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Results for “Effective temperature model”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Analysis of ultrafast magnetization switching dynamics in exchange-coupled ferromagnet–ferrimagnet heterostructures

Magnetization switching in ferromagnets has so far been limited to the current-induced spin–orbit–torque effects. Recent observation of helicity-independent all-optical magnetization switching (HI-AOS) in an exchange-coupled ferromagnet–ferrimagnet (FM-FEM) heterostructures expanded the range and applicability of such ultrafast heat-driven magnetization switching. Here we report the element-resolved HI-AOS dynamics of such an exchange-coupled system, using a modified microscopic three-temperature model. We have studied the effect of (i) the Curie temperature of the FM, (ii) FEM composition, (iii) the long-range Ruderman–Kittel–Kasuya–Yosida (RKKY) exchange-coupling strength, and (iv) the absorbed optical energy on the element-specific time-resolved magnetization dynamics. The phase-space of magnetization illustrates how the RKKY coupling strength and the absorbed optical energy influence the switching time. Our analysis demonstrates that the threshold switching energy depends on the composition of the FEM and the switching time depends on the Curie temperature of the FM as well as RKKY coupling strength. Importantly, this simulation anticipates new insights into developing faster and more energy-efficient spintronics devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗
DOE OSTI2023

Proxy quality control of biomass particles using thermogravimetric analysis and Gaussian process regression models

Abstract The temperature experienced by reactants during preparation in a reactor is a key component in determining the yield and homogeneity of usable chemical products such as biomass particles. Thermocouples with sensors can be used to monitor spatial temperature gradients within reactors but these sensors are often too expensive and/or invasive. The present work proposes a strategy to identify optimal machine learning models to infer the maximum effective temperature experienced by particles during oxidative biomass torrefaction using key thermochemical combustion parameters. The maximum rate of weight loss, the corresponding temperature, and fixed carbon content on a dry‐ash‐free basis are used as literature‐based predictor variables obtained from thermogravimetric analysis. The evaluation of 24 machine‐learning models using the standard tenfold cross‐validation method suggests that the exponential Gaussian process regression (GPR) model is the most effective, followed by other GPR models. These high‐performing GPR models were also utilized to predict the effective preparation temperature distribution of reactor‐produced biomass particles under eight conditions of varying residence time and air‐to‐biomass ratio. The effective preparation temperature and residence time of individual biomass particles were then encoded into the torrefaction severity factor and used to estimate the energy yield of the reactor output as a novel quality control method. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2022

Effect of microstructure and temperature on nuclear graphite oxidation using the 3D Random Pore Model

This work compared the 3D Random Pore Model (3D-RPM) with experimental and characterization data to systematically study the effect of nuclear graphite microstructure and air oxidation temperature. It is well known that oxidation-induced weight loss at elevated temperatures degrades graphite structure and properties; however, a fundamental understanding of the role of graphite microstructure is still unclear. In this work, three diverse grades of nuclear graphite—IG-110, NBG-18, and PCEA—were examined and tested at air oxidation temperatures of 600, 650, 700, and 750 °C following ASTM D7542. Here, the 3D-RPM reproduced the microstructure and temperature dependence of mass loss curves for these grades. For the first time, measurements and modeling were combined to show how bulk density and the amount and spatial distribution of open and closed porosity affects oxidation. IG-110 was less dense and had an open pore network that is finer and more uniformly spread, and showed fastest oxidation. PCEA porosity was less uniform and showed less oxidation, while NBG-18 was more dense, had the least fine and uniform porosity, and showed the slowest oxidation. In general, oxidation proceeds faster if open porosity is more uniformly distributed and can incrementally access closed pore surface area with more ease.

36 MATERIALS SCIENCE↗
DOE OSTI2026

3D probabilistic fracture mechanics / computational fluid dynamics simulation of a reactor pressure vessel under transient conditions

