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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Model-Data for Joint Estimation of Biogeochemical Model Parameters from Multiple Experiments: A Bayesian Approach Applied to Mercury Methylation

This modeling archive supports the manuscript submitted for publication in the Environmental Modeling and Software. This study is supported by ORNL-SFA and IDEAS-Watershed. This study aims to improve calibration of complex biogeochemical models using datasets from multiple experiments targeting specific subprocesses. The proposed Bayesian joint-fitting scheme calibrates the entire biogeochemical model in one go using all the available datasets and estimate parameter uncertainties using Markov Chain Monte Carlo (MCMC). This allows for complete propagation of uncertainties and utilization of the information shared between different datasets. Mapping joint distribution of parameters guides model improvement by identifying null spaces in the parameter space. This archive contains files used to perform MCMC, post-process outputs and visualize results.

East Fork Poplar Creek↗
DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models

Core Ideas We propose VSHC for calculating soil water percolation in continuous models. VSHC relates permeability to daily hydraulic properties to estimate hydraulic conductivity. VSHC performed well at field scale and improved estimates of peak streamflows. Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping‐bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new submodel, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long‐term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high‐flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale.

Doro, Luca↗
DOE OSTI2012

Coupling in silico microbial models with reactive transport models to predict the fate of contaminants in the subsurface (Final Report)

This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Integrating NASA Earth Science Capabilities into the Interagency Modeling and Atmospheric Assessment Center for Improvements in Atmospheric Transport and Dispersion Modeling

This report describes the development of algorithms to derive accurate surface roughness and displacement height values from NASA satellite data for both urban and vegetation environments and to evaluate the potential benefit of improved surface data characterization on atmospheric transport and dispersion modeling. One of the key factors limiting the accuracy of near-surface wind profile modeling and dispersion simulations is the lack of location-specific and seasonally-dependent surface characteristic values. Currently, land use category look-up tables are commonly used to provide grid-cell estimates of surface characteristics values, even though surface roughness values can vary significantly within the same land-use category. This report documents: i) the derivation of surface characteristic values by Goddard Space Flight Center (GSFC) and Stennis Space Center (SSC) from NASA satellite multispectral imagery, ii) their incorporation into atmospheric meteorological and transport models, and iii) the results of a dispersion modeling study for Oklahoma City and the surrounding region to evaluate the impact of GSFC/SSC roughness on National Atmospheric Release Advisory Center (NARAC) / Interagency Modeling and Atmospheric Assessment Center (IMAAC) emergency response dispersion predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Climate-Weather Modeling Studies Using a Prototype Global Cloud-System Resolving Model: ALCF-2 Early Science Program

Clouds remain the largest source of uncertainty in our understanding of global climate change. Different aspects of the planetary cloud field can provide positive and negative feedback to the Earth’s energy balance, and clouds of course are directly implicated in changes to the planetary distribution of precipitation. A fundamental problem in our current understanding of the role of clouds in the dynamics of climate are that current resolutions do not resolve the fundamental length scales associated with clouds. We expect our understanding of the role of clouds in climate to undergo a qualitative change as the resolutions of global models begin to encompass clouds. At these resolutions (which roughly scale with the tropopause height of 10km) non-hydrostatic dynamics become significant and deep convective processes are resolved. We are poised at the threshold of being able to run global scale simulations that include direct, nonparameterized, simulations of deep convective clouds. The goal of this research is to use the Argonne Leadership Computing Facility to explore the frontier of weather prediction and climate modeling with the newly developed Geophysical Fluid Dynamics (GFDL) global cloud-resolving model. A single unified atmospheric modeling system with a cubed-sphere dynamical core and bulk cloud micro-physics running at 3.5km resolutions was run with the goal of capturing the climatology of clouds and severe storms in a warming world. The ability to reproduce historical tropical storm statistics will be used as a test of this ground-breaking model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

09 BIOMASS FUELS↗
DOE OSTI2016

Model complexity and choice of model approaches for practical simulations of CO 2 injection, migration, leakage and long-term fate

