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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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NASA NTRS1998

A Three-Dimensional Analysis of the Galactic Gamma-Ray Emission Resulting from Cosmic-Ray Interaction with the Interstellar Gas and Radiation Fields

This final report outlines the progress of the contractor's support for the analysis of data under ADP (NRA 96-ADP-08; Proposal No. 167-96 adp). The primary task object was to construct a 3-D model for the distribution of high-energy (20 MeV-30 GeV) gamma-ray emission in the Galactic disk. Under this task the contractor was to utilize data from the EGRET instrument on the Compton Gamma-Ray Observatory, HI and CO surveys, radio-continuum surveys at 408 MHz, 1420 MHz, 5 GHz, and 19 GHz, the COBE Diffuse Infrared Background Experiment (DIRBE) all-sky maps from I to 240 um, and ground-based B,V, J, H and K photometry. The respective contributions to the high-latitude gamma-ray emission from cosmic ray-matter interactions, inverse Compton scattering, and extra-galactic emission were to be determined.

Sodraski, Thomas J.↗

NASA NTRS2000

A Three-Dimensional Analysis of the Galactic Gamma-Ray Emission Resulting from Cosmic-Ray Interactions with the Interstellar Gas and Radiation Fields

The primary task objective is to construct a 3-D model for the distribution of high-energy (20 MeV - 30 GeV) gamma-ray emission in the Galactic disk. Under this task the contractor will utilize data from the EGRET instrument on the Compton Gamma-Ray Observatory, H I and CO surveys, radio-continuum surveys at 408 MHz, 1420 MHz, 5 GHz, and 19 GHz, the COBE Diffuse Infrared Background Experiment (DIRBE) all-sky maps from 1 to 240 microns, and ground-based B, V, J, H, and K photometry. The respective contributions to the gamma-ray emission from cosmic ray/matter interactions, inverse Compton scattering, and extragalactic emission will be determined.

Sodroski, Thomas J.↗

NASA NTRS2002

Simulation of Etching in Chlorine Discharges Using an Integrated Feature Evolution-Plasma Model

To better utilize its vast collection of heterogeneous resources that are geographically distributed across the United States, NASA is constructing a computational grid called the Information Power Grid (IPG). This paper describes various tools and techniques that we are developing to measure and improve the performance of a broad class of NASA applications when run on the IPG. In particular, we are investigating the areas of grid benchmarking, grid monitoring, user-level application scheduling, and decentralized system-level scheduling.

Hwang, Helen H.↗

NASA NTRS2001

A 3-Dimensional Analysis of the Galactic Gamma-Ray Emission Resulting from Cosmic-Ray Interactions with the Interstellar Gas and Radiation Fields

The contractor will provide support for the analysis of data under ADP (NRA 96-ADP- 09; Proposal No . 167-96adp). The primary task objective is to construct a 3-D model for the distribution of high-energy (20 MeV - 30 GeV) gamma-ray emission in the Galactic disk. Under this task the contractor will utilize data from the EGRET instrument on the Compton Gamma-Ray Observatory, H I and CO surveys, radio-continuum surveys at 408 MHz, 1420 MHz, 5 GHz, and 19 GHz, the COBE Diffuse Infrared Background Experiment (DIME) all-sky maps from 1 to 240 p, and ground-based B, V, J, H, and K photometry. The respective contributions to the gamma-ray emission from cosmic ray/matter interactions, inverse Compton scattering, and extragalactic emission will be determined.

Sodroski, Thomas J.↗

NASA NTRS1995

Estimating the Modified Allan Variance

A paper at the 1992 FCS showed how to express the modified Allan variance (mvar) in terms of the third difference of the cumulative sum of time residuals. Although this reformulated definition was presented merely as a computational trick for simplifying the calculation of mvar estimates, it has since turned out to be a powerful theoretical tool for deriving the statistical quality of those estimates in terms of their equivalent degrees of freedom (edf), defined for an estimator V by edf V = 2(EV)2/(var V). Confidence intervals for mvar can then be constructed from levels of the appropriate 2 distribution.

