SEARCH · Search NASA

Results for “Multiscale Modeling and Simulation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Hydration-Controlled Proton Transport in Respiratory Complex I

Proton pumping by respiratory complex I is one essential element for generating the proton motive force that drives ATP synthesis in mitochondria. Although it is understood that electrons from NADH reduce ubiquinone at the peripheral arm and that four protons are transferred in the membrane domain, the mechanism by which this redox reaction initiates proton translocation remains unclear. A lateral pathway linking the quinone binding site to the membrane domain via ND1, ND3, and ND4L subunits has been proposed as a possible initial path of an excess proton. However, experimental structures indicate that the hydration connectivity between D66 ND3 and E34 ND4L is comparatively weaker than in neighboring segments, suggesting a potential regulatory point for proton transfer. Using multiscale reactive molecular dynamics (MS-RMD) and a water wire connectivity metric, we directly simulate proton transport through this region as coupled to the hydration by water molecules. Our results reveal that proton transfer is thermodynamically feasible when transient hydration aligns with the presence of an excess proton, revealing the strong coupling between hydration and proton transfer (PT) in this region of Complex I. These findings support a model where proton injection enhances local hydration, dynamically opening the pathway for proton transfer and regulating the onset of proton pumping in Complex I.

Chemical structure↗

DOE OSTI2023

Energy transfer and scale dynamics in 2D and 3D laser-driven jets

We demonstrate a methodology for diagnosing the multiscale dynamics and energy transfer in complex HED flows with realistic driving and boundary conditions. The approach separates incompressible, compressible, and baropycnal contributions to energy scale-transfer and quantifies the direction of these transfers in (generalized) wavenumber space. We use this to compare the kinetic energy (KE) transfer across scales in simulations of 2D axisymmetric vs fully 3D laser-driven plasma jets. Using the FLASH code, we model a turbulent jet ablated from an aluminum cone target in the configuration outlined. We show that, in addition to its well known bias for underestimating hydrodynamic instability growth, 2D modeling suffers from significant spurious energization of the bulk flow by a turbulent upscale cascade. In 2D, this arises as vorticity and strain from instabilities near the jet's leading edge transfer KE upscale, sustaining a coherent circulation that helps propel the axisymmetric jet farther (⁠ ≈25% by 3.5 ns) and helps keep it collimated. In 3D, the coherent circulation and upscale KE transfer are absent. Here, the methodology presented here may also help with inter-model comparison and validation, including future modeling efforts to alleviate some of the 2D hydrodynamic artifacts highlighted in this study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Impact of confined geometries on hopping and trapping of motile bacteria in porous media

We use a random walk particle-tracking (RWPT) approach to elucidate the impact of porous media confinement and cell-cell interactions on bacterial transport. The model employs stochastic alternating motility states consisting of hopping movement and trapping reorientation. The stochastic motility patterns are defined based on direct visualization of individual trajectory data. We validate our model against experimental data, at single-cell resolution, of bacterial E. coli motion in three-dimensional confined porous media. Results show that the model is able to efficiently simulate the spreading dynamics of motile bacteria as it captures the impact of cell-cell interaction and pore confinement, which marks the transition to a late-time subdiffusive regime. Furthermore, the model is able to qualitatively reproduce the observed directional persistence. Lastly, our RWPT model constitutes a meshless simple method which is easy to implement and does not invoke ad hoc assumptions but represents the basis for a multiscale approach to the study of bacterial dispersal in porous systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗

