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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Validity of path thermodynamic description of reactive systems: Microscopic simulations

Traditional stochastic modeling of reactive systems limits the domain of applicability of the associated path thermodynamics to systems involving a single elementary reaction at the origin of each observed change in composition. An alternative stochastic modeling has recently been proposed to overcome this limitation. These two ways of modeling reactive systems are in principle incompatible. Here, the question thus arises about choosing the appropriate type of modeling to be used in practical situations. In the absence of sufficiently accurate experimental results, one way to address this issue is through the microscopic simulation of reactive fluids, usually based on hard-sphere dynamics in the Boltzmann limit. In this paper, we show that results obtained through such simulations unambiguously confirm the predictions of traditional stochastic modeling, invalidating a recently proposed alternative.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Simulation-based assessment on stochastic load scheduling for building cooling systems

Here, to fill knowledge gaps related to stochastic load scheduling, we performed a comprehensive evaluation of the stochastic load scheduling for building cooling systems. Specifically, we studied the common uncertain variables in the load scheduling process for building cooling systems and categorized those variables based on their dynamic patterns. We then developed a generic stochastic load scheduling framework and applied it to building cooling systems that served a simulated community. This community consists of 100 heterogeneous houses and serves as a virtual testbed for evaluating the performance of stochastic load scheduling. In this evaluation, we considered representatives of uncertain variables with different dynamic patterns and included 100 realizations of the considered uncertainty in the evaluation to better catch the probability distribution of the control performance. The evaluation results suggest that deterministic load scheduling can reduce the operating energy cost by 18% but its performance can be affected by uncertainty. Stochastic load scheduling can further decrease the operating energy cost under uncertainty compared to deterministic load scheduling. We also found that the effectiveness of stochastic load scheduling in handling uncertainty is not directly associated with the number of uncertainty scenarios that are considered in its formulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2015

FEAMAC-CARES Software Coupling Development Effort for CMC Stochastic-Strength-Based Damage Simulation

Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MACGMC composite material analysis code. The resulting code is called FEAMACCARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMACCARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMACCARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.

Reliability↗
NASA NTRS2016

FEAMAC/CARES Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix Composites

Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MAC/GMC (Micromechanics Analysis Code/ Generalized Method of Cells) composite material analysis code. The resulting code is called FEAMAC/CARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMAC/CARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMAC/CARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.

composite structures↗
NASA NTRS2015

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix Composite

Reported here is a coupling of two NASA developed codes: CARES (Ceramics Analysis and Reliability Evaluation of Structures) with the MAC/GMC (Micromechanics Analysis Code/ Generalized Method of Cells) composite material analysis code. The resulting code is called FEAMAC/CARES and is constructed as an Abaqus finite element analysis UMAT (user defined material). Here we describe the FEAMAC/CARES code and an example problem (taken from the open literature) of a laminated CMC in off-axis loading is shown. FEAMAC/CARES performs stochastic-strength-based damage simulation response of a CMC under multiaxial loading using elastic stiffness reduction of the failed elements.

ceramic matrix composites↗
NASA NTRS2013

Simulation of Inflated Pahoehoe Lava Flows

A new stochastic model simulates late-stage pahoehoe lobes where random processes dominate emplacement. The model prescribes probabilistic rules for determining where and when parcels of lava move within the lobe. Unlike a classical Brownian motion random walk, the model allows individual parcels to remain dormant, but fluid, for multiple time steps. The randomness of parcel volume transfers within the lobe interior as well as at the margins qualitatively reflects inflation processes observed in the field. The fraction of inflated volume to total volume increases with the total volume, with greater than 75% of the lobe volume contributed through inflation for typical lobes. The influence on planform shape and topographic cross-sectional profiles of total volume, source area and shape, topographic confinement, and sequential breakouts at the lobe margins, are all explored with the stochastic model. Each of these factors influences the overall lobe thickness and width. The model provides a means for assessing the relative importance of these processes through comparisons with field data. For the first time, Gaussian and parabolic functions are quantitatively fit to field measurements of pahoehoe lobes. Both functional forms provide adequate description of the cross-sectional flow shapes. When comparing simulated lobes to field data, sequential breakouts at the lobe margins are found to be an important process controlling the final topographic distribution of observed pahoehoe lobes.

