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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.

42 ENGINEERING↗
DOE OSTI2019

Thermodynamic and structural evolution of mechanically milled and swift heavy ion irradiated Er 2 Ti 2 O 7 pyrochlore

Design and synthesis of thermodynamically metastable yet kinetically achievable materials possessing various desired functional and physical properties have recently drawn tremendous scientific-attention. In addition to conventional heat treatments and wet chemistry approaches, energy deposition into materials can induce unique nonequilibrium phases with distinct structures, chemistry, energetics, and properties. Mechanochemical synthesis and ion beam irradiation are two processing techniques that provide access to phases and states far from equilibrium. By a combination of high temperature oxide melt solution calorimetry, differential scanning calorimetry (DSC), neutron pair distribution function (PDF) analysis, and supplementary powder X-ray diffraction (XRD), the energetics and multiscale structural evolution on annealing of ball milled and swift heavy ion irradiated Er 2 Ti 2 O 7 pyrochlore were investigated. Despite very similar structural modifications of local atomic arrangements and only minor differences in the long range structure, both types of damage yield significant difference in the energetics of the produced material. Here, the energy of destabilization in the milled sample (70.2 ± 8.2 kJ/mol) is much less endothermic than that in the irradiated sample (457.3 ± 8.0 kJ/mol). The DSC profiles, supported by neutron scattering, X-ray diffraction, and solution calorimetry, reveal decoupled annealing events in different temperature ranges, separating crystallization of long range pyrochlore structure from annealing of short range weberite-like domains.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improved multiphysics model of the High Temperature Engineering Test Reactor for the simulation of loss-of-forced-cooling experiments

We present a multiphysics model of the High Temperature Engineering Test Reactor for comparison with past and predict future loss-of-forced-cooling (LOFC) experiments. The approach selected combines (1) 3-D full-core superhomogenization-corrected neutronics, (2) 3-D full-core homogenized or semi-heterogeneous heat transfer (macroscale), (3) 2-D axisymmetric fuel rod heat transfer (mesoscale), and (4) 1-D thermal-hydraulics channels. Although large sensitivities remain and the available experimental data are insufficient for use in a rigorous validation exercise, the overall transient behavior is successfully reproduced. The novelty of our work includes (1) a new macroscale-mesoscale heat transfer coupling approach relying on gap conductance to drastically speed up numerical convergence by two orders of magnitude, (2) determination of a radial effective thermal conductivity that yields reasonably close results between the homogenized and semi-heterogeneous macroscale thermal models, and (3) a preliminary study of the reactor's early behavior following a LOFC event, thus enabling further assessment of numerical models against fission power measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗
DOE OSTI2016

Appalachian Basin Play Fairway Analysis Gravity, Magnetics, and Earthquake Data

This archived dataset contains magnetic and gravity imaging data for the Appalachian Basin, compiled using Poisson Wavelet Multiscale Edge Detection, referred to as 'worm' for brevity, and stored in a PostGIS database, along with shapefiles and CSVs of relevant data. The archive also includes regional earthquake data going back to 1973 and relevant world stress map data. These data are used in estimating the seismic hazards (both natural and induced) for candidate direct use geothermal locations in the Appalachian Basin Play Fairway Analysis by Jordan et al. (2015).

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Toward predictive permeabilities: Experimental measurements and multiscale simulation of methanol transport in Nafion

A polymer membrane's permeability to solutes determines its suitability for various applications: a permeability value is essential for predicting performance in diverse contexts. Using aqueous methanol permeation through Nafion as an example, we describe a methodology for determining membrane permeability that accounts for boundary layer effects and the possibility of swelling. For the materials and apparatus used herein, analysis of a permeance measurement and computational fluid dynamics simulations show that the mass transfer boundary layer is on the order of ones to tens of microns. Additionally, the data are used to develop and validate a multiscale model describing solute permeation through a hydrated membrane as a series of physical mechanistic steps: reversible adsorption from solution at the membrane interface, diffusion driven by a concentration gradient within the membrane, and reversible desorption into solution at the opposite membrane interface. The validated model is used to predict methanol transport across a solar-driven CO 2 reduction device and to assess the impact of polymer changes on the measured value. The approach of combining experimental data, computational fluid dynamics, and the mechanistic multiscale model is expected to provide more accurate analysis of membrane permeation data in cases with polymer swelling or unusual device geometries, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An efficient protocol for excited states of large biochromophores

