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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Wide angle Michelson Doppler imaging interferometer

The optical system, stepping control, phase and modulation depth, array detector, and directions sensor are described for a specialized type of Michelson interferometer which works at sufficiently high resolution to measure the line widths and Doppler shifts of naturally occurring atmospheric emissions. With its imaging capability, the instrument can potentially supply this data independently for each element of the 100 x 100 detector array. The experiment seeks: (1) to obtain vertical profiles of atmospheric winds and temperatures as functions of latitude by observing near the limb; (2) to acquire exploratory wind and temperature data on smaller scale structures in airglow irregularities and in auroral forms; and (3) to collaborate with other Spacelab experiments, such as barium cloud releases, in providing wind and temperature data.

Shepherd, G. G.↗
DOE OSTI2015

Melting/freezing points of high concentrations of AlCl 3 in a saturated chloroaluminate ionic liquid

Melting/freezing points of AlCl 3 in saturated chloroaluminate ionic liquids [molar ratio 2:1 AlCl 3 :1-ethyl-3-methyl imidazolium chloride (EMIC)] are measured by differential scanning calorimetry (DSC). A critical range of temperature data (50-130 °C) for AlCl 3 dissolution and precipitation from saturated chloroaluminate ionic liquids is obtained. This range of temperature data is of significance to control phase transition of AlCl 3 in saturated chloroaluminate ionic liquids. By applying the chloroaluminate ionic liquids to electrolytes for energy storage usage, solid AlCl 3 can be partially dissolved and precipitated out during the charging/discharging cycle of energy storage equipment. Furthermore, the energy density of the electrolytes is expected to be greatly improved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Two-Dimensional Synthetic Aperture Radiometry over Land Surface During Soil Moisture Experiment in 2003 (SMEX03)

Microwave radiometry at low frequencies (L-band, approx. 1.4 GHz) has been known as an optimal solution for remote sensing of soil moisture. However, the antenna size required to achieve an appropriate resolution from space has limited the development of spaceborne L-band radiometers. This problem can be addressed by interferometric technology called aperture synthesis. The Soil Moisture and Ocean Salinity (SMOS) mission will apply this technique to monitor global-scale surface parameters in the near future. The first airborne experiment using an aircraft prototype of this approach, the Two-Dimensional Synthetic Aperture Radiometer (2D-STAR), was performed in the Soil Moisture Experiment in 2003 (SMEX03). The L-band brightness temperature data acquired in Alabama by the 2DSTAR was compared with ground-based measurements of soil moisture and with C-band data collected by the Polarimetric Scanning Radiometer (PSR). Our results demonstrate a good response of the 2D-STAR brightness temperature to changes in surface wetness, both in agricultural and forest lands. The behavior of the horizontally polarized brightness temperature data with increasing view-angle over the forest area was noticeably different than over bare soil. The results from the comparison of 2D-STAR and PSR indicate a better response of the 2D-STAR to the surface wetness under both wet and dry conditions. Our results have important implications for the performance of the future SMOS mission.

Ryu, Dongryeol↗
DOE OSTI2015

Nonparametric test of consistency between cosmological models and multiband CMB measurements

We present a novel approach to test the consistency of the cosmological models with multiband CMB data using a nonparametric approach. In our analysis we calibrate the REACT (Risk Estimation and Adaptation after Coordinate Transformation) confidence levels associated with distances in function space (confidence distances) based on the Monte Carlo simulations in order to test the consistency of an assumed cosmological model with observation. To show the applicability of our algorithm, we confront Planck 2013 temperature data with concordance model of cosmology considering two different Planck spectra combination. In order to have an accurate quantitative statistical measure to compare between the data and the theoretical expectations, we calibrate REACT confidence distances and perform a bias control using many realizations of the data. Our results in this work using Planck 2013 temperature data put the best fit ΛCDM model at 95% (∼ 2σ) confidence distance from the center of the nonparametric confidence set while repeating the analysis excluding the Planck 217 × 217 GHz spectrum data, the best fit ΛCDM model shifts to 70% (∼ 1σ) confidence distance. The most prominent features in the data deviating from the best fit ΛCDM model seems to be at low multipoles 18 < ℓ < 26 at greater than 2σ, ℓ ∼ 750 at ∼1 to 2σ and ℓ ∼ 1800 at greater than 2σ level. Excluding the 217×217 GHz spectrum the feature at ℓ ∼ 1800 becomes substantially less significance at ∼1 to 2σ confidence level. Results of our analysis based on the new approach we propose in this work are in agreement with other analysis done using alternative methods.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Comments on the challenge of using mesoscale data in mesoscale numerical models

