Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “thermodynamics of computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Multi-d CFD Modeling of a Free-piston Stirling Convertor at NASA Glenn

A high efficiency Stirling Radioisotope Generator (SRG) is being developed for possible use in long duration space science missions. NASA s advanced technology goals for next generation Stirling convertors include increasing the Carnot efficiency and percent of Carnot efficiency. To help achieve these goals, a multidimensional Computational Fluid Dynamics (CFD) code is being developed to numerically model unsteady fluid flow and heat transfer phenomena of the oscillating working gas inside Stirling convertors. Simulations of the Stirling convertors for the SRG will help characterize the thermodynamic losses resulting from fluid flow and heat transfer between the working gas and solid walls. The current CFD simulation represents approximated 2-dimensional convertor geometry. The simulation solves the Navier Stokes equations for an ideal helium gas oscillating at low speeds. The current simulation results are discussed.

Wilson, Scott D.↗
NASA NTRSDate not supplied

Molten Salt Electrolytes: Computational Analysis of Transport, Electrochemical Properties and Designing New Mixtures

Electric aircraft propulsion has gained a traction over the last decade due to possible high-energy density electrochemistries with reasonable cycle life and identification of non-flammable chemistries that can guarantee much better safety. Commercial Li-ion batteries cannot reach such high capacities because of weight limitations that arise from the widely used intercalation electrodes. Also, use of organic electrolytes make them highly susceptible to fire on exposure to air and humidity. Currently, use of Lithium metal anode along with conversion electrochemistries such as Li-O2 and Li-S are being pursued to achieve such high energy densities. Safer inorganic solid-state electrolytes, recently discovered Water-in-Salt electrolytes, molten salt electrolytes are some of the alternatives being pursued for a safer/non-flammable battery. Of these safer alternatives, molten-salt electrolytes offer some attractive properties: liquid at operating temperatures resulting in better electrode-wetting, stable interface with Li-metal anodes and good ionic conductivity; their only drawback being high operating temperatures. In this talk, we will discuss some of the computational studies, driven via atomistic simulations, of the properties of molten-salt electrolytes including transport mechanism and interface stability. We will also discuss predicting electrochemical properties of these high-temperature electrolytes. Further, we will discuss a thermodynamic approach to predicting new molten-salt eutectics with lower melting points.

Molten Salt Electrolytes↗
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 OSTI2024

Spectral gaps of two- and three-dimensional many-body quantum systems in the thermodynamic limit

We present an expression for the spectral gap, opening up new possibilities for performing and accelerating spectral calculations of quantum many-body systems. We develop and demonstrate one such possibility in the context of tensor network simulations. Our approach requires only minor modifications of the widely used simple update method and is computationally lightweight relative to other approaches. We validate it by computing spectral gaps of the 2D and 3D transverse-field Ising models and find strong agreement with previously reported perturbation theory results. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Computational Study of Mixing Solid Materials for CO2 Capture Technology

CO2 is one of the major combustion products that, once released into the air, can contribute to global climate change. Solid sorbents have been reported as promising candidates for CO2 sorbent applications due to their high CO2 absorption capacities at moderate working temperatures. By combining thermodynamic database mining with first-principles density functional theory and phonon lattice dynamics calculations, the National Energy Technology Laboratory has proposed and validated a theoretical screening methodology to identify the most promising CO2 sorbent candidates from a vast array of possible solid materials. The advantage of this method is that it identifies the thermodynamic properties of the CO2 capture reaction as a function of temperature and gas pressure without any experimental input beyond crystallographic structural information of the solid phases involved. The calculated thermodynamic properties of solid materials versus temperature and pressure changes were further used to evaluate the equilibrium properties for the CO2 adsorption/desorption cycles. The selected CO2 sorbent candidates were further considered for experimental validations. In this presentation, the results of M2O/Al2O3 (M=Li, Na, K) mixtures (MAlO2 and M5AlO4) capturing CO2 will be demonstrated in detail.