modeling↗
DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Particle Swarm Optimisation for group structure optimization for radiotherapy shielding

Neutron transport simulations are ubiquitous in nuclear engineering because they allow one to model experimental systems and render a model platform for easy perturbation of experimental designs. In addition, simulations allow one to gain experimental insight without actually having to go through the trouble of building a physical experiment. Neutron transport simulations can be stochastic or deterministic based. Stochastic neutron transport simulations are typically simulated using the Monte Carlo method and yield very accurate solutions but are computationally expensive, while deterministic methods are typically faster but can be less accurate. Here we focus on optimizing the accuracy of deterministic neutron transport simulations for radiotherapy simulations. Deterministic neutron transport requires discretization of angle, energy, and space to appropriately analyze the system one is trying to model. Discretization of energy is challenging because of the highly variable neutron flux at certain neutron energies. Improper discretization of energy in the transport model can lead to erroneous results and therefore inaccurate interpretations of the solution. In this study, we evaluate Particle Swarm Optimization (PSO) as a mechanism for selecting optimal group structures for radiotherapy shielding. We tested the particle swarm optimization algorithm on radiotherapy shielding problems using Los Alamos National Laboratory's (LANL) main deterministic transport code PARTISN. Results show that the optimized energy group structures generated from the optimization algorithm outperformed LANL's standard energy group structures, and therefore demonstrate utility in using PSO to expedite computation times due to the increased accuracy obtained with a smaller but optimized group structure. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Versatile stochastic model for predictive KMC simulation of fcc metal nanostructure evolution with realistic kinetics

Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1994

Simulation of magnetic field line stochasticity at the magnetopause

We have conducted a three-dimensional particle simulation to study the magnetic field line stochasticity at the magnetopause current layer. Our results show that the magnetic field lines become stochastic due to the overlap of the destabilized multiple tearing mode islands, which agrees with the percolation model suggested by Galeev et al. (1986). After the field lines become stochastic, these tearing modes grow even 2-3 times faster than in the linear stage and saturate at an amplitude level 3-4 times bigger than the single tearing mode without mode-mode coupling. The field line stochasticity also causes a strong particle diffusion across the current layer. The diffusion coefficient reaches to 10(exp 9) sq m/s for typical magnetopause parameters. Associated with the particle diffusion, the current layer becomes broader in width. As a result, the magnetic energy is dissipated into particle energy by heating parallel to the local magnetic field. The particle energy increases by 60%, while the magnetic helicity, which has always been regarded as a good invariant, changes by 20%.

Wang, Zhi↗
DOE OSTI2021

NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management

Large-scale implementation of geologic carbon storage (GCS) to help reduce atmospheric greenhouse gas emissions requires stakeholder confidence that injected CO2 will remain contained and that potential subsurface environmental risks are acceptably small and manageable. The U.S. Department of Energy’s National Risk Assessment Partnership (NRAP) has developed an open-source integrated assessment model (NRAP-Open-IAM) to help address questions about a potential GCS site’s ability to effectively contain injected CO 2 and protect groundwater and other overlying environmentally sensitive receptors. NRAP-Open-IAM allows a user to: (1) incorporate relevant site geologic and injection scenario data; (2) characterize important site features and events;(3) couple fast prediction models of various system components of the engineered geologic system; and (4) execute stochastic, dynamic simulation of whole GCS system performance, leakage risk assessment, and uncertainty quantification. NRAP-Open-IAM is available on GitLab (https://gitlab.com/NRAP/OpenIAM), and is accompanied by multiple application examples and detailed user and developer guides.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Optimal generalized multistep integration formulae for real-time digital simulation

The problem of discretizing a dynamical system for real-time digital simulation is considered. Treating the system and its simulation as stochastic processes leads to a statistical characterization of simulator fidelity. A plant discretization procedure based on an efficient matrix generalization of explicit linear multistep discrete integration formulae is introduced, which minimizes a weighted sum of the mean squared steady-state and transient error between the system and simulator outputs.