The dangers of addressing the initialization issues for limited-area mesoscale models by extending the lessons learned during the development of global analysis and prediction systems are discussed. Lack of impact with data inserts at one time suggests that the lateral boundary conditions imposed on the limited-area models might force the model simulation toward a preferred solution, work against the new data being inserted into the model and, therefore, limit the potential impact that this data can have on the model system. The second potential pitfall involves the imposition of balance constraints on the data that are being inserted into the model to compute winds from temperature data and/or temperature from wind data.

Uccellini, Louis W.↗
DOE OSTI2017

A Comparison of Cosmological Parameters Determined from CMB Temperature Power Spectra from the South Pole Telescope and the Planck Satellite

The Planck cosmic microwave background temperature data are best fit with a Lambda CDM model that mildly contradicts constraints from other cosmological probes. The South Pole Telescope (SPT) 2540 deg(2) SPT-SZ survey offers measurements on sub-degree angular scales (multipoles 650 <= l <= 2500) with sufficient precision to use as an independent check of the Planck data. Here we build on the recent joint analysis of the SPT-SZ and Planck data in Hou et al. by comparing Lambda CDM parameter estimates using the temperature power spectrum from both data sets in the SPT-SZ survey region. We also restrict the multipole range used in parameter fitting to focus on modes measured well by both SPT and Planck, thereby greatly reducing sample variance as a driver of parameter differences and creating a stringent test for systematic errors. We find no evidence of systematic errors from these tests. When we expand the maximum multipole of SPT data used, we see low-significance shifts in the angular scale of the sound horizon and the physical baryon and cold dark matter densities, with a resulting trend to higher Hubble constant. When we compare SPT and Planck data on the SPT-SZ sky patch to Planck full-sky data but keep the multipole range restricted, we find differences in the parameters n(s) and A(s)e(-2 tau). We perform further checks, investigating instrumental effects and modeling assumptions, and we find no evidence that the effects investigated are responsible for any of the parameter shifts. Taken together, these tests reveal no evidence for systematic errors in SPT or Planck data in the overlapping sky coverage and multipole range and at most weak evidence for a breakdown of Lambda CDM or systematic errors influencing either the Planck data outside the SPT-SZ survey area or the SPT data at l > 2000.

Aylor, K.↗
DOE OSTI2022

Thermal-Hydraulics Modeling and Simulations of Hot Pool Using the SAS-CFD Coupled Code

The main goal of this activity is to test the dynamic coupling of the SAS4A/SASSYS-1 (SAS) and CFD models, using a recently patched version of the SAS code intended to address an undocumented limitation that hindered the Versatile Test Reactor (VTR) simulation efforts in FY21. As described in previous VTR calculation reports, the undocumented limitation in SAS v5.4 does not allow the user to activate the CFD coupling option during restart calculations. Since the analysts were unaware of this limitation, prior SAS-CFD simulation results for the protected station blackout (PSBO) transient were erroneous. Root-cause analysis was performed to determine the cause of this undocumented limitation in SAS v5.4, the SAS software was updated in a new patch, and the SAS-CFD simulations were repeated with this patched software. The results of the SAS-CFD simulations documented in this report show that the software patch does address the cited issue, and that the patched software indeed supports the activation of the CFD coupling model in restart calculations. The SAS development team will determine the schedule for implementing the patch in an official software release. This report documents updated SAS-CFD simulations of the PSBO transient response in the VTR. The hot pool is modeled with the CFD code STAR-CCM+, which is coupled at the flow boundaries to the SAS model of the primary heat transport system. SAS computes the mass flow rate and temperature at each core subassembly outlet, the thermal insulation cavity bypass, and the IHX inlet windows. CFD in turn computes the absolute pressure and temperature at each of these boundaries. The SAS code will ignore the temperature data at flow boundaries where flow is directed into the hot pool, i.e., at the core subassembly outlets unless flow reversal occurs. Similarly, CFD will ignore temperature data at boundaries where the flow is directed out of the hot pool, i.e., at the IHX inlets except under flow reversal. The focus of this work is to ensure that the SAS software patch addresses the undocumented limitation described in prior VTR calculation reports, rather than the accurate assessment of thermal stratification in the VTR during protected transients. This motivates the development of a new, simplified CFD model with a coarser mesh to accelerate the testing process. The updated model, and simplifying assumptions, are documented in this report. In future work, the thermal stratification assessment should be performed in more detail. The simplified CFD model can be improved by performing grid convergence studies sensitivity studies of turbulence parameters (e.g., Prandtl number, turbulence production and dissipation parameters) on temperature distributions and thermal stratification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

