Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “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.

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

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Phillips, T. J.↗
DOE OSTI2018

Model-Based Characterization of Elevated Temperature and High Pressure Oxy-Coal Combustion Systems

Reaction Engineering International is leading a DOE-funded program focused on characterization of the impacts of high temperatures and pressures in oxy-coal combustion systems. A primary objective is to evaluate flame behavior, heat transfer, and ash chemistry at high pressure to facilitate the application of pressurized oxy-coal in full-scale systems. The University of Utah’s 300 kW pressurized entrained flow gasifier has been successfully modified and operated as a high pressure, slurry-fed, oxy-coal combustor at firing rates ranging from nearly 100 kW to over 180 kW with reactor pressures as high as 200 psi. This presentation will describe the modifications to the gasifier to allow it to operate as a high pressure, oxy-coal combustor; detail experimental data including measurements of radiant flux, wall surface temperatures, and ash aerosol characterization; and CFD modeling of the experimental conditions. In addition, an update will be provided for accomplishments achieved to date for the component of the program focused on modeling of high temperature oxy-coal combustion using undiluted directed oxygen with minimal flue gas recirculation at atmospheric pressure.

CFD modeling↗
DOE OSTI2022

Earth System Model Overestimation of Cropland Temperatures Scales With Agricultural Intensity

Intensive crop growth can modify regional climate by partitioning energy to latent heating through transpiration, cooling growing season temperatures. Recent work shows that cooling associated with agriculture can dampen anthropogenic warming over breadbasket regions. However, it is unknown whether climate models reproduce crop influences on regional climate, and thus the future risk of extreme climate events over global breadbasket regions. Here, we show that models overestimate growing season temperatures and underestimate evapotranspiration (ET) over global croplands, and that these differences increase with cropped area. We trace this warm and dry difference through each model's representation of the surface energy budget, showing that model differences in transpiration, leaf area index, and the ratio of transpiration to total ET drive the overall effect. While the implications of these model deficiencies for future projections are uncertain, they point to the importance of improving representations of crop-climate processes to better assess breadbasket vulnerability to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models

This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ~7% °C –1 . Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Reusable Solid Rocket Motor Nozzle Joint-4 Thermal Analysis

This study provides for development and test verification of a thermal model used for prediction of joint heating environments, structural temperatures and seal erosions in the Space Shuttle Reusable Solid Rocket Motor (RSRM) Nozzle Joint-4. The heating environments are a result of rapid pressurization of the joint free volume assuming a leak path has occurred in the filler material used for assembly gap close out. Combustion gases flow along the leak path from nozzle environment to joint O-ring gland resulting in local heating to the metal housing and erosion of seal materials. Analysis of this condition was based on usage of the NASA Joint Pressurization Routine (JPR) for environment determination and the Systems Improved Numerical Differencing Analyzer (SINDA) for structural temperature prediction. Model generated temperatures, pressures and seal erosions are compared to hot fire test data for several different leak path situations. Investigated in the hot fire test program were nozzle joint-4 O-ring erosion sensitivities to leak path width in both open and confined joint geometries. Model predictions were in generally good agreement with the test data for the confined leak path cases. Worst case flight predictions are provided using the test-calibrated model. Analysis issues are discussed based on model calibration procedures.

Clayton, J. Louie↗
NASA NTRS1997

Surface Temperature Assimilation in Land Surface Models

This paper examines the utilization of surface temperature as a variable to be assimilated in offline land surface hydrological models. Comparisons between the model computed and satellite observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the AM and PM overpass of the NOAA10) over the Red- Arkansas basin in the Southwestern United States (31 deg 50 min N - 36 deg N, 94 deg 30 min W - 104 deg 30 min W) for a period of one year (August 1987 to July 1988). The effect of assimilation is to reduce the difference between the surface soil moisture computed for the precipitation and/or shortwave radiation perturbed case and the unperturbed case compared to no assimilation.

