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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Emerging Trends in Power System Planning Models

This presentation highlights NREL's power system modeling capabilities, both existing and the future direction of improvements. Specific enhancements to the ReEDS (Regional Energy Deployment System) model and a new electricity market design testbed called EMIS (Electricity Markets and Investment Suite) were described. This content was part of a broader discussion to help inform the National Academies of Sciences, Engineering, and Medicine Committee on the Future of Electric Power in the U.S. on existing power system models and improvements needed in these models to capture the increasing complexity and interconnectedness of the power system.

capacity expansion modeling↗
DOE OSTI2025

Bridging interfacial properties and cell performance: A multiscale model for proton-exchange-membrane fuel cells

Here, to elucidate the impact of local interfaces on mass-transport resistance and overall cell performance of low-loaded proton-exchange-membrane fuel cells (PEMFCs), we present a multiscale modeling framework incorporating a novel modified agglomerate model. The model considers three distinct Pt-electrolyte interfaces: Pt on the carbon surface covered by either ionomer or water film and Pt inside carbon nanopores. Detailed mass-transport voltage-loss breakdowns reveal that coupled agglomerate-interface-scale mass transport dominates the mass-transport loss. The ionomer poisons the exterior-Pt surface through suppressing O 2 adsorption and intrinsic ORR activity, leading to low current-density performance. Conversely, interior-Pt interface enhances the kinetic performance but limits high current-density performance due to its low interfacial permeability. The exterior-Pt/water interface demonstrates superior kinetic performance and mass transport, though its practical implementation requires ensuring proton transport. By coupling the multiscale CL properties with ink parameters, the model identifies an optimal I to C ratio of approximately 0.5, a moderate value where the ionomer content is sufficient to guarantee proton transport without fully covering the Pt surface and forming large agglomeration, thus allowing the utilization of the Pt-water interface and avoiding high mass-transport loss. Overall, the model helps unravel limiting phenomena across different operating regimes and provides routes for optimizing performance.

Cell diagnostic↗
DOE OSTI2021

Time-lapse approach to correct deficiencies of 2D soil zymography

Membrane zymography is commonly used in rhizosphere ecology to map enzyme activities in intact soil samples and plant roots. The method consists of incubating a membrane saturated with an enzyme-specific fluorogenic substrate on the soil/root surface followed by measurements of fluorescence intensity of the product in the membrane. The traditional zymography is based on assumptions that fluorescence on membrane images is linearly increasing with time during zymography and an increase in product content is numerically equal to enzyme activity in soil below the membrane. These assumptions are unlikely to hold in experimental settings. In this work we introduce a new zymography technique, time-lapse zymography (TLZ); the approach that eliminates the need for assumptions of the traditional zymography and provides more realistic estimates of enzymatic activities. We assessed the new technique in a series of laboratory and modeling experiments, including quantification of the fluorescent product diffusion (e.g. MUF: 4-methylumbelliferone) from plant roots, enzyme activity measurements on the roots, and HYDRUS-2D & HP2 software calibration with obtained data. The calibrated model was used to analyze the processes governing spatial and temporal dynamics of MUF contents in the membrane. The results indicated that the enzyme diffusion within the membrane-soil system was negligible, and measured zymograms were adequately reproduced solely by accounting for substrate and product diffusions and for catalytic enzyme reaction described by the Michaelis-Menten equation. TLZ enabled identifying and using linear parts on MUF time series and accounting for MUF losses in each zymogram pixel, considerably improving the accuracy as compared to the traditional method. Results demonstrated that enzymatic activity from only a thin soil layer (~0.2 mm) is adequately represented in zymograms.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Data Science for Weather Impacts on Crop Yield

