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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Heats of Segregation and Segregation Profiles of BCC Metals

The composition of metal alloy surfaces is often different from that of the bulk. Some alloys exhibit surface segregation, where one or more species reside preferentially at or near the surface. A detailed understanding of this behavior is necessary to correctly model such phenomena as adhesion or catalysis. Several phenomenological approaches to the problem have been put forward, falling into two broad categories: Thermodynamic approaches, where the equilibrium distribution of chemical species is computed. Atomistic approaches, where the tendency of a species to segregate is determined by computation of the energies of single atoms of that species in bulk and surface environments.

Good, Brian S.↗
DOE OSTI2023

Solvent Phase Optimizations Improve Correlations with Experimental Stability Constants for Aqueous Lanthanide Complexes

Stability constants provide insight into ion complexation in water. While computational studies have been shown to model the energy of the complexation successfully using a thermodynamic cycle approach, it does not extend to calculating the stability constants for 1:1 lanthanide to ligand complexes in solution. Using B3LYP and 6-31+G* Pople basis with small core effective core potential (ECP) on the lanthanum ion, and a solvent model based on the full solute electron density (SMD) solvation model we computed and compared with previously published stability constants of the ligands: acetate, acetohydroximate, acetylacetonate, methanoate, tropolonate, hydroxide, catecholate, malonate, oxalate, phthalate, and sulfate. The best R 2 values for the thermodynamic cycle can only be determined by separating the mono and divalent ions to achieve an R 2 value of 0.86 and 0.74 for mono and divalent ions, respectively. We show that by optimizing the lanthanide-ligand structures in implicit solvent, we achieve an improved correlation between experimental and computed stability constants of R 2 value of 0.89 for the combined mono and divalent ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Modeling ARRM Xenon Tank Pressurization Using 1D Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Xenon storage↗
NASA NTRS2017

Modeling Xenon Tank Pressurization using One-Dimensional Thermodynamic and Heat Transfer Equations

As a first step in understanding what ground support equipment (GSE) is required to provide external cooling during the loading of 5,000 kg of xenon into 4 aluminum lined composite overwrapped pressure vessels (COPVs), a modeling analysis was performed using Microsoft Excel. The goals of the analysis were to predict xenon temperature and pressure throughout loading at the launch facility, estimate the time required to load one tank, and to get an early estimate of what provisions for cooling xenon might be needed while the tanks are being filled. The model uses the governing thermodynamic and heat transfer equations to achieve these goals. Results indicate that a single tank can be loaded in about 15 hours with reasonable external coolant requirements. The model developed in this study was successfully validated against flight and test data. The first data set is from the Dawn mission which also utilizes solar electric propulsion with xenon propellant, and the second is test data from the rapid loading of a hydrogen cylindrical COPV. The main benefit of this type of model is that the governing physical equations using bulk fluid solid temperatures can provide a quick and accurate estimate of the state of the propellant throughout loading which is much cheaper in terms of computational time and licensing costs than a Computation Fluid Dynamics (CFD) analysis while capturing the majority of the thermodynamics and heat transfer.

Thermodynamic tank modeling↗
DOE OSTI2024

Computed entropy spectra for grain boundary segregation in polycrystals

Abstract Grain boundary solute segregation influences most bulk material properties, and understanding solute thermodynamics at grain boundaries is critical for engineering them. However, the vast grain boundary space in polycrystals is challenging to evaluate due to its size, especially for the intrinsically hard-to-compute segregation excess entropy. Here data science methods are used to generate a database of site-wise grain boundary segregation entropy spectra for 155 dilute binary alloys within the harmonic approximation. The spectral framework allows scale bridging between the calculated atomistic site-wise energy-entropy spectra and macroscopic segregation entropy estimates. The results affirm that macroscopic averaging is not sufficient: a spectral treatment of grain boundary segregation is needed to accurately model bulk temperature dependence of grain boundary solute segregation. The calculated spectral entropy database and thermodynamic framework can be applied for both understanding segregation experiments and alloy design exercises, paving the way to a finite-temperature grain boundary genome.

Chemistry↗
DOE OSTI2025

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗
NASA NTRS1993

Space Life Support Engineering Program

This report covers the second year of research relating to the development of closed-loop long-term life support systems. Emphasis was directed toward concentrating on the development of dynamic simulation techniques and software and on performing a thermodynamic systems analysis in an effort to begin optimizing the system needed for water purification. Four appendices are attached. The first covers the ASPEN modeling of the closed loop Environmental Control Life Support System (ECLSS) and its thermodynamic analysis. The second is a report on the dynamic model development for water regulation in humans. The third regards the development of an interactive computer-based model for determining exercise limitations. The fourth attachment is an estimate of the second law thermodynamic efficiency of the various units comprising an ECLSS.