Lakshmi, Venkataraman↗
NASA NTRS1999

Surface Temperature Assimilation in Land Surface Models

This paper examines the utilization of surface temperature as a variable to be assimilated in offline land surface hydrological models. Comparisons between the model computed and satellite observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the AM and PM overpass of the NOAA10) over the Red-Arkansas basin in the Southwestern United States (31 degs 50 sec N - 36 degrees N, 94 degrees 30 seconds W - 104 degrees 3 seconds W) for a period of one year (August 1987 to July 1988). The effect of assimilation is to reduce the difference between the surface soil moisture computed for the precipitation and/or shortwave radiation perturbed case and the unperturbed case compared to no assimilation.

Lakshmi, Venkataraman↗
NASA NTRS1986

Program for Heat Flow in Welding

Program contains numerical model of temperature distribution in vicinity of weld. Weld model used to produce estimated welding power requirements, welding-power-loss analysis, heat-affected-zone temperature history, and weld-puddle cross-section plots. Applied to gas/tungsten-arc, plasma-arc, electron-beam, and laser-beam welds on wide plates under steady conditions. User predicts power requirements and temperature distributions. Weld model written in BASIC.

Nunes, A. C., Jr.↗
DOE OSTI2024

Site‐selective fluorescence and spectroscopic properties of Yb‐doped lanthanum titanate glasses

Abstract Ytterbium‐doped lanthanum titanate glasses were prepared by levitation melting for the detailed characterization of the spectroscopic properties in the rare‐earth titanate glass host. Low‐temperature fluorescence spectroscopy reveals distinct site‐selectivity in both static and lifetime fluorescence measurements suggesting an absence of clustering as well as significant variation of local ytterbium environments. Typical site‐selectivity behavior of a shrinking Stark manifold with lower excitation energy is observed. At 77 K, both the mean emission frequency and the fluorescence lifetime initially increase as the excitation energy decreases from about 11100 to 10750 and then slightly decrease at lower excitation energy. Temperature‐dependent lifetime measurements between 77 and 420 K show a decreasing lifetime with increasing temperature and are well described by a two‐level thermal activation model. The temperature‐dependent fluorescence spectroscopy coupled with a room temperature white light absorption measurement allow the determination of the Stark energy levels of in lanthanum titanate glass as well as the calculation of the laser cross‐sections.

Materials Science↗
NASA NTRS1981

A meteorologically driven maize stress indicator model

A maize soil moisture and temperature stress model is described which was developed to serve as a meteorological data filter to alert commodity analysts to potential stress conditions in the major maize-producing areas of the world. The model also identifies optimum climatic conditions and planting/harvest problems associated with poor tractability.

Taylor, T. W.↗
DOE OSTI2018

Parametric Modeling of AZ31-Mg Alloy Friction Stir Weld Temperature Histories

A parametric model of friction stir weld temperature histories is presented that uses constraint conditions, which are three-dimensional isothermal boundary conditions on the calculated temperature fields. This study describes further extension, with respect to formulation, of a parametric-modeling methodology, which is relatively optimal in terms of representation for application to friction stir welding and processing. These parametric representations of temperature histories can be used for modeling friction stir welds whose process conditions are similar to those in this study. Calculations of AZ31-Mg alloy friction stir weld temperature histories are presented, which use temperature-field constraint conditions based on measured weld cross sections and a model for the estimation of weld stir zone temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Impact of methane and black carbon mitigation on forcing and temperature: a multi-model scenario analysis

The relatively short atmospheric lifetimes of methane (CH 4 ) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH 4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Phenomenological Constitutive Modeling of High-Temperature Flow Behavior Incorporating Individual and Coupled Effects of Processing Parameters in Super-austenitic Stainless Steel