Efficient energy transport in photosynthetic antenna is a long-standing source of inspiration for artificial light harvesting materials. However, characterizing the excited states of the constituent chromophores poses a considerable challenge to mainstream quantum chemical and semiempirical excited state methods due to their size and complexity and the accuracy required to describe small but functionally important changes in their properties. In this paper, we explore an alternative approach to calculating the excited states of large biochromophores, exemplified by a specific method for calculating the Q y transition of bacteriochlorophyll a, which we name Chl-xTB. Using a diagonally dominant approximation to the Casida equation and a bespoke parameterization scheme, Chl-xTB can match time-dependent density functional theory’s accuracy and semiempirical speed for calculating the potential energy surfaces and absorption spectra of chlorophylls. We demonstrate that Chl-xTB (and other prospective realizations of our protocol) can be integrated into multiscale models, including concurrent excitonic and point-charge embedding frameworks, enabling the analysis of biochromophore networks in a native environment. We exploit this capability to probe the low-frequency spectral densities of excitonic energies and interchromophore interactions in the light harvesting antenna protein LH2 (light harvesting complex 2). The impact of low-frequency protein motion on interchromophore coupling and exciton transport has routinely been ignored due to the prohibitive costs of including it in simulations. Our results provide a more rigorous basis for continued use of this approximation by demonstrating that exciton transition energies are unaffected by low-frequency vibrational coupling to exciton interaction energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Multiscale Reduced Order Modeling and Parameter Estimation for Climate Sciences

Several problems in earth system modeling are dependent on highly multiscale phenomena, such as turbulence, where computational modeling is challenging and expensive. This issue is exacerbated in atmospheric and oceanic domains, due to inherent high-dimensionality of the problem. One approach to this problem has been reduced order modeling (ROM); which aims to represent the key physics of the phenomena as a low-dimensional system. AI methods have huge potential in building accurate, stable ROMs and parameter estimation for these ROMs, as it requires extracting nonlinearities and patterns from simulation and/or observational data. Developing physics-based AI approaches specialized for the complexities of multiscale data, along with strategies to account for uncertainties, will revolutionize rapid modeling, analysis and decision making for earth system problems of practical interest.

58 GEOSCIENCES↗
DOE OSTI2023

Multidimensional Diagnostics of the Interface Evolutions in Solid-State Lithium Batteries

All-solid-state lithium metal batteries hold tremendous potential as next-generation energy storage solutions. However, their performance is hindered by complex chemo-mechanical instabilities at the interface, which encompass electrolyte decomposition, loss of contact due to volume changes, and the growth of lithium filaments. Given the complexity of these failure mechanisms, it is imperative to employ multidimensional diagnostics that leverage a combination of tools capable of quantifying formed voids and filaments, identifying the chemical and mechanical properties of lithium dendrites and electrolyte decomposition products, as well as monitoring the evolution of these processes in situ. The primary objective of this project is to develop a comprehensive characterization platform for solid-state battery interfaces, integrating FIB-SEM tomography, ToF-SIMS, in-SEM nanoindentation, and in-SIMS AFM-based stiffness mapping to enable structural, chemical, and mechanical analyses. The project team has accomplished significant milestones, including: 1) The successful development of a characterization platform that combines FIB-SEM, ToF-SIMS, nanoindentation, and AFM. 2) The creation of solid-state cells at various scales. 3) Real-time visualization of the plating and stripping of lithium. 4) Operando analysis of the chemical composition and evolution of electrolyte decomposition products, encompassing intermediate and metastable species, at both the cathode and anode interfaces. 5) In situ analysis of mechanical properties coupled with chemical mapping. 6) The implementation of the multiscale characterization technique has yielded valuable insights into cell failure mechanisms and has led to the development of a solid-state lithium cell that exhibits exceptional durability, surpassing 2500 cycles. This project has resulted in 10 publications, 1 invention disclosure, 8 manuscripts under review or in preparation.

25 ENERGY STORAGE↗
DOE OSTI2017

Analysis of a Complex Faulted CO 2 Reservoir Using a Three-dimensional Hydro-geochemical-Mechanical Approach

This work applies a three-dimensional (3D) multiscale approach recently developed to analyze a complex CO 2 faulted reservoir that includes some key geological features of the San Andreas and nearby faults. The approach couples the STOMP-CO2-R code for flow and reactive transport modeling to the ABAQUS ® finite element package for geomechanical analysis. The objective is to examine the coupled hydro-geochemical-mechanical impact on the risk of hydraulic fracture and fault slip in a complex and representative CO 2 reservoir that contains two nearly parallel faults. STOMP-CO2-R/ABAQUS ® coupled analyses of this reservoir are performed assuming extensional and compressional stress regimes to predict evolutions of fluid pressure, stress and strain distributions as well as potential fault failure and leakage of CO 2 along the fault damage zones. The tendency for the faults to slip and pressure margin to fracture are examined in terms of stress regime, mineral composition, crack distributions in the fault damage zones and geomechanical properties. Here, this model in combination with a detailed description of the faults helps assess the coupled hydro-geochemical-mechanical effect.