DOE OSTI2019

ATF material model development and validation for priority fuel concepts

Development, implementation, and validation of material and behavior models for accident tolerant fuel (ATF) concepts in the Bison fuel performance code began in 2014 in response to the events that occurred at the Fukushima Daichii nuclear power plant in March 2011. Early on the focus was on U 3 Si 2 fuel and FeCrAl cladding as part of a high impact problem through the Nuclear Energy and Advanced Modeling Simulation (NEAMS) program. Then, developments for Cr 2 O 3 -doped UO 2 fuel, and SiC-SiC and Cr-coated zirconium-based claddings began based upon industry interests. In late fiscal year 2018 the Consortium for Advanced Simulation of Light Water Reactors (CASL) took over further ATF work in Bison in support of the Nuclear Regulatory Commission (NRC) engagement. Discussions with the NRC identified their list of priority fuel and cladding concepts, which included Cr 2 O 3 -doped UO 2 and U 3 Si 2 fuels, and Cr-coated zirconium-based and FeCrAl claddings. In particular, the NRC suggested that reports similar in form to NUREG/CR-7024 [1] that was developed for traditional LWR materials UO 2 and zirconium-based claddings (i.e., Zircaloy-4, M5®, ZIRLO) be created for the priority ATF concepts. The approach to ATF capability development in Bison since the beginning has been two-fold: (1) empirical correlations and (2) multiscale model development. Both approaches have uncertainty inherent to them. Uncertainty in empirical correlations is bounded by the experimental data upon which with the correlation was developed. Models developed through a multiscale approach have uncertainty associated with the lower length scale calculations and input parameters that must be propagated to the engineering scale model in Bison. In this report, the recommended models, their range of applicability (e.g., temperature, burnup), and associated uncertainty for the NRC priority fuel concepts Cr 2 O 3 -doped UO 2 and U 3 Si 2 are presented in a manner similar to the aforementioned NUREG. In addition, the Cr 2 O 3 -doped UO 2 models are validated to the Halden Reactor tess IFA-677.1 rods 1 and 5 and IFA-716.1 rod 1. For U 3 Si 2 the models are validated to the recent post-irradiation examination (PIE) data ATF-13 and ATF-15 rods that were irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory. Finally, an uncertainty quantification (UQ) and sensitivity analysis (SA) is completed on a single rod for each fuel concept that takes into account the defined uncertainty in select models. The results of the UQ and SA analyses indicate that given the large uncertainty in some of the input ATF models that the uncertainty on the Bison predictions of fuel performance metrics of interest bound the available experimental data. Correlation coefficients are also reported that identified the uncertain inputs with the strongest correlation (positive or negative) with the outputs of interest. Fuel performance metrics investigated include fuel elongation, rod internal pressure, fuel centerline temperature, and fission gas release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

ATF material model development and validation for priority cladding concepts

Development, implementation, and validation of material and behavior models for accident tolerant fuel (ATF) concepts in the Bison fuel performance code began in 2014 in response to the events that occurred at the Fukushima Daichii nuclear power plant in March 2011. Early on the focus was on U 3 Si 2 fuel and FeCrAl cladding as part of a high impact problem through the Nuclear Energy and Advanced Modeling Simulation (NEAMS) program. Then, developments for Cr 2 O 3 -doped UO 2 fuel, and SiC-SiC and Cr-coated zirconium-based claddings began based upon industry interests. In late fiscal year 2018 the Consortium for Advanced Simulation of Light Water Reactors (CASL) took over further ATF work in Bison in support of the Nuclear Regulatory Commission (NRC) engagement. Discussions with the NRC identified their list of priority fuel and cladding concepts, which included Cr 2 O 3 -doped UO 2 and U 3 Si 2 fuels, and Cr-coated zirconium-based and FeCrAl claddings. In particular, the NRC suggested that reports similar in form to NUREG/CR-7024 that was developed for traditional LWR materials UO 2 and zirconium-based claddings (i.e., Zircaloy-4, M5 ® , ZIRLO TM ) be created for the priority ATF concepts. The approach to ATF capability development in Bison since the beginning has been two-fold: (1) empirical correlations and (2) multiscale model development. Both approaches have uncertainty inherent to them. Uncertainty in empirical correlations is bounded by the experimental data upon which with the correlation was developed. Models developed through a multiscale approach have uncertainty associated with the lower length scale calculations and input parameters that must be propagated to the engineering scale model in Bison. In this report, the recommended models, their range of applicability (e.g., temperature, fluence), and associated uncertainty for the NRC priority clad concepts Cr-coated zirconium based clad and FeCrAl are presented in a manner similar to the aforementioned NUREG. In addition, in the absence of experimental data for validation, demonstration cases are presented that investigate the ballooning and burst behavior of Cr-coated and FeCrAl clads as well as tritium permeation in FeCrAl. A portion of the study by Gamble et al. on FeCrAl failure is also revisited with the latest updated models. First, the nominal results are shown using the as implemented models. Then a sensitivity analysis and uncertainty quantification is performed to assess the impact of the uncertainties in the models on the parameters of interest. For the Cr-clad ballooning case the parameter of interest is the time to burst. For the revisited FeCrAl study, the parameter of interest is the pressure at burst.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Multiscale Solar Water Heating (MSWH) v1.0

The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. Usage The user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. This functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. Features - Python module to calculate solar irradiation on a tilted surface - Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components - Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) - Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles - Django web framework to configure project, parametrize components and run simulation from a web browser The package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.

