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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Cosmic bullets as particle accelerators and radio sources

We have simulated in two dimensions the dynamical evolution of dense gas clouds(`cosmic bullets') moving supersonically through a uniform low-density medium. The diffusive shock acceleration of relativistic protons (cosmic rays) and their dynamical feedback on the background flow are included by the two-fluid model for this process. The acceleration of relativistic electrons is approximated by a test-particle model, and a passive magnetic field is followed by a simple advection scheme. Strong bow shocks, with Mach numbers similar to that of a bullet's motion, are the most important particle accelerators in the flow, while tail shocks and shocks inside the bullets do not play generally significant roles in this regard. For our simulation parameters, approximately greater than 10% of the initial bullet kinetic energy is converted to a combination of internal energy of gas and cosmic-ray protons by the time the bullets begin to be disrupted. Characteristically, the cosmic rays gain several percent of the available kinetic energy. Bullet destruction on timescales only a little larger than the ram pressure bullet crushing time begins in response to Kelvin-Helmholtz and especially to Rayleigh-Taylor instabilities along the forward bullet surface. For dense bullets this happens before the bullet is stopped by ram pressure. According to our simple model for synchrotron emission from relativistic electrons accelerated and transported within the flows, that emission increases rapidly as the bullet begins to fragment, when it is strongly dominated by field enhancement in sheared flows. Synchrotron emission from the acceleration region within the bow shock is, by contrast, much weaker.

Jones, T. W.↗
NASA NTRS2005

Water as a matrix for life

Life is based on non-covalent interactions. They might be either specific (enzyme-substrate interactions, selective ion transport) or nonspecific (lipid-lipid and lipid-protein interactions needed for membrane integrity, fusion and division). Their strength needs to be properly tuned, and this is mediated by the solvent. If interactions are too weak, there might be undesired response to natural fluctuations of physical and chemical parameters. If they are too strong it could impede kinetics and energetics of cellular processes. Thus, the solvent must allow for balancing these interactions. Physical and chemical properties of solvent provide strong constraints for life. Water exhibits a remarkable trait that it promotes both solvophobic and solvophilic interactions. Solvophobic interactions; related to high dielectric constant of the solvent) are necessary for self-organization of matter whereas solvophilic interactions are needed to ensure solubility of polar species. Water offers a large temperature domain of stable liquid and the characteristics hydrophobic effects are a consequence of the temperature in sensitivity of essential properties of its liquid state. Water, however, is not the only liquid with these favorable properties. I will compare in detail properties of water and other pure liquids or their mixtures that have a high dielectric constant and simultaneously support self-organization. I will also discuss properties of water that are unfavorable to life (e.g. its chemical activity against polymerization reactions) and close with summarizing what are alternatives to water as a matrix of life in space.

Pohorille, Andrew↗
NASA NTRSDate not supplied

Enabling Mission Flexibility to Battery Driven Deep Space Endeavors With Generalized Battery-Health-Monitoring Using Physics-Based and Data-Driven Reduced-Order Models

The needs and requirements for an electrochemical energy storage for deep space exploration is well explored. It is often understood that different mission sites and environmental conditions require different battery chemistries or technologies. Additionally, various engineering solutions are deployed to overcome specific chemical challenges. One often overlooked need is the “health” monitoring of an electrochemical storage system. The term generalized health monitoring, as envisioned in this work, refers to the monitoring of various aspects such as electrode health, electrolyte health, reaction pathway health, cooling system health, sensor health, and BMS health [1]. Generalized health monitoring allows mission leads, engineers, and scientists to incorporate flexibility in mission designs, make on-the-fly mission changes, and extend the duration of science missions. Moreover, it enables automation and data-driven decision-making without compromising safety and performance. Recently, our group developed a hierarchy of thermal reduced-order models (TROM) by combining a physics-based modeling approach and data-driven model reduction techniques applied to flight data [2]. The resulting TROMs were found to be not only accurate but also identifiable from the flight data. Consequently, the coefficient of variance of the model parameters is small over the course of hundreds of flights, allowing for monitoring the parameter evolution trajectories as the battery ages and degrades. These parameters constitute the metrics of the generalized health of a battery. Monitoring their evolution allows such models to be used for anomaly detection and prognostics, improving early detection of abnormal behavior and thus enabling timely maintenance, longer battery life, and enhanced battery safety. For this presentation, the practicality of the thermal model will be validated on a pack of 14cells under various topology configurations such as 1S14P, 2P7S, 7S2P, and 1P14S. It is well known that manufacturing and non-uniform aging lead to variability in the performance of a cell, which is exacerbated by cell balancing during active load. Additionally, in extreme scenarios, the paramount objective is to complete the mission, regardless of the stresses on the battery. Topology-induced balancing issues further stress the battery. The goal of this study is to determine if the noise (identifiability) in the reduced-order thermal model parameters is sensitive to topology, cell spacing, cooling strategy, and manufacturing or age variability. The variability in cells is considered by assuming a multimodal distribution for microscopic parameters of a cell (such as porosity, tortuosity, reaction kinetics, volumetric thermal conductivity, and volumetric heat capacity). The compounded effect of manufacturing variability, topological selection, cooling strategies, and cell balancing ages each cell in a battery differently. The study aims to clarify whether the challenge in extracting maximum information depends on the minimum number of sensors or models used for data extraction.

