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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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449 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Optical characterization of solar concentrator mirrors using the solar beam of the JPL 25-foot space simulator

The Jet Propulsion Laboratory 25-foot space simulator with its 5.8-m (19-ft) diameter simulated solar beam provides an excellent facility for measuring the optical characteristics of parabolic solar concentrator panels and gores. The virtual source position and size were determined by using a single lamp of the 37 xenon 30-kW source array with only the center lens in the 19-channel optical mixer. This data was used to define the optical test geometry, and it allowed accurate measurement of focal length and surface deviations of the mirror under test. A flux distribution of a typical solar concentrator placed directly on the solar beam gives measurements of performance at the focal point of the parabolic surface.

Maurice J Argoud↗
NASA NTRS1985

NASA Scatterometer Oceanic Wind Measurement System

Satellite scatterometers are active microwave radars designed to yield measurements of near surface horizontal wind velocity over the ocean. Scatterometers are unique in that they are the only existing microwave remote sensing instruments that allow measurements of both wind speed and wind direction. NASA will fly a scatterometer, NSCAT, aboard the Navy Ocean Remote Sensing System (N-ROSS) mission starting in late 1990. N-ROSS is a spaceborne ocean remote sensing system with a planned mission life of three years. In addition to the NSCAT, N-ROSS will have three other microwave instruments mounted on a single satellite flying in a near polar orbit: an altimeter; a special sensor microwave/imager (SSM/I); and a low frequency microwave radiometer. The NSCAT to be flown on N-ROSS is described.

M Freilich↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. Data-driven techniques have a number of advantages over other methods for monitoring complex space vehicles. Unlike model-based systems, the developer does not need to understand or encode the internal operation of the system. The knowledge required to monitor the system is automatically derived from archived data from system operation. Unlike rule-based systems, data-driven systems do not require system analysts to define nominal relationships among sensors. Analysts can and often do determine these relationships for a system with few sensors; it is more difficult to analytically determine the nominal relationship among a large number of sensors. Data-driven techniques are not limited to low-dimensional spaces and work as effectively with dozens of parameters as they do with a few. Knowledge bases formed by data-driven techniques are also easy to update. As the operating envelope of the monitored system is expanded, data-driven techniques can be quickly retrained to incorporate the new behavior into the knowledge base. The expertise and time-consuming process of updating a model or rule base to maintain consistency with the new operation is not required. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or analysis of archived events. System data is compared with the nominal IMS model to produce a measure of how well current system behavior matches the normal behavior defined by the training data. Significant deviations from the nominal system model can provide alerts to system malfunctions or precursors of significant failures. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments. Initially, the TVSM software will run open loop, providing system health information and recommendations to ground operators, without automatically performing fault-mitigating corrective actions. After the end of the satellite's mission, closed loop tests combining TVSM monitoring and diagnosis with reactive capabilities by the flight software will be performed. In addition to monitoring for long periods of actual operation, the experiment will include fault injection into TacSat-3 data as well as commanded operations to test and evaluate automatic ISHM monitoring and recovery under controlled conditions.

Satellites↗
NASA NTRS2026

Scientific Highlights and Status of the Mars Science Laboratory Mission, Years 9 through 12

We present the scientific highlights and status from years 9-12 of NASA’s Mars Science Laboratory mission, with its Curiosity rover. A thermochemolysis-based sample analysis revealed a variety of organic molecules preserved in clay mineral-rich lake/lake margin deposits of the Glen Torridon region. The stratigraphically higher clay-sulfate mineral transition on Aeolis Mons was found to be associated with a lithological change from lacustrine to dry aeolian depositional environments. Water intermittently returned to the surface after the increase in aridity, including during the deposition of wave ripple strata which indicate a climate capable of sustaining an ice-free lake in the early Hesperian. The overlying Mg sulfate-bearing unit has both poly- and monohydrated Mg sulfates and is also enriched in iron carbonate of a purity consistent with chemical sedimentation and therefore atmospheric sequestration. A channel-incised canyon within Gediz Vallis and distal alluvial deposits recorded numerous fluvial and debris flow events after the deposition, lithification, and erosion of the clay- and sulfate-bearing units. Bright clasts found in Gediz Vallis canyon are composed of native sulfur. The investigation of the modern atmosphere and environment focused on the influence of the crater and mountain topography and captured high-altitude noctilucent and iridescent clouds. Radiation monitoring now spans an 11-year solar cycle. Rover systems and science instruments remain capable of addressing mission scientific objectives. All ten scientific instruments continue to return high-value data despite degradation of the Chemistry and Camera instrument’s high-voltage system, loss of multispectral imaging capability, and loss of active neutron spectroscopy. The mission has mitigated the loss of redundant brakes on two arm joints, additional wheel wear, and highly reduced capability of the redundant flight computer. Efficiency improvements in rover energy utilization and operations staffing have allowed the mission team to maintain a high level of productivity despite declining rover power generation and funding.

