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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Accelerated Life Structural Benchmark Testing for a Stirling Convertor Heater Head

For proposed long-duration NASA Space Science missions, the Department of Energy, Lockheed Martin, Infinia Corporation, and NASA Glenn Research Center are developing a high-efficiency, 110 W Stirling Radioisotope Generator (SRG110). A structurally significant limit state for the SRG110 heater head component is creep deformation induced at high material temperature and low stress level. Conventional investigations of creep behavior adequately rely on experimental results from uniaxial creep specimens, and a wealth of creep data is available for the Inconel 718 material of construction. However, the specified atypical thin heater head material is fine-grained with a heat treatment that limits precipitate growth, and little creep property data for this microstructure is available in the literature. In addition, the geometry and loading conditions apply a multiaxial stress state on the component, far from the conditions of uniaxial testing. For these reasons, an extensive experimental investigation is ongoing to aid in accurately assessing the durability of the SRG110 heater head. This investigation supplements uniaxial creep testing with pneumatic testing of heater head-like pressure vessels at design temperature with stress levels ranging from approximately the design stress to several times that. This paper presents experimental results, post-test microstructural analyses, and conclusions for four higher-stress, accelerated life tests. Analysts are using these results to calibrate deterministic and probabilistic analytical creep models of the SRG110 heater head.

Krause, David L.↗
NASA NTRS2007

Development of a Prototype Automation Simulation Scenario Generator for Air Traffic Management Software Simulations

A technique for automated development of scenarios for use in the Multi-Center Traffic Management Advisor (McTMA) software simulations is described. The resulting software is designed and implemented to automate the generation of simulation scenarios with the intent of reducing the time it currently takes using an observational approach. The software program is effective in achieving this goal. The scenarios created for use in the McTMA simulations are based on data taken from data files from the McTMA system, and were manually edited before incorporation into the simulations to ensure accuracy. Despite the software s overall favorable performance, several key software issues are identified. Proposed solutions to these issues are discussed. Future enhancements to the scenario generator software may address the limitations identified in this paper.

Khambatta, Cyrus F.↗
NASA NTRS2012

Managing Small Spacecraft Projects: Less is Not Easier

Managing small, low cost missions (class C or D) is not necessarily easier than managing a full flagship mission. Yet, small missions are typically considered easier to manage and used as a training ground for developing the next generation of project managers. While limited resources can be a problem for small missions, in reality most of the issues inherent in managing small projects are not the direct result of limited resources. Instead, problems encountered by managers of small spacecraft missions often derive from 1) the perception that managing small projects is easier if something is easier it needs less rigor and formality in execution, 2) the perception that limited resources necessitate or validate omitting standard management practices, 3) less stringent or unclear guidelines or policies for small projects, and 4) stakeholder expectations that are not consistent with the size and nature of the project. For example, the size of a project is sometimes used to justify not building a full, detailed integrated master schedule. However, while a small schedule slip may not be a problem for a large mission, it can indicate a serious problem for a small mission with a short development phase, highlighting the importance of the schedule for early identification of potential issues. Likewise, stakeholders may accept a higher risk posture early in the definition of a low-cost mission, but as launch approaches this acceptance may change. This presentation discusses these common misconceptions about managing small, low cost missions, the problems that can result, and possible solutions.

Barley, Bryan↗
NASA NTRS2013

Waterless Clothes-Cleaning Machine

A waterless clothes-cleaning machine has been developed that removes loose particulates and deodorizes dirty laundry with regenerative chemical processes to make the clothes more comfortable to wear and have a fresher smell. This system was initially developed for use in zero-g, but could be altered for 1-g environments where water or other re sources are scarce. Some of these processes include, but are not limited to, airflow, filtration, ozone generation, heat, ultraviolet light, and photocatalytic titanium oxide.