Private businesses in sectors, such as food, energy, and retail, as well as public sector and federal agencies are interested in the predictive understanding of weather impacts on crop yield, which is an important aspect of food security. Scientific literature has mainly examined how crop yield is impacted by growing season-averaged weather indices. Although a few studies did consider weather extremes in their analysis, their scope was either restricted to measuring their conditional relationship with yield or the extreme event types considered were limited. Selection of regression models, whether the more commonly used linear approaches or nonlinear methods, have not been appropriately justified in this context. Here, we develop data-driven methods to examine two inter-related hypotheses for improved scientific understanding and enhanced predictive modeling. The first hypothesis, that extreme weather indices have a statistically significant information content in them is found to be valid based on linear and nonlinear methods for pairwise dependence. The second hypothesis, examines the value addition of nonlinear regression methods, and suggests that linear approaches may not alone be adequate. The results of this study can inform scientific understanding, generation and relevance of indices and end-to-end risk assessment systems in the context of climate impacts on crop yield. An immediate application may be in the context of NASA Earth Exchange (NEX) which facilitates the generation and dissemination of impacts relevant weather data and indices using a multitude of satellite-derived data sets and model outputs.

Data mining, food security, weather impacts↗
DOE OSTI2024

Impact of Systematic Modeling Uncertainties on Kilonova Property Estimation

The precise atomic structure and therefore the wavelength-dependent opacities of lanthanides are highly uncertain. This uncertainty introduces systematic errors in modeling transients like kilonovae and estimating key properties such as mass, characteristic velocity, and heavy metal content. Here, we quantify how atomic data from across the literature as well as choices of thermalization efficiency of r-process radioactive decay heating impact the light curve and spectra of kilonovae. Specifically, we analyze the spectra of a grid of models produced by the radiative transfer code Sedona that span the expected range of kilonova properties to identify regions with the highest systematic uncertainty. Our findings indicate that differences in atomic data have a substantial impact on estimates of lanthanide mass fraction, spanning approximately 1 order of magnitude for lanthanide-rich ejecta, and demonstrate the difficulty in precisely measuring the lanthanide fraction in lanthanide-poor ejecta. Mass estimates vary typically by 25%–40% for differing atomic data. Similarly, the choice of thermalization efficiency can affect mass estimates by 20%–50%. Observational properties such as color and decay rate are highly model dependent. Velocity estimation, when fitting solely based on the light curve, can have a typical error of ∼100%. Atomic data of light r-process elements can strongly affect blue emission. Even for well-observed events like GW170817, the total lanthanide production estimated using different atomic data sets can vary by a factor of ∼6.

Gravitational wave sources↗
NASA NTRS2009

Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

Smith, Craig↗
NASA NTRS2022

VESIcal: A Critical Approach to Volatile Solubility Modelling Using the Open-Source Engine Vesical

Accurate models of H(2)O and CO(2) solubility in silicate melts are vital for understanding volcanic plumbing systems. These models are used to estimate the depths of magma storage regions from melt inclusion volatile contents, investigate the role of volatile exsolution as a driver of volcanic eruptions, and track the degassing path followed by a magma ascending to the surface. However, despite the large increase in the number of experimental constraints over the last two decades, many recent studies still utilize an earlier generation of models which were calibrated on experimental datasets with restricted compositional ranges. This may be because many of the available tools for more recent models require large numbers of input parameters to be hand-typed (e.g., temperature, concentrations of H(2)O, CO(2), and 8–14 oxides), making them difficult to implement on large datasets. Here, we use a new open-source Python3 tool, VESIcal, to critically evaluate the behaviors and sensitivities of different solubility models for a range of melt compositions. Using literature datasets of andesitic-dacitic experimental products and melt inclusions as case studies, we illustrate the importance of evaluating the calibration dataset of each model. Finally, we highlight the limitations of particular data presentation methods, such as isobar diagrams, and provide suggestions for alternatives, and best practices regarding the presentation and archiving of data. This review will aid the selection of the most applicable solubility model for different melt compositions, and identifies areas where additional experimental constraints on volatile solubility are required.

magma↗
DOE OSTI2023

Assessment of Existing OpenStudio Measures: Reviews, Interviews, and Future Developments

