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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

Small Satellite Industrial Base Study: Foundational Findings

This report documents findings from a Small Satellite (SmallSat) Industrial Base Study conducted by The Aerospace Corporation between November 2018 and September 2019. The primary objectives of this study were a) to gain a better understanding of the SmallSat community’s technical practices, engineering approaches, requirements flow-downs, and common processes and b) identify insights and recommendations for how the government can further capitalize on the strengths and capabilities of SmallSat offerings. In the context of this study, SmallSats are understood to weigh no more than 500 kg, as described in “State of the Art Small Spacecraft Technology, NASA/TP-2018- 220027, December 2018. CubeSats were excluded from this study to avoid overlap and duplication of recently completed work or other studies already under way. The team also touched on differences between traditional space-grade and the emerging “mid-grade” and other non-space, alternate-grade EEEE (electrical, electronic, electromechanical, electro-optical) piece part categories. Finally, the participants sought to understand the potential effects of increased use of alternate-grade parts on the traditional space-grade industrial base. The study team was keenly aware that there are missions for which non-space grade parts currently are infeasible for the foreseeable future. National security, long-duration and high-reliability missions intolerant of risk are a few examples. The team sought to identify benefits of alternative parts and approaches that can be harnessed by the government to achieve greater efficiencies and capabilities without impacting mission success.

Allyson D Yarbrough↗

Proceedings of the 2010 NASA-Industry Low Pressure Turbine and Power Turbine (LPT/PT) Efficiency Improvement Workshop

This report includes materials from the NASA-Industry Low Pressure Turbine and Power Turbine (LPT/PT) Efficiency Improvement Workshop that took place on August 10 and 11, 2010, at the NASA Glenn Research Center. The materials include all the presentation slides and a workshop summary article that provides background information, describes the workshop motivation, and provides a summary of the open discussions that took place. Participation included specialists from academia, government laboratories, and industry, from the United States and abroad. The workshop was motivated by underperformance of large commercial engines related to lower-than-expected efficiency of the LPT. It focused on addressing the relevant flow physics. Recommendations were made for continued research. The main recommendation was to conduct rotating rig tests accompanied by the study of fundamental mechanism using computational fluid dynamics (CFD) and turbulence and transition model development.

Transition↗

NASA Engineering and Safety Center Technical Bulletin No. 21-05: Industry Recommendations from Arecibo Observatory Zinc Spelter Socket Joint Failure Analysis

A structural analysis and forensic investigation concluded that the Arecibo Observatory M4N socket joint failure in August 2020 was primarily due to cumulative damage caused by initially low structural design margins and a high percentage of sustained load, resulting in zinc creep deformation, progressive internal socket wire damage, and eventual loss of joint capacity. Open spelter sockets of this type are used throughout industry in stay cables. Recommendations are proposed to prevent failures of similar socket joints, including verification of positive stress margins in socket joint wires for all failure modes, periodic visual inspections with pass/fail criteria for zinc extrusion that are tied to structural qualification, and revisiting codes/ industry standards to capture lessons learned.

Arecibo Observatory↗

Embracing the fourth Industrial Revolution - Challenges, Opportunities and Path Forward for Propulsion

The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.

Machine learning↗

Embracing the Fourth Industrial Revolution - Challenges, Opportunities and Path Forward for Propulsion

The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.

Machine learning↗

ETM Industry: Tabletop Defining Notions for Cooperative Operating Practices

This tabletop plans to cover 3 main topics in regards to the research that NASA has conducted for High-E Traffic Management (ETM), as well as implementing it to stand up an ETM system in the Airspace Operations Lab to invite industry participants to join us in a collaborative evaluation at the end of 2023. (Or earlier for system architectural connectivity). Working to define the notions that go into Cooperative Operating Practices for a collaborative traffic management process, we will be showing and training to some of our early prototype concepts and discussing: 1. Operational Intent: We have built an OI generation tool and would like to discuss specifics to the requirements of OI size, update rates, and duration. 2. Strategic Conflict Detection: We have built a concept to detect overlapping OI’s and would like to discuss the output information; time horizon, geometry and confidence level of intersection. In addition we are looking at a service that would provide all users with additional information in regards to the probability of your actual flight intent getting within a specified separation envelope. 3. Cooperative Operating Practices (COPS): Specifically looking at COPs for strategic deconfliction, we are looking to industry to build the actual COPS based on various criteria; vehicle-to-vehicle interactions, or company to company agreements. What is the strategy when OIs intersect; wait and see, take a pre-negotiated COPS action, or ad-hoc negotiation and discuss what that looks like.

High-E Traffic Management (ETM)↗

Highly Resolved Mapping of NO 2 Vertical Column Densities From GeoTASO Measurements Over a Megacity and Industrial Area During the KORUS-AQ Campaign

The Korea–United States Air Quality (KORUS-AQ) campaign is a joint study between the United States National Aeronautics and Space Administration (NASA) and the South Korea National Institute of Environmental Research (NIER) to monitor megacity and transboundary air pollution around the Korean Peninsula using airborne and ground-based measurements. Here, tropospheric nitrogen dioxide (NO 2 ) slant column density (SCD) measurements were retrieved from Geostationary Trace and Aerosol Sensor Optimization (GeoTASO) L1B data during the KORUS-AQ campaign (2 May to 10 June 2016). The retrieved SCDs were converted to tropospheric vertical column densities using the air mass factor (AMF) obtained from a radiative transfer calculation with trace gas profiles and aerosol property inputs simulated with the Community Multiscale Air Quality (CMAQ) model and surface reflectance data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the first time, we examine highly resolved (250 m × 250 m resolution) tropospheric NO 2 over the Seoul and Busan metropolitan regions and the industrial region of Anmyeon. We reveal that the maximum NO 2 vertical column densities (VCDs) were 4.94×10 16 and 1.46×10 17 molec. cm −2 at 09:00 and 15:00 LT over Seoul, respectively, 6.86×10 16 and 4.89×10 16 molec. cm −2 in the morning and afternoon over Busan, respectively, and 1.64×10 16 molec. cm −2 over Anmyeon. The VCDs retrieved from the GeoTASO airborne instrument were correlated with those obtained from the Ozone Monitoring Instrument (OMI) (r=0.48), NASA's Pandora Spectrometer System (r=0.91), and NO 2 mixing ratios obtained from in situ measurements (r=0.07 in the morning, r=0.26 in the afternoon over the Seoul, and r>0.56 over Busan). Based on our results, GeoTASO is useful for identifying NO 2 hotspots and their spatial distribution in highly populated cities and industrial areas.

Gyo-Hwang Choo↗