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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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The design and development of a unique coupler crossbar 20 x 20 microwave switch matrix are described. The test results of the proof of concept model that meets the requirements for a high speed satellite switched, time division multiple access (SS-TDMA) system are presented.
We have carried out a proof-of-concept development and test effort that not only promises the reduction of parasitic effects of surface contamination (therefore increasing the integrity of 'in situ' measurements in the 60-130 km regime), but promises a uniquely expanded measurement set that includes electron densities, plasma conductivities, charged-particle mobilities, and mass discrimination of positive and negative ion distributions throughout the continuum to free-molecular-flow regimes. Three different sensor configurations were designed, built and tested, along with specialized driving voltage, electrometer and channeltron control electronics. The individual systems were tested in a variety of simulated space environments ranging from pressures near the continuum limit of 100 mTorr to the collisionless regime at 10(exp -6) Torr. Swept modes were initially employed to better understand ion optics and ion 'beam' losses to end walls and to control electrodes. This swept mode also helped better understand and mitigate the influences of secondary electrons on the overall performance of the PIMS design concept. Final results demonstrated the utility of the concept in dominant single-ion plasma environments. Accumulated information, including theoretical concepts and laboratory data, suggest that multi-ion diagnostics are fully within the instrument capabilities and that cold plasma tests with minimized pre-aperture sheath acceleration are the key ingredients to multi-ion success.
The Abort Region Determinator (ARD) is a console program in the space shuttle mission control center. During shuttle ascent, the Flight Dynamics Officer (FDO) uses the ARD to determine the possible abort modes and make abort calls for the crew. The goal of the Rule-based Abort region Determinator (RB/ARD) project was to test the concept of providing an onboard ARD for the shuttle or an automated ARD for the mission control center (MCC). A proof of concept rule-based system was developed on a LMI Lambda computer using PICON, a knowdedge-based system shell. Knowdedge derived from documented flight rules and ARD operation procedures was coded in PICON rules. These rules, in conjunction with modules of conventional code, enable the RB-ARD to carry out key parts of the ARD task. Current capabilities of the RB-ARD include: continuous updating of the available abort mode, recognition of a limited number of main engine faults and recommendation of safing actions. Safing actions recommended by the RB-ARD concern the Space Shuttle Main Engine (SSME) limit shutdown system and powerdown of the SSME Ac buses.
The next generation geodetic VLBI instrument is being developed with a goal of 1 mm position uncertainty in twenty-four hours. We have implemented a proof-of-concept system for a possible VLBI2010 signal chain, from feed through recorder, on the Westford (Massachusetts, USA) 18-m and MV-3 (Maryland, USA) 5-m antennas. Data have been obtained in four 512 MHz bands spanning the range 3.5 to 11 GHz to investigate the sensitivity and phase delay capability of the system. Using a new phase cal design, the phases have been aligned across four bands spanning 2 GHz with an RMS deviation of approximately eight degrees. Several components of the system will be improved for the prototype version of VLBI2010, including the feed, digital backend, and recorder, and these will be installed on a 12-m antenna that has been purchased and is ready for installation at the Goddard Space Flight Center outside of Washington, D.C., USA, site of the MV-3 antenna.
Low power Stirling convertors are being developed at NASA Glenn Research Center (GRC) to provide future small spacecraft with electrical power by converting heat from one or more Light Weight Radioisotope Heater Units (LWRHU). An initial design converts multiple watts of heat to one watt of electrical power output using a Stirling convertor. A variety of mission concepts have been studied by NASA and the U. S. Department of Energy (DOE) that would utilize low power Radioisotope Power Systems (RPS) for probes, landers, rovers, and repeaters. These missions would contain science instruments distributed across planetary surfaces or near objects of interest where solar flux is insufficient for using solar cells. Landers could be used to provide data such as, radiation, temperature, pressure, seismic activity, and other surface measurements for planetary science and to inform future mission planners. The studies propose using fractional versions of the General Purpose Heat Source (GPHS) or multiple LWRHUs to heat power conversion technologies for science instruments and communication. Dynamic power systems are capable of higher conversion efficiencies, which could enable equal power using less fuel or more power using equal fuel, when compared to less efficient static power conversion technologies. Providing spacecraft with more power would decrease duty cycling of basic functions and, therefore, increase the quality and abundance of science data. Efforts to develop the concept have focused on maturation of a 1-We convertor and controller design and performance evaluation of an evacuated metal foil insulation. A proof-of-concept 1-We convertor, controller, and evacuated metal foil insulation package have been fabricated and are undergoing characterization testing. The current status, findings, and path forward for the effort are explained in this paper.