Duan, Yuhua↗
DOE OSTI2023

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Thermodynamic stability assessment of nanocrystal systems requires precise free energy calculations. This study highlights the importance of meticulous control over various factors, including the thermostat, time step, potential cutoff, initial configuration, sampling method, and overall simulation duration. Free energy computations in dry (solvent-free) systems are on the order of several hundred $k_BT$ but can be obtained with consistent accuracy. However, calculation of internal energies becomes challenging, as they are typically much larger in magnitude than free energies and exhibit significant noise and reduced reliability. To address this limitation, we propose a new internal energy estimate that drastically reduces the noise. Here, we also present formulas that enable the optimization of the parameters of the harmonic bias potential for optimal convergence. Finally, we discuss the implications of these findings for the computation of free energies in nanocrystal clusters and superlattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

A phoenics model for the triaxial loading of an initially cylindrical mass of rate-type material with provisions for bulging and yield

This work traces the response of a granular material via the Ten Coefficient Truesdell rate-type constituitive model into the simplest meaningful loading: the triaxial test configuration. A functional relation has been posed for computing the rather peculiar relation between average applied stress and average porosity. Using that relation an attack has been mounted on the dilemma that exists between dynamic and constitutive use of the pressure variable; that is relating dynamic pressure, thermodynamic pressure, stress deviator and higher stress invariants. The resolution was as a linear superposition with a one-way feedback, in that while the dynamic component could not effect the constituitive component, the converse was not true since density appears in the momentum transport relation.

French, K. W., Jr.↗
NASA NTRS1999

Numerical Prediction of Transient Axial Thrust and Internal Flows in a Rocket Engine Turbopump

This paper presents the application of the Generalized Fluid System Simulation Program (GFSSP) to model the time-dependent flow in a complex secondary flow circuit of the turbopump of the Fastrac engine currently under development at Marshall Space Flight Center. GFSSP is a general purpose computer program for analyzing steady-state and time-dependant flowrates, pressures, temperatures, and concentrations in a complex flow network. The program employs a finite volume formulation of mass, momentum and energy conservation equations in conjunction with the thermodynamic equation of state of real fluids. GFSSP was used to calculate the axial thrust and internal flow distribution of the Fastrac engine turbopump during the start and shut down transients. The models discussed in this paper use boundary conditions that were extracted from turbopump test data. The GFSSP predicted turbopump secondary flow passage pressures and temperatures were compared with actual measured values.

VanHooser, Katherine↗
NASA NTRS1998

E-1 Dynamic Fluid-Flow Model Update: EASY/ROCETS Enhancement and Model Development Support

This report documents the research conducted to update computer models for dynamic fluid flow simulation of the E-1 test stand subsystems at te NASA John C. Stennis Space Center.Work also involved significant upgrades to the capabilities of EASY/ROCKETS library through the inclusion of the NIST-12 thermodynamic property database and development of new control system modules.

Follett, Randolph F.↗
NASA NTRS1985

Sensitivity of a thermodynamic sea ice model with leads to time step size

The characteristics of sea ice models, developed to study the physics of the growth and melt of ice at the ocean surface and the variations in ice extent, depend on the size of the time step. Thus, to study longer-term variations within a reasonable computer budget, a model with a scheme allowing longer time steps has been constructed. However, the results produced by the model can definitely depend on the length of the time step. The sensitivity of a model to time-step size can be reduced by appropriate approaches. The present investigation is concerned with experiments which use a formulation of a lead parameterization that can be considered as a first step toward the development of a lead parameterization suitable for a use in long-term climate studies.

Ledley, T. S.↗
NASA NTRS1998

Computational Analysis of Shock Layer Emission Measurements in an Arc-Jet Facility

This paper reports computational analysis of radiation emission experiments in a high enthalpy arc-jet wind tunnel at NASA Ames Research Center. Recently, as part of ongoing arc-jet characterization work, spectroscopic radiation emission experiments have been conducted at the 20 MW NASA Ames arc-jet facility. The emission measurements were obtained from the arc-jet freestream and from a shock layer formed in front of flatfaced models. Analysis of these data is expected to provide valuable information about the thermodynamic state of the gas in the arc-jet freestream and in the shock layer as well as thermochemical equilibration processes behind the shock in arc-jet flows. Knowledge of the thermodynamic state of the gas in arc-jet test flows and especially within the shock layer is essential to interpret the heat transfer measurements such as in surface catalysis experiments. The present work is a continuation of previous work and focuses on analysis of the emission data obtained at relatively low-pressure conditions for which the arc-jet shock layer is expected to be in thermal and chemical nonequilibrium. Building blocks of the present computational analysis are: (1) simulation of nonequilibrium expanding flow in the converging-diverging conical nozzle and supersonic jet; (2) simulation of nonequilibrium shock layer formed in front of the flat-faced cylinder model; and (3) prediction of line-of-sight radiation from the computed flowfield. For computations of the nonequilibrium flow in the conical nozzle and shock layer, multi-temperature nonequilibrium codes with the axisymmetric formulation are used. For computations of line-of-sight radiation. a nonequilibrium radiation code (NEQAIR) is used to predict emission spectra from the computed flowfield. Computed line-of-sight averaged flow properties such as vibrational and rotational temperatures, species number densities within the shock layer will be compared with those deduced from the experimental spectra. Detailed comparisons of computational and experimental spectra will also be presented.

