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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS)

Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.

Zhang, Yu↗
DOE OSTI2016

Lower Length Scale Model Development for Embrittlement of Reactor Presure Vessel Steel

This report summarizes the lower-length-scale effort during FY 2016 in developing mesoscale capabilities for microstructure evolution, plasticity and fracture in reactor pressure vessel steels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation induced defect accumulation and irradiation enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development of mesoscale capabilities for defect accumulation and solute precipitation are summarized. A crystal plasticity model to capture defect-dislocation interaction and a damage model for cleavage micro-crack propagation is also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Overview of lower length scale model development for accident tolerant fuels regarding U 3 Si 2 fuel and FeCrAl cladding

U 3 Si 2 and FeCrAl have been proposed as fuel and cladding concepts, respectively, for accident tolerance fuels with higher tolerance to accident scenarios compared to UO 2 . However, a lot of key physics and material properties regarding their in-pile performance are yet to be explored. To accelerate the understanding and reduce the cost of experimental studies, multiscale modeling and simulation are used to develop physics-based materials models to assist engineering scale fuel performance modeling. In this report, the lower-length-scale efforts in method and material model development supported by the Accident Tolerance Fuel (ATF) high-impact-problem (HIP) under the NEAMS program are summarized. Significant progresses have been made regarding interatomic potential, phase field models for phase decomposition and gas bubble formation, and thermal conductivity for U 3 Si 2 fuel, and precipitation in FeCrAl cladding. The accomplishments are very useful by providing atomistic and mesoscale tools, improving the current understanding, and delivering engineering scale models for these two ATF concepts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

DOE ASR Final Report on “Use of ARM Observations to Investigate the Role of Tropical Radiative Processes and Cloud Radiative Effects in Climate Simulations”

The overall objective of this ASR funded project is to investigate the role of cloud radiative effects, especially those associated with tropical thin cirrus clouds in the tropical tropopause layer, by analyzing the ARM observations combined with numerical models. In particular, we have processed and analyzed the observations from the Raman lidar at the ARM SGP and TWP sites. In the tenure of the project (8/15/2013 – 8/14/2016 and with a no-cost extension to 8/14/2017), we have been concentrating on (i) developing an automated feature detection scheme of clouds and aerosols for the ARM Raman lidar; (ii) developing an automated retrieval of cloud and aerosol extinctions for the ARM Raman lidar; (iii) investigating cloud radiative effects based on the observations on the simulated temperatures in the tropical tropopause layer using a radiative-convective model; and (iv) examining the effect of changes of atmospheric composition on the tropical lower-stratospheric temperatures. In addition, we have examined the biases in the CALIPSO-inferred aerosol direct radiative effects using ground-based Raman lidars at the ARM SGP and TWP sites, and estimated the impact of lidar detection sensitivity on assessing global aerosol direct radiative effects. We have also investigated the diurnal cycle of clouds and precipitation at the ARM site using the cloud radar observations along with simulations from the multiscale modeling framework. The main results of our research efforts are reported in the six referred journal publications that acknowledge the DOE Grant DE-SC0010557.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Progress update on lower length scale research and development on U3Si2 fuel and FeCrAl cladding

This report summarizes the lower length scale model development and studies in regards to two accident tolerant (ATF) concepts, U 3 Si 2 and FeCrAl. U 3 Si 2 is proposed to replace UO 2 fuel for its high thermal conductivity and higher uranium density. FeCrAl alloys are proposed to replace Zr based cladding for their high mechanical strength and good corrosion resistance. Before applying them in reactors, sufficient data are needed to establish their predictable in-pile performance, but largely missing, and they are costly and time consuming to obtain by experimental approaches. Under the NEAMS ATF high-impact-problem (HIP), multiscale modeling and simulations are used to develop atomistic and mesoscale tools, obtain fundamental material properties, and assess the behaviors of these two ATF concepts. The accomplishments in FY17 are briefly introduced in this report including the development of interatomic potentials, assessment of swelling in U 3 Si 2 , and Cr precipitation in FeCrAl alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Stochastic microstructural analysis of ceramic matrix composites using a high-fidelity multiscale framework

This paper presents a high-fidelity multiscale framework to simulate the mechanical behavior of ceramic matrix composites (CMCs), accounting for the complex micromorphology captured using detailed material characterization. First, high-resolution micrographs are obtained for the specific carbon fiber silicon-carbide-nitride matrix (C/SiNC) CMC to characterize the variability of the architectural features and manufacturing-induced defects at the microscale. An image processing algorithm is then used to precisely estimate the size and distribution of all subscale features and defects from the micrographs. The information is then used to generate a three-dimensional stochastic representative volume element (SRVE) to reconstruct microscale constituents accounting for the variability. As a result, the generated SRVEs are simulated using the high-fidelity generalized method of cells (HFGMC) micromechanics theory to investigate the effects of defects on the elastic properties of C/SiNC CMCs.

