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Results for “Space air temperature prediction”

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 19 records

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A high temperature fatigue and structures testing facility

As man strives for higher levels of sophistication in air and space transportation, awareness of the need for accurate life and material behavior predictions for advanced propulsion system components is heightened. Such sophistication will require complex operating conditions and advanced materials to meet goals in performance, thrust-to-weight ratio, and fuel efficiency. To accomplish these goals will require that components be designed using a high percentage of the material's ultimate capabilities. This serves only to complicate matters dealing with life and material behavior predictions. An essential component of material behavior model development is the underlying experimentation which must occur to identify phenomena. To support experimentation, the NASA Lewis Research Center's High Temperature Fatigue and Structures Laboratory has been expanded significantly. Several new materials testing systems have been added, as well as an extensive computer system. The intent of this paper is to present an overview of the laboratory, and to discuss specific aspects of the test systems. A limited discussion of computer capabilities will also be presented.

Bartolotta, Paul A.↗

Land-Breeze Forecasting

The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability, low temperatures, and fog development. Accurate predictions of the land breeze are critical for toxic material dispersion forecasts associated with space launch missions, since wind direction and low-level stability can change noticeably with the onset of a land breeze. This report presents a seven-year observational study of land breezes over east-central Florida from 1995 to 2001. This comprehensive analysis was enabled by the high-resolution tower observations over KSC/CCAFS. Five-minute observations of winds, temperature, and moisture along with 9 15-MHz Doppler Radar Wind Profiler data were used to analyze specific land-breeze cases, while the tower data were used to construct a composite climatology. Utilities derived from this climatology were developed to assist forecasters in determining the land-breeze occurrence, timing, and movement based on predicted meteorological conditions.

Case, Jonathan L.↗

Comparisons of free-flight experimental and predicted heating rates for the Space Shuttle

Experimental windward-ray heating rates measured during entry of the first Space Shuttle Orbiter mission are compared with predicted rates based on engineering and detailed equilibrium-air analyses. The experimental heating rates were reduced from temperature-time histories which are available only for the trajectory period after blackout which corresponds to a freestream Mach number and altitude of approximately 11.0 and 53 km, respectively. The experimental heating rates are computed for two measured emissivity data sets. The differences in the experimental heating rates based on the two emissivity data sets are sufficiently large that different interpretations of the STS-1 aerothermal environment may be inferred.

Zoby, E. V.↗

A simulation model for the analysis of Space Station gas-phase trace contaminants

A simulation model for the analysis of gas-phase trace contaminants in the cabin air of the NASA Space Station Reference Configuration was developed at the NASA Langley Research Center. The model predicts changes in trace contaminant concentrations from both physical and chemical sources and sinks as a function of time. Simulations were performed in which values for relative humidity, temperature, radiation intensity, pressure, and initial species concentrations were constrained to values for these parameters measured and modeled in the continental tropics at the earth's surface. Species concentrations simulated using the model compared favorably with concentrations in the continental tropics which demonstrated that the chemical mechanism in the trace contaminant model approximates changes in atmospheric species concentrations. The sensitivity of initial species concentrations to producing changes in additional species concentrations was also assessed. Results from the model indicated that chemical reactions will be important in determining the composition of cabin air in the Space Station. It is anticipated that the trace contaminant model will be useful in assessing the impact of experiments and commercial operations on the composition of the cabin air in the Space Station.

Brewer, Dana A.↗

Numerical computation of space shuttle orbiter flow field

The complete inviscid viscous real gas flow around the Space Shuttle Orbiter was computed. Real gas effects are important in predicting the reentry environment around the Orbiter because the high temperatures within the shock layer cause the air to dissociate and ionize, thus invalidating the perfect gas assumption. It is shown that real gas effects has a significant influence on the Orbiter aerodynamics. The approach utilizes a time dependent Navier-Stokes code to compute the subsonic nose portion of the flow field. This nose solution provides the initial conditions for the parabolized Navier-Stokes (PNS) code.

