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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Characterization of Gamma-Ray Imagers Using GADRAS

This document describes how gamma-ray imagers are characterized using the Gamma Detector Response and Analysis Software (GADRAS). The initial step of the characterization process entails definition of detector dimensions and estimation of a few parameters that are specific to gamma-ray imagers. Energy calibration and resolution parameters are then adjusted based on comparison between computed spectra and measurements for several calibration source. These steps are analogous to the way non-imaging spectrometers are characterized. The parameters are then refined by an empirical process to achieved good agreement between measured and computed spectra as functions of gamma-ray energy and angular group.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improved Models of R Coronae Borealis Stars

We present an improved numerical method to model subsolar He+CO-WD merger progenitors of R Corona Borealis stars that builds on our previous work. These improvements include a smooth entropy transition from the core to the envelope of the post-merger, inclusion of single-zone nucleosynthesis to mimic the effects of burning during the merger event, and post-processing the models with a larger nuclear network for analysis of s-process nucleosynthesis. We perform a parameter study to understand the effects of the entropy transition, peak temperature, and overshooting on our models. The models that best agree with observations of R Corona Borealis stars are processed with a much larger nuclear network to investigate s-process nucleosynthesis and the dredge-up of s-process products into the outer envelope in detail. We present a model with a significant enhancement in s-process elements, which also agrees with observed surface abundances and isotopic ratios of 16 O/ 16 O and C/O between 1 and 10. Finally, we find that the neutron exposure and initial neutron densities this model requires to obtain such an enhancement are much more consistent with i-process nucleosynthesis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Subsurface Seismic Structure Around the Sanford Underground Research Facility

To address the fundamental challenges of understanding processes associated with enhanced or engineered geothermal systems (EGS), teams from the EGS Collab SIGMA-V project are conducting stimulations at the Sanford Underground Research Facility. Various modalities of geophysical observations are collected and analyzed, and different types of parameters are modeled to help investigate these critical processes. Among these parameters, the three-dimensional stress field is one of the primary objectives. Seismic velocity models have been used to estimate the 3D stress field for other regions. A detailed seismic velocities and density model can help us infer spatial variations of the stress field in the study area. We inverted the 3D seismic structure around the site by using body-wave travel times, surface-wave dispersions and gravity observations simultaneously. The resulting model will be a starting point for more detailed investigations and could also be used to study subsurface geological and stress field variations of the broad area.

Chai, Chengping↗
DOE OSTI2019

Subsurface Seismic Structure Around the Sanford Underground Research Facility

To address the fundamental challenges of understanding processes associated with enhanced or engineered geothermal systems (EGS), teams from the EGS Collab SIGMA-V project are conducting stimulations at the Sanford Underground Research Facility. Various modalities of geophysical observations are collected and analyzed, and different types of parameters are modeled to help investigate these critical processes. Among these parameters, the three-dimensional stress field is one of the primary objectives. Seismic velocity models have been used to estimate the 3D stress field for other regions. A detailed seismic velocities and density model can help us infer spatial variations of the stress field in the study area. We inverted the 3D seismic structure around the site by using body-wave travel times, surface-wave dispersions and gravity observations simultaneously. The resulting model will be a starting point for more detailed investigations and could also be used to study subsurface geological and stress field variations of the broad area.

Chai, Chengping↗
DOE OSTI2025

Numerical design considerations for vapor transport deposition of metal-halide perovskite thin films

While metal-halide perovskites (MHPs) offer high efficiency and potential application in single junction and tandem solar cells, challenges remain in translating solution-based methods to commercial-scale production. Vapor transport deposition (VTD) offers advantages such as precise control over film composition and purity, as well as the possibility of achieving high thin film deposition rates for scale-up. In this work, a numerical model is developed to simulate the deposition process, analyzing the impact of parameters including source material temperature, carrier gas and dilution gas flow rates, and chamber pressure to optimize deposition rates and film uniformity. Geometrical parameters, such as throw distance, are also found to significantly affect rate and uniformity. Furthermore, the modeling results presented here offer valuable insight for improving the scalability of VTD for the processing of metal-halide perovskites.

Chemical vapor deposition↗
DOE OSTI2023

Bias-pulsed atomic layer etching of 4H-silicon carbide producing subangstrom surface roughness

A new approach to atomic layer etching (ALE) has been demonstrated, and its application to 4H-SiC is reported here. By pulsing only the DC bias for an Ar/Cl2 inductively coupled plasma-reactive ion etching system, the etch cycle duration is reduced by more than an order of magnitude relative to conventional ALE processes. Gas flows are not changed throughout the ALE process. With this process protocol, we achieved an etch rate of 2.48±0.09 Å/cycle with 6 s cycles, an RMS surface roughness (Rq) of 0.83±0.08 Å, and an ALE synergy value of S = 99%. The parameters explored within this ALE process demonstrate effective subangstrom smoothening of 4H-SiC surfaces and is well-suited for a variety of classical and quantum device nanofabrication.