Ceramic Matrix Composites↗
DOE OSTI2017

Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. For multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Electron Scale Structures and Magnetic Reconnection Signatures in the Turbulent Magnetosheath

Collisionless space plasma turbulence can generate reconnecting thin current sheets as suggested by recent results of numerical magnetohydrodynamic simulations. The Magnetospheric Multiscale (MMS) mission provides the first serious opportunity to verify whether small ion-electron-scale reconnection, generated by turbulence, resembles the reconnection events frequently observed in the magnetotail or at the magnetopause. Here we investigate field and particle observations obtained by the MMS fleet in the turbulent terrestrial magnetosheath behind quasi-parallel bow shock geometry. We observe multiple small-scale current sheets during the event and present a detailed look of one of the detected structures. The emergence of thin current sheets can lead to electron scale structures. Within these structures, we see signatures of ion demagnetization, electron jets, electron heating, and agyrotropy suggesting that MMS spacecraft observe reconnection at these scales.

Yordanova, E.↗
NASA NTRSDate not supplied

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗
NASA NTRSDate not supplied

Ocean and Earth System Modelling

Petascale supercomputing infrastructure + modelling and analysis capabilities + interdisciplinary upper-ocean expertise Multiscale ocean turbulence simulation Physical-biogeochemical interactions Analysis of large data sets from remote sensing and Earth system model ensembles

Ocean↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Coordinate Multiscale FeCrAl Modeling

Since the events at the Fukushima-Daiichi nuclear power plant in March 2011 significant research has unfolded at national laboratories, universities and other institutions into alternative materials that have potential enhanced ac- cident tolerance when compared to traditional UO2 fuel zircaloy clad fuel rods. One of the potential replacement claddings are iron-chromium-alunimum (FeCrAl) alloys due to their increased oxidation resistance [1–4] and higher strength [1, 2]. While the oxidation characteristics of FeCrAl are a benefit for accident tolerance, the thermal neu- tron absorption cross section of FeCrAl is about ten times that of Zircaloy. This neutronic penalty necessitates thinner cladding. This allows for slightly larger pellets to give the same cold gap width in the rod. However, the slight increase in pellet diameter is not sufficient to compensate for the neutronic penalty and enriching the fuel beyond the current 5% limit appears to be necessary [5]. Current estimates indicate that this neutronic penalty will impose an increase in fuel cost of 15-35% [1, 2]. In addition to the neutronic disadvantage, it is anticipated that tritium release to the coolant will be larger because the permeability of hydrogen in FeCrAl is about 100 times higher than in Zircaloy [6]. Also, radiation-induced hardening and embrittlement of FeCrAl need to be fully characterized experimentally [7]. Due to the aggressive development schedule for inserting some of the potential materials into lead test assemblies or rods by 2022 [8] multiscale multiphysics modeling approaches have been used to provide insight into these the use of FeCrAl as a cladding material. The purpose of this letter report is to highlight the multiscale modeling effort for iron-chromium-alunimum (FeCrAl) cladding alloys as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program through its Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The approach taken throughout the HIP is to utilize lower length scale approaches (e.g., density functional theory, cluster dynamics, rate theory, phase field, and Visco-Plastic- Self-Consistent (VPSC)) to develop more physically informed models at the engineering scale for use in the BISON [9] fuel performance code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Multiscale Modeling of Supercritical Combustion with Two-Level Simulation on Adaptive Beamlets