Allan Variance↗

NASA NTRS2022

Development of an Effective Finite-rate Oxidation Model for NuSil-coated Charred Carbon Preform Ablators

Recently, a detailed effective finite-rate surface chemistry model was developed for the oxidation of FiberForm [1] using the molecular beam experimental data of Poovathingal et al., [2]. FiberForm is the major building block of the thermal protection system (TPS) material Phenolic Impregnated Carbon Ablator (PICA), commonly used by NASA. The surface chemistry model consists of detailed surface reaction mechanisms such as adsorption, desorption, and several types of Langmuir-Hinshelwood (LH) reactions to characterize the oxygen-carbon interactions at the surface. This model provides excellent agreement with the experimental data for oxidation product compositions and corresponding translational energy distributions. Further, an effective oxidation model was constructed that captures the equivalent interaction of oxygen inside the microstructure (including multiple surface collisions) via a modified reactivity for a smooth wall boundary condition. This enables the use of this model directly into Computational Fluid Dynamics (CFD) codes and Material Response (MR) codes to accurately simulate the gas–surface interactions within FiberForm without using the detailed micro-structure. However, this effective model is valid only for the virgin FiberForm. As the TPS material undergoes ablation, the preform carbon burns and turns into char. In addition, PICA is also coated with a protective silicon coating called NuSil for the purpose of mitigating the spread of phenolic dust, and limit contamination during clean room operations. Fig. 1 shows a X-ray microtomography image of a charred NuSil-coated PICA. The NuSil layer introduces species containing silicon into the product mixture. Further, the reactivity of the carbon within the char layer is different from the virgin FiberForm as shown in Fig. 2. Recently a new set of molecular beam experiments were performed on this NuSil-coated TPS material [3] with the same type of oxygen beam used in the previous experiments. Using the latest experimental data, the previously developed effective model will be extended to account for the charred carbon as well as the NuSil coating. Finally, this new effective model with three phases – preform carbon, char, and NuSil; will be compared and validated against the experimental product compositions.

K Swaminathan Gopalan↗

DOE OSTI2015

Flattening of fuel importance for heterogeneous system to estimate maximal multiplication factor - 14595

In order to quantify risks of re-criticality incidents associated with loss of coolant accidents (LOCA), the maximum reactivity insertion by relocation of damaged fuel should be quantified. As the first step for the quantification, an automated search scheme is studied for an optimal geometry of damaged fuel in the coolant channel where the neutron multiplication factor k{sub eff} takes a maximal value. The scheme is based on the flattening of the fuel importance. The importance can be recognized as the substitution reactivity from fuel to water in heterogeneous systems. The flattening is achieved by substitution of water and the fuel so as to raise the k{sub eff} referring the local substitution reactivities. To calculate the reactivities efficiently, the first order perturbation scheme is adopted. In the scheme, the adjoint flux is calculated with the PARTISN code. The multi group constants used for the calculation and the perturbed reaction rates are estimated with the continuous energy Monte Carlo code MCNP-5. The proposed methods are tested for a quarter pin cell model that is constructed using Cartesian mesh. From a random distribution of a given amount of fragmented fuel, an optimal geometry is found where the fragmented fuels are aggregated. The multiplication factor in the geometry is greater than that in the original random distribution by 1.4%Δk/k. That indicates the significance of this study. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

A Bayesian approach to the long-baseline neutrino oscillation sensitivity of DUNE

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector.

Abbaslu, Saeed [IPM, Tehran] (ORCID:00000003356771↗

DOE OSTI2017

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robust and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.

09 BIOMASS FUELS↗

NASA NTRS1988

Electron density distributions in the high-latitude magnetosphere

Electron density profiles were constructed to study the plasma density depletions in the nightside auroral zone and the density variations with increasing altitude in the polar cap, using electric field spectrum measurements from the plasma wave instrument on DE-1. Sharply defined regions of depleted plasma densities were commonly observed on nightside auroral field lines, in which electron densities were strongly depleted in relation to the adjacent plasmaspheric and polar densities, forming a low-density cavity at about 70 deg invariant latitude. A correlation was found between low auroral plasma densities, upflowing ion distributions, and an energetic precipitating electron population, indicating that electron density depletions in the nightside auroral zone are directly associated with auroral acceleration processes.