42 ENGINEERING↗
DOE OSTI2021

Igniting Weak Interactions in Neutron Star Postmerger Accretion Disks

The merger of two neutron stars or a neutron star and a black hole typically results in the formation of a postmerger accretion disk. Outflows from disks may dominate the overall ejecta from mergers and be a major source of r-process nuclei in our universe. We explore the parameter space of such disks and their outflows and r-process yields by performing 3D general-relativistic magnetohydrodynamic simulations with weak interactions and approximate neutrino transport. We discuss the mapping between the initial binary parameters and the parameter space of the resulting disks, chiefly characterized by their initial accretion rate. We demonstrate the existence of an ignition threshold for weak interactions at around ~10 -3 M⊙ s -1 for typical parameters by means of analytic calculations and numerical simulations. We find a degenerate, self-regulated, neutrino-cooled regime above the threshold and an advection-dominated regime below the threshold. Excess heating in the absence of neutrino cooling below the threshold leads to ≳60% of the initial disk mass being ejected in outflows, with typical velocities of ~(0.1–0.2)c, compared to ≲40% at ~(0.1–0.15)c above the threshold. While disks below the threshold show suppressed production of light r-process elements, disks above the threshold can produce the entire range of r-process elements, in good agreement with the observed solar system abundances. Disks below the ignition threshold may produce an overabundance of actinides seen in actinide-boost stars. As gravitational-wave detectors start to sample the neutron star merger parameter space, different disk realizations may be observable via their associated kilonova emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A High-Fidelity Molecular Model of the Cu(111) Repeating Unit

Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Experimental analysis of convective drying of paper and board

Conventional multi-cylinder drying of paper and board involves a mixture of conductive drying from steam-heated dryer cylinders and convective drying by the flow of heated air over the surface of the paper web in the pockets. Pocket ventilation is a critical component in assisting heat and mass transfer during the drying process but is the primary contributor towards removing evaporated water from the web. Air temperature, velocity, and humidity are critical parameters involved in the convective drying process. This paper covers an experimental study involving the design and development of a small lab-scale setup for convective drying of various grades of paper and board, monitoring multiple parameters like paper temperature, moisture content, air humidity, temperature, and velocity measured in situ as the drying proceeds with continuous and accurate sampling capabilities for all parameters in the sample and the system. Instantaneous drying rates, heat, and mass transfer coefficients were also deduced for every time step till the paper completely dried. Furthermore, the coefficients obtained were also reported in the form of dimensionless correlations, and the results were compared against traditional correlations used in the modelling of paper drying. Furthermore, this data will be useful in process development, modelling, design, and the paper drying process simulation.

42 ENGINEERING↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2025

Impact of U-10Mo HALEU Fuel Element Tolerances on the Massachusetts Institute of Technology Reactor safety and operational performance – Neutronics

The U.S. is coordinating efforts for the conversion of six U.S. high performance research reactors (USHPRR), including one critical assembly from highly enriched uranium (HEU) to low-enriched uranium (LEU). In order to continue the mission of these reactors, including the Massachusetts Institute of Technology Reactor (MITR), and achieve similar performance, high assay low-enriched uranium (HALEU) with a high-density metallic alloy of uranium with 10 wt% molybdenum (U-10Mo) is being considered. Following the preliminary design of the proposed MITR LEU fuel elements using the U-10Mo monolithic alloy, the impact of the fabrication specification was assessed. This work focuses on the analysis of select neutronics characteristics of the MITR LEU core as a function of the variation of the relevant fuel specification parameters (e.g., U-10Mo composition, fuel plate thickness, etc.). A separate article submitted to this journal addresses the impact on the thermal hydraulic performance. The analyses in these works are performed based on an all-LEU conversion management plan identified in previous work, in which only the proposed elements are utilized for achieving the conversion of MITR. The variations of two main neutronics characteristics are assessed as a function of the variability of the specification parameters resulting from the fabrication process: the MITR LEU core reactivity and the fuel cycle length. The main findings of this work show that the MITR core can meet the operational requirements during the LEU transition plan under the limiting fabrication parameter combinations considered. In addition, the analyses show that the dependency of the core neutronics characteristics on the specification parameters is highly linear within the specification tolerances. The rates of variation are reported in detail for each parameter and can serve as a powerful tool for future MITR fuel management in cases such as when HALEU supply is established that may allow additional cycle length or other operational benefits.