Automation↗
DOE OSTI2015

In Situ Synthesis of Uranium Carbide and its High Temperature Cubic Phase

New in situ data for the U-C system are presented, with the goal of improving knowledge of the phase diagram to enable production of new ceramic fuels. The none quenchable, cubic, δ-phase, which in turn is fundamental to computational methods, was identified. Rich datasets of the formation synthesis of uranium carbide yield kinetics data which allow the benchmarking of modeling, thermodynamic parameters etc. The order-disorder transition (carbon sublattice melting) was observed due to equal sensitivity of neutrons to both elements. This dynamic has not been accurately described in some recent simulation-based publications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Heavy-Meson Spectrum Tests of the Oktay--Kronfeld Action

We present heavy-meson spectrum results obtained using the Oktay--Kronfeld (OK) action on MILC asqtad lattices. The OK action was designed to improve the heavy-quark action of the Fermilab formulation, such that heavy-quark discretization errors are reduced. The OK action includes dimension-6 and -7 operators necessary for tree-level matching to QCD through order $\mathrm{O}(\Lambda^3/m_Q^3)$ for heavy-light mesons and $\mathrm{O}(v^6)$ for quarkonium, or, equivalently, through $\mathrm{O}(a^2)$ with some $\mathrm{O}(a^3)$ terms with Symanzik power counting. To assess the improvement, we extend previous numerical tests with heavy-meson masses by analyzing data generated on a finer ($a \approx 0.12\;$fm) lattice with the correct tadpole factors for the $c_5$ term in the action. We update the analyses of the inconsistency parameter and the hyperfine splittings for the rest and kinetic masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Kinetics and morphological evolution of liquid metal dealloying

Liquid metal dealloying (LMD) has recently emerged as a novel technique to fabricate bulk nanostructures using a bottom-up self-organization method, but the literature lacks fundamental studies of this kinetic process. In this work, we conduct an in-depth study of the kinetics and fundamental microstructure evolution mechanisms during LMD using Tisingle bondTa alloys immersed in molten Cu as a model system. We develop a model of LMD kinetics based on a quantitative characterization of the effects of key parameters in our system including alloy composition, dealloying duration, and dealloying temperature. Further, this work demonstrates that the dealloying interface is at or near equilibrium during LMD, and that the rate-limiting step is the liquid-state diffusion of dissolving atoms away from the dealloying interface (diffusion-limited kinetics). The quantitative comparison between theoretically predicted and measured dealloying rates further reveals that convective transport and rejection of the dissolving element during coarsening of the structure also influence the dealloying kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Systems, methods and computer-readable media to model kinetic performance of rechargeable electrochemical devices

A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics. The computing system also analyzes the cell information of the electrochemical cell with a Butler-Volmer (BV) expression modified to determine exchange current density of the electrochemical cell by including kinetic performance information related to pulse-time dependence, electrode surface availability, or a combination thereof. A set of sigmoid-based expressions may be included with the modified-BV expression to determine kinetic performance as a function of pulse time. The determined exchange current density may be used with the modified-BV expression, with or without the sigmoid expressions, to analyze other characteristics of the electrochemical cell. Model parameters can be defined in terms of cell aging, making the overall kinetics model amenable to predictive estimates of cell kinetic performance along the aging timeline.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Compton scattering of the microwave background by quasar-blown bubbles