Persoon, Ann M.↗

DOE OSTI2016

Simulation Model of Microsphere Distribution for Selective Internal Radiation Therapy Agrees With Observations

Purpose: To perform a detailed analysis of microsphere distribution in biopsy material from a patient treated with {sup 90}Y-labeled resin spheres and characterize microsphere distribution in the hepatic artery tree, and to construct a novel dichotomous bifurcation model for microsphere deposits and evaluate its accuracy in simulating the observed microsphere deposits. Methods and Materials: Our virtual model consisted of arteries that successively branched into 2 new generations of arteries at 20 nodes. The artery diameter exponentially decreased from the lowest generation to the highest generation. Three variable parameters were optimized to obtain concordance between simulations and measure microsphere distributions: an artery coefficient of variation (ACV) for the diameter of all artery generations and the microsphere flow distribution at the nodes; a hepatic tree distribution volume (HDV) for the artery tree; and an artery diameter reduction (ADR) parameter. The model was tested against previously measured activity concentrations in 84 biopsies from the liver of 1 patient. In 16 of 84 biopsies, the microsphere distribution regarding cluster size and localization in the artery tree was determined via light microscopy of 30-μm sections (mean concentration, 14 microspheres/mg; distributions divided into 3 groups with mean microsphere concentrations of 4.6, 14, and 28 microspheres/mg). Results: Single spheres and small clusters were observed in terminal arterioles, whereas large clusters, up to 450 microspheres, were observed in larger arterioles. For 14 microspheres/mg, the optimized parameter values were ACV=0.35, HDV = 50 cm{sup 3}, and ADR=6 μm. For 4.6 microspheres/mg, ACV and ADR decreased to 0.26 and 0 μm, respectively, whereas HDV increased to 130 cm{sup 3}. The opposite trend was observed for 28 microspheres/mg: ACV = 0.49, HDV = 20 cm{sup 3}, and ADR = 8 μm. Conclusion: Simulations and measurements reveal that microsphere clusters are larger and more common in volumes with high microsphere concentrations and indicate that the spatial distribution of the artery tree must be considered in estimates of microsphere distributions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

Jacobs, John M.↗

DOE OSTI2019

Adaptive sparse polynomial dimensional decomposition for derivative-based sensitivity

In this report applications, such as the plasma-coupled combustion system we consider, derivative-based sensitivity indices (DSI) are known to have several advantages over Sobol's total sensitivity indices, especially for small sample sizes. Several properties of derivative-based sensitivity measures are leveraged to develop a new and efficient numerical approach to estimate them. It is based on computing the DSI measures by effectively cost-free Monte Carlo sampling of an adaptively constructed orthogonal polynomial surrogate with uncertain input parameters that can have arbitrary probability distributions. The adaptivity reduces the number of necessary model evaluations, which is demonstrated both in a constructed example (the Moon function) and in two plasma-combustion systems with up to 55 uncertain parameters. Unimportant parameters are successfully identified and neglected with a low number of model evaluations, which makes it an attractive non-intrusive approach when adjoint solutions are unavailable to provide sensitivity information.

42 ENGINEERING↗

DOE OSTI2014

SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the use of probabilistic models into clinical chart checking for improved detection of potential errors in RT plans.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Learning the temporal evolution of multivariate densities via normalizing flows

In this work, we propose a method to learn multivariate probability distributions using sample path data from stochastic differential equations. Specifically, we consider temporally evolving probability distributions (e.g., those produced by integrating local or nonlocal Fokker–Planck equations). Here, we analyze this evolution through machine learning assisted construction of a time-dependent mapping that takes a reference distribution (say, a Gaussian) to each and every instance of our evolving distribution. If the reference distribution is the initial condition of a Fokker–Planck equation, what we learn is the time-T map of the corresponding solution. Specifically, the learned map is a multivariate normalizing flow that deforms the support of the reference density to the support of each and every density snapshot in time. We demonstrate that this approach can approximate probability density function evolutions in time from observed sampled data for systems driven by both Brownian and Lévy noise. We present examples with two- and three-dimensional, uni- and multimodal distributions to validate the method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

An extended numerical manifold method for unsaturated soil-water interaction analysis at micro-scale