Moerder, D. D.↗
NASA NTRS2018

Recent Developments in the Code RITRACKS (Relativistic Ion Tracks)

The code RITRACKS (Relativistic Ion Tracks) was developed to simulate detailed stochastic radiation track structures of ions of different types and energies. Many new capabilities were added to the code during the recent years. Several options were added to specify the times at which the tracks appear in the irradiated volume, allowing the simulation of dose-rate effects. The code has been used to simulate energy deposition in several targets: spherical, ellipsoidal and cylindrical. More recently, density changes as well as a spherical shell were implemented for spherical targets, in order to simulate energy deposition in walled tissue equivalent proportional counters. RITRACKS is used as a part of the new program BDSTracks (Biological Damage by Stochastic Tracks) to simulate several types of chromosome aberrations in various irradiation conditions. The simulation of damage to various DNA structures (linear and chromatin fiber) by direct and indirect effects has been improved and is ongoing. Many improvements were also made to the graphic user interface (GUI), including the addition of several labels allowing changes of units. A new GUI has been added to display the electron ejection vectors. The parallel calculation capabilities, notably the pre- and post-simulation processing on Windows and Linux machines have been reviewed to make them more portable between different systems. The calculation part is currently maintained in an Atlassian Stash® repository for code tracking and possibly future collaboration.

Plante, Ianik↗
NASA NTRS1983

Stochastic self-propagating star formation in three-dimensional disk galaxy simulations

The behavior of stochastic self-propagating star formation (SSPSF) in three dimensions is examined in simulation for the first time, emphasizing the effect of the added dimension on the sensitivity of spiral structure to the probability of star formation. The model produces global equilibrium spiral structure over a much more restricted range of star formation probabilities and relaxation times than in two dimensions. Spiral structure also occurs as a transient phenomenon in the runs which eventually fill or evolve to structured nonspiral states. The equilibrium spirals are not as distinctive as those produced by two-dimensional models. However, there are refinements which may modify these results, such as allowing for the depletion of gas in the interstellar medium due to conversion to long-lived low mass stars.

Statler, T.↗
DOE OSTI2025

Thermally induced mimicry of quantum cluster excitations and implications for the magnetic transition in FePSe 3

In two dimensional magnets, the interplay of thermal fluctuations and spin anisotropy control the existence of long-range magnetic order. In the van der Waals antiferromagnets FePX 3 , orbital degeneracy in the 𝑡 2⁢𝑔 levels of the Fe 2+ ions in octahedral coordination yields strong uniaxial anisotropy, which stabilizes magnetic order up to 𝑇 ≈ 100 K. Recent inelastic neutron scattering measurements around the magnetic ordering transition have shown the existence of a broad spectrum of magnetic fluctuations with nontrivial momentum dependence, which has been interpreted as evidence for localized entangled cluster excitations. In this paper, we offer an alternative interpretation using classical nonlinear spin dynamics simulations. We present stochastic Landau Lifshitz dynamics simulations that reproduce the neutron scattering measurements of Chen et al. [npj Quantum Mater. 9, 40 (2024)] on FePSe 3 . These calculations faithfully explain the dynamical structure factor's momentum and energy dependence and point to a classical origin for the excitations observed in neutron spectroscopy and that the order-disorder transition can be understood in terms of thermal fluctuations overcoming the anisotropy energy.

Landau-Lifschitz-Gilbert equation↗