Johnson, Glenn↗
NASA NTRS2010

Goal Selection for Embedded Systems with Oversubscribed Resources

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗
NASA NTRS2010

Onboard Run-Time Goal Selection for Autonomous Operations

We describe an efficient, online goal selection algorithm for use onboard spacecraft and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗
NASA NTRS2009

Tractable Goal Selection with Oversubscribed Resources

We describe an efficient, online goal selection algorithm and its use for selecting goals at runtime. Our focus is on the re-planning that must be performed in a timely manner on the embedded system where computational resources are limited. In particular, our algorithm generates near optimal solutions to problems with fully specified goal requests that oversubscribe available resources but have no temporal flexibility. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. This enables shorter response cycles and greater autonomy for the system under control.

Rabideau, Gregg↗
NASA NTRS2015

Investigation on the Practicality of Developing Reduced Thermal Models

Throughout the spacecraft design and development process, detailed instrument thermal models are created to simulate their on-orbit behavior and to ensure that they do not exceed any thermal limits. These detailed models, while generating highly accurate predictions, can sometimes lead to long simulation run times, especially when integrated with a spacecraft observatory model. Therefore, reduced models containing less detail are typically produced in tandem with the detailed models so that results may be more readily available, albeit less accurate. In the current study, both reduced and detailed instrument models are integrated with their associated spacecraft bus models to examine the impact of instrument model reduction on run time and accuracy. Preexisting instrument bus thermal model pairs from several projects were used to determine trends between detailed and reduced thermal models; namely, the Mirror Optical Bench (MOB) on the Gravity and Extreme Magnetism Small Explorer (GEMS) spacecraft, Advanced Topography Laser Altimeter System (ATLAS) on the Ice, Cloud, and Elevation Satellite 2 (ICESat-2), and the Neutral Mass Spectrometer (NMS) on the Lunar Atmosphere and Dust Environment Explorer (LADEE). Hot and cold cases were run for each model to capture the behavior of the models at both thermal extremes. It was found that, though decreasing the number of nodes from a detailed to reduced model brought about a reduction in the run-time, a large time savings was not observed, nor was it a linear relationship between the percentage of nodes reduced and time saved. However, significant losses in accuracy were observed with greater model reduction. It was found that while reduced models are useful in decreasing run time, there exists a threshold of reduction where, once exceeded, the loss in accuracy outweighs the benefit from reduced model runtime.

0000↗
NASA NTRS2020

High Pressure Transcritical Combustion (HPTC Combustion)

Combustion is the predominant source of the energy in the US and worldwide, and an overwhelming majority in the transportation sector, particularly liquid hydrocarbons (i.e., gasoline, diesel and jet fuel). Engine manufacturers move to higher operating pressures, above and beyond the critical pressures of the fuel, in order to optimize performance, maximize efficiency and reduce pollutant formation. The design of the next generation of engines, however, are limited by a lack of fundamental understanding of the thermo-physical properties, fluid behavior and chemical kinetics at these high pressures. Terrestrial laboratory studies are hampered by the ubiquitous buoyant flow that renders fundamental experiments difficult and/or impossible to interpret. Studying high pressure transcritical phenomena in microgravity allows researchers to investigate the fundamental aspects of phase change, chemical kinetics and property evaluation in a simplified geometry without the complicating influence of a buoyancy-induced flow.

Combustion↗
NASA NTRS2020

Winter Arctic Sea Ice Thickness from ICESat-2 Freeboards

NASA’s ICESat-2 mission was launched in September 2018 with the primary goal of monitoring our rapidly changing polar regions. The sole instrument onboard, the Advanced Topographic Laser Altimeter System (ATLAS), is now providing routine, very high-resolution, surface elevation data across the globe, including the Arctic and Southern Oceans. In this study we demonstrate our new processing chain for converting the along-track ICESat-2 sea ice freeboard product (ATL10) into sea ice thickness, focusing our initial efforts on the Arctic Ocean. For this conversion we primarily make use of snow depth and density data from the NASA Eulerian Snow on Sea Ice Model (NESOSIM). The coarse resolution (~100 km) snow data are redistributed onto the high resolution (~30 - 100 m) ATL10 freeboards using relationships obtained from snow depth and freeboard data collected by NASA’s Operation IceBridge mission. We present regional sea ice thickness distributions and highlight their seasonal evolution through our first winter-season of data collection. We include ice thickness uncertainty estimates, while also acknowledging the limitations of these estimates. We generate a gridded monthly thickness product and compare this with various monthly sea ice thickness estimates obtained from ESA’s CryoSat-2 satellite mission, with ICE 33 Sat-2 showing consistently lower thicknesses. Finally, we compare our February/March 2019 thickness estimates to ICESat February/March (19th February – 21st March) 2008 ice thickness estimates using the same input assumptions, which show a ~0.40 m or ~21% thinning across an inner Arctic Ocean domain in this 11-year time period.