Conversion↗
DOE OSTI2018

Survey of DAKOTA's V&V Capabilities in the Simulation of Residual Stresses in a Simple Composite Structure

Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses can result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, a process modeling methodology was developed and implemented into Sandia National Laboratories' SIERRA/SolidMechanics code. This method can be used to predict the process-induced stresses in any composite structure, regardless of material composition or geometric complexity. However, to develop confidence in these predictions, they must be rigorously validated. Specifically, sensitivity studies should be completed to define which model parameters are critical to the residual stress predictions. Then, the uncertainty associated with those critical parameters should be quantified and processed through the model to develop stress-state predictions encompassing the most important sources of physical variability. Numerous sensitivity analysis and uncertainty quantification methods exist, each offering specific strengths and weaknesses. Therefore, the objective of this study is to compare the performance of several accepted sensitivity analysis and uncertainty quantification methods during the manufacturing process simulation of a composite structure. The examined methods include simple sampling techniques as well as more sophisticated surrogate approaches. The computational costs are assessed for each of the examined methods, and the results of the study indicate that the surrogate approaches are the most computationally efficient validation methods and are ideal for future residual stress investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Numerical parameter optimizations of the Ignition and Growth model for a HMX plastic bonded explosive

We present here a novel method for optimizing parameters of the Ignition and Growth (I&G) reactive flow model for high explosives. The I&G model predicts the shock initiation response of explosives subjected to dynamic loading. However, calibrating the model is a time-consuming process because it has several parameters, typically requires multiple data sets, and there are no direct correlations between parameters and data. In this study, we couple a scalable optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop four I&G model parameter sets for the HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane)-based explosive LX-07 [90 wt. % HMX, 10 wt. % Viton A] based on minimizing the difference between calculations and measurements at the embedded pressure gauges in 1D gun shock experiments. Our study shows that a cost function based on both shock time of arrival and pressure pulse shape demonstrates the best agreement with experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗
DOE OSTI2024

Parameter identification methods for low-order gray box building energy models: A critical review

The body of knowledge on gray box building energy modeling (GBBEM) has been developed over the past few decades and has undergone some important changes recently. Starting with simple methods and simple buildings, the science of GBBEM has grown to encompass complex and more computationally intensive techniques and complex commercial buildings. Numerous works including a recent review have considered model structure and inputs in a nearly systematic way, but no extant work systematically reviews the approaches for GBBEM parameter search initialization and final identification, despite this being arguably the most difficult and impactful part of the modeling process. To this end, we critically review 55 extant works describing advantages, limitations, and domain of applicability of several classes of parameter initialization and optimization techniques specifically for GBBEM. We categorize the classes of methods and analyze the evidence of their applicability for different applications within the field of GBBEM. We find an emerging consensus that initialization of parameter searches for anything other than the simplest building elements is often challenging and sometimes requires a stochastic approach to begin the parameter identification process. After this initial process, faster methods have been used in some cases but often the nature of the problem requires stochastic methods for this portion of the process as well. For less complex systems, more deterministic and efficient methods have been shown to be effective. Finally, we draw conclusions as to the domain of applicability of different classes of initialization and optimization techniques for GBBEEM and offer suggestions for research directions that are likely to prove fruitful.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Five percent measurement of the gravitational constant in the Large Magellanic Cloud

We perform a novel test of General Relativity by measuring the gravitational constant in the Large Magellanic Cloud (LMC). The LMC contains six well-studied Cepheid variable stars in detached eclipsing binaries. Radial velocity and photometric observations enable a complete orbital solution, and precise measurements of the Cepheids’ periods permit detailed stellar modelling. Both are sensitive to the strength of gravity, the former via Kepler’s third law and the latter through the gravitational free-fall time. We jointly fit the observables for stellar parameters and the gravitational constant. Performing a full Markov Chain Monte Carlo analysis of the parameter space including all relevant nuisance parameters, we constrain the gravitational constant in the Large Magellanic Cloud relative to the Solar System to be G LMC /G SS = $0.93{^{+0.05}_{-0.04}}$. We discuss the implications of this 5% measurement of Newton’s constant in another galaxy for dark energy and modified gravity theories. This result excludes one Cepheid, CEP-1812, which is an outlier and needs further study: it is either a highly unusual system to which our model does not apply, or it prefers G LMC < G SS at 2.6σ. We also obtain new bounds on critical parameters that appear in semi-analytic descriptions of stellar processes. In particular, we measure the mixing length parameter to be $α = 0.90{^{+0.36}_{-0.26}}$ (when assumed to be constant across our sample), and obtain constraints on the parameters describing turbulent dissipation and convective flux.

79 ASTRONOMY AND ASTROPHYSICS↗