OpenStudio Measure development is continuously in progress and greatly propelled by the collaborative efforts within the building energy modeling community. To ensure the widespread adoption and benefit of OpenStudio Measures, developers must understand the current status of Measure development and the needs of OpenStudio Measure users. The first step involves a comprehensive review of existing content to prevent redundancy and gain insights into how OpenStudio Measures are used in the building energy modeling community. This knowledge can then be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users can be leveraged to shape future Measures. Numerous OpenStudio Measures have been created and shared on the Building Component Library (BCL). The BCL is an open-source repository housing various OpenStudio-related resources, including building component blocks, descriptive metadata, and Measures describing modifications to building energy models. The OpenStudio Measures in BCL encompass a wide range of energy conservation Measures from basic lighting power reduction to complex HVAC model transformation. They also enable users to generate customized reports and facilitate the integration of energy simulation with other analytical processes. This report presents review of 272 currently available OpenStudio Measures in BCL. The OpenStudio Measures were reviewed by category and subcategory. These Measures are summarized by their functionalities and keywords. To gain insights into how OpenStudio Measures are used in building energy modeling community, interviews were conducted. A total of 12 interview responses were collected from 6 individuals in the industry and 6 individuals in academia. The knowledge acquired from reviewing the existing Measures and interview results will be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users will be leveraged to shape future Measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1986

Ionospheric electron content prediction from SERIES/GPS data

Total electron contents along arbitrary lines-of-sight are derived from dual band SERIES P-code data. At present, in a normal observing session, five Global Positioning Satellites (GPS) can be observed for a time interval of 5 h. A SERIES observing session consists of about 300 line-of-sight measurements. Transmitter offsets are different for each satellite and no reliable a priori data can be obtained at present. The electron content and the satellite offsets are estimated simultaneously by a least squares procedure using a simple empirical model. The present accuracy of this technique is estimated to be 6 x 10 to the 16th el/sq m. The results are compared with Faraday rotation measurements. The method may be used for local or global ionospheric content monitoring.

Lanyi, Gabor↗
NASA NTRS2011

In Situ Trace Element Measurements on Roda and the Origin of Diogenites

The origin of diogenites remains poorly understood. A recent model interprets many diogenites to have been formed from melts that were derived by remelting initial magma ocean cumulates, and these penultimate parent melts were then contaminated by melts derived from remelting of the basaltic (eucritic) crust to form the ultimate diogenite parent melts [1] (hereafter the remelting model). This is a very complicated petrogenesis that has profound implications for the geological evolution of 4 Vesta if correct. This model was developed based on trace element analyses of bulk rock samples that had been leached in acids to remove phosphates; the compositions of the residues were interpreted to be close to those of cumulus orthopyroxenes plagioclase, chromite and olivine [1]. In situ measurements of phases in diogenites can be used to test this model. We have begun a campaign of laser ablation ICP-MS of orthopyroxene grains in diogenites for this purpose. Here we report our first results on one diogenite, Roda. We have determined a suite of trace lithophile elements on nine, mm-sized pyroxene grains separated from Roda that have previously been studied [2, 3]. A key observation supporting the remelting model is the very low Eu/Eu* of leached residues; values too low to represent orthopyroxene that crystallized from melts with chondritic Sm/Eu and Gd/Eu [1]. (Eu* = Eu interpolated from REE diagrams.) Crustal remelts have low Sm/Eu and Gd/Eu, and orthopyroxenes that crystallized from parent melts contaminated by them would have very low Eu/Eu* [1]. Roda grains have Eu/Eu* of 0.243 to 0.026; the latter a value lower than any measured on bulk diogenite leached residues (0.041) [1]. There is a general negative correlation between Eu/Eu* and some incompatible elements (Zr, Nb, Hf), but not others (LREE). This appears inconsistent with the remelting model as it would suggest an evolving parent melt with La de-creasing as Zr increased and Eu/Eu* decreased. Grain R-15 includes trace-element-rich trapped melt phases [2, 3]. This grain has the highest Eu/Eu* and LREE contents, indicating that the trapped melt had a high Eu/Eu*. Thus, our first data on one diogenite do not provide support for the remelting model [1]. Roda is unusual in that its orthopyroxene grains show wide ranges in trace element contents [4]. Previous in situ REE analyses of grain R-15 did not reveal evidence for subsolidus equilibration with trace-element-rich trapped melt phases, and led to the suggestion that Roda may be polymict, with different grains representing different lithologies of diverse compositions [3]. Thus, based on our results on Roda, it is perhaps premature to abandon the remelting model. In situ measurements on a suite of diogenites is planned to further address this issue.