58 GEOSCIENCES↗
DOE OSTI2025

Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

A systems science approach based on canonical correlation analysis (CCA) is applied as a new, behavioral way to validate global geospace models. The biggest novelty of the technique is that it validates models at a system level, whereby a side‐by‐side comparison is performed of CCA applied to a 30‐day observational and the corresponding simulation data sets comprising quiet, moderate and active times. The simulation used the Multiscale Atmosphere‐Geospace Environment (MAGE) model. It is shown that (a) CCA must be combined with sensitivity analysis to be effective, (b) the MAGE model generally reproduces the observed behavior (more so for quieter time intervals), quantified by the intercorrelations between different variables and (c) the technique identifies the SuperMAG SML index as a quantity for which refinements of the model are needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Separability of microtearing mode and electron temperature gradient turbulence regimes

The separability of microtearing mode (MTM)-dominated and electron temperature gradient (ETG)-driven turbulence regimes is studied with multiscale nonlinear gyrokinetic simulations. The simulations are based on National Spherical Torus Experiment-like, high-confinement mode pedestal parameters, where electromagnetic perturbations are large. Linear analysis indicates a wide scale-separation between the MTM and ETG modes in binormal wavenumber space (perpendicular to the magnetic field line), with no unstable modes at intermediate scales. Likewise, single-scale nonlinear analyses, retaining ion-only or electron-only spatio-temporal scales, produce seemingly well-converged transport states. Surprisingly, the multiscale simulation, which contains both the ion and electron scales, closely follows the transport from the electron-scale simulation. This trend is robust over a wide range of electron temperature gradient. Remarkably, compared to ion-scale simulations, MTM turbulence is significantly reduced at multiscale resolution even when ETG turbulence is low. In this case, traditional ion-scale resolution overestimates the electron energy flux, and it is not possible to accurately simulate the MTM turbulence with separable ion-scale simulations. Here, while the analysis confirms the validity of electron-scale simulations for predicting the electron transport, it also indicates that multiscale simulation may be required for reproducing the turbulence spectrum for systems with coupled MTM-ETG turbulence.

H-mode↗
DOE OSTI2016

Asynchronous in situ connected-components analysis for complex fluid flows

Fluid flow in porous media is at the heart of problems such as groundwater contamination and carbon sequestration, and presents an important challenge for scientific computing. For this class of problem, large three-dimensional simulations are performed to advance scientific inquiry. On massively parallel computing systems, the volume of data generated by such approaches can become a productivity bottleneck if the raw data generated from the simulation is analyzed in a post-processing step. We present a physics-based framework for in situ data reduction that is theoretically grounded in multiscale averaging theory. We show how task parallelism can be exploited to concurrently perform a variety of analysis tasks with data-dependent costs, including the generation of iso-surfaces, morphological analyses, and connected components analysis. A task management framework is constructed to launch asynchronous analysis threads, manage dependencies between different tasks, promote data locality and hide the impact of data transfers. The framework is applied to analyze GPU-based simulations of two-fluid flow in porous media, generating a set of averaged measures that represents the overall system behavior. We demonstrate how the approach can be applied to perform physically-consistent averaging over fluid subregions using connected components analysis. Simulations performed on Oak Ridge National Lab s Titan supercomputer are profiled to demonstrate the performance of the associated multi-threaded in situ analysis for typical production simulation of two-fluid flow.

Mcclure, James↗
DOE OSTI2025

Beyond Price-Taker: Multiscale Optimization of Wind and Battery Integrated Energy Systems

Integrating renewable energy into the electric grid is challenging due to the intermittency and variability of wind and other non-dispatchable resources. Integrated energy systems (IESs) combine multiple energy technologies (e.g., fossil, nuclear, renewables, storage) to reduce costs and improve flexibility and reliability. However, standard techno-economic analysis (TEA) methods often overestimate the benefits of IESs because they fail to account for energy market adjustments. This paper systematically studies the limitations of the prevailing price-taker assumption for TEA and optimization of hybrid energy systems. As an illustrative case study, we retrofit an existing wind farm in the RTS-GMLC test system (which loosely mimics the Southwest U.S.) with battery energy storage to form an IES. We show that the standard price-taker model overestimates the electricity revenue and the net present value (NPV) of the IES up to 178% and 30.4%, respectively, compared to our more rigorous multiscale optimization. These differences arise because introducing storage creates a more flexible resource that impacts the larger wholesale electricity market. Moreover, this work highlights the impact of the IES has on the market via various strategic bidding, and underscores the importance of moving beyond price-taker for optimal storage sizing and TEA of IESs. We conclude by discussing opportunities to generalize the proposed framework to other IESs, and highlight emerging research questions regarding the complex interactions between IESs and markets.