Seagrave, Richard C.↗
DOE OSTI2024

Quantum Thermodynamics of Nonequilibrium Processes in Lattice Gauge Theories

A key objective in nuclear and high-energy physics is to describe nonequilibrium dynamics of matter, e.g., in the early Universe and in particle colliders, starting from the standard model of particle physics. Classical computing methods, via the framework of lattice gauge theory, have experienced limited success in this mission. Quantum simulation of lattice gauge theories holds promise for overcoming computational limitations. Because of local constraints (Gauss’s laws), lattice gauge theories have an intricate Hilbert-space structure. This structure complicates the definition of thermodynamic properties of systems coupled to reservoirs during equilibrium and nonequilibrium processes. We show how to define thermodynamic quantities such as work and heat using strong-coupling thermodynamics, a framework that has recently burgeoned within the field of quantum thermodynamics. Our definitions suit instantaneous quenches, simple nonequilibrium processes undertaken in quantum simulators. To illustrate our framework, we compute the work and heat exchanged during a quench in a Z 2 lattice gauge theory coupled to matter in 1+1 dimensions. Here, the thermodynamic quantities, as functions of the quench parameter, evidence a phase transition. For general thermal states, we derive a simple relation between a quantum many-body system’s entanglement Hamiltonian, measurable with quantum-information-processing tools, and the Hamiltonian of mean force, used to define strong-coupling thermodynamic quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

Calculations and curve fits of thermodynamic and transport properties for equilibrium air to 30000 K

A self-consistent set of equilibrium air values were computed for enthalpy, total specific heat at constant pressure, compressibility factor, viscosity, total thermal conductivity, and total Prandtl number from 500 to 30,000 K over a range of 10(exp -4) atm to 10(exp 2) atm. The mixture values are calculated from the transport and thermodynamic properties of the individual species provided in a recent study by the authors. The concentrations of the individual species, required in the mixture relations, are obtained from a free energy minimization calculation procedure. Present calculations are based on an 11-species air model. For pressures less than 10(exp -2) atm and temperatures of about 15,000 K and greater, the concentrations of N(++) and O(++) become important, and consequently, they are included in the calculations determining the various properties. The computed properties are curve fitted as a function of temperature at a constant value of pressure. These curve fits reproduce the computed values within 5 percent for the entire temperature range considered here at specific pressures and provide an efficient means for computing the flowfield properties of equilibrium air, provided the elemental composition remains constant at 0.24 for oxygen and 0.76 for nitrogen by mass.

Gupta, Roop N.↗
DOE OSTI2020

Rechargeable Alkali-Ion Battery Materials: Theory and Computation

Since its development in the 1970s, the rechargeable alkali-ion battery has proven to be a truly transformative technology, providing portable energy storage for devices ranging from small portable electronics to sizable electric vehicles. Here, we present a review of modern theoretical and computational approaches to the study and design of rechargeable alkali-ion battery materials. Additionally, starting from fundamental thermodynamics and kinetics phenomenological equations, we rigorously derive the theoretical relationships for key battery properties, such as voltage, capacity, alkali diffusivity, and other electrochemically relevant computable quantities. We then present an overview of computational techniques for the study of rechargeable alkali-ion battery materials, followed by a critical review of the literature applying these techniques to yield crucial insights into battery operation and performance. Finally, we provide perspectives on outstanding challenges and opportunities in the theory and computation of rechargeable alkali-ion battery materials.

25 ENERGY STORAGE↗
NASA NTRS1986

Thermodynamic evaluation of transonic compressor rotors using the finite volume approach

The development of a computational capability to handle viscous flow with an explicit time-marching method based on the finite volume approach is summarized. Emphasis is placed on the extensions to the computational procedure which allow the handling of shock induced separation and large regions of strong backflow. Appendices contain abstracts of papers and whole reports generated during the contract period.

Moore, John↗
NASA NTRS2014

Vaporization Studies of Olivine via Knudsen Effusion Mass Spectrometry

Olivine is the major mineral in the Earth's upper mantle occurring predominantly in igneous rocks and has been identified in meteorites, asteroids, the Moon and Mars. Among many other important applications in planetary and materials sciences, the thermodynamic properties of vapor species from olivine are crucial as input parameters in computational modelling of the atmospheres of hot, rocky exoplanets (lava planets). There are several weight loss studies of olivine vaporization in the literature and one Knudsen Effusion Mass Spectrometry (KEMS) study. In this study, we examine a forsterite-rich olivine (93% forsterite and 7% fayalite, Fo93Fa7) with KEMS to further understand its vaporization and thermodynamic properties.