Mittlefehldt, David W.↗
DOE OSTI2021

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

The viscosity of magmatic silicate liquids: A model for calculation

A simple model has been designed to allow reasonably accurate calculations of viscosity as a function of temperature and composition. The problem of predicting viscosities of anhydrous silicate liquids has been investigated since such viscosity numbers are applicable to many extrusive melts and to nearly dry magmatic liquids in general. The fluidizing action of water dissolved in silicate melts is well recognized and it is now possible to predict the effect of water content on viscosity in a semiquantitative way. Water was not incorporated directly into the model. Viscosities of anhydrous compositions were calculated, and, where necessary, the effect of added water and estimated. The model can be easily modified to incorporate the effect of water whenever sufficient additional data are accumulated.

Bottinga, Y.↗
DOE OSTI2022

Using Chemical Reactor Models to Predict Fluidized Bed Pyrolysis Yields of Biomass Feedstocks

A detailed biomass pyrolysis kinetics scheme is implemented in reduced-order reactor models to predict chemical species yields from a fluidized bed reactor. The biomass composition in terms of cellulose, hemicellulose, lignins, and extractives are determined for several biomass feedstocks. Model results are compared to yields measured from a two-inch diameter bench-scale fluidized bed reactor operating at fast pyrolysis conditions. The reduced-order chemical reactor models compare favorably with the experimental measurements and capture trends in product yields due to biomass compositional effects such as high ash content. This work offers a computationally inexpensive approach to predict the quality of biomass pyrolysis products in a timely manner. Source code for the reactor models along with a biomass composition web tool are made available online for future scientific research efforts.

09 BIOMASS FUELS↗
DOE OSTI2022

Optimal Control of Biomass Feedstock Processing System Under Uncertainty in Biomass Quality

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput.

09 BIOMASS FUELS↗
DOE OSTI2024

Coupled neutronics, thermochemistry, corrosion modeling and sensitivity analyses for isotopic evolution in molten salt reactors

This study presents a computational methodology for analyzing isotopic evolution and associated uncertainties in molten salt reactors (MSRs), focusing on both fluoride- and chloride-based fuel salts. The primary goal is to enhance the understanding of isotopic behavior in MSRs and provide data to support future experimental efforts. The methodology integrates transport-coupled depletion calculations using OpenMC, equilibrium thermodynamics modeling with Thermochimica, and a corrosion model. Sensitivity analyses are performed to evaluate the impact of power density, air ingress, and humidity content on isotopic evolution in MSR concepts. This study examines representative F- and Cl-based MSR designs, highlighting the dominant influence of power density on isotopic composition, which significantly affects isotope production and depletion rates, accounting for approximately 76% of the observed variance in element concentration. Air ingress and humidity content also affect the redox potential, solubility of heavier elements, and corrosion rates, thereby altering the expected isotopic evolution in the reactor. On average, air ingress accounts for around 17% of the variance in element concentrations, while humidity explains the remaining 7%. These variances differ significantly from element to element, depending on the element’s role in depletion, redox potential evolution, and galvanic corrosion. The findings indicate that power density, air ingress, and humidity content are all critical factors for optimizing reactor design and operational strategies. Furthermore, the study provides expected ranges for key impurities in the fuel salt, which are crucial for guiding future experimental studies and refining MSR designs. Finally, this study demonstrates the importance of modeling depletion coupled with the evolution of redox potential and chemical interactions in MSR fuel salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2005