The performance of disk arrays in shared-memory database machines

In this paper, we examine how disk arrays and shared memory multiprocessors lead to an effective method for constructing database machines for general-purpose complex query processing. We show that disk arrays can lead to cost-effective storage systems if they are configured from suitably small formfactor disk drives. We introduce the storage system metric data temperature as a way to evaluate how well a disk configuration can sustain its workload, and we show that disk arrays can sustain the same data temperature as a more expensive mirrored-disk configuration. We use the metric to evaluate the performance of disk arrays in XPRS, an operational shared-memory multiprocessor database system being developed at the University of California, Berkeley.

Katz, Randy H.↗
NASA NTRS1983

Regional geothermal exploration in Egypt

A study is presented of the evaluation of the potential geothermal resources of Egypt using a thermal gradient/heat flow technique and a groundwater temperature/chemistry technique. Existing oil well bottom-hole temperature data, as well as subsurface temperature measurements in existing boreholes, were employed for the thermal gradient/heat flow investigation before special thermal gradient holes were drilled. The geographic range of the direct subsurface thermal measurements was extended by employing groundwater temperature and chemistry data. Results show the presence of a regional thermal high along the eastern margin of Egypt with a local thermal anomaly in this zone. It is suggested that the sandstones of the Nubian Formation may be a suitable reservoir for geothermal fluids. These findings indicate that temperatures of 150 C or higher may be found in this reservoir in the Gulf of Suez and Red Sea coastal zones where it lies at a depth of 4 km and deeper.

Morgan, P.↗
NASA NTRS1987

Shuttle payload bay thermal environments: Summary and conclusion report for STS Flights 1-5

The thermal data for the payload bay of the first five shuttle flights is summarized and the engineering evaluation of that data is presented. After a general discussion on mission profiles and vehicle configurations, the thermal design and flight instrumentation systems of the payload bay are described. The thermal flight data sources and a categorization of the data are then presented. A thermal flight data summarization section provides temperature data for the five phases of a typical mission profile. These are: prelaunch, ascent, on-orbit, entry and postlanding. The thermal flight data characterization section encompasses this flight data for flight to flight variations, payload effects, temperature ranges, and other variations. Discussion of the thermal environment prediction models in use by industry and various NASA Centers, and the results predicted by these models, is followed by an evaluation of the correlation between the actual flight data and the results predicted by the models. Finally, the available thermal data are evaluated from the viewpoint of the user concerned with establishing the thermal environment in the payload bay. The data deficiencies are discussed and recommendations for their elimination are presented.

Fu, J. H.↗
NASA NTRS2020

Comparing Cumulative Flight Thermal Fatigue to Ground Test Results for Memory Components on the Mars Curiosity Rover

