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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Multi-Physics Simulation of TREAT Kinetics using MAMMOTH

With the advent of next generation reactor systems and new fuel designs, the U.S. Department of Energy (DOE) has identified the need for the resumption of transient testing of nuclear fuels. DOE has decided that the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is best suited for future testing. TREAT is a thermal neutron spectrum nuclear test facility that is designed to test nuclear fuels in transient scenarios. These specific fuels transient tests range from simple temperature transients to full fuel melt accidents. The current TREAT core is driven by highly enriched uranium (HEU) dispersed in a graphite matrix (1:10000 U-235/C atom ratio). At the center of the core, fuel is removed allowing for the insertion of an experimental test vehicle. TREAT’s design provides experimental flexibility and inherent safety during neutron pulsing. This safety stems from the graphite in the driver fuel having a strong negative temperature coefficient of reactivity resulting from a thermal Maxwellian shift with increased leakage, as well as graphite acting as a temperature sink. Air cooling is available, but is generally used post-transient for heat removal. DOE and INL have expressed a desire to develop a simulation capability that will accurately model the experiments before they are irradiated at the facility, with an emphasis on effective and safe operation while minimizing experimental time and cost. At INL, the Multi-physics Object Oriented Simulation Environment (MOOSE) has been selected as the model development framework for this work. This paper describes the results of preliminary simulations of a TREAT fuel element under transient conditions using the MOOSE-based MAMMOTH reactor physics tool.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Simulation of plasma transport in MPS-LD linear plasma device by using BOUT++

Here a linear plasma device (LPD) module based on the 2D transport module under the BOUT++ framework is developed in this paper to simulate plasma transport in the LPD. The LPD module includes three parts, i.e. magnetic field calculation, simulation mesh generation and plasma transport setup. The magnetic field is calculated with the circular current loop using the location and current information of each coil. The mesh generation code can produce a simulation mesh for LPD by employing the magnetic field. The plasma transport model is based on the reduced Braginskii equations, which consist of the continuity equation, momentum equation, and energy equation. The fluid neutral model is applied for neutral particle simulation. Deuterium (D) and helium (He) ions and atoms can be simulated by the model. The first attempt to simulate plasma transport in the new LPD, called multiple plasma simulation linear plasma device (MPS-LD), is presented using the developed model. The D plasma transport in the MPS-LD is simulated and benchmarked against the two-point model, showing the validation of the BOUT++ simulation. The effects of radial transport on the heat load to the target are studied, which illustrates the significant impact of the radial diffusivities $D_⟂$ and $\mathcal{X}_{⟂i,e}$ on the plasma. Moreover, the He impurity injection process during the discharge is studied with emphasis on plasma–impurity interactions. The simulation results show that He injection can reduce the plasma energy load to the target significantly, and the efficiency depends on the He source density and injection velocity. The present work provides an alternative and flexible simulation tool for plasma transport in LPDs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

AbacusHOD : a highly efficient extended multitracer HOD framework and its application to BOSS and eBOSS data

ABSTRACT We introduce the AbacusHOD model and present two applications of AbacusHOD and the AbacusSummit simulations to observations. AbacusHOD is a Halo Occupation Distribution (HOD) framework written in Python that is particle-based, multitracer, highly generalized, and highly efficient. It is designed specifically with multitracer/cosmology analyses for next-generation large-scale structure surveys in mind, and takes advantage of the volume and precision offered by the new state-of-the-art AbacusSummit cosmological simulations. The model is also highly customizable and should be broadly applicable to any upcoming surveys and a diverse range of cosmological analyses. In this paper, we demonstrate the capabilities of the AbacusHOD framework through two example applications. The first example demonstrates the high efficiency and the large HOD extension feature set through an analysis of full-shape redshift-space clustering of BOSS galaxies at intermediate to small scales ($\lt 30\, h^{-1}$ Mpc), assessing the necessity of introducing secondary galaxy biases (assembly bias). We find strong evidence for using halo environment instead of concentration to trace secondary galaxy bias, a result which also leads to a moderate reduction in the ‘lensing is low’ tension. The second example demonstrates the multitracer capabilities of the AbacusHOD package through an analysis of the extended Baryon Oscillation Spectroscopic Survey cross-correlation measurements between three different galaxy tracers: luminous red galaxies, emission-line galaxies, and quasi-stellar objects. We expect the AbacusHOD framework, in combination with the AbacusSummit simulation suite, to play an important role in a simulation-based analysis of the upcoming Dark Energy Spectroscopic Instrument data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Global energetics and local physics as drivers of past, present and future monsoons

