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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry–meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM 2.5 ). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O 3 , sulfate, nitrate, ammonium, elemental carbon, tropospheric O 3 residual, and column nitrogen dioxide (NO 2 ). For example, the mean biases have been reduced by more than 10 W m –2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O 3 . However, relatively large biases still exist for cloud predictions, some PM 2.5 species, and PM 10 that warrant follow-up studies to better understand those issues. The impacts of chemistry–meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O 3 , nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM 2.5 by 3.1 % (up to 27.8 %), 4.2 % (up to 16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 % (up to 49.1 %), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

58 GEOSCIENCES↗
NASA NTRS1997

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

Lewalle, Jacques↗
NASA NTRS1998

Environmental Remote Sensing: New Development and Applications

The term 'scale', both in space and time, is central to remote sensing and geographic information systems (GIS). The emergency and widespread use of GIS technologies, including remote sensing, has generated interest in addressing scale as generic Issue, and in the development and implementation of techniques for dealing explicitly with the vicissitudes of scale as a multidisciplinary issue. Traditionally, the paper map has been used as the primary conveyor of 'scale', represented by the ratio between the distance as measured between pairs of points on the map and distance as measured between the same pairs of points on the Earth's surface. GIS and remote sensing, however, have expanded upon the paper map and now provide opportunities for representing multiscale representations; that is databases or models that contain spatial and temporal data that have been obtained and stored at different scales.

Quattrochi, Dale A.↗
NASA NTRS2019

Four Years of Airborne Measurements of Wildfire Emissions in California, with a Focus on the Evolution of Emissions During the Soberanes Megafire

Biomass burning is an important source of trace gases and particles which can influence air quality on local, regional, and global scales. With wildfire events increasing due to changes in land use, increasing population, and climate change, characterizing wildfire emissions and their evolution is vital. In this work we report in situ airborne measurements of carbon dioxide (CO2), methane (CH4), water vapor (H2O), ozone (O3), and formaldehyde (HCHO) from nine wildfire events in California between 2013 and 2016, which were sampled as part of the Alpha Jet Atmospheric eXperiment (AJAX) based at NASA Ames Research Center. One of those fires, the Soberanes Megafire, began on 22 July 2016 and burned for three months. During that time, five flights were executed to sample emissions near and downwind of the Soberanes wildfire. In situ data are used to determine enhancement ratios (ERs), or excess mixing ratio relative to CO2, as well as assess O3 production from the fire. Changes in the emissions as a function of fire evolution are explored. Air quality impacts downwind of the fire are addressed using ground-based monitoring site data, satellite smoke products, and the Community Multiscale Air Quality (CMAQ) photochemical grid model.

Iraci, Laura T.↗
NASA NTRSDate not supplied

Nearfield Anisotropic Mesh Adaptivity for the Third AIAA Sonic Boom Workshop

The Third AIAA Sonic Boom Workshop provides a unique opportunity to verify nearfield Computational Fluid Dynamics (CFD) tools. The workshop gathered nearfield CFD pressures from families of Mach-aligned, manually-tailored meshes on the C608 Low Boom Flight Test Demonstrator and the shock-plume interaction wind tunnel model. Here two classical adaptive strategies, multiscale and goal-oriented, are compared to the results obtained on tailored grids. The multiscale strategy is implemented independently in two separate toolsets. Details of the adapted mesh density are shown that resolve the complex interaction of boundary layers, shocks, expansions, and vortical structures. Mesh convergence of nearfield pressure signatures and their integral is shown. These detailed comparisons between adapted and manually-tailored meshes and independent implementations of mesh adaptation demonstrate the readiness of these methods for controlling the discretization error of nearfield sonic boom predication.

Julien Vanharen↗
NASA NTRSDate not supplied

Application of a Rapid Design Tool to a 3D Woven Structural Joint

The optimization of composite structural joints is an iterative process and a multiscale problem. High fidelity finite element modeling of joints with 3D woven and laminated materials can become computationally expensive. The aim of this paper is to establish a reliable analysis process for the optimization of a composite Y-joint (curved Pi-joint), to be used in an aircraft fuselage, using commercial rapid joint design, analysis, and optimization software. The rapid joint design tool was investigated as a substitute and/or complement to a finite element analysis software. A composite Pi-joint and a composite Y-joint were evaluated using the rapid joint design tool to determine the applicability and limits of the software. Furthermore, three main preliminary parametric studies were performed to better understand the capability of the tool in predicting the stress distributions and trends in the Y-joint. The parameters investigated were the joint curvature, the laminated skin thickness, the adhesive systems, and the ply composition. Lastly, trends in predicted failure load were produced as a function of skin thickness (16ply, 24ply and 32ply). Failure loads were found with varying joint curvature and skin thickness using stress-based adherend failure criterion. The rapid joint design tool was also validated against existing experimental results.