Grahovac, Milica↗

DOE OSTI2024

Peridynamic Models for Random Media Found by Coarse Graining

Using coarse graining, the upscaled mechanical properties of a solid with small scale heterogeneities are derived. The method maps internal forces at the small scale onto peridynamic bond forces in the coarse grained mesh. These upscaled bond forces are used to calibrate a peridynamic material model with position-dependent parameters. These parameters incorporate mesoscale variations in the statistics of the small scale system. The upscaled peridynamic model can have a much coarser discretization than the original small scale model, allowing larger scale simulations to be performed efficiently. The convergence properties of the method are investigated for representative random microstructures. In conclusion, a bond breakage criterion for the upscaled peridynamic material model is also demonstrated.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Coalescence dynamics of prismatic dislocation loops due to vacancy supersaturation

Recovery processes in metals with a high defect concentration are at the heart of a structural alloy's usability in engineering applications. However, such processes take place via nonconservative mechanisms mediated by point defect diffusion and are governed by their interactions with the underlying microstructure. Indeed, one of the main challenges in studying recovery processes is their intrinsic multiscale complexity, which often negates the direct use of experimental techniques. Here, in this Research Letter, we study the mechanism of dislocation loop coalescence in metals by simulating the interaction dynamics between vacancies and prismatic loops using a stochastic framework that seamlessly bridges point defect kinetics with dislocation mechanics. Our simulations reveal two fundamental discoveries: first, that climb processes are governed by local fluctuations that are not captured by continuum elastodiffusion models, and, second, that prismatic loops create internal traps for vacancies, leading to the formation of rings around the perimeter of the loops that affect how coalescence takes place. Our results show an excellent agreement with in situ experimental observations of loop coalescence in Fe under irradiation.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

remote sensing↗

DOE OSTI2021

Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys

We report that mechanical properties are fundamental to structural materials, where dislocations play a decisive role in describing their mechanical behavior. Although the high-yield stresses of multiprincipal element alloys (MPEAs) have received extensive attention in the last decade, the relation between their mechanistic origins remains elusive. Our multiscale study of density functional theory, atomistic simulations, and high-resolution microscopy shows that the excellent mechanical properties of MPEAs have diverse origins. The strengthening effects through Shockley partials and stacking faults can be decoupled in MPEAs, breaking the conventional wisdom that low stacking fault energies are coupled with wide partial dislocations. This study clarifies the mechanistic origins for the strengthening effects, laying the foundation for physics-informed predictive models for materials design.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Ionic Interdiffusion at Cathode|Solid-Electrolyte Interface: A Machine Learning–Assisted Multiscale Investigation and Mitigation Strategies

Future lithium batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. However, most solid electrolytes are thermodynamically unstable against layered oxide cathodes. In this study, the stability of LiCoO2 (LCO) cathode with Li10GeP2S12 (LGPS) solid electrolyte is investigated using ab initio molecular dynamics (AIMD) and machine learning molecular dynamics (MLMD). The propensity of ionic interdiffusion, formation of a passivating interphase layer, and corresponding decay in cell performance is addressed using a continuum model. Large-scale MLMD simulations confirm that the LCO|LGPS interface permits interdiffusion of cobalt (Co) and other ionic species, leading to the formation and growth of a resistive interphase and to dramatic capacity fade even in the first cycle. We examine the literature evidence that incorporating a thin layer of LiNb0.5Ta0.5O3 (LNTO) between LCO and LGPS prevents the interdiffusion of ions. Atomistic simulations suggest that substituting lithium (Li) in LNTO with Co is thermodynamically unfavorable, thereby inhibiting ionic interdiffusion. The stable Nb5+/Ta5+ states form a rigid metal-oxide framework, which consequently also prevents the substitution of niobium (Nb) or tantalum (Ta). However, continuum-level analysis suggests that the higher mechanical stiffness of LNTO can lead to interfacial delamination between the LCO and LNTO. This phenomenon reduces the effectiveness of the protective layer. This paper, therefore, highlights the need to develop novel interlayers that balance low ionic interdiffusion with low mechanical stiffness.

Ncube, Musawenkosi K.↗

DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗

DOE OSTI2023

Multiscale Development and Validation of the Stainless Steel Alloy Corrosion (SStAC) Tool for High Temperature Engine Materials

The goal of this project was to create a simulation tool to assist in part design, reducing costs by eliminating the need for conservative material selection, and enabling alloy optimization to improve corrosion resistance. Thus, it helps decrease costs for existing engines and assists in the material and engine design for the engines of the future. To meet our stated goal, we developed the Stainless-Steel Alloy Corrosion (SStAC) tool, which: (1) Models corrosion of engine valves fabricated from 21-2N valve steel in an engine environment at temperatures up to 800 °C. (2) Runs in 1D for a fast estimate of the corrosion rate, and in 2D or 3D for more detailed simulations that represent any part geometry and predict the precise location and rate of corrosion and its impact on the mechanical and thermal behavior. (3) Was implemented using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE). (4) Couples the corrosion model with mechanics and thermal transport models. The SStAC tool can predict the corrosion rate of 21-2N engine valves with less than 10% error.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Development and Evaluation of an Explicit Treatment of Aerosol Processes at Cloud Scale Within a Multi‐Scale Modeling Framework (MMF)

