are fueled by the data and, in turn, guide directions for future experimental and computational strategies. In this spirit, we discuss the importance of competing interactions, length scales, and constraints as pervasive sources of spatio-temporal complexity. We use representative examples drawn from materials and condensed matter, including the important role of elasticity in some technologically important quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cooperative Research and Development Agreement among National Energy Technology Laboratory, Advanced Manufacturing LLC, and Connecticut Center for Advanced Technology [Abstract]

The National Energy Technology Laboratory (NETL), Advanced Manufacturing LLC (AMLLC) and Connecticut Center for Advanced Technology (CCAT) will collaborate to develop and manufacture cost-effective, oxide dispersion-strengthened, NiCrFeCo-rich high entropy alloys that are superior to Nickel-based superalloys (e.g. IN740) for repair or replacement service in extreme environments. The new alloys can result in higher efficiency and reduced cost of advanced power systems such as advanced ultra-supercritical (AUSC) boilers and gas turbines. High throughput, multiscale computational modeling will be performed to accelerate alloy discovery by interrogating the intrinsic properties of the alloys including thermodynamic, kinetic, and mechanical properties. Validation and evaluation will be performed, including additive manufacturing, microstructure characterization, and mechanical properties tests.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electrochemical Hydrogen Compression Cell Design (CRADA Final Report)

Electrochemical compression and purification is a high potential technology that is likely to outcompete mechanical compression for hydrogen end use applications. However, testing and understanding what is occurring within the cell is difficult as it is not readily accessible through experimentation. Thus, the main target is to increase performance and reduce cost of electrochemical hydrogen compression (EHC) and purification (EHP) cells and stacks using multiscale mathematical modeling informed by experiment. The models can provide physical insight into limiting processes and develop mitigation methods, which can be proven out through rapid sub-scale testing of the devices.

08 HYDROGEN↗
DOE OSTI2023

Results of the Micromorphic Upscaling Workflow for the PSAAP III Year 3 Report

Predicting the mechanical response and failure of heterogeneous materials has proven difficult. Multiscale numerical methods based in higher order continuum theories attempt to bridge the gap between microscale and macroscale structural behavior. Micromorphic continuum theories have shown promise. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling workflows. These include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This work discusses micromorphic upscaling efforts of the University of Colorado Boulder PSAAP III multidisciplinary simulation center (MSC). Verification studies are presented that compare the accuracy of the upscaling workflow with analytical solutions for a trivial stress state and homogeneous material using direct numerical simulations (DNS) conducted in the Ratel finite element method (FEM) and GEOS material point method (MPM) codes. These verification studies consider upscaling using the Micromorphic Filter for a “single filter domain”. Finally, DNS of a heterogeneous composite material is upscaled using a “multiple filter domain” method.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reaction engineering: a lost (and found) art for a decarbonized future [Slides]

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For traditional industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, new-age process concepts proposing to use "exotic" reactors and/or sustainable inputs (e.g., renewable carbon resources, electrons, photons, plasma) face a dearth of well documented reaction engineering principles & design practices that eclipses their rapid adoption. This presentation features two vignettes of (the return of) reaction engineering in sustainable process science, first in the valorization of lignin from biomass, and second in understanding multimodal catalyst deactivation in industrial-scale reactors within the Catofin process for propane dehydrogenation. Overall, this seminar seeks to educate student researchers on practical means of advancing laboratory reactor technologies towards commercial practice.

09 BIOMASS FUELS↗
DOE OSTI2023

Conceptual Design of Integrated Energy Systems via Multiscale Market Simulations and Surrogate Models for Market Interactions

This final report describes novel capabilities developed as part of DISPATCHES, Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems, for designing hybrid energy systems (HES) a.k.a. integrated energy systems (IES) in the context of a larger electricity market. Capabilities are demonstrated on case studies for nuclear and renewable power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Establishment of a Vertically Integrated Domestic Manufacturing Process for Production of Substrates Needed for Manufacture of Gas Diffusion Layers

In this project, AvCarb, LLC evaluated the baseline performance metrics of commercial carbon veils and their corresponding Gas Diffusion Layers (GDLs) with the goal of establishing an optimized, vertically integrated production system for wet-laid nonwoven substrates used in gas diffusion media for electrochemical energy storage and conversion devices. Mechanical testing and microstructural characterization were conducted and used to develop a multiscale computational model capable of simulating and predicting the performance of GDLs in fuel cells. Although the project successfully generated foundational transport and modeling data, it was terminated prior to identifying the critical GDL design parameters necessary for full optimization. The program aimed to improve carbon veil fabrication through enhanced fiber dispersion, fiber-fiber adhesion control, and improved web formation, enabling the production of high-quality, uniform substrates. Simulations were intended to guide mixing and solution delivery system design and process conditions, followed by production-scale trials to evaluate fiber dispersion, web uniformity, and mechanical robustness. At full deployment, the proposed production line would have been capable of producing approximately 650,000 m² of carbon veil annually. This capability remains strategically important, as the United States currently lacks a domestic source of wet-laid nonwoven carbon substrates that satisfy the stringent quality requirements for fuel-cell GDLs and electrolyzers representing an ongoing supply-chain vulnerability. Beyond supply-chain benefits, the project established a robust benchmarking dataset for existing commercial carbon veils while advancing next-generation material concepts targeting improved performance and manufacturing consistency.

Olson, Cynthia Lemay↗
DOE OSTI2023

Electric Grid Visualization: Hourly Renewable Generation, Load, Unserved Load, and Locational Marginal Prices during a Heatwave

Visualization of hourly solar and wind generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018, 2058, and 2098. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided.

Climate Change↗
DOE OSTI2023

WRF Output from 270m domain running simulation with no 3D morphology, NUDAPT 3D morphology, 100m resolution 3D morphology and 10m resolution 3D morphology

This is a group of four datasets that were run for an experiment testing the effect of the resolution and the coverage of 3D urban morphological inputs on meteorological output. This data is associated with the paper "Sensitivity of Urban Morphology to the Resolution of Urban Morphological Feature Inputs: Implications for Characterizing Urban Sustainability."

integrated multisector multiscale modeling↗
DOE OSTI2024

WRF Output from 270m domain running simulation with no 3D morphology, NUDAPT 3D morphology, 100m resolution 3D morphology and 10m resolution 3D morphology

This is a group of four datasets that were run for an experiment testing the effect of the resolution and the coverage of 3D urban morphological inputs on meteorological output. This data is associated with the paper "Sensitivity of Urban Morphology to the Resolution of Urban Morphological Feature Inputs: Implications for Characterizing Urban Sustainability."

integrated multisector multiscale modeling↗