At least 10% of quasars drive rapid outflows from the central regions of their host galaxies. The mass and energy flow rates in these winds are difficult to measure, but their kinetic luminosities probably exceed 10(exp 45) ergs/s. This kind of outflow easily sunders the interstellar medium of the host and blows a bubble in the intergalactic medium. After the quasar shuts off, the hot bubble continues to shock intergalactic gas until its leading edge merges with the Hubble flow. The interior hot gas Compton scatters microwave background photons, potentially providing a way to detect these bubbles. Assuming that quasar kinetic luminosities scale with their blue luminosities, we integrate over the quasar luminosity function to find the total distortion (y) of the microwave background produced by the entire population of quasar wind bubbles. This calculation of y distortion is remarkably insensitive to the properties of the intergalactic medium (IGM), quasar lifetimes, and cosmological parameters. Current Cosmic Background Explorer (COBE) limits on y constrain the kinetic luminosities of quasars to be less than several times their bolometric radiative luminosities. Within this constraint, quasars can still expel enough kinetic luminosity to shock the entire IGM by z = 0, but cannot heat and ionize the IGM by z = 4 unless omega(sub IGM) much less than 10(exp -2).

Voit, G. Mark↗
DOE OSTI2019

Dynamic Interaction of Nitrogen Atoms with the Surface of an Aluminum Crystal

A possibility of reconstructing the ion-atom dynamic interaction potential from the dependence of the rainbow scattering angle of nitrogen atoms under the conditions of grazing incidence on the surface of an aluminum crystal on the total kinetic energy of the accelerated atomic particles is demonstrated. The parameters of the dynamic interaction potential are determined within the energy range from 10 to 70 keV using the best possible fit between the calculated dependence of the rainbow scattering angle on the energy of the particles incident on the aluminum crystal surface along the crystallographic directions and the available experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1975

Theoretical study of production of unique glasses in space

The potential of producing the glassy form of selected materials in the weightless, containerless nature of space processing is examined through the development of kinetic relationships describing nucleation and crystallization phenomena. Transformation kinetics are applied to a well-characterized system (SiO2), an excellent glass former (B2O3), and a poor glass former (Al2O3) by conventional earth processing methods. Viscosity and entropy of fusion are shown to be the primary materials parameters controlling the glass forming tendency. For multicomponent systems diffusion-controlled kinetics and heterogeneous nucleation effects are considered. An analytical empirical approach is used to analyze the mullite system. Results are consistent with experimentally observed data and indicate the promise of mullite as a future space processing candidate.

Larsen, D. C.↗
DOE OSTI2016

Spectroscopy and Kinetics of Combustion Gases at High Temperatures

This report describes our research program that involves two complementary activities: (1) development and application of cw laser absorption methods for the measurement of concentration time-histories and fundamental spectroscopic parameters for species of interest in combustion; and (2) shock tube studies of reaction kinetics relevant to combustion. This first part of this report covers research during the final three-year support period, i.e. March 2012 – November 2015. The later part of this report summarizes research conducted over multiple-year periods between March 1988 to March 2012. Publications supported by DOE for each period are summarized at the end of that report section.

10 SYNTHETIC FUELS↗
DOE OSTI2024

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. Finally, this versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Kinetics and Thermochemistry of ClCO Formation from the Cl + CO Association Reaction