Reactor pressure vessels (RPVs) are safety-critical light-water-reactor components that, under irradiation, experience long-term material degradation in the form of embrittlement. This can increase their susceptibility to fracture under thermal-shock conditions, which could occur during off-normal transients such as loss-of-coolant accidents (LOCAs). During a LOCA, the most severe conditions for the RPV occur when emergency core cooling water is injected through the cold legs into the water-and-steam-filled RPV. The rapid cooling of the downcomer and internal RPV surface causes decreased temperature and elevated thermally driven tensile stresses in the RPV wall. This, combined with long-term material embrittlement, may cause fracture initiation at pre-existing flaws, challenging the integrity of the RPV. Assessing RPV integrity during transients with a large spatial variation in the coolant temperature requires a modeling approach that considers the effects of spatially varying coolant temperature on the fracture probability of a population of flaws distributed throughout the RPV, accounting for spatially varying embrittlement. Here, the present study addresses this need by demonstrating first-of-its-kind coupling of a high-fidelity 3D computational fluid dynamics code with 3D probabilistic fracture mechanics This was accomplished using representative models of a pressurized-water reactor subjected to small- and medium-break LOCA conditions, both of which can result in large spatial temperature variations. While the observed impact of accounting for 3D effects was minimal under the small-break LOCA this study indicates a significant increase in the probability of fracture initiation under the medium-break LOCA when 3D effects are considered, relative to a spatially uniform cooling scenario.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Temperature and dose effects on dislocation loops in self-ion irradiated high-purity iron

Body-centered cubic (BCC) Fe-based alloys are promising candidate materials for advanced nuclear reactors. However, a detailed understanding of irradiation induced dislocation loop microstructure development remains unresolved. It is a widespread belief that 〈001〉 loops become increasingly favorable over ½〈111〉 loops as irradiation temperature rises above ∼300 C. Unfortunately, the temperature effects on 〈001〉 loop have been primarily examined in in-situ irradiation on TEM thin foils but poorly explored on bulk Fe due to exceedingly limited experimental studies on bulk specimens, raising concerns about the potential influence of TEM thin foil artifacts on observed results. Here, in this study, we conducted experiments on ultra-high purity BCC Fe specimens irradiated with 6.7–8 MeV Fe ions over a wide temperature range on bulk samples. We investigated the effects of temperature (T irr = 250–500 °C), dose rate (10⁻⁵ to 10⁻³ dpa/s), and dose (0.35 to 3.5 dpa) on the formation and evolution of 〈001〉 and ½〈111〉 loops as well as cavity (void) formation. Post-irradiation Burgers vector analysis via g•b method on dislocation segments and loops revealed that 〈001〉 loop fraction does not show a monotonic positive correlation with irradiation temperature. Combined with previous and current theoretical as well as experimental findings, we explore the temperature effects on all existing models of 〈001〉 loop formation. We conclude that the prevailing reports regarding the dominance of 〈001〉 loops in Fe at elevated temperatures are mainly attributable to the loss of glissile ½〈111〉 clusters in TEM thin foil experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Greater vulnerability of snowmelt-fed river thermal regimes to a warming climate

While the advective flux from cool melt runoff can be a significant source of thermal energy to mountainous rivers, it has been a much less addressed process in river temperature modeling and thus our understanding is limited with respect to the spatiotemporal effect of melt on river temperatures at the watershed scale. In particular, the extent and magnitude of the melt cooling effect in the context of a warming climate are not yet well understood. To address this knowledge gap, we improved a coupled hydrology and stream temperature modeling system, Distributed Hydrology Soil Vegetation Model and River Basin Model (DHSVM-RBM), to account for the thermal effect of cool snowmelt runoff on river temperatures. The model was applied to a snow-fed river basin in the Pacific Northwest to evaluate the responses of snow, hydrology, stream temperatures, and potential fish growth to future climates. Historical simulations suggest that snowmelt can notably reduce the basin-wide peak summer temperatures particularly at high-elevation tributaries, while the thermal impacts of melt water can persist through the summer along the mainstem. Ensemble climate projections suggested that a warming climate will decrease basin mean peak snow and summer streamflow by 92% and 60% by the end of the century. Due to the compounded influences of warmer temperatures, lower flows and diminished cooling from melt, rivers reaches in high elevation snow-dominated areas were projected to be most vulnerable to future climate change, showing the largest increases in summer peak temperatures. As a result, thermal habitat used by anadromous Pacific salmon was projected to exhibit substantially lower growth potential during summer in future. These results have demonstrated the necessity of accounting for snowmelt influence on stream temperature modeling in mountainous watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ultra-High Temperature Thermal Conductivity Measurements of a Reactive Magnesium Manganese Oxide Porous Bed Using a Transient Hot Wire Method