Tannehill, J. C.↗

Climate Response of Direct Radiative Forcing of Anthropogenic Black Carbon

The equilibrium climate effect of direct radiative forcing of anthropogenic black carbon (BC) is examined by 100-year simulations in the Goddard Institute for Space Studies General Circulation Model II-prime coupled to a mixed-layer ocean model. Anthropogenic BC is predicted to raise globally and annually averaged equilibrium surface air temperature by 0.20 K if BC is assumed to be externally mixed. The predicted increase is significantly greater in the Northern Hemisphere (0.29 K) than in the Southern Hemisphere (0.11 K). If BC is assumed to be internally mixed with the present day level of sulfate aerosol, the predicted annual mean surface temperature increase rises to 0.37 K globally, 0.54 K for the Northern Hemisphere, and 0.20 K for the Southern Hemisphere. The climate sensitivity of BC direct radiative forcing is calculated to be 0.6 K W (sup -1) square meters, which is about 70% of that of CO2, independent of the assumption of BC mixing state. The largest surface temperature response occurs over the northern high latitudes during winter and early spring. In the tropics and midlatitudes, the largest temperature increase is predicted to occur in the upper troposphere. Direct radiative forcing of anthropogenic BC is also predicted to lead to a change of precipitation patterns in the tropics; precipitation is predicted to increase between 0 and 20 N and decrease between 0 and 20 S, shifting the intertropical convergence zone northward. If BC is assumed to be internally mixed with sulfate instead of externally mixed, the change in precipitation pattern is enhanced. The change in precipitation pattern is not predicted to alter the global burden of BC significantly because the change occurs predominantly in regions removed from BC sources.

Chung, Serena H.↗

Potential of a Plant Gas Exchange Mechanistic Model to Predict Plant Transpiration in Veggie on ISS

Plants are an essential part of long-duration space travel, as they enable food production and contribute to air revitalization through photosynthesis, and water recycling through transpiration. Understanding their growth mechanisms is essential to use them to sustain human life in space. In particular, gas exchange – e.g., CO2 absorption and water transpiration – are modified in microgravity because of the lack of buoyancy-driven convection, and in the long run, this could result in impaired plant growth. Water absorbed by the plants mainly depends on their size and on environmental conditions (air temperature, humidity and ventilation), but in microgravity watering plants is a delicate operation – too much water results in flooded roots and too little water leads in a few hours to wilted plants. This is regularly experienced in the Veggie system on ISS, which enables small-scale food production in microgravity since 2014. This presentation explores how a mechanistic model of plant gas exchange can help predict plant transpiration in Veggie and thus better predict daily watering. For each plant, inputs on canopy leaf area (acquired with daily photos), air temperature and relative humidity in the plant compartment, as well as airspeed at the top of its canopy enable accurate predictions of transpiration in microgravity. This brings a better understanding of water movement through the plant in microgravity in relation to ventilation and plant size and would result in easier management of plant watering in Veggie. Ultimately, this work could be applied to any space crop production in microgravity and be used for water management and yield predictions. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA.

Lucie Poulet↗

Potential of a Plant Gas Exchange Mechanistic Model to Predict Plant Transpiration in Veggie on ISS

Plants are an essential part of long-duration space travel, as they enable food production and contribute to air revitalization through photosynthesis, and water recycling through transpiration. Understanding their growth mechanisms is essential to use them to sustain human life in space. In particular, gas exchange – e.g., CO2 absorption and water transpiration – are modified in microgravity because of the lack of buoyancy-driven convection, and in the long run, this could result in impaired plant growth. Water absorbed by the plants mainly depends on their size and on environmental conditions (air temperature, humidity and ventilation), but in microgravity watering plants is a delicate operation – too much water results in flooded roots and too little water leads in a few hours to wilted plants. This is regularly experienced in the Veggie system on ISS, which enables small-scale food production in microgravity since 2014. This presentation explores how a mechanistic model of plant gas exchange can help predict plant transpiration in Veggie and thus better predict daily watering. For each plant, inputs on canopy leaf area (acquired with daily photos), air temperature and relative humidity in the plant compartment, as well as airspeed at the top of its canopy enable accurate predictions of transpiration in microgravity. This brings a better understanding of water movement through the plant in microgravity in relation to ventilation and plant size and would result in easier management of plant watering in Veggie. Ultimately, this work could be applied to any space crop production in microgravity and be used for water management and yield predictions. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA.

