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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Temperature-stress modeling

Temperature-stress modeling for silicon dendritic web growth is described. Temperature/stress fields near growth front are examined. The effects of lateral temperature gradients are also explored.

Seidensticker, R. G.↗
DOE OSTI2019

Model of temperature, evaporation, and productivity in elevated experimental algae raceways and comparison with commercial raceways

Elevated Experimental Raceways (EERs) have been used at many research sites in the United States to evaluate algal biomass productivity. This paper develops temperature and evaporation models for EERs and then evaluates whether the temperature profile and resultant productivity in an EER is representative of large-scale commercial raceways. Open water surface evaporation and temperature models with shading algorithms were programmed in Python and calibrated with temperature and evaporation data from the EERs in the Regional Algal Feedstock Testbed (RAFT) experiments at the University of Arizona. The final calibrated model for EERs was named the EERTEM (Elevated Experimental Raceway Temperature and Evaporation Model). The energy balance algorithms in the Biomass Assessment Tool (BAT model) were also added to the Python code and used to develop temperature simulations of standard commercial paddlewheel raceways. A comparison of BAT and EERTEM simulations indicated that EER temperature fluctuations are not representative of in ground commercial paddlewheel raceways, primarily due to the buffering effect of soil heat flux in commercial raceways. With the different temperature profiles, biomass productivities of three algae species in the EERs were compared to productivities in commercial raceways. Differences in productivity between EERTEM and BAT model temperature profiles were observed when the maximum daytime temperature of one raceway was in the optimal growth range but the temperature of the other raceway exceeded or was below the optimal growth range.

Khawam, George↗
DOE OSTI2014

Effects of electrostatic discharge on three cryogenic temperature sensor models

Cryogenic temperature sensors are not usually thought of as electrostatic discharge (ESD) sensitive devices. However, the most common cryogenic thermometers in use today are thermally sensitive diodes or resistors - both electronic devices in their base form. As such, they are sensitive to ESD at some level above which either catastrophic or latent damage can occur. Instituting an ESD program for safe handling and installation of the sensor is costly and it is desirable to balance the risk of ESD damage against this cost. However, this risk cannot be evaluated without specific knowledge of the ESD vulnerability of the devices in question. This work examines three types of cryogenic temperature sensors for ESD sensitivity - silicon diodes, Cernox(trade mark, serif) resistors, and wire wound platinum resistors, all manufactured by Lake Shore Cryotronics, Inc. Testing was performed per TIA/EIA FOTP129 (Human Body Model). Damage was found to occur in the silicon diode sensors at discharge levels of 1,500 V. For Cernox(trade mark, serif) temperature sensors, damage was observed at 3,500 V. The platinum temperature sensors were not damaged by ESD exposure levels of 9,900 V. At the lower damage limit, both the silicon diode and the Cernox(trade mark, serif) temperature sensors showed relatively small calibration shifts of 1 to 3 K at room temperature. The diode sensors were stable with time and thermal cycling, but the long term stability of the Cernox(trade mark, serif) sensors was degraded. Catastrophic failure occurred at higher levels of ESD exposure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Modeling stream temperature in the Anthropocene: An earth system modeling approach

A new large-scale stream temperature model has been developed within the Community Earth System Model (CESM) framework. The model is coupled with the Model for Scale Adaptive River Transport (MOSART) that represents river routing and a water management model (WM) that represents the effects of reservoir operations and water withdrawals on flow regulation. The coupled models allow the impacts of reservoir operations and withdrawals on stream temperature to be explicitly represented in a physically based and consistent way. The models have been applied to the Contiguous United States driven by observed meteorological forcing. It is shown that the model is capable of reproducing stream temperature spatiotemporal variation satisfactorily by comparison against the observed streamflow from over 320 USGS stations. Including water management in the models improves the agreement between the simulated and observed streamflow at a large number of stream gauge stations. Both climate and water management are found to have important influence on the spatiotemporal patterns of stream temperature. More interestingly, it is quantitatively estimated that reservoir operation could cool down stream temperature in the summer low-flow season (August – October) by as much as 1~2oC over many places, as water management generally mitigates low flow, which has important implications to aquatic ecosystems. In conclusion, sensitivity of the simulated stream temperature to input data and reservoir operation rules used in the WM model motivates future directions to address some limitations in the current modeling framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Modeling the surface temperature of earth-like planets