Laser flash photolysis of Cl2/CO/M mixtures (M = N2, CO, Ar, CO2) has been employed in conjunction with Cl((sup 2)P(sub J)) detection by time-resolved resonance fluorescence spectroscopy to investigate equilibration kinetics in the reactions Cl((sup 2)P(sub J)) + CO ClCO as a function of temperature (185-260 K) and pressure (14-200 Torr). The association and dissociation reactions are found to be in the low-pressure limit over the range of experimental conditions investigated. In N2 and/or CO buffer gases, the temperature dependences of the ClCO formation and dissociation reaction rate constants are described by the Arrhenius expressions k(sub 1) = (1.05 +/- 0.36) x 10(exp -34) exp[(810 +/- 70)/T] cm(exp 6)/molecules(exp 2).s and k(sub -1) = (4.1 +/- 3.1) x 10(exp -10) exp[(-2960 +/- 60)/T]cu cm/(molecule.s) (errors are 2 sigma). Second- and third-law analyses of the temperature dependence of the equilbrium constant (k/k-1) lead to the following thermodynamic parameters for the association reaction: Delta-H(sub 298) = -7.7 +/- 0.6 kcal/mol, Delta-H(sub 0) = -6.9 +/- 0.7 kcal/mol, Delta-S(sub 298) = -23.8 +/- 2.0 cal/mole.K, Delta-H(sub f,298)(ClCO) = 5.2 +/- 0.6 kcal/mol (errors are 2 sigma). The results repported in this study significantly reduce the uncertainties in all reported kinetic and thermodynamic parameters.

Nicovich, J. M.↗
DOE OSTI2019

Surface Wetting Controls Calcium Carbonate Crystallization Kinetics

Because of the widespread presence of foreign substrates in natural settings, mineral precipitation usually occurs via heterogeneous nucleation. This process is controlled by the interplay between the fluid supersaturation and interfacial energies present between the fluid, nucleus, and substrate. Among a number of physicochemical parameters, the surface wetting properties have been shown to be a key parameter controlling heterogeneous nucleation. The present study aims at elucidating the pathway and kinetics of CaCO 3 heterogeneous nucleation on a set of phlogopite micas with and without fluorine/hydroxyl substitutions, yielding substrates with contrasting hydrophilicity. Our results show that, irrespective of surface wetting properties, amorphous calcium carbonate (ACC) is formed during the early stages. The surface wetting properties have a strong effect on the crystallization kinetics: ACC precipitates persist longer on the hydrophilic (hydroxylated) surface than on the less hydrophilic (fluorinated) one. We show that this stabilization could have a thermodynamic origin because of the lower interfacial free energy between the hydrated amorphous precursor and the hydrophilic substrate. Furthermore, these results are highly relevant for biomineralization studies, where differences in wetting properties of organic moieties present in calcifying organisms could be used to accelerate or decelerate the crystallization of the initially formed amorphous precursor phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Joint estimation of biogeochemical model parameters from multiple experiments: A bayesian approach applied to mercury methylation

Here, to characterize complex biogeochemical systems, results from multiple experiments, where each targets a specific subprocess, are commonly combined. The resulting datasets are interpreted through the calibration of biogeochemical models for process inference and predictions. Commonly used calibration approaches of fitting datasets from individual experiments to subprocess models one at a time is prone to missing information shared between datasets and incomplete uncertainty propagation. We propose a Bayesian joint-fitting scheme addressing the above-mentioned concerns by jointly fitting all the available datasets, thus calibrating the entire biogeochemical model in one go using Markov Chain Monte Carlo (MCMC). The identification of null spaces in the parameter distributions from MCMC guided the simplification of certain subprocess models. For example, fast kinetic sorption was replaced by equilibrium sorption, and Monod demethylation was replaced by first-order demethylation. Joint fitting of datasets resulted in complete uncertainty propagation with parameter estimates informed by all available data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Computer-Aided Construction of Chemical Kinetic Models

The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriate refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

The Harrison Diffusion Kinetics Regimes in Solute Grain Boundary Diffusion

Knowledge of the limits of the principal Harrison kinetics regimes (Type-A, B and C) for grain boundary diffusion is very important for the correct analysis of the depth profiles in a tracer diffusion experiment. These regimes for self-diffusion have been extensively studied in the past by making use of the phenomenological Lattice Monte Carlo (LMC) method with the result that the limits are now well established. The relationship of those self-diffusion limits to the corresponding ones for solute diffusion in the presence of solute segregation to the grain boundaries remains unclear. In the present study, the influence of solute segregation on the limits is investigated with the LMC method for the well-known parallel grain boundary slab model by showing the equivalence of two diffusion models. It is shown which diffusion parameters are useful for identifying the limits of the Harrison kinetics regimes for solute grain boundary diffusion. It is also shown how the measured segregation factor from the diffusion experiment in the Harrison Type-B kinetics regime may differ from the global segregation factor.

99 GENERAL AND MISCELLANEOUS↗