Gokcen, Tahir↗
NASA NTRS2007

Criterion for Identifying Vortices in High-Pressure Flows

A study of four previously published computational criteria for identifying vortices in high-pressure flows has led to the selection of one of them as the best. This development can be expected to contribute to understanding of high-pressure flows, which occur in diverse settings, including diesel, gas turbine, and rocket engines and the atmospheres of Jupiter and other large gaseous planets. Information on the atmospheres of gaseous planets consists mainly of visual and thermal images of the flows over the planets. Also, validation of recently proposed computational models of high-pressure flows entails comparison with measurements, which are mainly of visual nature. Heretofore, the interpretation of images of high-pressure flows to identify vortices has been based on experience with low-pressure flows. However, high-pressure flows have features distinct from those of low-pressure flows, particularly in regions of high pressure gradient magnitude caused by dynamic turbulent effects and by thermodynamic mixing of chemical species. Therefore, interpretations based on low-pressure behavior may lead to misidentification of vortices and other flow structures in high-pressure flows. The study reported here was performed in recognition of the need for one or more quantitative criteria for identifying coherent flow structures - especially vortices - from previously generated flow-field data, to complement or supersede the determination of flow structures by visual inspection of instantaneous fields or flow animations. The focus in the study was on correlating visible images of flow features with various quantities computed from flow-field data.

Bellan, Josette↗
DOE OSTI2026

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗
DOE OSTI2020

Accelerating Ab Initio Simulation via Nested Monte Carlo and Machine Learned Reference Potentials

As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Inorganic Halide Double Perovskites with Optoelectronic Properties Modulated by Sublattice Mixing

All-inorganic halide double perovskites have emerged as a promising class of materials that are potentially more stable and less toxic than lead-containing hybrid organic-inorganic perovskite optoelectronic materials. In this work, 311 cesium chloride double perovskites (Cs 2 BB'Cl 6 ) were selected from a set of 903 compounds as likely being stable on the basis of a statistically learned tolerance factor (t) for perovskite stability. First-principles calculations on these 311 double perovskites were then performed to assess their stability and identify candidates with band gaps appropriate for optoelectronic applications. We predict that 261 of the 311 Cs 2 BB'Cl 6 compounds are likely synthesizable on the basis of a thermodynamic analysis of their decomposition to competing compounds (decomposition enthalpy <0.05 eV/atom). Of these 261 likely synthesizable compounds, 47 contain no toxic elements and have direct or nearly direct (within 100 meV) band gaps between 1 and 3 eV, as computed with hybrid density functional theory (HSE06). Within this set, we identify the triple-alkali perovskites Cs 2 [Alk] + [TM] 3+ Cl 6 , where Alk is a group 1 alkali cation and TM is a transition-metal cation, as a class of Cs 2 BB'Cl 6 double perovskites with remarkable optical properties, including large and tunable exciton binding energies as computed by the GW-Bethe-Salpeter equation (GW-BSE) method. We attribute the unusual electronic structure of these compounds to the mixing of the Alk-Cl and TM-Cl sublattices, leading to materials with small band gaps, large exciton binding energies, and absorption spectra that are strongly influenced by the identity of the transition metal. The role of the double-perovskite structure in enabling these unique properties is probed through an analysis of the electronic structures and chemical bonding of these compounds in comparison with other transition-metal and alkali transition-metal halides.

14 SOLAR ENERGY↗
DOE OSTI2021

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Topological field theory with Haagerup symmetry

Here, we construct a (1 + 1)d topological field theory (TFT) whose topological defect lines (TDLs) realize the transparent Haagerup $\mathscr{H}$ 3 fusion category. This TFT has six vacua, and each of the three non-invertible simple TDLs hosts three defect operators, giving rise to a total of 15 point-like operators. The TFT data, including the three-point coefficients and lasso diagrams, are determined by solving all the sphere four-point crossing equations and torus one-point modular invariance equations. We further verify that the Cardy states furnish a non-negative integer matrix representation under TDL fusion. While many of the constraints we derive are not limited to this particular TFT with six vacua, we leave open the construction of TFTs with two or four vacua. Finally, TFTs realizing the Haagerup $\mathscr{H}$ 1 and $\mathscr{H}$ 2 fusion categories can be obtained by gauging algebra objects. This article makes a modest offering in our pursuit of exotica and the quest for their eventual conformity.

97 MATHEMATICS AND COMPUTING↗