Global constraints on momentum and energy govern the variability of the rainfall belt in the intertropical convergence zone and the structure of the zonal mean tropical circulation. The continental-scale monsoon systems are also facets of a momentum- and energy-constrained global circulation, but their modern and palaeo variability deviates substantially from that of the intertropical convergence zone. The mechanisms underlying deviations from expectations based on the longitudinal mean budgets are neither fully understood nor simulated accurately. We argue that a framework grounded in global constraints on energy and momentum yet encompassing the complexities of monsoon dynamics is needed to identify the causes of the mismatch between theory, models and observations, and ultimately to improve regional climate projections. In a first step towards this goal, disparate regional processes must be distilled into gross measures of energy flow in and out of continents and between the surface and the tropopause, so that monsoon dynamics may be coherently diagnosed across modern and palaeo observations and across idealized and comprehensive simulations. Accounting for zonal asymmetries in the circulation, land/ocean differences in surface fluxes, and the character of convective systems, such a monsoon framework would integrate our understanding at all relevant scales: from the fine details of how moisture and energy are lifted in the updrafts of thunderclouds, up to the global circulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Transition State Theory Methods To Measure Diffusion in Flexible Nanoporous Materials: Application to a Porous Organic Cage Crystal

Transition state theory (TST) methods are useful for predicting adsorbate diffusivities in nanoporous materials at timescales inaccessible to molecular dynamics (MD). Most TST applications treat the nanoporous framework as rigid, which is inaccurate in highly flexible materials or where adsorbate dimensions are comparable to the size of pore aperatures. In this study, we demonstrate two computationally efficient TST methods for simulating adsorbate diffusion in nanoporous materials where framework flexibility has a significant influence on diffusion. These methods are applied to light gas diffusion in porous organic cage crystal 3 (CC3), a highly flexible molecular crystal that has shown promise in gas separation applications. Diffusion in CC3 is modeled as a series of uncorrelated adsorbate hops between cage molecules and the voids between adjacent cages. The first method we applied to compute adsorbate hopping rates in CC3 is implicit ligand sampling (ILS). In ILS TST, hopping rates are calculated in an ensemble of rigid framework snapshots captured from a fully flexible MD trajectory of the empty CC3 structure. The second TST method we applied is umbrella sampling (US), where hopping rates are computed from a series of biased MD simulations. Our ILS and US TST calculations are shown to agree well with direct MD simulation of adsorbate diffusion in CC3. We anticipate that the efficient TST methods detailed here will be broadly applicable other classes of flexible nanoporous materials such as metal–organic frameworks.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A High Performance Computational Framework for Dynamic Security Assessment under Uncertainty

Dynamic security assessment (DSA) is a critical function to evaluate power grids’ capability to survive the transition caused by a set of disturbances to an acceptable steady-state condition. Its computational burden is heavy. With the challenges brought by renewable energy and new smart grid technologies, DSA under uncertainty has to be considered to study the impact of forecast errors on DSA simulation, which further increases the computational burden. To address this challenge, this paper presents a high performance computational framework to support DSA simulation user uncertainty. The computational framework aims to provide a seamless workflow that links data from high performance computing, statistical analysis, to visualization so that a problem can be easily expressed in a way compatible with different functions. It also enables software compatibility such that application development can be more efficient. Case study results of the ESCA60 system and a western U.S. size system show the advantages and efficiency of the computational framework.

dynamic security assessment, high performance comp↗
DOE OSTI2019

A Framework to Delineate Precipitation-Runoff Regimes: Precipitation vs. Snowpack in the Western U.S.

We propose a framework to classify precipitation events accompanied by snow process (precipitation-and-snow, or PAS events) into five regimes, based on the relative contributions of snowpack change and precipitation amount to the runoff response. This framework is applied to a regional climate simulation over the western U.S. to reveal the regions where snow process plays important roles. Over the western U.S., PAS events account for 50-90% of all the precipitation events. About 60-80% of PAS events feature snow accumulation, but snow melting frequently happens in high-elevation areas. Compared with snow accumulation events, snow melting events have a more limited spatial distribution. Different regimes peak in different months between early winter and late spring. Lastly, the impact of atmospheric rivers is investigated. Although accounting for only 2% of the grid-scale precipitation events, atmospheric rivers trigger significant snowmelt and contribute to 20% and 11% of light and heavy snow melting events, respectively.

Chen, Xiaodong↗
DOE OSTI2020

Deep Reinforcement Learning-Based Edge Caching in Wireless Networks

With the purpose to offload data traffic in wireless networks, content caching techniques have recently been studied intensively. Using these techniques and caching a portion of the popular files at the local content servers, the users can be served with less delay. Most of the content replacement policies are based on the content popularity, that depends on the users' preferences. In practice, such information varies over time. Therefore, an approach to determine the file popularity patterns must be incorporated into caching policies. In this context, we study content caching at the wireless network edge using a deep reinforcement learning framework with Wolpertinger architecture. In particular, we propose deep actor-critic reinforcement learning based policies for both centralized and decentralized content caching. For centralized edge caching, we aim at maximizing the cache hit rate. In decentralized edge caching, we consider both the cache hit rate and transmission delay as performance metrics. These proposed frameworks are assumed to neither have any prior information on the file popularities nor know the potential variations in such information. Via simulation results, the superiority of the proposed frameworks is verified by comparing them with other policies, including least frequently used (LFU), least recently used (LRU), and first-in-first-out (FIFO) policies.