Low power Stirling convertors are being developed at NASA Glenn Research Center to provide future small spacecraft with electrical power by converting heat from one or more Light Weight Radioisotope Heater Units (LWRHU). An initial design converts multiple watts of heat to one watt of electrical power output using a Stirling convertor. A variety of mission concepts have been studied by NASA and the U. S. Department of Energy that would utilize low power Radioisotope Power Systems (RPS) for probes, landers, rovers, and repeaters. These missions would contain science instruments distributed across planetary surfaces or near objects of interest where solar flux is insufficient for using solar cells. Landers could be used to provide data such as, radiation, temperature, pressure, seismic activity, and other surface measurements for planetary science and to inform future mission planners. The studies propose using fractional versions of the General Purpose Heat Source or multiple LWRHUs to heat power conversion technologies for science instruments and communication. Dynamic power systems are capable of higher conversion efficiencies, which could enable equal power using less fuel or more power using equal fuel, when compared to less efficient static power conversion technologies. Providing spacecraft with more power would decrease duty cycling of basic functions and, therefore, increase the quality and abundance of science data. Efforts to develop the concept have focused on maturation of a 1-We convertor and controller design and performance evaluation of an evacuated metal foil insulation. A proof-of-concept 1-We convertor, controller, and evacuated metal foil insulation package have been fabricated and are undergoing characterization testing. The current status, findings, and path forward for the effort are explained in this paper.
Low power Stirling convertors are being developed at NASA Glenn Research Center (GRC) to provide future small spacecraft with electrical power by converting heat from one or more Light Weight Radioisotope Heater Units (LWRHU). An initial design converts multiple watts of heat to one watt of electrical power output using a Stirling convertor. A variety of mission concepts have been studied by NASA and the U.S. Department of Energy (DOE) that would utilize low power Radioisotope Power Systems (RPS) for probes, landers, rovers, and repeaters. These missions would contain science instruments distributed across planetary surfaces or near objects of interest where solar flux is insufficient for using solar cells. Landers could be used to provide data such as, radiation, temperature, pressure, seismic activity, and other surface measurements for planetary science and to inform future mission planners. The studies propose using fractional versions of the General Purpose Heat Source (GPHS) or multiple LWRHUs to heat power conversion technologies for science instruments and communication. Dynamic power systems are capable of higher conversion efficiencies, which could enable equal power using less fuel or more power using equal fuel, when compared to less efficient static power conversion technologies. Providing spacecraft with more power would decrease duty cycling of basic functions and, therefore, increase the quality and abundance of science data. Efforts to develop the concept have focused on maturation of a 1-We (1-watt electrical) convertor and controller design and performance evaluation of an evacuated metal foil insulation. A proof-of-concept 1-We convertor, controller, and evacuated metal foil insulation package have been fabricated and are undergoing characterization testing. The current status, findings, and path forward for the effort are explained in this paper.
SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the second of six in the Data Quality and Uncertainty Integration project, develops the proof of concept, including programming in C and a collection of spreadsheet tools, for estimating the operational uncertainty from three-component solar irradiance measurements using information available from SERI QC. The report establishes a field reference for determining the operational uncertainty for each irradiance component based on the SERI QC coupling. Results demonstrate that the operational uncertainty estimates based on global irradiance best represent the collective results for all sky conditions.
