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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Analysis of chromatograph systems using orthogonal collocation

Research is generating fundamental engineering design techniques and concepts for the chromatographic separator of a chemical analysis system for an unmanned, Martian roving vehicle. A chromatograph model is developed which incorporates previously neglected transport mechanisms. The numerical technique of orthogonal collocation is studied. To establish the utility of the method, three models of increasing complexity are considered, the latter two being limiting cases of the derived model: (1) a simple, diffusion-convection model; (2) a rate of adsorption limited, inter-intraparticle model; and (3) an inter-intraparticle model with negligible mass transfer resistance.

Woodrow, P. T.↗
NASA NTRS2007

Observations of the Li, Be, and B Isotopes and Constraints on Cosmic-ray Propagation

The abundance of Li, Be, and B isotopes in galactic cosmic rays (GCR) between E=50-200 MeV/nucleon has been observed by the Cosmic Ray Isotope Spectrometer (CRIS) on NASA's ACE mission since 1997 with high statistical accuracy. Precise observations of Li, Be, B can be used to constrain GCR propagation models. We find that a diffusive reacceleration model with parameters that best match CRIS results (e.g. B/C, Li/C, etc) are also consistent with other GCR observations. A approx. 15-20% overproduction of Li and Be in the model predictions is attributed to uncertainties in the production cross-section data. The latter becomes a significant limitation to the study of rare GCR species that are generated predominantly via spallation.

deNolfo, G. A.↗
NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗
DOE OSTI2016

An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems

Stochastic modelling is critical for studying many biochemical processes in a cell, in particular when some reacting species have low population numbers. For many such cellular processes the spatial distribution of the molecular species plays a key role. The evolution of spatially heterogeneous biochemical systems with some species in low amounts is accurately described by the mesoscopic model of the Reaction-Diffusion Master Equation. The Inhomogeneous Stochastic Simulation Algorithm provides an exact strategy to numerically solve this model, but it is computationally very expensive on realistic applications. We propose a novel adaptive time-stepping scheme for the tau-leaping method for approximating the solution of the Reaction-Diffusion Master Equation. This technique combines effective strategies for variable time-stepping with path preservation to reduce the computational cost, while maintaining the desired accuracy. The numerical tests on various examples arising in applications show the improved efficiency achieved by the new adaptive method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Diffusive flux in a model of stochastically gated oxygen transport in insect respiration

Oxygen delivery to insect tissues is controlled by transport through a branched tubular network that is connected to the atmosphere by valve-like gates, known as spiracles. In certain physiological regimes, the spiracles appear to be randomly switching between open and closed states. Quantitative analysis of this regime leads a reaction-diffusion problem with stochastically switching boundary condition. We derive an expression for the diffusive flux at long times in this problem. Our approach starts with the derivation of the passage probability for a single particle that diffuses between a stochastically gated boundary, which models the opening and closing spiracle, and the perfectly absorbing boundary, which models oxygen absorption by the tissue. This passage probability is then used to derive an expression giving the diffusive flux as a function of the geometric parameters of the tube and characteristic time scales of diffusion and gate dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1978

The effect of nonlinear diffusive heat transport in a simple climate model

The effects of nonlinear diffusive heat transport in North's (1975) model is reexamined. By inserting the nonlinearity into the original energy balance equation rather than the spectrally transformed linear algebraic equations, and including one more mode in the spectral expansion, it is found that nonlinear diffusion does give a significantly different sensitivity for states near the current climate. For linear diffusion, an increase of 0.1% of the solar constant from the present value is sufficient to melt all the ice on the earth, whereas an increase of about five times as large is required for nonlinear diffusion. This difference in sensitivity shows the importance of dynamical modeling in simple climate models.

Lin, C. A.↗
NASA NTRS1993

Simulations of diffusion-reaction equations with implications to turbulent combustion modeling

An enhanced diffusion-reaction reaction system (DRS) is proposed as a statistical model for the evolution of multiple scalars undergoing mixing and reaction in an isotropic turbulence field. The DRS model is close enough to the scalar equations in a reacting flow that other statistical models of turbulent mixing that decouple the velocity field from scalar mixing and reaction (e.g. mapping closure model, assumed-pdf models) cannot distinguish the model equations from the original equations. Numerical simulations of DRS are performed for three scalars evolving from non-premixed initial conditions. A simple one-step reversible reaction is considered. The data from the simulations are used (1) to study the effect of chemical conversion on the evolution of scalar statistics, and (2) to evaluate other models (mapping-closure model, assumed multivariate beta-pdf model).