42 ENGINEERING↗
DOE OSTI2020

Xcompact3D: An open-source framework for solving turbulence problems on a Cartesian mesh

Xcompact3D is a Fortran 90–95 open-source framework designed for fast and accurate simulations of turbulent flows, targeting CPU-based supercomputers. It is an evolution of the flow solver Incompact3D which was initially designed in France in the mid-90’s for serial processors to solve the incompressible Navier–Stokes equations. Incompact3D was then ported to parallel High Performance Computing (HPC) systems in the early 2010’s. Very recently the capabilities of Incompact3D have been extended so that it can now tackle more flow regimes (from incompressible flows to compressible flows at low Mach numbers), resulting in the design of a new user-friendly framework called Xcompact3D. The present manuscript presents an overview of Xcompact3D with a particular focus on its functionalities, its ready-to-run simulations and a few case studies to demonstrate its impact.

17 WIND ENERGY↗
DOE OSTI2013

On estimating cosmology-dependent covariance matrices

We describe a statistical model to estimate the covariance matrix of matter tracer two-point correlation functions with cosmological simulations. Assuming a fixed number of cosmological simulation runs, we describe how to build a 'statistical emulator' of the two-point function covariance over a specified range of input cosmological parameters. Because the simulation runs with different cosmological models help to constrain the form of the covariance, we predict that the cosmology-dependent covariance may be estimated with a comparable number of simulations as would be needed to estimate the covariance for fixed cosmology. Our framework is a necessary first step in planning a simulations campaign for analyzing the next generation of cosmological surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Techno-Economic Analysis of Data-Driven and Transactive Approaches for Resilience Enhancement

As extreme weather events lead to more frequent power outages, understanding and enhancing grid resilience is critical to mitigating economic losses and non-energy impacts from service disruptions. Here, this study introduces a novel techno-economic analysis framework for evaluating resilience enhancement mechanisms. The framework combines grid response modeling with a co-simulation approach and valuation methodology to provide a comprehensive assessment. We apply this framework to a realistic case study of the Texas grid during Winter Storm Uri in February 2021. Two advanced resilience strategies are analyzed: a data-driven rolling outage mechanism and a transactive energy (TE) based allocation scheme. The rolling outage scheme selectively serves customers based on real-time curtailment needs, while the TE scheme allows customers to trade energy allocations according to their preferences. Our findings show that both the rolling outage and TE schemes significantly outperform conventional methods (i.e. controlled outages) by reducing the amount of energy not supplied to customers by 41% and 64%, respectively. These approaches also enhance flexibility and customer satisfaction, while improving energy utilization for greater resilience. Additionally, they maintain thermal comfort about 3.5 times better and substantially lower customer risk exposure. A key contribution of this study is addressing both utility and customer perspectives while considering both energy and non-energy impacts. The techno-economic analysis indicates that implementing these resilience enhancement strategies would incur an additional 1.1Bto1.6B in utility costs but has the potential to avoid 17.3Bto18B of customer losses as compared to existing solutions, thereby underscoring the value of investing in advanced resilience, as it provides significant societal benefits to customers.

42 ENGINEERING↗
DOE OSTI2019

Integration of the Nek5000 Computational Fluid Dynamics Code with the NEAMS Workbench

The mission of the US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems using computing architectures ranging from laptops to leadership-class facilities. NEAMS is organized into three product lines: the Fuels Product Line (FPL),the Reactors Product Line (RPL), and the Integration Product Line (IPL). The FPL and RPL focus on the development of high-fidelity tools such as the MOOSE-based applications BISON and MARMOT [3, 9] at Idaho National Laboratory, and the PROTEUS neutronics code and the NEK5000 computational fluid dynamics code from the Simulation-based High-efficiency Advanced Reactor Prototyping (SHARP) framework [10]. The NEAMS IPL will enable users to apply high-fidelity simulations to inform lower order models for the design, analysis, and licensing of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