Machine learning (ML) models can handle large data sets without assuming underlying relationships and can be useful for evaluating disease characteristics, yet they are more commonly used for predicting individual disease risk than for identifying factors at the population level. We offer a proof of concept applying random forest (RF) algorithms to Candida-positive hospital encounters in an electronic health record database of patients in the United States. Candida-positive encounters were extracted from the Cerner HealthFacts database; invasive infections were laboratory-positive sterile site Candida infections. Features included demographics, admission source, care setting, physician specialty, diagnostic and procedure codes, and medications received before the first positive Candida culture. We used RF to assess risk factors for 3 outcomes: any invasive candidiasis (IC) vs non-IC, within-species IC vs non-IC (eg, invasive C. glabrata vs noninvasive C. glabrata), and between-species IC (eg, invasive C. glabrata vs all other IC). Fourteen of 169 (8%) variables were consistently identified as important features in the ML models. When evaluating within-species IC, for example, invasive C. glabrata vs non-invasive C. glabrata, we identified known features like central venous catheters, intensive care unit stay, and gastrointestinal operations. In contrast, important variables for invasive C. glabrata vs all other IC included renal disease and medications like diabetes therapeutics, cholesterol medications, and antiarrhythmics. Known and novel risk factors for IC were identified using ML, demonstrating the hypothesis-generating utility of this approach for infectious disease conditions about which less is known, specifically at the species level or for rarer diseases.
Recently, the Workforce and Diversity Management Office at KSC have launched a major initiative to develop and implement a competency/skill approach to Human Resource management. As the competency/skill dictionary is being elaborated, the need for a competency-based workforce-planning model is recognized. A proof of concept for such a model is presented using a multidimensional data model that can provide the data infrastructure necessary to drive intelligent decision support systems for workforce planing. The components of competency-driven workforce planning model are explained. The data model is presented and several schemes that would support the workforce-planning model are presented. Some directions and recommendations for future work are given.
Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Here, pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.
Development of sustainable and scalable technologies to convert lignocellulosic biomass to biofuels is critical to achieving carbon neutrality. The potential of transgenic bioenergy crops as a renewable source of sugars and lipids has been demonstrated at bench-scale. However, scaling up these processes is important for holistic analysis. Here proof-of-concept for chemical-free hydrothermal pretreatment of transgenic energycane-oilcane line L13 at an industrially relevant scale to recover vegetative lipids along with cellulosic sugars is presented. Pilot-scale processing of 97 kg of transgenic energycane-oilcane L13 stems and high solids pretreatment of bagasse enhanced the recovery of cellulosic glucose and xylose by 5-fold as compared to untreated bagasse and helped in the enrichment of vegetative lipids in the biomass residues which allowed its recovery at the end of the bioprocess. Palmitic and oleic acids were the predominant fatty acids (FAs) extracted from stems and leaves. The processing did not affect lipid composition. The efficiency of lipid recovery from untreated biomass was 75.9% which improved to 88.7% upon pretreatment. The vegetative tissues of transgenic energycane-oilcane L13 contained 0.42 metric tons/hectare of lipids. Processing vegetative tissues yielded 0.38 metric tons/hectare of lipids. This approaches an oil yield similar to soybean (global average 0.44 metric tons/hectare) and is almost twice as high as the oil yield from sugarcane engineered to hyperaccumulate lipids (0.20 metric tons/hectare). The study suggests that further optimization by state-of-the-art metabolic engineering and biomass processing can establish transgenic bioenergy crops for commercial drop-in fuel production.
A magnetically-geared actuator is being developed for extremely cold space environments to avoid the wiring and significant efficiency penalty associated with heating grease-lubricated actuators as well as the stringent life and loading constraints imposed by dry film lubricated mechanical gears. This paper describes the lessons learned while designing, manufacturing, and assembling a proof-of-concept prototype similar to the preliminary design of the actuator.