Lucie Poulet↗

Advancing the Understanding of Snow Accumulation, Melting, and Associated Thermal Insulation Using Spatially Dense Snow Depth and Temperature Time Series

Snow thermal insulation is a critical factor influencing ground thermal dynamics and associated biogeochemical processes. We analyzed the spatiotemporal variability of snow accumulation, melting, and thermal insulation dynamics using spatially dense, collocated snow depth and ground interface temperature time series over two consecutive years. We demonstrated that considering late‐winter snow depth alone was insufficient to fully capture the complexity in snow and insulation dynamics. The influence of vegetation and topography on snow depth distribution varied over the season, across sites and years. We found that deep snow with a long melting period had a substantial impact on thawing n‐factors. To better predict snow insulation effects, we proposed a new weighted snow depth metric that integrates mean daily snow depth and air temperature throughout the cold season. Our results provide insights for developing space‐time remote sensing products and evaluating the representation of snow and permafrost processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Preflight reentry heat transfer analysis of Space Shuttle

Preflight predictions of the structural temperature distributions during entry are compared with data from the initial Shuttle flight. Finite element thermal analysis programming was used to model the heat flow on Shuttle structures and actual gas properties of air were employed in the analyses of aerodynamic heating. Laminar, separated, and turbulent heat fluxes were calculated for varying locations on the craft using velocity-attitude and angle-of-attack projections taken from the nominal STS-1 trajectory. Temperature time histories of the first flight are compared with laminar and turbulent flow assumptions and an unpredicted rapid cooling 1800 sec into entry is credited to inaccurate assumptions of structural heat dissipative properties or flow conditions in that time phase of the flight; additional discrepancies in descriptions of heating of the upper fuselage are attributed to a lack of knowledge of the complex flow patterns existing over that area of the Shuttle body.

Ko, W. L.↗

Quantum-cascade-laser-absorption-spectroscopy diagnostic for temperature, pressure, and NO X 2 Π 1/2 at 500 kHz in shock-heated air at elevated pressures

The design, validation, and application of a quantum-cascade-laser-absorption-spectroscopy diagnostic for measuring gas temperature, pressure, and nitric oxide (NO) in high-temperature air are presented. A distributed-feedback quantum-cascade laser (QCL) centered near 1976 c m − <#comment/> 1 was used to scan across two transitions of NO in its ground electronic state ( X 2 Π <#comment/> 1 / 2 ). A measurement rate of 500 kHz was achieved using a single QCL by: (1) performing current modulation through a bias-tee, and (2) targeting closely spaced transitions with a large difference in lower-state energy. The diagnostic was validated in a mixture of 95% argon and 5% NO, which was shock-heated to ≈ <#comment/> 2000 to 3700 K. The average mean percent differences between laser-absorption-spectroscopy (LAS) measurements and predictions from shock-jump relations for temperature, pressure, and NO mole fraction were 3.1%, 4.1%, and 6.5%, respectively. The diagnostic was then applied to characterize shock-heated air at high temperatures (up to ≈ <#comment/> 5500 K ) and high pressures (up to 12 atm) behind either incident or reflected shocks. The LAS measurements were compared to theoretical predictions from shock-jump relations, pressure sensors mounted in the wall of the shock tube, and equilibrium values of the NO mole fraction. The average mean percent differences between LAS measurements and their aforementioned reference values were 3.2%, 10.8%, and 10.4% for temperature, pressure, and NO mole fraction, respectively. Last, a comparison between a measured NO mole fraction time history and a time-stepped homogeneous reactor simulation performed using two different chemical kinetics mechanisms is presented.

Gilvey, Jonathan J. (ORCID:0000000317664383)↗

Regional Assimilation of NASA Atmospheric Infrared Sounder (AIRS) Data

The NASA Short-term Prediction Research and Transition (SPORT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NW S forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21 st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA s Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes. It is imperative that the scientific community is prepared to take full advantage of next-generation satellite data that will become available within the next decade. The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over both land and ocean. The assimilation system used in this study is the Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts at 12 km produced by the next generation Weather Research and Forecast (WRF) model.