Pelletized magnesium manganese oxide shows promise for high temperature thermochemical energy storage. It can be thermally reduced in the temperature range between 1250 °C and 1500 °C and re-oxidized with air at typical gas-turbine inlet pressures (1–25 bar) in the temperature range between 600 °C and 1500 °C. The combined thermal and chemical volumetric energy density is approximately 2300 MJ/m3. The rate at which a thermochemical storage module can be charged is limited by heat transfer inside the solid packed bed. Hence, the effective thermal conductivity of packed beds of magnesium-manganese oxide pellets is a crucial parameter for engineering Mg-Mn-O redox storage devices. We have measured the effective thermal conductivity of a packed bed of 3.66 ± 0.516 mm sized magnesium manganese oxide (Mn to Mg molar ratio of 1:1) pellets in the temperature range of 300–1400 °C. Since the material is electrically conductive at temperatures above 600 °C, the sheathed transient hot wire method is used for measurements. Raw data is analyzed using the Blackwell solution to extract the bed thermal conductivity. The effective thermal conductivity standard deviation is less than 10% for a minimum of three repeat measurements at each temperature. Experimental results show an increase in the effective thermal conductivity with temperature from 0.50 W/m °C around 300 °C to 1.81 W/m °C close to 1400 °C. We propose a dual porosity model to express the effective thermal conductivity as a function of temperature. This model also considers the effect of radiation within the bed, as this is the dominant heat transfer mode at high temperatures. The proposed model accounts for microscale pellet porosity, macroscale bed porosity, pellet size, solid thermal conductivity (phonon transport), and radiation (photon transport). The coefficient of determination between the proposed model and the experimental results is greater than 0.90.

Engineering↗
DOE OSTI2025

HD 143811 AB b: A Directly Imaged Planet Orbiting a Spectroscopic Binary in Sco-Cen

We present confirmation of HD 143811 AB b, a substellar companion to spectroscopic binary HD 143811 AB through direct imaging with the Gemini Planet Imager (GPI) and Keck NIRC2. HD 143811 AB was observed as a part of the GPI Exoplanet Survey in 2016 and 2019 and is a member of the Sco-Cen star formation region. The exoplanet is detected ∼430 mas from the host star by GPI. With two GPI epochs and one from Keck/NIRC2 in 2022, we confirm through common proper motion analysis that the object is bound to its host star. We derive an orbit with a semimajor axis of $64^{+32}_{-14}$ au and eccentricity $0.23^{+0.24}_{-0.16}$. Spectral analysis of the GPI H-band spectrum and NIRC2 L′ photometry provides additional proof that this object is a substellar companion. We compare the spectrum of HD 143811 AB b to PHOENIX stellar models and Exo-Radioactive-Convective Equilibrium Model (REM) exoplanet atmosphere models and find that Exo-REM models provide the best fits to the data. From the Exo-REM models, we derive an effective temperature of $1042^{+178}_{-132}$ K for the planet and translate the derived luminosity of the planet to a mass of 5.6 ± 1.1 M Jup assuming hot-start evolutionary models. HD 143811 AB b is the first directly imaged planet around a binary that is not on an ultrawide orbit. Future characterization of this object will shed light on the formation of planets around binary star systems.

Astronomy and AstroPhysics↗
DOE OSTI2025

Electron cyclotron emission measurements and modeling in optically semi-transparent plasma on the HSX stellarator

On the Helically Symmetric Experiment (HSX), electron cyclotron emission (ECE) at the second harmonic of the electron gyrofrequency is measured with a 16-channel heterodyne receiver. An ECE radiometer diagnostic has been calibrated with a broadband frequency source, allowing independent measurements of the electron temperature. The antenna pattern has a significant impact on the measurements, and modeling its effect is necessary to produce an ECE radiation temperature spectrum. Measurements, calibration results, and modeling of the ECE data are presented in this paper. At a relatively high plasma density, HSX plasmas are thermal, and the radiation temperature measured by the radiometer is in good agreement with the electron temperature measured by a Thomson scattering diagnostic. At a relatively low plasma density, the deviation from a Maxwellian distribution is large, and asymmetry in the radiation temperature profile is measured. These measurements are supported by single-pass and multi-pass ray tracing calculations of the electron cyclotron emission using the TRAVIS ray tracing code. Thermal and nonthermal electron populations exist in HSX, and the effect of these populations on the asymmetry in the measured emission is presented.