Girimaji, Sharath S.↗
DOE OSTI2015

Modelling oxygen self-diffusion in UO 2 under pressure

Access to values for oxygen self-diffusion over a range of temperatures and pressures in UO 2 is important to nuclear fuel applications. Here, elastic and expansivity data are used in the framework of a thermodynamic model, the cBΩ model, to derive the oxygen self-diffusion coefficient in UO 2 over a range of pressures (0–10 GPa) and temperatures (300–1900 K). Furthermore, the significant reduction in oxygen self-diffusion as a function of increasing hydrostatic pressure, and the associated increase in activation energy, is identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Understanding copper diffusion in CuInSe 2 with first-principles based atomistic and continuum models

We investigate the diffusion of copper in CuInSe 2 using thermodynamic and kinetic models based on density functional theory calculations, attempting to reconcile large differences in reported experimental diffusivities. We find that observations of rapid chemical diffusion can be explained by large thermodynamic factors, which we calculate using a compositionally constrained model of intrinsic point defect formation. We further characterize how copper diffusion coefficients depend on material synthesis conditions and exhibit their variation across the CuInSe 2 secondary phase diagram. In doing so, we identify stable off-stoichiometries that are dominated by either vacancy- or interstitial-mediated diffusion mechanisms. These results are employed in the development of a continuum reaction–diffusion model, which we use to simulate experimental depth profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Analysis of transient fission gas behaviour in oxide fuel using BISON and TRANSURANUS

The modelling of fission gas behaviour is a crucial aspect of nuclear fuel analysis in view of the related effects on the thermo-mechanical performance of the fuel rod, which can be particularly significant during transients. Experimental observations indicate that substantial fission gas release (FGR) can occur on a small time scale during transients (burst release). To accurately reproduce the rapid kinetics of burst release in fuel performance calculations, a model that accounts for non-diffusional mechanisms such as fuel micro-cracking is needed. In this work, we present and assess a model for transient fission gas behaviour in oxide fuel, which is applied as an extension of diffusion-based models to allow for the burst release effect. The concept and governing equations of the model are presented, and the effect of the newly introduced parameters is evaluated through an analytic sensitivity analysis. Then, the model is assessed for application to integral fuel rod analysis. The approach that we take for model assessment involves implementation in two structurally different fuel performance codes, namely, BISON (multi-dimensional finite element code) and TRANSURANUS (1.5D semi-analytic code). The model is validated against 19 Light Water Reactor fuel rod irradiation experiments from the OECD/NEA IFPE (International Fuel Performance Experiments) database, all of which are simulated with both codes. The results point out an improvement in both the qualitative representation of the FGR kinetics and the quantitative predictions of integral fuel rod FGR, relative to the canonical, purely diffusion-based models, with both codes. The overall quantitative improvement of the FGR predictions in the two codes is comparable. Furthermore, calculated radial profiles of xenon concentration are investigated and compared to experimental data, demonstrating the representation of the underlying mechanisms of burst release by the new model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1978

A theoretical study of a laminar diffusion flame

Theoretical models of an axisymmetric laminar diffusion flame are discussed, with an emphasis on the behavior of such flames at increasing pressures. The flame-sheet or Burke-Schumann model (in terms of Bessel functions) and various boundary layer numerical solutions are presented and their results compared with experimental data. The most promising theoretical model combines the numerical flow field solution of the Patankar-Spalding computer code with the Pratt-Wormeck chemical reaction subroutine. The flame shapes for pressures of 1, 5, 10, 20, and 50 atmospheres were computed and agree remarkably well with experimental data. There is a noticeable shape change with pressure, believed to be a result of buoyancy effects. The chemical concentration profiles do not exhibit much dependence on pressure, a reflection of the fact that only one chemical mechanism was utilized at all pressures.

Frair, K. L.↗
NASA NTRS1997

Diffuse-Interface Methods in Fluid Mechanics

The authors review the development of diffuse-interface models of hydrodynamics and their application to a wide variety of interfacial phenomena. The authors discuss the issues involved in formulating diffuse-interface models for single-component and binary fluids. Recent applications and computations using these models are discussed in each case. Further, the authors address issues including sharp-interface analyses that relate these models to the classical free-boundary problem, related computational approaches to describe interfacial phenomena, and related approaches describing fully-miscible fluids.