Planetary atmospheres↗
NASA NTRS1989

A survey of upwind methods for flows with equilibrium and non-equilibrium chemistry and thermodynamics

Several versions of flux-vector split and flux-difference split algorithms were compared with regard to general applicability and complexity. Test computations were performed using curve-fit equilibrium air chemistry for an M = 5 high-temperature inviscid flow over a wedge, and an M = 24.5 inviscid flow over a blunt cylinder for test computations; for these cases, little difference in accuracy was found among the versions of the same flux-split algorithm. For flows with nonequilibrium chemistry, the effects of the thermodynamic model on the development of flux-vector split and flux-difference split algorithms were investigated using an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Several numerical examples are presented, including nonequilibrium air chemistry in a high-temperature shock tube and nonequilibrium hydrogen-air chemistry in a supersonic diffuser.

Grossman, B.↗
NASA NTRS1993

Numerical Model for Isothermal and Non-Isothermal Crystallization of Liquids and Glasses

A new numerical model of isothermal and non-isothermal first order phase transformations, such as the crystallization of liquids and glasses, is presented. This model computes directly the volume fraction transformed, taking into account time-dependent nucleation rates and cluster-size-dependent growth velocities. The model is applied to the crystallization of lithium disilicate glass, using the appropriate kinetic and thermodynamic parameters. The model is used (1) to determine the validity of common methods for computing the volume fraction transformed as a function of time in isothermal experiments when a time-dependent nucleation rate is expected, (2) to simulate non-isothermal differential scanning calorimetry (DSC) studies of glass devitrification as a function of scan rate, and (3) to compute the effect of preannealing on the DSC peak parameters. A novel behavior of the nucleation rate with scan rate is predicted, arising because the relaxation of the cluster distribution cannot be described by a single relaxation time. Comparisons of the calculations with experimental data on this glass demonstrate the validity of the model.

Kelton, K. F.↗
NASA NTRSDate not supplied

In Pursuit of CFD-based Wind Tunnel Calibrations

Computational fluid dynamic simulations of models tested in wind tunnels require a high level of fidelity and accuracy, particularly for the purposes of CFD validation efforts. Considerable effort is required to ensure a sufficient characterization of both the physical geometry of the wind tunnel, the thermodynamics of the tunnel, and flow conditions in the test section. The condition setting process among subsonic wind tunnels, closed or open throat, is generally the same, though they can differ in specific details of the thermodynamics. The derivation, application, and error estimation of condition setting and calibration is discussed. Computational flow solutions of the high-speed leg of the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel are used to evaluate the calibration process and discuss calibration curve sensitivities. Duplicating the characteristics of a particular wind tunnel is difficult at best. A calibration curve derived from the computational method is the most consistent method to use for tunnel condition setting.

wind tunnel↗
DOE OSTI2020

Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness

One of the long-standing holy grails of molecular evolution has been the ability to predict an organism’s fitness directly from its genotype. With such predictive abilities in hand, researchers would be able to more accurately forecast how organisms will evolve and how proteins with novel functions could be engineered, leading to revolutionary advances in medicine and biotechnology. In this work, we assemble the largest reported set of experimental TEM-1 β-lactamase folding free energies and use this data in conjunction with previously acquired fitness data and computational free energy predictions to determine how much of the fitness of β-lactamase can be directly predicted by thermodynamic folding and binding free energies. We focus upon β-lactamase because of its long history as a model enzyme and its central role in antibiotic resistance. Based upon a set of 21 β-lactamase single and double mutants expressly designed to influence protein folding, we first demonstrate that modeling software designed to compute folding free energies such as FoldX and PyRosetta can meaningfully, although not perfectly, predict the experimental folding free energies of single mutants. Interestingly, while these techniques also yield sensible double mutant free energies, we show that they do so for the wrong physical reasons. We then go on to assess how well both experimental and computational folding free energies explain single mutant fitness. We find that folding free energies account for, at most, 24% of the variance in β-lactamase fitness values according to linear models and, somewhat surprisingly, complementing folding free energies with computationally-predicted binding free energies of residues near the active site only increases the folding-only figure by a few percent. This strongly suggests that the majority of β-lactamase’s fitness is controlled by factors other than free energies. Overall, our results shed a bright light on to what extent the community is justified in using thermodynamic measures to infer protein fitness as well as how applicable modern computational techniques for predicting free energies will be to the large data sets of multiply-mutated proteins forthcoming.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

tLaSDI: Thermodynamics-informed latent space dynamics identification

Here we propose a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

97 MATHEMATICS AND COMPUTING↗