25 ENERGY STORAGE↗
DOE OSTI2017

Comprehensive End-to-End Design of Novel High Energy Density Materials: II. Computational Modeling and Predictions

In this work, we have proposed a holistic approach to design novel energetic materials by bridging synthesis, experimental characterization, computational modeling, and validation. Multiscale computational modeling that combines first-principles calculations, analytical theory, and empirical statistical analysis served to further advance the proposed methodology. The established materials design guiding principles led to development of a set of new energetic molecules, PHE-1, PHE-2, and PHE-3, that represent improved variations of the heterocyclic energetics and are predicted to be superior to the existing conventional energetic materials. Molecular mechanisms of the enhanced performance and sensitivity of the proposed energetic materials as a function of their chemical composition and structure are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

tell: a Python package to model future total electricity loads in the United States

The purpose of the Total ELectricity Load (tell) model is to generate 21st century profiles of hourly electricity load (demand) across the Conterminous United States (CONUS). tell loads reflect the impact of climate and socioeconomic change at a spatial and temporal resolution adequate for input to an electricity grid operations model. tell uses machine learning to develop profiles that are driven by projections of climate/meteorology and population. tell also harmonizes its results with United States (U.S.) state-level, annual projections from a national- to global-scale energy-economy model. This model accounts for a wide range of other factors affecting electricity demand, including technology change in the building sector, energy prices, and demand elasticities, which stems from model coupling with the U.S. version of the Global Change Analysis Model (GCAM-USA). tell was developed as part of the Integrated Multisector Multiscale Modeling (IM3) project. IM3 explores the vulnerability and resilience of interacting energy, water, land, and urban systems in response to compound stressors, such as climate trends, extreme events, population, urbanization, energy system transitions, and technology change

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Building a Cyberinfrastructure for Environmental System Science: Modeling Frameworks, Data Management, and Scientific Workflows, Workshop Report, Potomac, Maryland, April 30-May 1, 2015

The Environmental System Science (ESS) activity within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) seeks to advance a robust, predictive understanding of terrestrial environments, extending from bedrock to the top of the vegetative canopy and from molecular to global scales, through an iterative cycle of model-driven experimentation and observation dubbed MODEX. Considerable progress has been made toward achieving this overarching goal, but widely recognized is the fragmentation across projects and disciplines of the relevant modeling and simulation capabilities, observational and experimental data, analysis algorithms, and workflow tools. This fragmentation creates significant challenges for studying impacts and feedbacks in these complex multiscale systems. These challenges are further exacerbated by ongoing disruptive changes in high-performance computational architectures and the exponential growth in the types and volume of data that render obsolete the conventional approaches to software development and data management. Overcoming these challenges will require the development of a BER Climate and Environmental Sciences Division (CESD)–wide enabling cyberinfrastructure to support data management, cross-domain modeling, data analysis, and collaborative research. To explore the potential for working groups to initiate and guide a more integrated and community-based cyberinfrastructure, BER held the ESS Workshop on Model-Data Integration: Modeling Frameworks, Data Management, and Scientific Workflows on April 30-May 1, 2015, following the ESS Principal Investigator Meeting in Potomac, Maryland. Participants included model developers, software engineers, and data management specialists from eight national laboratories, which represented a wide range of projects and programs from CESD as well as cross-cutting projects from DOE’s Office of Advanced Scientific Computing Research (ASCR; both BER and ASCR are operated from within DOE’s Office of Science). A series of plenary talks provided background information and clarified the workshop’s three objectives: (1) develop requirements for this community-based cyberinfrastructure to ensure enhanced scientific productivity of the community as a whole; (2) identify challenges associated with developing this new cyberinfrastructure using a phased approach guided by project-driven use cases; and, given these requirements and challenges, (3) chart a path forward for ESS working groups to lead the phased development of the new cyberinfrastructure.

54 ENVIRONMENTAL SCIENCES↗