We introduce a novel Earth-like planet surface temperature model (ESTM) for habitability studies based on the spatial–temporal distribution of planetary surface temperatures. The ESTM adopts a surface energy balance model (EBM) complemented by: radiative–convective atmospheric column calculations, a set of physically based parameterizations of meridional transport, and descriptions of surface and cloud properties more refined than in standard EBMs. The parameterization is valid for rotating terrestrial planets with shallow atmospheres and moderate values of axis obliquity (ϵ≲45{sup ∘}). Comparison with a 3D model of atmospheric dynamics from the literature shows that the equator-to-pole temperature differences predicted by the two models agree within ≈5 K when the rotation rate, insolation, surface pressure and planet radius are varied in the intervals 0.5≲Ω/Ω{sub ⊕}≲2, 0.75≲S/S{sub ∘}≲1.25, 0.3≲p/(1 bar)≲10, and 0.5≲R/R{sub ⊕}≲2, respectively. The ESTM has an extremely low computational cost and can be used when the planetary parameters are scarcely known (as for most exoplanets) and/or whenever many runs for different parameter configurations are needed. Model simulations of a test-case exoplanet (Kepler-62e) indicate that an uncertainty in surface pressure within the range expected for terrestrial planets may impact the mean temperature by ∼60 K. Within the limits of validity of the ESTM, the impact of surface pressure is larger than that predicted by uncertainties in rotation rate, axis obliquity, and ocean fractions. We discuss the possibility of performing a statistical ranking of planetary habitability taking advantage of the flexibility of the ESTM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Integrated modeling of temperature profiles in L-mode tokamak discharges

Simulations of doublet III-D, the joint European tokamak, and the tokamak fusion test reactor L-mode tokamak plasmas are carried out using the PTRANSP predictive integrated modeling code. The simulation and experimental temperature profiles are compared. The time evolved temperature profiles are computed utilizing the Multi-Mode anomalous transport model version 7.1 (MMM7.1) which includes transport associated with drift-resistive-inertial ballooning modes (the DRIBM model [T. Rafiq et al., Phys. Plasmas 17, 082511 (2010)]). The tokamak discharges considered involved a broad range of conditions including scans over gyroradius, ITER like current ramp-up, with and without neon impurity injection, collisionality, and low and high plasma current. The comparison of simulation and experimental temperature profiles for the discharges considered is shown for the radial range from the magnetic axis to the last closed flux surface. The regions where various modes in the Multi-Mode model contribute to transport are illustrated. In the simulations carried out using the MMM7.1 model it is found that: The drift-resistive-inertial ballooning modes contribute to the anomalous transport primarily near the edge of the plasma; transport associated with the ion temperature gradient and trapped electron modes contribute in the core region but decrease in the region of the plasma boundary; and neoclassical ion thermal transport contributes mainly near the center of the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Physics-informed machine-learning model of temperature evolution under solid phase processes

We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.

36 MATERIALS SCIENCE↗
NASA NTRS1992

A new two-temperature dissociation model for reacting flows

A new two-temperature dissociation model for flows undergoing compression is derived from kinetic theory. The model minimizes uncertainties associated with the two-temperature model of Park. The effects of the model on AOTV type flowfields are examined and compared with the Park model. Calculations are carried out for flows with and without ionization. When considering flows with ionization, a four temperature model is employed. For Fire II conditions, the assumption of equilibrium between the vibrational and electron-electronic temperatures is somewhat poor. A similar statement holds for the translational and rotational temperatures. These trends are consistent with results obtained using the direct simulation Monte Carlo method.