Cyclotron radiation↗
DOE OSTI2021

Improve the Search of Very Metal-poor Stars Using the Deep Learning Method

Very metal-poor (VMP) stars have [Fe/H] < -2.0 dex. They are among the oldest stars in the universe, and their unique metallicity can help explore the enrichment mechanism and evolutionary history of the chemical elements of stars in the early universe. However, most current stellar parameter estimation methods do not perform well in determining the stellar parameters of VMP stars, which limits our ability to discover and exploit the properties of VMP stars. In this study, we propose a new model based on a convolutional neural network to determine the stellar atmospheric parameters of VMP stars. We tested our model on the LAMOST spectra; our model can determine the effective temperature (T {sub eff}), surface gravity (log g), metallicity ([Fe/H]), and carbon abundance ([C/Fe]) of the LAMOST spectra with precisions σ(T {sub eff}) = 134.82 K, σ(log g) = 0.33 dex, σ ([Fe/H]) = 0.20 dex, and σ([C/Fe]) = 0.35 dex. Furthermore, our model can distinguish VMP stars from normal stars with an accuracy of 88.65%. We also compared this model with other widely used methods, and found that this method performs better than other methods. It can be applied to the stellar parameter pipelines of upcoming large surveys such as 4MOST, WEAVES, and MOONS to search for VMP stars and identify carbon-enhanced metal-poor stars.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A theoretical calculation of stacking fault energy of Ni alloys: The effects of temperature and composition

Combining cluster expansion (CE) method with one dimensional axial Ising model, this work investigated the effects of alloying elements and configurational variations due to temperature on the stacking fault energy (SFE) of FCC Ni binary alloys. Ensembles of large numbers of atomistic structures, each with more than ~400 atoms, were generated to consider sufficient long-range chemical disorder and temperature effects due to configurational entropy. Here, a Monte Carlo Metropolis algorithm was used to generate these structures, whose energies were then evaluated based on the effective cluster interactions obtained from CE. As a baseline, this work had shown the SFE of pure Ni and Al to be 127 mJ/m 2 and 137 mJ/m 2 , respectively, which agreed with the experimental values of 125 mJ/m 2 and 150 mJ/m 2 reported in the literature. Additions of Al, Ti, Cr and Co to pure Ni were found to decrease the SFE to different extents. Although temperature does not strongly influence the SFE of the FCC Ni-Al and Ni-Cr binary alloys, it can lead to significant changes to the SFE of the FCC Ni-Ti and Ni-Co alloys. While effects of temperature and composition on SFE observed in this work were calculated from binary Ni alloys, the general trends are nonetheless expected to be valid in the γ phase of multicomponent Ni superalloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The effects of stress, temperature and facet structure on growth of { 10 1 &#xAF; 2 } twins in Mg: a molecular dynamics and phase field study

The present study focuses on the roles of structure, stress and temperature on the mobility of facets bounding twin domains and on the overall impact on the growth kinetics of { 10 1 &#xAF; 2 } twins in Mg. We first use molecular dynamics simulations (MD) to study the relationship between interface structures, stress, temperature and mobility. As facets can exhibit distinct atomic scale structures, we also quantify the effect of stress relaxation mediated by misfit dislocations on the mobility of the basal-prismatic interface. The information gathered for ten different facets is used to calibrate an anisotropic phase field model predicting the effects of temperature and stress on the kinetics and shape of a growing { 10 1 &#xAF; 2 } 3D twin, by comparison with MD data. The comparative analysis suggests that, as compared to simulations of individual facets, the effective mobility of facets can be significantly different during growth of a 3D twin. This can be attributed to the complex three-dimensional internal stress state of the twin and to coupling in facet motion triggered by facet junctions. As such, by directly fitting both the twin growth kinetics and morphology as predicted by MD for different stresses and temperatures, we can identify a limited set of rate-limiting facets that control twin growth and morphology, and measure their effective mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Sonora Brown Dwarf Atmosphere and Evolution Models. I. Model Description and Application to Cloudless Atmospheres in Rainout Chemical Equilibrium

Here we present a new generation of substellar atmosphere and evolution models, appropriate for application to studies of L-, T-, and Y-type brown dwarfs and self-luminous extrasolar planets. The models describe the expected temperature-pressure profiles and emergent spectra of atmospheres in radiative-convective equilibrium with effective temperatures and gravities within the ranges 200 ≤ T eff ≤ 2400 K and $2.5\leqslant \mathrm{log}g\leqslant 5.5$. These ranges encompass masses from about 0.5 to 85 Jupiter masses for a set of metallicities ([M/H] = – 0.5 to + 0.5), C/O ratios (from 0.5 to 1.5 times that of solar), and ages. These models expand the diversity of model atmospheres currently available, notably to cooler effective temperatures and greater ranges in C/O. Notable improvements from past such models include updated opacities and atmospheric chemistry. Here we describe our modeling approach and present our initial tranche of models for cloudless, chemical equilibrium atmospheres. We compare the modeled spectra, photometry, and evolution to various data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Microstructure-sensitive modeling of high temperature creep in grade-91 alloy