Alek A Petty↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

Research into parachute performance continues to be a source of significant investment from the National Aeronautics and Space Administration to mitigate risks and to enable a variety of exploration missions, including landing on Mars as well as returning to Earth. The cost of flight tests to certify any changes to the current state-of-the-art parachute designs limits the development of next generation parachute systems. Fluid-structure interaction simulations could help accelerate this process once validated. The Launch, Ascent, and Vehicle Aerodynamics team is developing the capability to perform such fluid-structure interaction simulations by coupling a higher-order Cartesian immersed boundary computational fluid dynamics solver with adaptive mesh refinement to a finite element structural dynamics solver in space and time. We continue the effort to validate this tool with the Advanced Supersonic Parachute Inflation Research Experiments SR03 flight test featuring a strengthened parachute akin to the Mars 2020 mission that landed the Perseverance rover on Mars, and a higher freestream dynamic pressure prior to inflation. The effect of the flow conditions’ angle of attack and of the initial parachute shape are quantified. The impact of relaxing modeling assumptions with regards to radial stiffeners on the parachute canopy is also investigated. Results demonstrate improvements in agreement with the pull force recorded during the SR03 flight test as the initial conditions of the flow and parachute are brought closer to those experienced in flight, and further improved when the radial stiffener modeling assumptions are relaxed.

ESM↗
NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

Research into parachute performance continues to be a source of significant investment from the National Aeronautics and Space Administration to mitigate risks and to enable a variety of exploration missions, including landing on Mars as well as returning to Earth. The cost of flight tests to certify any changes to the current state-of-the-art parachute designs limits the development of next generation parachute systems. Fluid-structure interaction simulations could help accelerate this process once validated. The Launch, Ascent, and Vehicle Aerodynamics team is developing the capability to perform such fluid-structure interaction simulations by coupling a higher-order Cartesian immersed boundary computational fluid dynamics solver with adaptive mesh refinement to a finite element structural dynamics solver in space and time. We continue the effort to validate this tool with the Advanced Supersonic Parachute Inflation Research Experiments SR03 flight test featuring a strengthened parachute akin to the Mars 2020 mission that landed the Perseverance rover on Mars, and a higher freestream dynamic pressure prior to inflation. The effect of the flow conditions’ angle of attack and of the initial parachute shape are quantified. The impact of relaxing modeling assumptions with regards to radial stiffeners on the parachute canopy is also investigated. Results demonstrate improvements in agreement with the pull force recorded during the SR03 flight test as the initial conditions of the flow and parachute are brought closer to those experienced in flight, and further improved when the radial stiffener modeling assumptions are relaxed.

ESM↗
NASA NTRSDate not supplied

Quantification of Numerical Uncertainty via Nonlinear Dynamical Approach

Motivations (Ensure a Higher Level of Confidence in the Predictability & Reliability of Numerical Simulation for Multiscale Complex Nonlinear Fluid Problems) - The last two decades have been an era when computation is ahead of analysis & when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems & non-traditional fields (Especially when computations offer the ONLY way of generating this type of data limited simulations). - At present some of the numerical uncertainties can be explained and minimized by traditional numerical analysis and standard CFD practices. However, such practices, usually based on linearized analysis, MIGHT NOT be sufficient for strongly nonlinear and/or stiff problems. - We need a good understanding of the nonlinear behavior of numerical schemes being used as an integral part of code verification, validation and certification.