On the soft limit of the large scale structure power spectrum: UV dependence

We derive a non-perturbative equation for the large scale structure power spectrum of long-wavelength modes. Thereby, we use an operator product expansion together with relations between the three-point function and power spectrum in the soft limit. The resulting equation encodes the coupling to ultraviolet (UV) modes in two time-dependent coefficients, which may be obtained from response functions to (anisotropic) parameters, such as spatial curvature, in a modified cosmology. We argue that both depend weakly on fluctuations deep in the UV. As a byproduct, this implies that the renormalized leading order coefficient(s) in the effective field theory (EFT) of large scale structures receive most of their contribution from modes close to the non-linear scale. Consequently, the UV dependence found in explicit computations within standard perturbation theory stems mostly from counter-term(s). We confront a simplified version of our non-perturbative equation against existent numerical simulations, and find good agreement within the expected uncertainties. Our approach can in principle be used to precisely infer the relevance of the leading order EFT coefficient(s) using small volume simulations in an 'anisotropic separate universe' framework. Our results suggest that the importance of these coefficient(s) is a ∼ 10% effect, and plausibly smaller.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

TRANSP-based closed-loop simulations of current profile optimal regulation in NSTX-Upgrade

Active control of the toroidal current density profile is critical for the upgraded National Spherical Torus eXperiment device (NSTX-U) to maintain operation at the desired high-performance, MHD-stable, plasma regime. Initial efforts towards current density profile control have led to the development of a control-oriented, physics-based, plasma-response model, which combines the magnetic diffusion equation with empirical correlations for the kinetic profiles and the non-inductive current sources. The developed control-oriented model has been successfully tailored to the NSTX-U geometry and actuators. Moreover, a series of efforts have been made towards the design of model-based controllers, including a linear-quadratic-integral optimal control strategy that can regulate the current density profile around a prescribed target profile while rejecting disturbances. In this work, the tracking performance of the proposed current-profile optimal controller is tested in numerical simulations based on the physics-oriented code TRANSP. These high-fidelity closed-loop simulations, which are a critical step before experimental implementation and testing, are enabled by a flexible framework recentlydeveloped to perform feedback control design and simulation in TRANSP.

current profile control↗
DOE OSTI2022

GDSA Framework Development and Process Model Integration FY2022

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is disposal system modeling (Sassani et al. 2021). The SFWST Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2022 advances of the Geologic Disposal Safety Assessment (GDSA) performance assessment (PA) development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to assess probabilistically the performance of generic disposal options and generic sites. The modeling capability under development is called GDSA Framework (pa.sandia.gov). GDSA Framework is a coordinated set of codes and databases designed for probabilistically simulating the release and transport of disposed radionuclides from a repository to the biosphere for post-closure performance assessment. Primary components of GDSA Framework include PFLOTRAN to simulate the major features, events, and processes (FEPs) over time, Dakota to propagate uncertainty and analyze sensitivities, meshing codes to define the domain, and various other software for rendering properties, processing data, and visualizing results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Computational studies of adsorption in metal organic frameworks and interaction of nanoparticles in condensed phases

In this review, we describe recent efforts to systematically study nano-structured metal organic frameworks (MOFs), also known as metal organic heat carriers, with particular emphasis on their application in heating and cooling processes. We used both molecular dynamics and grand canonical Monte Carlo simulation techniques to gain a molecular-level understanding of the adsorption mechanism of gases in these porous materials. We investigated the uptake of various gases such as refrigerants R12 and R143a. We also evaluated the effects of temperature and pressure on the uptake mechanism. Our computed results compared reasonably well with available measurements from experiments, thus validating our potential models and approaches. In addition, we investigated the structural, diffusive and adsorption properties of different hydrocarbons in Ni-2(dhtp). Finally, to elucidate the mechanism of nanoparticle dispersion in condensed phases, we studied the interactions among nanoparticles in various liquids, such as n-hexane, water and methanol.

Annapureddy, HVR↗
DOE OSTI2023

First-principles based plasma profile predictions for optimized stellarators

In the present Letter, first-of-its-kind computer simulations predicting plasma profiles for modern optimized stellarators—while self-consistently retaining neoclassical transport, turbulent transport with 3D effects, and external physical sources—are presented. These simulations exploit a newly developed coupling framework involving the global gyrokinetic turbulence code GENE-3D, the neoclassical transport code KNOSOS, and the 1D transport solver TANGO. This framework is used to analyze the recently observed degradation of energy confinement in electron-heated plasmas in the Wendelstein 7-X stellarator, where the central ion temperature was 'clamped' to $T_\textrm i \approx 1.5$ keV regardless of the external heating power. By performing first-principles based simulations, we provide key evidence to understand this effect, namely the inefficient thermal coupling between electrons and ions in a turbulence-dominated regime, which is exacerbated by the large $T_\textrm e/T_\textrm i$ ratios, and show that a more efficient ion heat source, such as direct ion heating, will increase the on-axis ion temperature. This work paves the way towards the use of high-fidelity models for the development of the next generation of stellarators, in which neoclassical and turbulent transport are optimized simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