Predicting the effects of microstructure on high-temperature creep responses of steel components is critical to minimize the risks of failure and maximize economic viability in the energy sector. In this research, a recently developed advanced mechanistic constitutive model is employed to study the effect of microstructure on the creep responses and to rationalize experimentally reported variability in the performances of grade-91 alloy. Hundreds of experimental creep tests from the literature are used to assess the predictability of the model. The model proposed is shown to accurately predict the steady-state creep rates and also the less commonly considered, yet important, primary-to-secondary transients for a wide range of creep conditions. Further, the model is capable of extrapolating the creep response of grade 91 alloy even outside of the calibration regime. Using this model, the roles of initial microstructure described in terms of grain size, dislocation density, and precipitate content, on the creep responses are investigated. The effect of initial microstructure on the steady-state creep rates and creep-strain is found to vary with stress and temperature. Grain size plays a significant role in the low-stress creep, where the diffusional creep is dominant. On the other hand, the effects of dislocation densities and precipitate content are significant in the dislocation-plasticity-dominated high-stress and temperature regimes. Furthermore, by comparing model predictions against a large experimental creep database, it is found that variability in the creep responses can be rationalized on the basis of differences in the initial microstructure. Overall, this work provides a robust pathway for microstructure-aware engineering design, verification, and validation of metallic components for energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Rising ambient temperatures due to climate change will increase urban populations’ exposures to extreme heat. During hot hours, a key protective adaptation is increased air conditioning and associated consumption of electricity for cooling. But during cold hours, milder temperatures have the offsetting effect of reducing consumption of electricity and other fuels for heating. We elucidate the net consequences of these opposing effects in 36 cities in different world regions. We couple reduced-form statistical models of cities’ hourly responses of electric load to temperature with temporally downscaled projections of temperatures simulated by 21 global climate models (GCMs), projecting the effects of warming on the demand for electricity circa 2050. Cities' responses, temperature exposures and impacts are heterogeneous, with changes in total annual consumption ranging from –2.7 to 5.7%, and peak power demand increasing by as much as 9.5% at the multi-GCM median. The largest increases are concentrated in more economically developed mid-latitude cities, with less developed urban areas in the tropics exhibiting relatively small changes. The results highlight the important role of the structure of electricity demand: large temperature increases in tropical cities are offset by their inelastic responses, which can be attributed to lower air-conditioning penetration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Calibration and modification of the constitutive model for the mechanical response of P91

The objective of this first milestone was to calibrate and if necessary, modify a constitutive model predicting the primary and secondary creep response of P91. The overall path to be followed consists of first calibrating this constitutive model against experimental data available from the literature (this milestone). In parallel, data acquired by indentation tests will be used to calibrate the model (this involves transforming the indentation data into equivalent uniaxial tests). An overall comparison of model parameters will allow assessing to what extent these rapid tests can be used to calibrate models predicting the overall mechanical response of the bulk. Given that COVID naturally hindered the gathering of new experimental data, the choice was made to ensure that LANL would have sufficient funds in year two to perform the bulk of the new calibration work. The following report details (i) how and which of the bulk experimental data was selected, (ii) constitutive model formulation, (iii) predictions of the constitutive model: effects of imposed stress, temperature and precipitate content, (iv) future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A Study of Wake Characteristics of Marine Turbine Arrays: Preprint

As the marine energy industry continues to develop and installations grow from single turbines to small arrays and larger farms, understanding and predicting wake behavior using modeling tools is necessary for array design and optimization. The wake characteristics of upstream turbines, including velocity deficit, wake swirling, tip vortices, wake shape and direction, and flow recovery, influence the inflow conditions experienced by downstream turbines in an array and, subsequently, affect the individual turbine loading and power generated by the array. These wake characteristics are influenced by many factors, including site geography, inflow shear profile, turbulence, waves, the strength of the current resource, gravitational forces, storm surges, and seasonal effects like temperature and wind conditions. Efficient array modeling tools that capture these wake effects and resulting turbine-to-turbine interactions need to be developed to optimize farm layouts and design individual turbines for operation within arrays. Unlike the wind industry, the marine energy research community is largely limited to the use of either numerical tools or tank/flume testing to understand marine turbine wake interactions. This paper will investigate recent advances in numerical and experimental marine turbine wake modeling, with a focus on recent publications and on both axial-flow and cross-flow marine turbines. A summary of recent research on these topics is provided. Additionally, a demonstration of turbine wake interactions using computational fluid dynamics is presented.

marine hydrokinetic turbine↗