Mars↗
NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗
NASA NTRS1965

Aerodynamic Design of Axial Flow Compressors

An overview of 'Aerodynamic systems design of axial flow compressors' is presented. Numerous chapters cover topics such as compressor design, potential and viscous flow in two dimensional cascades, compressor stall and blade vibration, and compressor flow theory. Theoretical aspects of flow are also covered. This work is based substantially on a three-volume Confidential Research Memorandum f h t issued by the National Advisory Committee for Aeronautics in 1956 and declassified in .1958 for release to the general public. The material, which was of a fundamental character, has been updated for the present edition in the light of subsequent developments in the field and has been carefully reexamined for current validity by members of the staff of the NASA Lewis Research Center, Cleveland, Ohio. It is now published for the first time in a single volume to meet continuing demand for the information and to make it readily available in convenient form to the engineering community both within and outside the National Aeronautics and Space Administration.

Axial flow compressor↗
NASA NTRS2019

Safe, High Power/Voltage Battery Module Design Challenges

NASA seeks to demonstrate a path for achieving safe, high power, and high performing Li-ion battery designs for the purpose of establishing design guidelines for our aeronautic and spacecraft applications. Safe means passively resistant to thermal runaway propagation of any single cell catastrophic thermal runaway. High power means capable of 3C continuous discharge without overheating. High performing means achieving > 160 Wh/kg, 200 Wh/L. The biggest challenge has been balancing a high flux light weight path for cell heat dissipation during the high rate discharge that minimizes thermal gradients between cells and also protects adjacent cells from the heat load of thermal runaway cell. Our solution includes an oscillating heat pipe spine that contacts every 18650 cell in the pack and careful cell design selection to maximize the range of initial temperatures conditions where the battery can safely complete the 3C discharge.

Thermal runaway↗
NASA NTRS2026

Adaptation and Response in Drylands (ARID): A Dryland Research Agenda and Campaign Strategy

Dryland ecosystems cover 41% of Earth’s land surfaces, account for 44% of cultivated lands and 60% of food sources, and make large contributions to the global water and carbon cycles. However, these ecosystems are experiencing unprecedented extremes including heatwaves, floods, and droughts as well as hotter temperatures and often declining water resource availability. These ecosystems are some of the most challenging to monitor given their high temporal variability with rapid response to their environment as well as vast spatial variability with intermixing of different plant species and life forms amongst bare soil coverage. The Adaptation and Response in Drylands (ARID) campaign was selected by National Aeronautics and Space Administration (NASA) as a scoping study to develop a research agenda for a dryland field campaign. Here, we detail our ARID science research agenda and implementation plan that were developed based on an extensive community engagement effort in over 160 events with over a thousand scientists, land managers, and Tribal communities between 2023 and 2024. The selected science themes cover drought and climate variability, ecosystem structure, function, and biodiversity, carbon cycle interannual variability and trends, and social ecological systems (land management and adaptation). We then detail our remote sensing, modeling, and field-based strategies to capture high temporal and high spatial resolution processes. Finally, our implementation strategy is presented which includes focus area selections in a core intensive western U.S. domain and distributed international domains. This strategy includes our overarching guiding principles of using multi-temporal airborne acquisitions and super sites as well as enhancing land management in co-development with end-user partners. While originally developed for NASA, our ARID report creates a blueprint for any future dryland field campaign, at any scale, that can be implemented widely for foundational and applied science objectives.

drylands↗