Supercritical carbon dioxide (sCO 2 ) direct-powered turbine technology is a promising choice for the next generation of high-efficiency and low-emissions fossil fuel power systems. Breakthrough improvements in the design and development of the sCO 2 oxy-combustion devices are hampered by the lack of high-fidelity simulation tools suitable for the supercritical highly-CO 2 diluted reactive flow environment. The critically missing capabilities in many commercial and research codes exist due to the unaccounted effects of many nonlinearities, and the small-scale complex processes which become prominent at supercritical conditions. The present approach aims to address many shortcomings of the currently used models by adopting and generalizing a multiscale modeling concept of the Two-Level Simulation (TLS). In the TLS, all small-scale flow fields are simulated explicitly, albeit on one-dimensional (1D) domains -- beamlets represented by a collection of line segments embedded in a three-dimensional (3D) computational domain. In this research, we laid theoretical groundwork needed for application of the developed approach to variable density turbulent reacting flows and to sCO 2 combustors, in particular. The small-scale governing equations on the beamlets were introduced and analyzed by drawing a comparison with the supercritical Direct Numerical Simulation (DNS) data sets to validate the TLS modeling assumptions. A series of the 2D DNS studies of premixed flame propagation in pipes, in a highly CO 2 -diluted environment, was performed in order to elucidate the effects of dilution on the laminar burning velocity, flame thickness, as well as on the dynamics and morphology of a corrugated flame front. The demonstrated approach could be applicable to high-fidelity modeling of other supercritical combustion devices including liquid rocket engines.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Uncertainty quantification in elastic constants of SiC f /SiC m tubular composites using global sensitivity analysis

Silicon carbide fiber and silicon carbide matrix (SiC f /SiC m ) tubes produced through the chemical vapor infiltration process have become a candidate cladding material in nuclear applications. The performance of this composite is influenced by many variables such as braiding angle, porosity, material properties, etc., which vary over a range of values due to the inherent fluctuations in the manufacturing process. In this study, the variability in elastic constants of SiC f /SiC m composite has been quantified through multiscale finite element (FE) simulations, variable screening, and high-fidelity surrogate modeling. The key variables dominantly affecting the elastic constants of SiC f /SiC m tubes were identified using global sensitivity analysis. A surrogate to the high-fidelity FE-based model was used in Monte Carlo simulations to generate a hundred thousand samples from which the uncertainty in elastic constants was assessed. It turned out that the coefficient of variation was less than 10%.

Materials Science↗
NASA NTRS2010

Toward Realistic Simulation of low-Level Clouds Using a Multiscale Modeling Framework With a Third-Order Turbulence Closure in its Cloud-Resolving Model Component

This study presents preliminary results from a multiscale modeling framework (MMF) with an advanced third-order turbulence closure in its cloud-resolving model (CRM) component. In the original MMF, the Community Atmosphere Model (CAM3.5) is used as the host general circulation model (GCM), and the System for Atmospheric Modeling with a first-order turbulence closure is used as the CRM for representing cloud processes in each grid box of the GCM. The results of annual and seasonal means and diurnal variability are compared between the modified and original MMFs and the CAM3.5. The global distributions of low-level cloud amounts and precipitation and the amounts of low-level clouds in the subtropics and middle-level clouds in mid-latitude storm track regions in the modified MMF show substantial improvement relative to the original MMF when both are compared to observations. Some improvements can also be seen in the diurnal variability of precipitation.

Xu, Kuan-Man↗
DOE OSTI2017

Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

The major goal of this project was to contribute improvements to the infrastructure of an Earth System Model in order to support research in the Multiscale Methods for Accurate, Efficient, and Scale-Aware models of the Earth System project. In support of this, the NCAR team accomplished two main tasks: improving input/output performance of the model and improving atmospheric model simulation quality. Improvement of the performance and scalability of data input and diagnostic output within the model required a new infrastructure which can efficiently handle the unstructured grids common in multiscale simulations. This allows for a more computationally efficient model, enabling more years of Earth System simulation. The quality of the model simulations was improved by reducing grid-point noise in the spectral element version of the Community Atmosphere Model (CAM-SE). This was achieved by running the physics of the model using grid-cell data on a finite-volume grid.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Task-oriented machine learning surrogates for tipping points of agent-based models

We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numerical analysis of their emergent dynamics. The specific tasks of interest here include the detection of tipping points, and the uncertainty quantification of rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing the mimetic behavior of traders, and a compartmental stochastic epidemic model on an Erdös-Rényi network. We contrast the pros and cons of the different types of surrogate models and the effort involved in learning them. Importantly, the proposed framework reveals that, around the tipping points, the emergent dynamics of both benchmark examples can be effectively described by a one-dimensional stochastic differential equation, thus revealing the intrinsic dimensionality of the normal form of the specific type of the tipping point. This allows a significant reduction in the computational cost of the tasks of interest.

97 MATHEMATICS AND COMPUTING↗