Chou, Shih-Hung↗

Wall catalysis experiment on AFE

This paper describes the wall catalysis experiment which is planned as part of the Aeroassist Flight experiments (AFE) that will be flown from the Space Shuttle Orbiter in late 1993. Research on candidate high-catalytic efficiency overcoats for the experiment conducted in an arc-jet air stream are discussed. The temperature distribution over the AFE heat shield is also predicted using a reacting boundary layer solution that includes surface kinetics and optical properties determined from these tests.

Stewart, David A.↗

Preliminary Findings of the Photovoltaic Cell Calibration Experiment on Pathfinder Flight 95-3

The objective of the photovoltaic (PV) cell calibration experiment for Pathfinder was to develop an experiment compatible with an ultralight UAV to predict the performance of PV cells at AM0, the solar spectrum in space, using the Langley plot technique. The Langley plot is a valuable technique for this purpose and requires accurate measurements of air mass (pressure), cell temperature, solar irradiance, and current-voltage(IV) characteristics with the cells directed normal to the direct ray of the sun. Pathfinder's mission objective (95-3) of 65,000 ft. maximum altitude, is ideal for performing the Langley plot measurements. Miniaturization of electronic data acquisition equipment enabled the design and construction of an accurate and light weight measurement system that meets Pathfinder's low payload weight requirements.

Vargas-Aburto, Carlos↗

Prediction modeling of physiological responses and human performance in the heat with application to space operations

This institute has developed a comprehensive USARIEM heat strain model for predicting physiological responses and soldier performance in the heat which has been programmed for use by hand-held calculators, personal computers, and incorporated into the development of a heat strain decision aid. This model deals directly with five major inputs: the clothing worn, the physical work intensity, the state of heat acclimation, the ambient environment (air temperature, relative humidity, wind speed, and solar load), and the accepted heat casualty level. In addition to predicting rectal temperature, heart rate, and sweat loss given the above inputs, our model predicts the expected physical work/rest cycle, the maximum safe physical work time, the estimated recovery time from maximal physical work, and the drinking water requirements associated with each of these situations. This model provides heat injury risk management guidance based on thermal strain predictions from the user specified environmental conditions, soldier characteristics, clothing worn, and the physical work intensity. If heat transfer values for space operations' clothing are known, NASA can use this prediction model to help avoid undue heat strain in astronauts during space flight.

Pandolf, Kent B.↗

Investigation of the role of thermal boundary layer processes in initiating convection under the NASA SPACE Field Program

The current NWS ground based network is not sufficient to capture the dynamic or thermodynamic structure leading to the initiation and organization of air mass moist convective events. Under this investigation we intend to use boundary layer mesoscale models (McNider and Pielke, 1981) to examine the dynamic triggering of convection due to topography and surface thermal contrasts. VAS and MAN's estimates of moisture will be coupled with the dynamic solution to provide an estimate of the total convective potential. Visible GOES images will be used to specify incoming insolation which may lead to surface thermal contrasts and JR skin temperatures will be used to estimate surface moisture (via the surface thermal inertia) (Weizel and Chang, 1988) which can also induce surface thermal contrasts. We will use the SPACE-COHMEX data base to evaluate the ability of the joint mesoscale model satellite products to show skill in predicting the development of air mass convection. We will develop images of model vertical velocity and satellite thermodynamic measures to derive images of predicted convective potential. We will then after suitable geographic registration carry out a pixel by pixel correlation between the model/satellite convective potential and the 'truth' which are the visible images. During the first half of the first year of this investigation we have concentrated on two aspects of the project. The first has been in generating vertical velocity fields from the model for COHMEX case days. We have taken June 19 as the first case and have run the mesoscale model at several different grid resolutions. We are currently developing the composite model/satellite convective image. The second aspect has been the attempted calibration of the surface energy budget to provide the proper horizontal thermal contrasts for convective initiation. We have made extensive progress on this aspect using the FIFE data as a test data set. The calibration technique looks very promising.

Mcnider, Richard T.↗