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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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174 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Variable Conductance Heat Pipe Cooling of Stirling Convertor and General Purpose Heat Source

In a Stirling Radioisotope Power System (RPS), heat must be continuously removed from the General Purpose Heat Source (GPHS) modules to maintain the modules and surrounding insulation at acceptable temperatures. The Stirling convertor normally provides this cooling. If the Stirling convertor stops in the current system, the insulation is designed to spoil, preventing damage to the GPHS at the cost of an early termination of the mission. An alkali-metal Variable Conductance Heat Pipe (VCHP) can be used to passively allow multiple stops and restarts of the Stirling convertor. In a previous NASA SBIR Program, Advanced Cooling Technologies, Inc. (ACT) developed a series of sodium VCHPs as backup cooling systems for Stirling RPS. The operation of these VCHPs was demonstrated using Stirling heater head simulators and GPHS simulators. In the most recent effort, a sodium VCHP with a stainless steel envelope was designed, fabricated and tested at NASA Glenn Research Center (GRC) with a Stirling convertor for two concepts; one for the Advanced Stirling Radioisotope Generator (ASRG) back up cooling system and one for the Long-lived Venus Lander thermal management system. The VCHP is designed to activate and remove heat from the stopped convertor at a 19 degC temperature increase from the nominal vapor temperature. The 19 degC temperature increase from nominal is low enough to avoid risking standard ASRG operation and spoiling of the Multi-Layer Insulation (MLI). In addition, the same backup cooling system can be applied to the Stirling convertor used for the refrigeration system of the Long-lived Venus Lander. The VCHP will allow the refrigeration system to: 1) rest during transit at a lower temperature than nominal; 2) pre-cool the modules to an even lower temperature before the entry in Venus atmosphere; 3) work at nominal temperature on Venus surface; 4) briefly stop multiple times on the Venus surface to allow scientific measurements. This paper presents the experimental results from integrating the VCHP with an operating Stirling convertor and describes the methodology used to achieve their successful combined operation.

Tarau, Calin↗
NASA NTRS2013

Alkali Metal Backup Cooling for Stirling Systems - Experimental Results

In a Stirling Radioisotope Power System (RPS), heat must be continuously removed from the General Purpose Heat Source (GPHS) modules to maintain the modules and surrounding insulation at acceptable temperatures. The Stirling convertor normally provides this cooling. If the Stirling convertor stops in the current system, the insulation is designed to spoil, preventing damage to the GPHS at the cost of an early termination of the mission. An alkali-metal Variable Conductance Heat Pipe (VCHP) can be used to passively allow multiple stops and restarts of the Stirling convertor. In a previous NASA SBIR Program, Advanced Cooling Technologies, Inc. (ACT) developed a series of sodium VCHPs as backup cooling systems for Stirling RPS. The operation of these VCHPs was demonstrated using Stirling heater head simulators and GPHS simulators. In the most recent effort, a sodium VCHP with a stainless steel envelope was designed, fabricated and tested at NASA Glenn Research Center (GRC) with a Stirling convertor for two concepts; one for the Advanced Stirling Radioisotope Generator (ASRG) back up cooling system and one for the Long-lived Venus Lander thermal management system. The VCHP is designed to activate and remove heat from the stopped convertor at a 19 C temperature increase from the nominal vapor temperature. The 19 C temperature increase from nominal is low enough to avoid risking standard ASRG operation and spoiling of the Multi-Layer Insulation (MLI). In addition, the same backup cooling system can be applied to the Stirling convertor used for the refrigeration system of the Long-lived Venus Lander. The VCHP will allow the refrigeration system to: 1) rest during transit at a lower temperature than nominal; 2) pre-cool the modules to an even lower temperature before the entry in Venus atmosphere; 3) work at nominal temperature on Venus surface; 4) briefly stop multiple times on the Venus surface to allow scientific measurements. This paper presents the experimental results from integrating the VCHP with an operating Stirling convertor and describes the methodology used to achieve their successful combined operation.

Schwendeman, Carl↗
NASA NTRS2014

Development and Characterization of Embedded Sensory Particles Using Multi-Scale 3D Digital Image Correlation

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

Cornell, Stephen R.↗
NASA NTRS2013

Investigation of Insulation Materials for Future Radioisotope Power Systems (RPS)

NASA's Radioisotope Power System (RPS) Technology Advancement Project is developing next generation high temperature insulation materials that directly benefit thermal management and improve performance of RPS for future science missions. Preliminary studies on the use of multilayer insulation (MLI) for Stirling convertors used on the Advanced Stirling Radioisotope Generator (ASRG) have shown the potential benefits of MLI for space vacuum applications in reducing generator size and increasing specific power (W/kg) as compared to the baseline Microtherm HT (Microtherm, Inc.) insulation. Further studies are currently being conducted at NASA Glenn Research Center (GRC) on candidate MLI foils and aerogel composite spacers. This paper presents the method of testing of foils and spacers and experimental results to date.