Bonded Joints↗
NASA NTRSDate not supplied

Energy landscape in Ni-Co-Cr and related alloys

Among multi-principal element alloys, the NiCoCr middle-entropy alloy has an outstanding combination of strength and ductility at both low and elevated temperatures. Equiatomic NiCoCr is a single-phase alloy with the face centered cubic (fcc) crystal structure. A low stacking fault energy in the fcc matrix is a cause of a relatively low creep in this alloy. The hexagonal close-packed (hcp) structure differs from the fcc by a stacking of atomic layers. The energy difference between the hcp and fcc structures is known to correlate with the stacking fault energy in the fcc phase. We compute formation and relative structural energies versus composition in the Ni-Co-Cr ternary and related quaternary systems, discuss possibilities of compositional adjustments, and compare theoretical predictions with experiment. We acknowledge funding by NASA’s Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Multiscale↗
DOE OSTI2025

Investigating the Effect of Water on the Mechanical Properties of Cellulose from Multiscale Molecular Dynamics Simulations

Classical molecular dynamics (MD) simulations provide insight into the structure and physicochemical properties of materials with atomic resolution. However, the length and time scales accessible to atomistic MD are orders of magnitude smaller than many relevant processes such as the response of a bulk material to experimentally accessible strain rates, which presents challenges when comparing models to experimental measurements. Bottom-up coarse-graining provides a means for systematically mapping atomistic information to lower resolution models to increase the length and time scales achievable by simulation. Cellulose is an abundant carbohydrate biopolymer with applications to many fields of research, such as materials science and renewable energy, due to its desirable mechanical properties and viability for conversion into biofuel. The effect of moisture content on the Young's modulus of cellulose is of special interest due to its native environment often being in the hydrated secondary plant cell wall and the grinding energy requirements for biomass feedstock preprocessing. The current work investigates the effects of water solvent on the Young's modulus of cellulose calculated from coarse-grained MD mechanical stress simulations. The coarse-grained model was parametrized from atomistic MD calculations of cellulose-cellulose potentials of mean force using umbrella sampling techniques under vacuum and solvated conditions. The Young's moduli of the coarse-grained cellulose assemblies parametrized from cellulose in vacuum or solvated in water were computed via mechanical stress simulations to highlight the importance of capturing solvent interactions for modeling the mechanical behavior of cellulose.

BASIC BIOLOGICAL SCIENCES,RADIATION PROTECTION AND↗
DOE OSTI2022

Impact of Tropical Cyclone Wind Forcing on the Global Climate in a Fully Coupled Climate Model

Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1° atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25° atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs’ impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air–sea enthalpy fluxes, and cloud amount. Here, the added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2024

WUS324: Multiscale Full Waveform Inversion Approaching Convergence Improves Waveform Fits While Imaging Seismic Structure of the Western United States

Abstract We report a new model of radially anisotropic crustal and upper mantle structure of the western United States (WUS324) obtained from full waveform inversion of earthquake data. We ran three multiscale inversion stages beyond model WUS256 (Rodgers et al., 2022, https://doi.org/10.1029/2022jb024549 ) allowing them to approach convergence to fit a larger data set to a shorter minimum period of 16 s. WUS324 is based on 324 total iterations from its starting model, significantly more (16 times) than previous studies. Waveform misfit reductions are 66%–70% for both the inversion data and an independent validation data set providing confidence in the predictive power of the model. WUS324 provides much better fits and reveals shear wavespeed, v S , structure of this large region with more detail than previous waveform tomography models. We show representative images demonstrating the resolution of diverse seismic structure across this highly heterogeneous region including oceanic lithosphere, subducting slabs and continental magmatism.

58 GEOSCIENCES↗
DOE OSTI2023

Constraint energy minimizing generalized multiscale finite element method for multi-continuum Richards equations

In fluid flow simulation, the multi-continuum model is a useful strategy. When the heterogeneity and contrast of coefficients are high, the system becomes multiscale, and some kinds of reduced order methods are demanded. Combining these techniques with nonlinearity, we will consider in this paper a dual-continuum model which is generalized as a multi-continuum model for a coupled system of nonlinear Richards equations as unsaturated flows, in complex heterogeneous fractured porous media; and we will solve it by a novel multiscale approach utilizing the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM). In particular, such a nonlinear system will be discretized in time and then linearized by Picard iteration (whose global convergence is proved theoretically). Subsequently, we tackle the resulting linearized equations by the CEM-GMsFEM and obtain proper offline multiscale basis functions to span the multiscale space (which contains the pressure solution). More specifically, we first introduce two new sources of samples, and the GMsFEM is used over each coarse block to build local auxiliary multiscale basis functions via solving local spectral problems, that are crucial for detecting high-contrast channels. Second, per oversampled coarse region, local multiscale basis functions are created through the CEM as constrainedly minimizing an energy functional. Various numerical tests for our approach reveal that the error converges with the coarse-grid size and that only few oversampling layers as well as basis functions are needed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Irradiation damage reduces alloy corrosion rate via oxide space charge compensation effects