A magnetically-geared actuator is being developed for extremely cold space environments to avoid the wiring and significant efficiency penalty associated with heating grease-lubricated actuators as well as the stringent life and loading constraints imposed by dry film lubricated mechanical gears. This paper describes the lessons learned while designing, manufacturing, and assembling a proof-of-concept prototype similar to the preliminary design of the actuator.
Significance The COVID-19 pandemic has had an unprecedented impact. Although several vaccines have received emergency use authorization, demand has created enormous logistical challenges—including supply, access, and distribution—that justify research for alternative strategies. Phage are viruses that only infect bacteria and can be safely administered to humans. Here, as a proof-of-concept study, we demonstrate that aerosol vaccination with lung-targeted phage particles displaying short SARS-CoV-2 S protein epitopes and subcutaneous vaccination with targeted AAVP particles carrying the entire S protein gene both elicit systemic and specific immune responses in immunocompetent mice. Given their unique attributes, including sturdiness, simple-to-engineer platform, cost-effectiveness for rapid large-scale production, and stability at room temperature, these phage-based approaches may become attractive tools for COVID-19 vaccine development.
The National Airspace System (NAS) must be improved to increase capacity, reduce flight delays, and minimize environmental impacts of air travel. NASA has been tasked with aiding the Federal Aviation Administration (FAA) in NAS modernization. Automatic Dependent Surveillance-Broadcast (ADS-B) is an enabling technology that is fundamental to realization of the Next Generation Air Transportation System (NextGen). Despite the 2020 FAA mandate requiring ADS-B Out equipage, airspace users are lacking incentives to equip with the requisite ADS-B avionics. A need exists to validate in flight tests advanced concepts of operation (ConOps) that rely on ADS-B and other data links without requiring costly equipage. A potential solution is presented in this paper. It is possible to emulate future data link capabilities using the existing in-flight Internet and reduced-cost test equipment. To establish proof-of-concept, a high-fidelity traffic operations simulation was modified to include a module that simulated Internet transmission of ADS-B messages. An advanced NASA ConOp, Flight Deck Interval Management (FIM), was used to evaluate technical feasibility. A preliminary assessment of the effects of latency and dropout rate on FIM was performed. Flight hardware that would be used by proposed test environment was connected to the simulation so that data transfer from aircraft systems to test equipment could be verified. The results indicate that the FIM ConOp, and therefore, many other advanced ConOps with equal or lesser response characteristics and data requirements, can be evaluated in flight using the proposed concept.
Abstract Many oncology drugs have been found to induce cardiotoxicity in a subset of patients, which significantly limits their clinical use and impedes the benefit of lifesaving anticancer treatments. Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) carry donor-specific genetic information and have been proposed for exploring the interindividual difference in oncology drug-induced cardiotoxicity. Herein, we evaluated the inter- and intraindividual variability of iPSC-CM-related assays and presented a proof of concept to prospectively predict doxorubicin (DOX)-induced cardiotoxicity (DIC) using donor-specific iPSC-CMs. Our findings demonstrated that donor-specific iPSC-CMs exhibited greater line-to-line variability than the intraindividual variability in impedance cytotoxicity and transcriptome assays. The variable and dose-dependent cytotoxic responses of iPSC-CMs resembled those observed in clinical practice and largely replicated the reported mechanisms. By categorizing iPSC-CMs into resistant and sensitive cell lines based on their time- and concentration-related phenotypic responses to DOX, we found that the sensitivity of donor-specific iPSC-CMs to DOX may predict in vivo DIC risk. Furthermore, we identified a differentially expressed gene, DND microRNA-mediated repression inhibitor 1 (DND1), between the DOX-resistant and DOX-sensitive iPSC-CMs. Our results support the utilization of donor-specific iPSC-CMs in assessing interindividual differences in DIC. Further studies will encompass a large panel of donor-specific iPSC-CMs to identify potential novel molecular and genetic biomarkers for predicting DOX and other oncology drug-induced cardiotoxicity.
Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).