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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Pohorille, Andrew↗
NASA NTRS2012

Performance Evaluation of Staged Bosch Process for CO2 Reduction to Produce Life Support Consumables

Utilizing carbon dioxide to produce water and hence oxygen is critical for sustained manned missions in space, and to support both NASA's cabin Atmosphere Revitalization System (ARS) and In-Situ Resource Utilization (ISRU) concepts. For long term missions beyond low Earth orbit, where resupply is significantly more difficult and costly, open loop ARS, like Sabatier, consume inputs such as hydrogen. The Bosch process, on the other hand, has the potential to achieve complete loop closure and is hence a preferred choice. However, current single stage Bosch reactor designs suffer from a large recycle penalty due to slow reaction rates and the inherent limitation in approaching thermodynamic equilibrium. Developmental efforts are seeking to improve upon the efficiency (hence reducing the recycle penalty) of current single stage Bosch reactors which employ traditional steel wool catalysts. Precision Combustion, Inc. (PCI), with support from NASA, has investigated the potential for utilizing catalysts supported over short-contact time Microlith substrates for the Bosch reaction to achieve faster reaction rates, higher conversions, and a reduced recycle flows. Proof-of-concept testing was accomplished for a staged Bosch process by splitting the chemistry in two separate reactors, first being the reverse water-gas-shift (RWGS) and the second being the carbon formation reactor (CFR) via hydrogenation and/or Boudouard. This paper presents the results from this feasibility study at various operating conditions. Additionally, results from two 70 hour durability tests for the RWGS reactor are discussed.

Vilekar, Saurabh A.↗
NASA NTRS2016

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

A new engine cycle analysis tool, called Pycycle, was recently built using the OpenMDAO framework. This tool uses equilibrium chemistry based thermodynamics, and provides analytic derivatives. This allows for stable and efficient use of gradient-based optimization and sensitivity analysis methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a multi-point turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Turbine engine↗
NASA NTRS2022

Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling

The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.

turbulent fluxes↗
DOE OSTI2022

Modeling and Analysis of a Thermophotovoltaic Integrated Self-Powered Furnace

This work investigates the energy efficiency and carbon reduction potential of self-powered residential building heating equipment using a thermodynamic modeling approach. An integrated thermophotovoltaic power module and residential scale furnace system (40,000 Btu/h) were modeled and studied in detail to assess the influence of different design configurations on primary energy efficiency. Operational characteristics such as total power generation, electrical efficiency, and heat recovery were examined in a self-powered system configuration. A sensitivity analysis was conducted to determine the influence of the electric grid’s carbon dioxide footprint (carbon intensity) and the cost of electricity on the environmental, as well as the economic, benefit associated with the self-powered configuration. Compared with a traditional furnace powered by an electric grid at a carbon intensity of 0.5 kg CO 2eq /kWh EL , the self-powered furnace was shown to decrease the annual carbon dioxide emissions by approximately 550 kg (~75% reduction), while also saving more than USD 200 in utility expenses, annually. Additionally, the carbon emission reduction potential of blending different concentrations of hydrogen in natural gas fuel was also studied.

14 SOLAR ENERGY↗
DOE OSTI2021

An experimental database of cell performance for vanadium redox flow battery

The continual growth in energy demand has resulted in the deployment of renewable energy generators to reduce the impact of fossil fuel dependence. However, these generators often suffer from intermittency and require energy storage when there is over-generation and the subsequent release of this stored energy at high demand. One promising energy storage technology which can provide a solution to improve energy management and grid stability, is the redox flow battery. Among the numerous flow battery systems, vanadium redox flow battery is the most iconic solution to large scale energy storage, giving a more efficient link between energy production, especially from renewables, and energy demand. The aim of the current database is to characterize the performance of the cell design and to provide training/validation data for physical model or data-driven model. The database includes hundreds of experimental cell performance data of vanadium redox flow battery with various current densities for multiple charge-discharge cycles. All the cell parameters, chemical parameters, material parameters, operation parameters and thermodynamic parameters of the cell system are listed. Coulomb, voltaic and energy efficiencies are also provided. The database will be helpful for researchers in the field of redox flow batteries.

Gao, Peiyuan↗
NASA NTRS1983

Second-law efficiency of solar-thermal cavity receivers

Properly quantified performance of a solar-thermal cavity receiver must not only account for the energy gains and losses as dictated by the First Law of thermodynamics, but it must also account for the quality of that energy. However, energy quality can only be determined from the Second Law. An equation for the Second Law efficiency of a cavity receiver is derived from the definition of available energy, which is a thermodynamic property that measures the maximum amount of work obtainable when a system is allowed to come into unrestrained equilibrium with the surrounding environment. The fundamental concepts of the entropy and availability of radiation were explored from which a workable relationship among the reflected cone half-angle, the insolation, and the concentrator geometric characteristics was developed as part of the derivation of the Second Law efficiency. First and Second Law efficiencies were compared for data collected from two receivers that were designed for different purposes. A Second Law approach to quantifying the performance of a solar-thermal cavity receiver lends greater insight into the total performance than does the conventional First Law method.