HEC↗
NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

BACKGROUND The medical capabilities necessary for long-duration exploration missions (LDEMs) will differ tremendously from those currently available to crew medical officers (CMOs) on the International Space Station (ISS). Ground support will be more challenging due to distance-related communication delays and data transmission, and resource utilization must be optimized given limited ability for resupply. Clinical decision support systems (CDSSs) can help mitigate these limitations. The recent launch of generative artificial intelligence (AI) tools based upon large language models (LLM) support the creation of a smart assistant for onboard triage, diagnosis, and guided treatment of medical conditions during these missions. The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool can help predict which clinical problems and outcomes are likely to occur for a design reference mission (DRM) and assist Medical Operations and systems engineering teams in creating a medical system that may optimally mitigate the predicted risks. The purpose of this study was to identify AI tools currently available or in development for the assistive diagnosis and care of medical conditions predicted for an extended duration Lunar mission. METHODS The 119 medical conditions currently built into the IMPACT suite were categorized into systems, and these diagnoses were used as keywords for our literature search. Using PubMed and Google Scholar, we performed a literature survey of AI tools applicable to these conditions. Article inclusion criteria included publication between the years 2017-2023, as the sentinel paper discussing the “selective attention” driving ChatGPT and other generative transformer models was published in June 2017. Where applicable, we reviewed only the top 1000 research articles (based on relevance) for each of the keywords/phrases. AI tools whose training sets were exclusive to a pediatric patient population were excluded. We also excluded any medical diagnostic tools (such as CT, MRI, mass spectrometry) or procedures (such as endoscopy, surgery) that are unlikely to be available during LDEMs due to mass and volume constraints, CMO knowledge, skills, and abilities, and/or inherent procedural risks. RESULTS Our survey highlighted several AI-driven tools for the triage, diagnosis, and management of those medical conditions highlighted by IMPACT. Selected publications for each medical condition were then screened for inclusion within ten systems-based categories including: general diagnostic tools (25), tools to diagnose and manage respiratory (40), dermatologic (34), neurologic (28), auditory and vestibular (30), ophthalmic (34), musculoskeletal (104), infection-associated (92), and gynecologic (19) conditions, as well as tools that could be deployed in the setting of trauma and emergency (34). CONCLUSIONS Numerous AI-driven tools were highlighted within this literature survey, ranging from chatbot assistants that triage knee pain to vision transformer models for diagnosis of ophthalmic conditions using ocular surface images captured with a mobile phone. Remaining challenges include optimizing connectivity and integration of existing and developing systems into the vehicles or habitats. Notably, findings from this survey could help guide the initial design of an all-encompassing, onboard medical AI assistant for use during future LDEMs.

R A Lacinski↗
NASA NTRSDate not supplied

Evaluation of Particle Degradation of a Ytterbium Disilicate Gas Turbine Coating in a Combustion Environment

Ytterbium disilicate (Yb2Si2O7) is a state-of-the-art topcoat material used in environmental barrier coatings (EBCs) to protect SiC-SiC composites from water vapor corrosion in gas turbine engines. However, it’s degradation by thermochemical and thermomechanical particle interactions may limit its use in next generation engine systems. Several static furnace tests have been performed on Yb2Si2O7 to elucidate methods of degradation, although dynamic testing in an engine-relevant environment has not been carried out. Ultimately, testing and evaluation of materials that incorporates all environmental damage modes will allow for an accurate assessment of long-term durability and operating lifetime. This work details the investigation of particle-induced erosion and corrosion of Yb2Si2O7 in NASA Glenn’s Erosion Burner Rig Facility. Coating durability was investigated as a function of test temperature, particle size, and deposition rate. Thermal cycling was also incorporated into testing to determine the interplay of heating/cooling cycles with particle degradation. Overall, these analyses will be used to determine coating robustness in an engine relevant environment.

Jamesa L Stokes↗