This report documents the accomplishments achieved during the project titled “Model complexity and choice of model approaches for practical simulations of CO 2 injection,migration, leakage and long-term fate” funded by the US Department of Energy, Office of Fossil Energy. The objective of the project was to investigate modeling approaches of various levels of complexity relevant to geologic carbon storage (GCS) modeling with the goal to establish guidelines on choice of modeling approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Coordinate Multiscale U 3 Si 2 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 accident tolerance when compared to traditional \uo~fuel zircaloy clad fuel rods. One of the potential replacement fuels is uranium silicide (\usi) for its higher thermal conductivity and uranium density. The lower melting temperature is of potential concern during postulated accident conditions. Another disadvantage for \usi~ is the lack of experimental data under power reactor conditions. Due to the aggressive development schedule for inserting some of the potential materials into lead test assemblies or rods by 2022~\cite{bragg-sitton_2014} multiscale multiphysics modeling approaches have been used to provide insight into these materials. \\ \noindent The purpose of this letter report is to highlight the multiscale modeling effort for \usi~fuel as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuel (ATF) High Impact Problem (HIP). This fiscal year two new models for \usi~fuel have been incorporated into the BISON fuel performance code~\cite{Williamson2012} based upon lower length scale simulations using the GRASS-SST rate theory code. The models are briefly described in the following sections.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Model comparisons of the reactive burn model SURF in three ASC codes

A study of the SURF reactive burn model was performed in FLAG, PAGOSA and XRAGE. In this study, three different shock-to-detonation transition experiments were modeled in each code. All three codes produced similar model results for all the experiments modeled and at all resolutions. Buildup-to-detonation time, particle velocities and resolution dependence of the models was notably similar between the codes. Given the current PBX 9502 equations of state and SURF calibrations, each code is equally capable of predicting the correct detonation time and distance when impacted by a 1D impactor at pressures ranging from 10-16 GPa, as long as the resolution of the mesh is not too coarse.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota

This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A modular biogeochemical modeling suite for next-generation ocean models (Final Report)

The Marine Biogeochemistry Library (MARBL) is a self-contained implementation of ocean biogeochemistry suitable for incorporation in Earth system models. The default configuration of MARBL represents multiple nutrient co-limitation (N, P, Si, and Fe), includes three explicit phytoplankton functional groups (diatoms, diazotrophs, and pico/nano phytoplankton), and one implicit group (calcifiers); there is one zooplankton group. MARBL includes fully prognostic carbonate chemistry and simulates sinking particulate organic matter implicitly, subject to ballasting by mineral dust, biogenic mineral carbonate and opal. MARBL represents subgrid-scale variations in light, variable C:P stoichiometry, semi-labile and refractory dissolved organic material pools, prognostic oceanic emission of ammonia, and an explicit ligand tracer that complexes iron. MARBL is fully runtime-configurable, and is flexible enough to accommodate a variable number of plankton functional types and ecosystem configurations. Critically, MARBL is implemented to be independent of any particular ocean general circulation model (OGCM); it is a standalone library that interfaces with an OGCM's via an explicit "driver" layer. MARBL can thus be coupled to multiple OGCM's, enabling efficient maintenance, development, and cross-model inter-comparison. MARBL is the ocean biogeochemistry component for the Community Earth System Model and the DOE’s Energy Exascale Earth System Model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

BISON BWR Fuel Modeling Capability: Material Models (FY2020)

Until this year the BISON fuel performance code has been developed primarily for pressurized water reactor (PWR), accident tolerant fuel (ATF), and advanced reactor (e.g., tri-structural isotropic (TRISO), metallic) analyses. The main focus of this work is to develop and document required material models that would aid predicting cladding failure with a specific hydride distribution to be investigated for boiling water reactor (BWR) applications in the next fiscal year. In terms of materials, the primary differences between a BWR and PWR is the use of gadolinia doping of the UO 2 fuel, the use of Zircaloy-2 for the cladding, and the addition of a liner on the inner surface of the cladding for improved pellet-clad mechanical interaction (PCMI)performance. The liner is typically made of pure zirconium or a lower tin content zirconium alloy (e.g. Zr-0.3%Sn). This work details the development and documentation of material and behavioral models for BWR analysis such as the addition of material and behavior models for gadolinia doped UO 2 , pure zirconium, Zr-0.3%Sn, and Zircaloy-2 as well as the ease-of-use additions to allow internal meshing capabilities to include liners. Another important aspect affecting cladding performance is hydrogen diffusion and hydride precipitation in the cladding. A model was added previously for non-lined, homogeneous claddings. In this work, instructions are provided on how to apply the model to BWR liner cladding. Representative experimental values are provided for the hydrogen diffusion parameters and precipitation-dissolution kinetics for typical liner materials of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

FECM/NETL CO 2 Transport Cost Model (2022): Model Overview [Slides]

The FECM/NETL CO 2 Transport Cost Model (CO 2 _T_COM) is an Excel spreadsheet model that calculates the cost of transporting CO 2 from the beginning to the end of a pipeline. This document provides an overview of the model. This document is intended to provide a user with a briefer description of the model and how to use the model than the user’s manual.