Radiation effects in materials often compound and accelerate other detrimental phenomena such as embrittlement, oxidation and creep. However, irradiation can also decrease the oxidation rate, for instance with ZrNb alloys nuclear fuel cladding. In this study, we rationalize this observation on Zr-0.5Nb alloy by introducing a mechanism based on oxide space charge modification, resulting from irradiation enhanced Nb clustering. Here, this mechanism is investigated using a multiscale approach: from the macroscale, to determine post-irradiation oxidation kinetics, to the atomic scale, using in-situ atom probe tomography sample oxidation, to observe elemental solute redistribution across the oxide/metal interface. The mechanism is further supported by high resolution transmission electron microscopy characterization and density functional theory calculations. A point defect model is proposed to account for oxide space charge effects and their changes under irradiation. This integrated, multiscale experimental and modeling approach challenges the current paradigm on irradiation effects and how they can potentially improve materials performance in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Generalizable coordination of large multiscale workflows: challenges and learnings at scale

The advancement of machine learning techniques and the heterogeneous architectures of most current supercomputers are propelling the demand for large multiscale simulations that can automatically and autonomously couple diverse components and map them to relevant resources to solve complex problems at multiple scales. Nevertheless, despite the recent progress in workflow technologies, current capabilities are limited to coupling two scales. In the first-ever demonstration of using three scales of resolution, we present a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback. We expand upon the massively parallel Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a recent, award-winning workflow, and generalize the framework beyond its original design. We discuss the challenges and learnings in executing a massive multiscale simulation campaign that utilized over 600,000 node hours on Summit and achieved more than 98% GPU occupancy for more than 83% of the time. We present innovations to enable several orders of magnitude scaling, including simultaneously coordinating 24,000 jobs, and managing several TBs of new data per day and over a billion files in total. Finally, we describe the generalizability of our framework and, with an upcoming open-source release, discuss how the presented framework may be used for new applications.

Bhatia, Harsh↗
DOE OSTI2021

Upscaling Reactive Transport and Clogging in Shale Microcracks by Deep Learning

Fracture networks in shales exhibit multiscale features. A rock system may contain a few main fractures and thousands of microcracks, whose length and aperture are orders of magnitude smaller than the former. It is computationally prohibitive to resolve all the fractures explicitly for such multiscale fracture networks. One traditional approach is to model the small-scale features (e.g., microcracks in shales) as an effective medium. Although this fracture-matrix conceptualization significantly reduces the problem complexity, there are classes of physical processes that cannot be accurately upscaled by effective medium approximations, e.g., microcrack clogging during mineral reactions. Here, we employ deep learning in place of effective medium theory to upscale physical processes in small-scale features. Specifically, we consider reactive transport in a fracture-microcrack network where microcracks can be clogged by precipitation. A deep learning multiscale algorithm is developed, in which the microcracks are upscaled as a wall boundary condition of the main fractures. The wall boundary condition is constructed by recurrent neural networks, which take concentration histories as input and predict the solute transport from main fractures to microcracks. The deep learning multiscale algorithm is firstly employed in specific scenarios, then a general model is developed which can work under various conditions. The new approach is validated against fully resolved simulations and an analytical solution, providing a reliable and efficient solution for problems that cannot be upscaled by effective medium models.

58 GEOSCIENCES↗
DOE OSTI2020

A multiscale cohesive law for carbon fiber networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. In this study, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mathematical Foundations for Nonlocal Interface Problems: Multiscale Simulations of Heterogeneous Materials (Final LDRD Report)

Nonlocal models provide a much-needed predictive capability for important Sandia mission applications, ranging from fracture mechanics for nuclear components to subsurface flow for nuclear waste disposal, where traditional partial differential equations (PDEs) models fail to capture effects due to long-range forces at the microscale and mesoscale. However, utilization of this capability is seriously compromised by the lack of a rigorous nonlocal interface theory, required for both application and efficient solution of nonlocal models. To unlock the full potential of nonlocal modeling we developed a mathematically rigorous and physically consistent interface theory and demonstrate its scope in mission-relevant exemplar problems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

A Multiscale Cohesive Law for Carbon Fiber Networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. Here, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

W. SCHILL↗