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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 19 records

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NASA NTRS2002

Overview of Photovoltaic Calibration and Measurement Standards at GRC

Photovoltaic (PV) systems (cells and arrays) for spacecraft power have become an international market. This market demands accurate prediction of the solar array power output in space throughout the mission life of the spacecraft. Since the beginning of space flight, space-faring nations have independently developed methods to calibrate solar cells for power output in low Earth orbit (LEO). These methods rely on terrestrial, laboratory, or extraterrestrial light sources to simulate or approximate the air mass zero (AM0) solar intensity and spectrum.

Baraona, Cosmo↗

NASA NTRS2014

Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft

Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, high-confidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.

Battery Discharge Prediction↗

NASA NTRS2014

A Battery Health Monitoring Framework for Planetary Rovers

Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

prediction↗

NASA NTRS1974

User's manual for the Shuttle Electric Power System analysis computer program (SEPS), volume 2 of program documentation

The Shuttle Electric Power System Analysis SEPS computer program which performs detailed load analysis including predicting energy demands and consumables requirements of the shuttle electric power system along with parameteric and special case studies on the shuttle electric power system is described. The functional flow diagram of the SEPS program is presented along with data base requirements and formats, procedure and activity definitions, and mission timeline input formats. Distribution circuit input and fixed data requirements are included. Run procedures and deck setups are described.

Bains, R. W.↗

NASA NTRSDate not supplied

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗

NASA NTRS1996

Man-Machine Interaction Design and Analysis System (MIDAS): Memory Representation and Procedural Implications for Airborne Communication Modalities

The Man-Machine Interaction Design and Analysis System (MIDAS) has been under development for the past ten years through a joint US Army and NASA cooperative agreement. MIDAS represents multiple human operators and selected perceptual, cognitive, and physical functions of those operators as they interact with simulated systems. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. Specific examples include: nuclear power plant crew simulation, military helicopter flight crew response, and police force emergency dispatch. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communications issues connected with aircraft-based separation assurance.

Corker, Kevin M.↗

NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

NASA NTRS1990

A tool for modeling concurrent real-time computation

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Sharma, D. D.↗

NASA NTRS2007

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical radioisotope power system (RPS) launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources were designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Lewandowski, Edward J.↗

NASA NTRS2006

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical RPS launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources was designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Suarez, Vicente J.↗

NASA NTRS2008

Irrigation Requirement Estimation using MODIS Vegetation Indices and Inverse Biophysical Modeling; A Case Study for Oran, Algeria

Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over the study site, for the month of July, spray irrigation resulted in an irrigation amount of about 1.4 mm per occurrence with an average frequency of occurrence of 24.6 hours. The simulated total monthly irrigation for July was 34.85 mm. In contrast, the drip irrigation resulted in less frequent irrigation events with an average water requirement about 57% less than that simulated during the spray irrigation case. The efficiency of the drip irrigation method rests on its reduction of the canopy interception loss compared to the spray irrigation method. When compared to a country-wide average estimate of irrigation water use, our numbers are quite low. We would have to revise the reported country level estimates downward to 17% or less

Bounoua, L.↗

NASA NTRS2017

Energy in a Planetary Context

The potential present day habitability of solar system bodies beyond Earth is limited to subsurface environments, where the availability of energy in biologically useful form is a paramount consideration. Energy availability is commonly quantified in terms of molar Gibbs energy changes for metabolisms of interest, but this can provide an incomplete and even misleading picture. A second aspect of life's requirement for energy - the rate of delivery, or power - strongly influences habitability, biomass abundance, growth rates, and, ultimately, rates of evolution. We are developing an approach to quantify metabolic power, using a cell-scale reactive transport model in which physical and chemical environmental parameters are varied. Simultaneously, we evaluate cell-specific energy flux requirements and their dependence on environmental "extremes". Comparison of metabolic power supply and demand provides a constraint on how biomass abundance varies across a range of environmental parameters, and thereby a prediction of the relative habitability of different environments. We are evaluating the predictive capability of this approach through comparison to observed distributions of microbial abundance in a range of subsurface (predominantly serpentinizing) systems.

MARINE GEOMICROBIOLOGY↗

NASA NTRSDate not supplied

Modeling Spacecraft Power Systems Using the SPACE Code

The NASA Glenn Research Center’s Power Architecture and Analysis Branch performs spacecraft electrical power system (EPS) performance analysis using the System Power Analysis for Capability Evaluation (SPACE) model. Accurately predicting EPS performance requires a wide range of inputs, including the spacecraft’s position, attitude, solar array temperature, load demand, and data on the EPS itself. By operating as a combined analysis tool with integrated orbit mechanics, attitude, shadowing, thermal, solar array, battery, and electrical component models, SPACE provides flexibility for the analyst to examine various scenarios without a time-consuming iterative process involving separate analysis tools and groups. SPACE also achieves short run times by tailoring the complexity of the included models, providing enough fidelity to ensure accurate EPS performance predictions without being bogged down by unnecessary detail. These advantages that SPACE has over similar power system models has contributed to its successful use on a variety of human spaceflight programs for over three decades, and makes it applicable across the development cycle from early conceptual design up through on-orbit operations.