This paper explores the methods used to examine Mars Curiosity Rover’s flight temperature data to the Package Qualification and Verification (PQV) accelerated thermal cycle life test data in response to flight anomalies. The redundant Rover Compute Element (RCE-A, B) has experienced an inability to mount the flash memory several times. The leading cause of these anomalies is likely the loss of electrical connectivity, which is theorized to be due to cracks on the memory component solder joints by thermal cycle fatigue. To investigate this theory, the number of thermal cycles accumulated in flight was compared to PQV accelerated thermal cycle life test data. The goal of this study was to inform mission operations of the risk associated with thermal cycling damage on the RCE. However, since the RCE-B does not have continuous temperature data from the Platinum Resistance Thermometer (PRT) closest to the flash memory, a model was made to correlate continuous data from two other nearby sensors on the RCE-B to the noncontiguous sensor. Using the Rainflow Counting Algorithm, the reconstituted data was converted into the number of equivalent thermal cycles. The Coffin-Manson Equation was used to compare flight thermal cycles to the PQV test. The accelerated life test showed cracking on the memory component solder joints after 500 cycles of 80°C temperature excursions. This study found that the RCE-A and RCE-B have undergone an equivalent of 144 and 430 cycles of 80°C temperature excursions during flight, respectively.

Berger, Lindsey N↗
NASA NTRS2021

Comparing Cumulative Flight Thermal Fatigue to Ground Test Results for Memory Components on the Mars Curiosity Rover

This paper explores the methods used to examine Mars Curiosity Rover’s flight temperature data in relation to the Package Qualification and Verification (PQV) accelerated thermal cycle life test data in response to flight anomalies. The redundant Rover Compute Element (RCE-A, B) has experienced an inability to mount the flash memory several times. The leading cause of these anomalies is likely the loss of electrical connectivity, which is theorized to be due to cracks on the memory component solder joints by thermal cycle fatigue. To investigate this theory, the number of thermal cycles accumulated in flight was compared to PQV accelerated thermal cycle life test data. The goal of this study was to inform mission operations of the risk associated with thermal cycling damage on the RCE. However, since the RCE-B does not have continuous temperature data from the Platinum Resistance Thermometer (PRT) closest to the flash memory, a model was made to correlate continuous data from two other nearby sensors on the RCE-B to the noncontiguous sensor. Using the Rainflow Counting Algorithm, the reconstituted data was converted into the number of equivalent thermal cycles. The Coffin-Manson Equation was used to compare flight thermal cycles to the PQV test. The accelerated life test showed cracking on the memory component solder joints after 500 cycles of 80°C temperature excursions. This study found that the RCE-A and RCE-B have undergone an equivalent of 144 and 430 cycles of 80°C temperature excursions during flight, respectively.

Bell, Charles↗
DOE OSTI2014

Fourier analysis of conductive heat transfer for glazed roofing materials

For low-rise buildings, roof is the most exposed surface to solar radiation. The main mode of heat transfer from outdoor via the roof is conduction. The rate of heat transfer and the thermal impact is dependent on the thermophysical properties of roofing materials. Thus, it is important to analyze the heat distribution for the various types of roofing materials. The objectives of this paper are to obtain the Fourier series for the conductive heat transfer for two types of glazed roofing materials, namely polycarbonate and polyfilled, and also to determine the relationship between the ambient temperature and the conductive heat transfer for these materials. Ambient and surface temperature data were collected from an empirical field investigation in the campus of Universiti Teknologi MARA Shah Alam. The roofing materials were installed on free-standing structures in natural ventilation. Since the temperature data are generally periodic, Fourier series and numerical harmonic analysis are applied. Based on the 24-point harmonic analysis, the eleventh order harmonics is found to generate an adequate Fourier series expansion for both glazed roofing materials. In addition, there exists a linear relationship between the ambient temperature and the conductive heat transfer for both glazed roofing materials. Based on the gradient of the graphs, lower heat transfer is indicated through polyfilled. Thus polyfilled would have a lower thermal impact compared to polycarbonate.

42 ENGINEERING↗
DOE OSTI2024

Estimating soil thermal inertia profiles from the passive equilibration of a temperature probe: Supporting data and code

This dataset contains measurements of soil thermal properties and organic layer thickness at three field sites on the Seward Peninsula near Nome, Alaska, USA. Code is also provided for estimation of soil thermal properties from temperature data, including a forward heat transfer mode, a library of simulated temperature data, and an inversion scheme to retrieve thermal properties from temperature measurements (Lamb et al., 2025). This dataset and code is published in support of the manuscript “Estimating Soil Thermal Inertia Profiles from the Passive Equilibration of a Temperature Probe” by Lamb et al., 2025, in which an experimental thermal measurements technique is developed. The dataset contains measurements of soil thermal properties and organic layer thickness obtained with an industry standard thermal properties analyzer and direct observations, as well as data generated using the experimental technique to estimate thermal properties and soil structure from temperature observations. All data is reported in .csv format, and all code is written in Python 3.7 using standard packages. This research was performed as a part of the NGEE Arctic project, which aims to advance model predictions of arctic carbon cycle responses to a changing climate over the 21st Century.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗
NASA NTRS1983