Olynick, David R.↗
NASA NTRS1987

Assessment of two-temperature kinetic model for ionizing air

A two-temperature chemical-kinetic model for air is assessed by comparing theoretical results with existing experimental data obtained in shock-tubes, ballistic ranges, and flight experiments. In the model, named the TTv model, one temperature (T) is assumed to characterize the heavy-particle translational and molecular rotational energies, and another temperature (Tv) to characterize the molecular vibrational, electron translational, and electronic excitation energies. The theoretical results for nonequilibrium air flow in shock tubes are obtained using the computer code STRAP (Shock-Tube Radiation Program), and for flow along the stagnation streamline in the shock layer over spherical bodies using the newly developed code STRAP (Stagnation-Point Radiation Program). Substantial agreement is shown between the theoretical and experimental results for relaxation times and radiative heat fluxes. At very high temperatures the spectral calculations need further improvement. The present agreement provides strong evidence that the two-temperature model characterizes principal features of nonequilibrium air flow. New theoretical results using the model are presented for the radiative heat fluxes at the stagnation point of a 6-m-radius sphere, representing an aeroassisted orbital transfer vehicle, over a range of free-stream conditions. Assumptions, approximations, and limitations of the model are discussed.

Park, Chul↗
DOE OSTI2018

A new approach to modeling temperature-related mortality: Non-linear autoregressive models with exogenous input

Highlights: • NARX models are established in other environmental research, but are unused in temperature-related mortality research. • NARX models do not assume any particular shape to the temperature-mortality association. • NARX models are cross-validated and are easily modified to take on real-time, multi-step-ahead predictions and hindcasts. • Year-round, daily mortality in 41 different US cities was modeled using an ensemble of NARX models in each location. • Models show skill everywhere. Results vary spatially and seasonally, improving upon a persistence model by 17% points. • When compared with distributed lag non-linear models, the output time series are largely similar Temperature-mortality relationships are nonlinear, time-lagged, and can vary depending on the time of year and geographic location, all of which limits the applicability of simple regression models in describing these associations. This research demonstrates the utility of an alternative method for modeling such complex relationships that has gained recent traction in other environmental fields: nonlinear autoregressive models with exogenous input (NARX models). All-cause mortality data and multiple temperature-based data sets were gathered from 41 different US cities, for the period 1975–2010, and subjected to ensemble NARX modeling. Models generally performed better in larger cities and during the winter season. Across the US, median absolute percentage errors were 10% (ranging from 4% to 15% in various cities), the average improvement in the r-squared over that of a simple persistence model was 17% (6–24%), and the hit rate for modeling spike days in mortality (>80th percentile) was 54% (34–71%). Mortality responded acutely to hot summer days, peaking at 0–2 days of lag before dropping precipitously, and there was an extended mortality response to cold winter days, peaking at 2–4 days of lag and dropping slowly and continuing for multiple weeks. Spring and autumn showed both of the aforementioned temperature-mortality relationships, but generally to a lesser magnitude than what was seen in summer or winter. When compared to distributed lag nonlinear models, NARX model output was nearly identical. These results highlight the applicability of NARX models for use in modeling complex and time-dependent relationships for various applications in epidemiology and environmental sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Systematic validation of non-equilibrium thermochemical models using Bayesian inference

The validation process proposed by Babuška et al. [1] is applied to thermochemical models describing post-shock flow conditions. In this validation approach, experimental data is involved only in the calibration of the models, and the decision process is based on quantities of interest (QoIs) predicted on scenarios that are not necessarily amenable experimentally. Moreover, uncertainties present in the experimental data, as well as those resulting from an incomplete physical model description, are propagated to the QoIs. We investigate four commonly used thermochemical models: a one-temperature model (which assumes thermal equilibrium among all inner modes), and two-temperature models developed by Macheret et al. [2], Marrone and Treanor [3], and Park [4]. Up to 16 uncertain parameters are estimated using Bayesian updating based on the latest absolute volumetric radiance data collected at the Electric Arc Shock Tube (EAST) installed inside the NASA Ames Research Center. Following the solution of the inverse problems, the forward problems are solved in order to predict the radiative heat flux, QoI, and examine the validity of these models. Our results show that all four models are invalid, but for different reasons: the one-temperature model simply fails to reproduce the data while the two-temperature models exhibit unacceptably large uncertainties in the QoI predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