A novel constitutive model has been developed for predicting flow responses of super-austenitic stainless steel over a wide range of strains (0.05-0.6), temperatures (1173-1423 K) and strain rates (0.001-1 s{sup −1}). Further, the predictability of this new model has been compared with the existing Johnson–Cook (JC) and modified Zerilli–Armstrong (M-ZA) model. The JC model is not befitted for flow prediction as it is found to be exhibiting very high (~ 36%) average absolute error (δ) and low (~ 0.92) correlation coefficient (R). On the contrary, the M-ZA model has demonstrated relatively lower δ (~ 13%) and higher R (~ 0.96) for flow prediction. The incorporation of couplings of processing parameters in M-ZA model has led to exhibit better prediction than JC model. However, the flow analyses of the studied alloy have revealed the additional synergistic influences of strain and strain rate as well as strain, temperature, and strain rate apart from those considered in M-ZA model. Hence, the new phenomenological model has been formulated incorporating all the individual and synergistic effects of processing parameters and a ‘strain-shifting’ parameter. The proposed model predicted the flow behavior of the alloy with much better correlation and generalization than M-ZA model as substantiated by its lower δ (~ 7.9%) and higher R (~ 0.99) of prediction.

36 MATERIALS SCIENCE↗
NASA NTRS1965

Thermal scale modeling.

Test models of spacecraft to investigate thermal behavior, particularly Mariner temperature control model

SPACECRAFT MODEL↗
NASA NTRS2003

Use of MODIS Land and Sea Surface Temperatures to Initialize Mesoscale Models

As computer power continues to increase, mesoscale models are initialized at all hours of the day and continue to be run at higher and higher spatial resolutions. As a result, initializing land surface temperature can be problematic. The majority of research-based models are initialized at 00 and 12 UTC when upper air observations and reanalysis fields are available. The landsea surface temperatures are then set equal to the two-meter air temperature produced by the preprocessor analysis system. This particular procedure might be valid in the early morning hours just prior to sunrise, but it becomes less valid during the remainder of the diurnal cycle. Operational models, such as the Rapid Update Cycle run at the National Centers for Environmental Prediction (NCEP), are initialized every hour on a daily basis. This presents a unique challenge to the initial specification of the land temperature, especially during the first several hours of the solar heating cycle when land and overlying air temperatures are far from being the same. Another issue that needs to be addressed is the spatial variability of land surface temperature. By early next year, the NCEP operational Eta model will be employed at 8 km resolution. Methods to accurately specify the initial land surface temperature at such high resolution need to be explored. This paper presents the results of using data from the NASA Moderate Imaging Sensor aboard the TERRA Satellite to initialize land and sea surface temperatures within the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) 5'th generation Mesoscale Model (MM5). We have simulated a northern Gulf Coast sea breeze case to demonstrate the utility of using the MODIS data to initialize both the land and sea surface temperature fields. Model grid configurations of 12-, 4-, and l-km are employed.

Arnold, James E.↗
DOE OSTI2019

Constitutive Modeling of High-Temperature Flow Stress of Armor Steel in Ballistic Applications: A Comparative Study

Armox 500T is one of the armor grade steels extensively used as armor against bullet penetration in ballistic applications. In such applications, the material undergoes plastic deformation at large strain rates (10{sup 3} s{sup −1}) at temperatures of the order of 673-1373 K. In the present work, an attempt has been made to predict strain rate and temperature-dependent flow behavior of Armox 500T steel through physical-based model like modified Zerilli–Armstrong (M-ZA) and phenomenological-based models like Cowper Symonds (CS), modified Johnson–Cook (M-JC), Arrhenius (Arr.) and Khan–Huang–Liang (KHL) constitutive material model. Isothermal uniaxial compression tests at low strain rates (10{sup −3}-10{sup −1} s{sup −1}) and dynamic compression tests at high strain rates (600-3000 s{sup −1}) in the temperatures range of 673-1373 K have been carried out to determine constitutive material model parameters. In addition, an artificial neural network (ANN) model that works on multilayer perceptron (MLP) based back propagation neural network (BPNN) has also been developed. The results from all these models have been compared in terms of three statistical parameters namely correlation coefficient (R), mean absolute percent error (MAPE) and its standard deviation (Δ). The results revealed that M-JC model shows highest correlation coefficient and lowest average absolute error. Further, ANN model prediction has the highest accuracy with R = 0.999 and MAPE = 1.052.

36 MATERIALS SCIENCE↗