An accurate radiative transfer model for use in the direct physical inversion of HIRS2 and MSU temperature sounding data

The direct computation of atmospheric transmittance and clear column radiances for the channels of HIRS2 and MSU as a function of atmospheric and surface conditions is described in detail. A comparison is made between the observations and the calculated radiances derived from colocated oceanic radiosondes. It is found that under clear conditions, calculated brightness temperatures for the HIRS2 have a standard deviation of the order of 0.7 C compared with observations, whereas MSU channels have a standard deviation of approximately 1 C. In some channels, small biases are found that can be removed by an empirical 'tuning' with coefficients that can be successfully transferred from one season to another. Less satisfactory agreement is obtained from a comparison of calculations with 'reconstructed' clear radiances, which are used in analyzing sounding data under partially cloudy conditions.

Susskind, J.↗
NASA NTRS1980

Heat Capacity Mapping Mission (HCMM)

Tapes for day and night passes on May 16 and May 20, 1978 and a day pass on May 3, 1980 were processed. Results indicate that it is extremely difficult to locate a field of 9 pixel size and temperature data from the HCMM are consistently lower than temperatures measured with a scanner flown at low altitudes. The temperature differences between the satellite and aircraft data appear to be temperature dependent, being smaller at lower temperatures. Three data points are in the format (airc, HCMM) (12,9), (30,23), and (39,30). The linear equation for these three points is T sub HCMM = 0.778 T sub airc -0.33.

Jackson, R. D.↗
DOE OSTI2018

Data Driven Temperature Control of Heat Exchangers

The following poster presents a couple of approaches for temperature control at heat exchanger’s exit. One of the approaches is based on using n-step ahead neural network while the other approach utilizes a combination of control + learning module for temperature control. Designing robust controllers for typical heat exchangers is very challenging primarily because of complexities associated with the synthesis of dynamics of industrial heat exchangers. Even if a dynamics model is synthesized, the accuracy of it would be called into question as there can be lot of unmodeled system dynamics and random noise in input parameters. In many situations, the degree of uncertainty in the model of system being controlled limits the utility of optimal control design. Controller can be manually tuned on the field but it is very difficult to determine manual adjustments that result in overall improvement. These practical challenges call for learning based approaches for temperature control that would result in optimal heat exchanger performance. We utilize the existing mathematical model for air-water system synthesized by Underwood and Crawford for testing our algorithms. Underwood and Crawford developed a model of heating coil by fitting a second-order non-linear equations to measurements of air and water temperature and flow rates obtained from the actual coil. The uncertainties in the model include air and water inlet temperatures and air-flow rate. These uncertainties are modeled as random variables that are sampled from a uniform distribution. The control variable is the water flow rate which is controlled for regulating the air-outlet temperature. Neural networks are frequently used in various literatures for learning time-series. We propose a modified version of neural networks known as n-step ahead neural network that take the state variables and output at time t as input to successfully predict output at time t+n. The variable n is a hyper-parameter which can be optimized based on performance constraints. The n-step ahead neural network was then trained on training data generated from experimental model to high training accuracies. This trained model performed appreciably in its objective to regulate outlet temperature of a heat exchanger. The second approach uses a combination of control and learning module for temperature regulation. The control module used is a proportional controller while the learning module used is steady state neural network. The steady state neural network is used to learn the controller output as a function of random variables and temperature set-point. The proportional controller is then used to compensate for transient behavior of linearized system around various operating points. The algorithm works effectively for temperature regulation as neural network captures the non-linear input-output behavior of closed loop system leaving proportional controller to compensate for steady state errors of a linearized plant. The proposed algorithm’s performances were evaluated against the performance of a PI controller. Further, the robustness of the algorithms were also studied in great detail under small perturbations around tuned parameters of the proposed algorithms.

Sundar, Sreenath↗