Moynihan, P. I.↗
DOE OSTI2025

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2020

Effects of Surface Terminations of 2D Bi 2 WO 6 on Photocatalytic Hydrogen Evolution from Water Splitting

Two-dimensional (2D)-structured photocatalysts with atomically thin layers not only have the potential to enhance hydrogen generation efficiency but also allow more direct investigations of the effects of surface terminations on photocatalytic activity. In this work, taking 2D Bi 2 WO 6 as a model, we found that the configuration of bilayer Bi 2 O 2 sandwiched by alternating WO 4 layers enabled the thermodynamic driving potential for photocatalytic hydrogen evolution. Without Pt deposition, the H 2 generation efficiency can reach to 56.9 μmol/g/h by 2D Bi 2 WO 6 as compared with no activity of Bi 2 WO 6 nanocrystals under simulated solar light. This configuration is easily functionalized by adsorption of Cl – /Br – to form Bi–Cl/Bi–Br bonds, which leads to the decrease of recombination in photogenerated charge carriers and narrower band gaps. This work highlights an effective way to design photocatalysts with efficient hydrogen evolution by tuning the surface terminations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys

Since the introduction of Metropolis Monte Carlo (MC) sampling, it and its variants have become standard tools used for thermodynamics evaluations of physical systems. However, a long-standing problem that hinders the effectiveness and efficiency of MC sampling is the lack of a generic method (a.k.a. MC proposal) to update the system configurations. Consequently, current practices are not scalable. Here we propose a parallel MC sampling framework for thermodynamics evaluation—DeepThermo. By using deep learning–based MC proposals that can globally update the system configurations, we show that DeepThermo can effectively evaluate the phase transition behaviors of high entropy alloys, which have an astronomical configuration space. For the first time, we directly evaluate a density of states expanding over a range of ~e 10,000 for a real material. We also demonstrate DeepThermo’s performance and scalability up to 3,000 GPUs on both NVIDIA V100 and AMD MI250X-based supercomputers.

Yin, Junqi↗
NASA NTRS1978

Absorption of solar radiation by alkali vapors

A theoretical study of the direct absorption of solar radiation by the working fluid of high temperature, high efficiency energy converters has been carried out. Alkali vapors and potassium vapor in particular were found to be very effective solar absorbers and suitable thermodynamically for practical high temperature cycles. Energy loss via reradiation from a solar boiler was shown to reduce the overall efficiency of radiation-heated energy converters, although a simple model of radiation transfer in a potassium vapor solar boiler revealed that self-trapping of the reradiation may reduce this loss considerably. A study was also made of the requirements for a radiation boiler window. It was found that for sapphire, one of the best solar transmitting materials, the severe environment in conjunction with high radiation densities will require some form of window protection. An aerodynamic shield is particularly advantageous in this capacity, separating the window from the absorbing vapor to prevent condensation and window corrosion and to reduce the radiation density at the window.

Mattick, A. T.↗
DOE OSTI2021

Energy-efficient sorption-based gas clothes dryer systems

Standard electric resistance and fuel-driven dehydration technologies exhibit a maximum coefficient of performance of well below 1 mainly due to enthalpy losses associated with the air leaving the dehydration system. To improve energy efficiency, condensing dryer systems condense the moisture captured from a product in a closed-loop air circulation cycle. Existing condensing dehydration systems including heat pump dryers, however, need to significantly cool the air to achieve dehumidification. The added cooling and subsequent heating to return the air to a desired drying temperature consume substantial energy and thus reduce drying performance. Here, an innovative sorption-based gas dehydration system is proposed to overcome barriers deteriorating energy efficiency in existing gas, electric, or heat pump dryer systems. Decoupling latent and sensible loads, the system employs a liquid-desiccant solution to directly capture air humidity, thereby allowing circulation of the air in a closed loop to achieve high drying energy efficiency. In other words, the system captures waste latent heat from the moisture produced during the dehydration process and reuses it to improve energy efficiency. This study focuses on a comprehensive quasi-steady-state thermodynamic modeling of the proposed sorption-based dehydration concept employed for a gas clothes dryer application to predict transient response and overall drying performance (i.e., time and energy metrics). The analysis indicates the proposed sorption-based gas clothes dryer system can deliver a specific moisture extraction rate of 1.71 kg of water per kWh (i.e., a combined energy factor of 3.167 kg (6.98 lbm) of dry cloth per kWh) with a drying time of 44 min. This is a 112% energy improvement compared with state-of-the-art gas clothes dryers exhibiting a combined energy factor of 1.50 kg (3.3 lbm) of dry cloth per kWh. The technology pursued here can potentially be employed as a platform for many fuel-driven equipment to take advantage of available waste thermal energy in the environment instead of simply burning a fuel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Millisecond Conversion of Metastable 2D Materials by Flash Joule Heating