To investigate unsaturated soil-water interaction at micro-scale, this work extends the numerical manifold method (NMM) by incorporating a soil-water coupling model considering specific capillary water distribution and capillary force calculation. The soil skeleton is constructed by a soil skeleton generation algorithm with random polygons. To more realistically capture the interaction between soil grains and capillary water, a capillary mechanics-based geometric algorithm is proposed to iteratively calculate the capillary water distribution. The capillary forces corresponding to the capillary water distribution are calculated based on the Young-Laplace equation. The proposed capillary water solving framework is first verified by reproducing the soil-water characteristic curve and the capillary water distribution of an ideal contact-disk model against analytical solutions. To further validate the ability of the capillary water solving framework to predict hydraulic behavior of the real soil, a laboratory test on the Toyoura sand is reproduced numerically. Then an ideal direct shear test is performed to further validate the two-way soil-water coupling procedure, in which a comparison between the numerical and analytical results regarding the shear strength and matric suction is presented. Finally, microscopic hydraulic and compression tests are conducted on two soil specimens with the same porosity and mean grain diameter but different uniformity coefficients. The results elucidate that the extended method is a potential tool to explore unsaturated soil behaviors at micro-scale.

58 GEOSCIENCES↗

NASA NTRS1995

Tire footprint studies

This presentation covers the results of tire footprint studies conducted in the Landing Gear Development Facility of the USAF Wright Laboratory at the Wright Patterson Air force Base, OH. Tire footprint studies are essential in understanding tire wear mechanisms and computing tire tread wear rates. The power input into the tread is the driving force for tread wear. Variables needed for power input calculations include the footprint pressure and slip velocity distributions. Studies were performed on the effects of power input distributions due to vertical load, camber, yaw, inflation pressure, and tire construction. For the present study, two tire constructions, one radial and the other bias, were selected. These tires were for the F-16 Block 30 fighter aircraft, both of which were previously worn. The present study was limited to steady straight roll with a 14,000 lb vertical load, a 310 psi inflation pressure, and zero yaw and camber. All tests were conducted on the Tire Force Machine (TFM) with a specialized sensor plate with embedded pressure sensors (X, Y, and Z) and slip sensors (X and Y). All tests were conducted for a table speed of 1 in/s. Tests on the TFM show that the power intensity distributions and total power for both tire constructions are quite similar for straight roll. Later on, tests were also conducted on a modified dynamometer which was overlaid with a grit wear surface. The tire speed was maintained at 40 miles per hour and yaw was set to four degrees. Dynamometer tests showed that radial tires have more tread wear than the bias tire; however, in the field, radial tires have longer life.

Chawla, Mangal↗

DOE OSTI2017

Parametric Evaluation of SiC/SiC Composite Cladding with UO 2 Fuel for LWR Applications: Fuel Rod Interactions and Impact of Nonuniform Power Profile in Fuel Rod

SiC/SiC composites are candidates for accident tolerant fuel cladding in light water reactors. In the extreme nuclear reactor environment, SiC-based fuel cladding will be exposed to neutron damage, significant heat flux, and a corrosive environment. Here, to ensure reliable and safe operation of accident tolerant fuel cladding concepts such as SiC-based materials, it is important to assess thermo-mechanical performance under in-reactor conditions including irradiation and realistic temperature distributions. The effect of non-uniform dimensional changes caused by neutron irradiation with spatially varying temperatures, along with the closing of the fuel–cladding gap, on the stress development in the cladding over the course of irradiation were evaluated. The effect of non-uniform circumferential power profile in the fuel rod on the mechanical performance of the cladding is also evaluated. These analyses have been performed using the BISON fuel performance modeling code and the commercial finite element analysis code Abaqus. A constitutive model is constructed and solved numerically to predict the stress distribution in the cladding under normal operating conditions. The dependence of dimensions and thermophysical properties on irradiation dose and temperature has been incorporated into the models. Initial scoping results from parametric analyses provide time varying stress distributions in the cladding as well as the interaction of fuel rod with the cladding under different conditions of initial fuel rod-cladding gap and linear heat rate. It is found that a non-uniform circumferential power profile in the fuel rod may cause significant lateral bowing in the cladding, and motivates further analysis and evaluation.

Accident tolerant fuel↗