SURFACE DIFFUSION↗
DOE OSTI2022

A Robust Numerical Treatment of Solid-Phase Diffusion in Pseudo Two-Dimensional Lithium-Ion Battery Models

Solid-phase diffusion in active materials of lithium-ion batteries significantly affects charging and safety-related behavior of lithium-ion batteries. Therefore, it is essential to develop an efficient and robust numerical algorithm for solving solid-phase diffusion equations in physics-based battery models. In this work, we discuss the origins of numerical instabilities that can occur when solving the solid-phase diffusion equations using iterative methods. Then, in order to resolve such issues, we propose a simple numerical treatment to the surface flux term of discretized solid-phase diffusion equations. To demonstrate its numerical robustness, the proposed method is implemented into a pseudo two-dimensional (P2D) physics-based battery model and simulations are conducted at wide ranges of operating conditions. Even with extremely poor initial guesses for the Li+ concentrations of the active materials, computations using the proposed method do not diverge and the their computational speeds are comparable to those with conventional initial guesses. Comprehensive tests of the proposed method are also performed with a dynamic current profile based on US06 driving profile and a multi-stage charging profile with very high initial C-rate (12C).

battery modeling↗
NASA NTRS1977

Cooling rate estimations based on kinetic modelling of Fe-Mg diffusion in olivine

A finite one-dimensional kinetic model was developed to estimate the cooling rates of lunar rocks. The model takes into consideration the compositional zonation of olivine and applies Buening and Buseck (1973) data on ion diffusion in olivine. Since the 'as-solidified' profile of a given olivine is not known, a step-function, with infinite gradient, is assumed; the position of this step is based on mass balance considerations of the measured compositional profile. A minimum cooling rate would be associated with the preservation of a given gradient. The linear cooling rates of lunar rocks 12002 and 15555 were estimated by use of the olivine cooling-rate indicator to be 10 C/day and 5 C/day, respectively. These values are lower than those obtained by dynamic crystallization studies (10-20 C/day).

Taylor, L. A.↗
DOE OSTI2018

Predicting Effective Diffusion Coefficients in Mudrocks Using a Fractal Model and Small-Angle Neutron Scattering Measurements

The determination of effective diffusion coefficients of gases or solutes in the water–saturated pore space of mudrocks is time consuming and technically challenging. Yet, reliable values of effective diffusion coefficients are important to predict migration of hydrocarbon gases in unconventional reservoirs, dissipation of (explosive) gases through clay barriers in radioactive waste repositories, mineral alteration of seals to geological CO 2 storage reservoirs and contaminant migration through aquitards. In this study, small angle and very small angle neutron scattering techniques have been utilized to determine a range of transport properties in mudrocks, including porosity, pore size distributions and surface and volume fractal dimensions of pores and grains, from which diffusive transport parameters can be estimated. Using a fractal model derived from Archie's Law, we calculate effective diffusion coefficients from these parameters and compare them to laboratory–derived effective diffusion coefficients for CO 2 , H 2 , CH 4 and HTO on either the same or related mudrock samples. The samples include Opalinus Shale from the underground laboratory in Mont Terri, Switzerland; Boom Clay from a core drilled in Mol, Belgium and a marine claystone cored in Utah, USA. The predicted values were compared to laboratory diffusion measurements. The measured and modeled diffusion coefficients show good agreement, differing generally by less than factor 5. Furthermore, neutron or X–ray scattering analysis is therefore proposed as a novel method for fast, accurate estimation of effective diffusion coefficients in mudrocks, together with simultaneous measurement of multiple transport parameters including porosity, pore size distributions and surface areas, important for (reactive) transport modelling.

58 GEOSCIENCES↗
DOE OSTI2016

The influence of hydrothermal temperature and time toward crystallinity of zeolite X supported on glass wool for CO{sub 2} adsorption

In this study, the influence of hydrothermal temperature and time at zeolite X supported on glasswool were investigated. The results of characterization using XRD showed that a single phase zeolite X with highest crystallinity was obtained when hydrothermal temperature and time at 100°C during 24 hours (ZXF100-24H). The CO{sub 2} adsorption capacity of ZXF100-24H has reached up to 10.15 wt. %. Kinetics of CO{sub 2} adsorption onto zeolite X supported on glasswool was investigated using pseudo-first-order, pseudo-second-order and intra-particle diffusion kinetic models. After evaluating three kinetic models for CO{sub 2} adsorption at adsorption temperatures of 30°C, 40°C and 50°C, it was found that intra-particle diffusion kinetic model provided the best fitting for the adsorption data. Furthermore, the thermodynamic parameters of CO{sub 2} adsorption were obtained as follows, Gibbs free energy change (ΔG°) are −0.409 kJ/mol at 30°C, −0.274 kJ/mol at 40°C and −0.138 kJ/mol at 50 °C, whereas the enthalpy change (ΔH°) is −4.53 kJ/mol and the entropy change (ΔS°) is −0.0135 kJ/(mol K).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