Abstract Modeling the aerosol lifecycle in traditional global climate models (GCM) is challenging for a variety of reasons, not the least of which is the coarse grid. The multiscale modeling framework (MMF), in which a cloud resolving model replaces conventional parameterizations of cloud processes within each GCM grid column, provides a promising framework to address this challenge. Here we develop a new version of MMF that for the first time treats aerosol processes at cloud scale to improve the aerosol‐cloud interaction representation in the model. We demonstrate that the model with the explicit aerosol treatments shows significant improvements of many aspects of the simulated aerosols compared to the previous version of MMF with aerosols parameterized at the GCM grid scale. The explicit aerosol treatments produce a significant increase of the column burdens of black carbon (BC), primary organic aerosol, and sulfate by up to 40% in many remote regions, a decrease of the sea‐salt aerosol burdens by 40% in remote regions. These differences are caused by the differences in aerosol convective transport and wet removal between these two models. The new model also shows reduced bias of BC surface concentration in North America and BC vertical profiles in the high latitudes. However, the biased‐high BC concentrations in the upper troposphere over the remote Pacific regions remain, requiring further improvements on other process representations (e.g., secondary activation neglected in the model).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗

DOE OSTI2022

WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations

Abstract We report a new model (WUS256) of radially anisotropic seismic wavespeeds of the crust and upper mantle of the western United States (WUS) obtained from adjoint waveform tomography for the purpose of improving synthetic waveform fits to observed data. WUS256 is based on inversion of over 94,000 waveforms from 72 earthquakes recorded by nearly 3,400 stations. We started with the SPiRaL global model (Simmons et al., 2021, https://doi.org/10.1093/gji/ggab277 ) and waveforms in the period band of 50–120 s. We followed a conservative multiscale inversion approach with eight stages and 256 total inversion iterations which enabled monotonic misfit reduction to 20‐s minimum‐period waves. WUS256 relied on time‐frequency (TF) phase misfits and a trust region limited memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) optimization. Hessian‐vector products were used to qualitatively assess model resolution. Results indicate that WUS256 has good coverage of the continental regions to depths of about 150 km and is able to resolve features on lateral scales of about 200 km. We quantify waveform fits by the reduction in TF and normalized amplitude difference misfits between WUS256 and the SPiRaL starting model. WUS256 significantly improves waveform fits with misfit reduction 64% for both inversion and validation data sets compared to the SPiRaL starting model and shows even better fits compared to other models. Waveform fits illustrate that WUS256 reproduces body‐waves, fundamental mode surface waves as well as late arriving dispersed and/or scattered short period surface waves. The improvement in waveform fit indicates that WUS256 can be used to reproduce path effects on regional complete waveforms and moment tensor inversions.

58 GEOSCIENCES↗

NASA NTRS2015

Thermal Testing and Model Correlation of the Magnetospheric Multiscale (MMS) Observatories

The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth's magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. This paper presents the complete thermal balance (TB) test performed on the first of four observatories to go through thermal vacuum (TV) and the minibalance testing that was performed on the subsequent observatories to provide a comparison of all four. The TV and TB tests were conducted in a thermal vacuum chamber at the Naval Research Laboratory (NRL) in Washington, D.C. with the vacuum level higher than 1.3 x 10 (sup -4) pascals (10 (sup -6) torr) and the surrounding temperature achieving -180 degrees Centigrade. Three TB test cases were performed that included hot operational science, cold operational science and a cold survival case. In addition to the three balance cases a two hour eclipse and a four hour eclipse simulation was performed during the TV test to provide additional transient data points that represent the orbit in eclipse (or Earth's shadow) The goal was to perform testing such that the flight orbital environments could be simulated as closely as possible. A thermal model correlation between the thermal analysis and the test results was completed. Over 400 1-Wire temperature sensors, 200 thermocouples and 125 flight thermistor temperature sensors recorded data during TV and TB testing. These temperature versus time profiles and their agreements with the analytical results obtained using Thermal Desktop and SINDA/FLUINT are discussed. The model correlation for the thermal mathematical model (TMM) is conducted based on the numerical analysis results and the test data. The philosophy of model correlation was to correlate the model to within 3 degrees Centigrade of the test data using the standard deviation and mean deviation error calculation. Individual temperature error goal is to be within 5 degrees Centigrade and the heater power goal is to be within 5 percent of test data. The results of the model correlation are discussed and the effect of some material and interface parameters on the temperature profiles are presented.

Correlation↗