Controllable phase engineering is vital for precisely tailoring material properties since different phase structures have various electronic states and atomic arrangements. Rapid synthesis of thermodynamically metastable materials, especially two-dimensional metastable materials, with high efficiency and low cost remains a large challenge. Here we report flash Joule heating (FJH) as an electrothermal method to achieve the bulk conversion of transition metal dichalcogenides, MoS 2 and WS 2 , from 2H phases to 1T phases in milliseconds. The conversions can reach up to 76% of flash MoS 2 using tungsten powder as conductive additive. Different degrees of phase conversion can be realized by controlling the FJH conditions, such as reaction duration and additives, which allows the study of ratio-dependent properties. First-principles calculations confirm that structural processes associated with the FJH, such as vacancy formation and charge accumulation, result in stabilization of the 1T phases. Furthermore, FJH offers rapid access to bulk quantities of the hitherto hard-to-access 1T phases, a promising method for further fundamental research and diverse applications of metastable phases.

2D materials↗
NASA NTRS1988

Demixing kinetics of phase separated polymer solutions in microgravity

Phase separated solutions of two neutral polymers in buffer provide a useful and versatile medium for the partition separation of biological cells. However, the efficiency of such separations is orders of magnitude lower than the thermodynamic limit. To test the hypothesis that this inefficiency is at least partially due to the convection and sedimentation that occur during the gravity driven demixing that follows introduction of cells to the systems, a series of experiments were begun aimed at performing cell partition in a low g environment. Demixing of isopycnic three polymer solvent systems was studied, experiments were performed on KC-135 aircraft and one shuttle middeck experiment was completed. Analysis of the results of these experiments and comparisons with the predictions of scaling relations for the dependence of phase domain size on time, derived for a number of possible demixing mechanisms, are presented.

Brooks, D. E.↗
NASA NTRS1999

Methane Pyrolysis and Disposing Off Resulting Carbon

Sabatier/Electrolysis (S/E) is a leading process for producing methane and oxygen for application to Mars ISPP. One significant problem with this process is that it produces an excess of methane for combustion with the amount of oxygen that is produced. Therefore, one must discard roughly half of the methane to obtain the proper stoichiometric methane/oxygen mixture for ascent from Mars. This is wasteful of hydrogen, which must be brought from Earth and is difficult to transport to Mars and store on Mars. To reduced the problem of transporting hydrogen to Mars, the S/E process can be augmented by another process which reduces overall hydrogen requirement. Three conceptual approaches for doing this are (1) recover hydrogen from the excess methane produced by the S/E process, (2) convert the methane to a higher hydrocarbon or other organic with a lower H/C ratio than methane, and (3) use a separate process (such as zirconia or reverse water gas shift reaction) to produce additional oxygen, thus utilizing all the methane produced by the Sabatier process. We report our results here on recovering hydrogen from the excess methane using pyrolysis of methane. Pyrolysis has the advantage that it produces almost pure hydrogen, and any unreacted methane can pass through the S/E process reactor. It has the disadvantage that disposing of the carbon produced by pyrolysis presents difficulties. Hydrogen may be obtained from methane by pyrolysis in the temperature range 10000-12000C. The main reaction products are hydrogen and carbon, though very small amounts of higher hydrocarbons, including aromatic hydrocarbons are formed. The conversion efficiency is about 95% at 12000C. One needs to distinguish between thermodynamic equilibrium conversion and conversion limited by kinetics in a finite reactor.

Sharma, P. K.↗
DOE OSTI2020

Overcoming immiscibility toward bimetallic catalyst library

Bimetallics are emerging as important materials that often exhibit distinct chemical properties from monometallics. However, there is limited access to homogeneously alloyed bimetallics because of the thermodynamic immiscibility of the constituent elements. Overcoming the inherent immiscibility in bimetallic systems would create a bimetallic library with unique properties. Here, we present a nonequilibrium synthesis strategy to address the immiscibility challenge in bimetallics. As a proof of concept, we synthesize a broad range of homogeneously alloyed Cu-based bimetallic nanoparticles regardless of the thermodynamic immiscibility. The nonequilibrated bimetallic nanoparticles are further investigated as electrocatalysts for carbon monoxide reduction at commercially relevant current densities (>100 mA cm -2 ), in which Cu 0.9 Ni 0.1 shows the highest multicarbon product Faradaic efficiency of ~76% with a current density of ~93 mA cm -2 . The ability to overcome thermodynamic immiscibility in multimetallic synthesis offers freedom to design and synthesize new functional nanomaterials with desired chemical compositions and catalytic properties.

25 ENERGY STORAGE↗