Evidence for Harmonic Content and Frequency Evolution of Oscillations During the Rising Phase of X-ray Bursts From 4U 1636-536

We report on a study of the evolution of burst oscillation properties during the rising phase of X-ray bursts from 4U 1636-536 observed with the proportional counter array (PCA) on board the Rossi X-Ray Timing Explorer (RXTE) . We present evidence for significant harmonic structure of burst oscillation pulses during the early rising phases of bursts. This is the first such detection in burst rise oscillations, and is very important for constraining neutron star structure parameters and the equation of state models of matter at the core of a neutron star. The detection of harmonic content only during the initial portions of the burst rise is consistent with the theoretical expectation that with time the thermonuclear burning region becomes larger, and hence the fundamental and harmonic amplitudes both diminish. We also find, for the first time from this source, strong evidence of oscillation frequency increase during the burst rise. The timing behavior of harmonic content, amplitude, and frequency of burst rise oscillations may be important in understanding the spreading of thermonuclear flames under the extreme physical conditions on neutron star surfaces.

Bgattacharyya, Sudip↗
NASA NTRS2023

An Investigation into the Effect of Liquid Accumulation on Thermo-Physiologic State using an Advanced Moisture Model Coupled with a High Resolution Human Thermal Model

A physics-based mathematical model for simulating heat and moisture transport on the skin and within clothing was developed to improve the accuracy of human thermal modeling predictions. In a previous study, a set of sweating hotplate experiments was specifically created to obtain test data for model validation. The clothing moisture model was subsequently coupled with a human thermal model and tested by simulating human experiments described in the open literature, which served to verify the model’s ability to predict whole body thermo-physiologic state in work-rest cycles during which sweating was known to occur. In this study, a human subject test was specifically designed to validate the model’s ability to predict local and whole body sweat evaporation and accumulation on the surface of the body. The human subject test incorporated twelve clothed male subjects of moderate physical fitness, ages 18-30, which were prescribed a work-rest cycle in a climate-controlled chamber (25 °C, 50% RH). Two activity levels were considered during the active stage (4 MET vs. 6.5 MET), and two sets of ending ambient conditions were considered for the final rest stage (25 °C vs. 15 °C, 50% RH). Model predictions were compared to the measured local skin temperatures, core temperatures, and whole body sweat losses. In general, the model was able to reproduce the trends observed in the human subject trial, but more importantly, provided insight into how dynamic changes in liquid content can impact the evolution of local and whole body thermo-physiologic state. This study demonstrates the ability of an advanced moisture model to capture distinct physics attributable to moisture accumulation, allowing for increased accuracy in predicting human thermal state and for interpreting the results of measurements derived from human subject tests.

human thermal model↗
DOE OSTI2026

Anisotropic Melt Inclusions as a Confounding Signal for Ice‐Penetrating Radar Observations

Ice-penetrating radar is a powerful geophysical tool for understanding the subsurfaces of Earth, Mars, and icy moons. Radar reflectivity, attenuation, and birefringence are used to infer subsurface hydrology, englacial temperature, water content, and crystal orientation fabric. However, conventional radar sounding analyses either ignore melt or use classical mixing models which assume spherical melt inclusions, obscuring anisotropic contributions of melt. Here, we use geometric mixing models to calculate the reflectivity, attenuation, and birefringence of temperate ice containing anisotropic melt. We find that anisotropic melt can introduce significant deviations in radar measurements. For instance, melt anisotropy may impact reflectivity-based estimates of water content by up to 30% volume fraction, while attenuation-based estimates may vary by up to 43%. Critically, a melt volume fraction of just $f$ ~ 10 -5 can reproduce birefringence signals previously attributed to ice fabric. We conclude that melt anisotropy may significantly impact analyses of englacial hydrology, subglacial hydrology, and ice fabric.

58 GEOSCIENCES↗