42 ENGINEERING↗
DOE OSTI2022

The Schwarz Alternating Method for the Seamless Coupling of Nonlinear Reduced Order Models and Full Order Models

Projection-based model order reduction allows for the parsimonious representation of full order models (FOMs), typically obtained through the discretization of a set of partial differential equations (PDEs) using conventional techniques (e.g., finite element, finite volume, finite difference methods) where the discretization may contain a very large number of degrees of freedom. As a result of this more compact representation, the resulting projection-based reduced order models (ROMs) can achieve considerable computational speedups, which are especially useful in real-time or multi-query analyses. One known deficiency of projection-based ROMs is that they can suffer from a lack of robustness, stability and accuracy, especially in the predictive regime, which ultimately limits their useful application. Another research gap that has prevented the widespread adoption of ROMs within the modeling and simulation community is the lack of theoretical and algorithmic foundations necessary for the “plug-and-play” integration of these models into existing multi-scale and multi-physics frameworks. This paper describes a new methodology that has the potential to address both of the aforementioned deficiencies by coupling projection-based ROMs with each other as well as with conventional FOMs by means of the Schwarz alternating method [41]. Leveraging recent work that adapted the Schwarz alternating method to enable consistent and concurrent multiscale coupling of finite element FOMs in solid mechanics [35, 36], we present a new extension of the Schwarz framework that enables FOM-ROM and ROM-ROM coupling, following a domain decomposition of the physical geometry on which a PDE is posed. In order to maintain efficiency and achieve computation speed-ups, we employ hyper-reduction via the Energy-Conserving Sampling and Weighting (ECSW) approach [13]. We evaluate the proposed coupling approach in the reproductive as well as in the predictive regime on a canonical test case that involves the dynamic propagation of a traveling wave in a nonlinear hyper-elastic material.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures, specifically, by providing situational awareness in near real-time about flood impacts to enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions to forecast flood events at regional to global scale. Given the global coverage of two operational flood models – GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the purpose of this project is to implement a Model of Models (MoM) approach to integrate the outputs from these two models to classify flood severity at watershed level worldwide, and send alerts based on severity similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes) to flood impacted communities. The alerts containing flood impacts and severity information will be disseminated through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. The current version of the MoM approach was implemented for a case study flood event that occurred during January and February of 2020 in South and Central Africa. The findings of the case study event reveal that the approach is effective in identifying potential flood impact areas and the spatio-temporal variation of flood severity, flood depth and extent at watershed level, which will be used to assess infrastructure and societal impacts using earth-observation data and for alerting.

Kar, Bandana↗
DOE OSTI2013

GPU-accelerated Software Library for Unsteady Flamelet Modeling of Turbulent Combustion with Complex Chemical Kinetics

Modeling and simulation of turbulent combustion are computationally demanding and challenging problems due to the complexity of turbulent flows and the complex chemical reaction kinetics. Recent advances in high performance computing (HPC) has allowed simulations to utilize increasing computer power to obtain newer insights that were not feasible before. The arrival of GPUs and many-core processors is set to revolutionize the HPC landscape. This paper presents an unsteady flamelet software library developed for utilizing GPUs as an onboard accelerator while the flow solver continues to run on conventional host processors using legacy software. The software was architected to expose multiple levels of parallelism and concurrency available in the unsteady flamelet model which is also necessary to realize the full potential of these accelerators. While the model and its coupling with the flow solver have been known for some time, the potential to target these models and libraries for newer HPC architectures provides a greater incentive for pursuing combustion model development.

Sankaran, Ramanan↗
DOE OSTI2015

Phase 1 Free Air CO2 Enrichment Model-Data Synthesis (FACE-MDS): Model Output Data (2015)

These datasets comprise the model output from phase 1 of the FACE-MDS. These include simulations of the Duke and Oak Ridge experiments and also idealised long-term (300 year) simulations at both sites (please see the modelling protocol for details). Included as part of this dataset are modelling and output protocols. The model datasets are formatted according to the output protocols. Phase 1 datasets are reproduced here for posterity and reproducibility although the model output for the experimental period have been somewhat superseded by the Phase 2 datasets.

54 ENVIRONMENTAL SCIENCES↗