Cornell, Peggy A.↗
NASA NTRS2013

Investigation of Insulation Materials for Future Radioisotope Power Systems

NASA's Radioisotope Power Systems (RPS) Technology Advancement Project is developing next generation high-temperature insulation materials that directly benefit thermal management and improve performance of RPS for future science missions. Preliminary studies on the use of multilayer insulation (MLI) for Stirling convertors used on the Advanced Stirling Radioisotope Generator (ASRG) have shown the potential benefits of MLI for space vacuum applications in reducing generator size and increasing specific power (W/kg) as compared to the baseline Microtherm HT (Microtherm, Inc.) insulation. Further studies are currently being conducted at NASA Glenn Research Center on candidate MLI foils and aerogel composite spacers. This paper presents the method of testing of foils and spacers and experimental results to date.

Cornell, Peggy A.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-17800-DND

Currently, there are two national challenge problems that guide much of the research in durability and damage tolerance at NASA Langley. The first, Airframe Digital Twin, is a concept that combines as-built vehicle components, as-experienced loads and environments, and other vehicle-specific characteristics to enable ultrahigh fidelity modeling of aircraft and spacecraft throughout their service lives. The second, Materials Genome Initiative, is an analog to the Human Genome Project, and is intended to improve the rate at which materials scientists can discover, understand fundamental physics, and improve material systems. This presentation will highlight several research projects ongoing at NASA Langley that are in support of the above challenge problems. Two of those topics will be the subject of detailed discussion. First, investigations of microstructurally-small fatigue cracking (MSFC) in Al-2Cu and Al-4Cu, fabricated in-house, will be presented. Single- and oligo-crystals of Al-Cu specimens were loaded in uniaxial fatigue, while high-resolution in-situ measurements of deformation were made using image correlation (IC) in a scanning-electron microscope (SEM). The Al-Cu specimens were then replicated as crystal plasticity finite element models (CPFEM), where evolution of slip localization near grain boundaries was computed. Comparison among experiment and CPFEM is made. In addition, XRay diffraction measurements of the as-fabricated specimens were carried out, where direct measurements of the embedded copper precipitates were made, and their influence on growing MSFCs were directly observed. The second main topic will illustrate ongoing work in the area of so-called damage-sensing particles. In this work, shape-memory alloys are embedded in an aluminum alloy matrix. Upon the propagation of a fatigue crack, these particles undergo a strain-induced phase transformation which is detected using an acoustic sensor, providing real-time information on propagating cracks. Experiments and simulations regarding the development of this system will also be detailed.

Jacob Hochhalter↗
NASA NTRSDate not supplied

Revolutionary Vertical Lift Technology (RVLT) Overview

The Aircraft Working Group enables the Advanced Air Mobility (AAM) ecosystem through vehicle development and production as well as individual vehicle management and operations. Aircraft design and operations management develop AAM-inspired concepts and technologies to help define requirements and standards addressing key challenges such as safety, integration, noise, automation, and scalability. This presentation focuses on RVLT electronic Vertical Takeoff Landing Propulsion overview.

Peggy Cornell↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
NASA NTRSDate not supplied

A Knowledge Graph Framework for Organizing Heterogeneous Datasets for Utilization in Classical and Quantum Computing: Current Challenges and Future Directions

"The escalating impact of climate change induced extreme weather events in urban, suburban, and rural environments demands a rethink of how we have been using the single event-based or use-case-based knowledge graph models. The lack of representation in interaction within environmental variables found in literature led to the development of a novel framework that reflects the true nature of the interconnectedness in our environment. We propose an Environmental Interaction Knowledge Graph (EIKG) framework. This general EIKG framework works as the basis for interconnected environmental events by knitting interrelated events such as hurricanes leading to storm surges, which lead to flood events that could cause mudslides, landslides, etc., The cascading nature of one event leading to another related event in the environment requires an adequate understanding of each event using contextual information before conducting any data-driven analytics. This vision paper showcases how the EIKG:floods, EIKG:wildfire EIKG:landslides, etc, can be derived from a base case framework of EIKG as those individual events are interconnected with some common denominator variables. As an example, the precipitation variable is used in the flood case study as well as in the wildfire case study, as excessive precipitation levels lead to floods, and lack of precipitation leads to droughts and wildfires. We identify the precipitation variable as a “common-denominator-variable” in extreme weather events that play a key role in modeling the environment leading to different extreme weather events based on the variability of that variable (varying values where low precipitation leads to drought, and high values lead to floods). We use the insights gained from EIKG to conduct classical and Quantum Machine Learning (QML) based data analysis on the research questions developed. Our preliminary study shows how the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC) are used along with the classical machine learning models to compare the model accuracies. Our study elaborates on how a quantitative analysis uses state-of-the-art machine learning techniques that include implementing both classical and quantum machine learning models and developing the knowledge graph. The EIKG is used to organize heterogeneous datasets and integrate the relations to case-specific extreme weather events such as floods. The study uses datasets such as county-to-country residential mobility data, socioeconomic datasets from the US Census Bureau, climate and weather-related Earth Observational data from NASA, and critical infrastructure data from the Homeland Infrastructure datasets."

Knowledge Graphs, Quantum Computing, Heterogenous ↗