Electrical Power System↗

NASA NTRS1988

Satellite communications experiment for the Ontario air ambulance service

A satellite communications experiment was conducted to develop a reliable voice communications system between paramedics and doctors at certain larger medical centers. The experiment used INMARSAT's Atlantic Ocean Region satellite which provides coverage to the western border of Ontario. Forward downlink power from the satellite is in great demand, so two highly power-efficient modulation schemes were chosen for evaluation during the experiment. These were amplitude-companded single-sideband (ACSSB) and linear predictive coding in conjunction with DMSK modulation. Good performance with a signal to noise ratio of about 10 dB was demonstrated from many parts of the province with the evevation angle to the satellite ranging from five to twenty degrees and with the aircraft both in-flight and on the runway.

Butterworth, John S.↗

NASA NTRS1997

Quantitative Measurement of Oxygen in Microgravity Combustion

A low-gravity environment, in space or in ground-based facilities such as drop towers, provides a unique setting for studying combustion mechanisms. Understanding the physical phenomena controlling the ignition and spread of flames in microgravity has importance for space safety as well as for better characterization of dynamical and chemical combustion processes which are normally masked by buoyancy and other gravity-related effects. Due to restrictions associated with performing measurements in reduced gravity, diagnostic methods which have been applied to microgravity combustion studies have generally been limited to capture of flame emissions on film or video, laser Schlieren imaging and (intrusive) temperature measurements using thermocouples. Given the development of detailed theoretical models, more sophisticated diagnostic methods are needed to provide the kind of quantitative data necessary to characterize the properties of microgravity combustion processes as well as provide accurate feedback to improve the predictive capabilities of the models. When the demands of space flight are considered, the need for improved diagnostic systems which are rugged, compact, reliable, and operate at low power becomes apparent. The objective of this research is twofold. First, we want to develop a better understanding of the relative roles of diffusion and reaction of oxygen in microgravity combustion. As the primary oxidizer species, oxygen plays a major role in controlling the observed properties of flames, including flame front speed (in solid or liquid flames), extinguishment characteristics, flame size and flame temperature. The second objective is to develop better diagnostics based on diode laser absorption which can be of real value in both microgravity combustion research and as a sensor on-board Spacelab as either an air quality monitor or as part of a fire detection system. In our prior microgravity work, an eight line-of-sight fiber optic system measured water vapor mole fractions in the NASA Lewis 2.2-sec Drop Tower. In that system, the laser and all electronics resided at the top of the drop tower and was connected via a fiber optic cable to the rig, on which a 'pitch and catch' set of fiber collimating lenses were used to transmit the laser beam across a jet diffusion flame. This system required eight independent detection/demodulation units and had poor spatial resolution. This research builds on this earlier work, resulting in an improved capability for quantitative, nonintrusive measurement of major combustion species. A vertical cavity surface-emitting diode laser (VCSEL) and a continuous spatial scanning method permit the measurement of temporal and spatial profiles of the concentrations and temperatures of molecular oxygen. High detection sensitivity is achieved with wavelength modulation spectroscopy (WMS). One-g experiments are performed using a slot diffusion flame. Microgravity measurements on a solid fuel (cellulose sheet) system are planned for the NASA Lewis 2.2-second Drop Tower Facility.

Silver, Joel A.↗

NASA NTRS2002

International Space Station Power System Model Validated

System Power Analysis for Capability Evaluation (SPACE) is a computer model of the International Space Station's (ISS) Electric Power System (EPS) developed at the NASA Glenn Research Center. This uniquely integrated, detailed model can predict EPS capability, assess EPS performance during a given mission with a specified load demand, conduct what-if studies, and support on-orbit anomaly resolution.

Hojnicki, Jeffrey S.↗

NASA NTRS1986

Predictive momentum management for the Space Station

Space station control moment gyro momentum management is addressed by posing a deterministic optimization problem with a performance index that includes station external torque loading, gyro control torque demand, and excursions from desired reference attitudes. It is shown that a simple analytic desired attitude solution exists for all axes with pitch prescription decoupled, but roll and yaw coupled. Continuous gyro desaturation is shown to fit neatly into the scheme. Example results for pitch axis control of the NASA power tower Space Station are shown based on predictive attitude prescription. Control effector loading is shown to be reduced by this method when compared to more conventional momentum management techniques.

Hatis, P. D.↗

NASA NTRS1984

Space Power for Communication Satellites Beyond 1995

The space power trends for communication satellites beginning in the mid-70's are reviewed. Predictions of technology advancements and requirements were compared with actual growth patterns. The conclusions derived suggest that the spacecraft power system technology base and present rate of advancement will not be able to meet the power demands of the early to mid-90's. It is recommended that an emphasis on accelerating the technology development be made to minimize the technology gap.

Pierce, P. R.↗