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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗
NASA NTRS1972

Analysis of fungal type isolates taken from a 90-day manned test of an advanced regenerative life support system

Fungal-like cultures isolated before, during, and after the 90-day test from samples of space station simulator (SSS) atmosphere, surfaces, subsystem componets, and crew dermal sites were identified to genus. Out of the original 525 isolates, approximately 80% were classified as bacteria. Laboratory methods (culture media, moisturization, and incubation temperatures) favored the recovery of medically significant bacteria rather than fungi. Therefore, fungal isolates were mostly, nonfastidious types which are ubiquitous in soil and air and commonly contaminate laboratory cultures of pathogens. Predominant isolates were species of Aspergillus, Penicillium, Pullularia, Rhodotorula, and various yeasts. No instances of fungal proliferation were observed; test data reflect the survival of environmental types indigenous to the SSS pretests.

Sofios, M.↗
NASA NTRS1983

Thermomechanical loading of multilayered cylindrical geometries in thermal cycling from 300 to 1300 K

The principal of multiple material layering is well known as an effective method of reducing heat transfer; however, thermal gradients can impose significant loads and lead to delamination and subsequent component failure. An analysis is developed and experimental data are discussed for the thermomechanical effects of multilayered materials on a heat sink substrate of cylindrical geometry subject to thermal cycling. The geometry is heated in cross-flow by a high-velocity flame and cooled in crossflow by ambient-temperature air from a critical flow orifice. Each layer of material possesses a threshold beyond which small changes in temperature or mechanical loading greatly influence the life in thermal cycling of the layered materials. Comparisons are made between the thermomechanical loads predicted by various numerical codes for the linear case and by a simplified analytic model.

Hendricks, R. C.↗
NASA NTRS1994

The development and operation of the international solar-terrestrial physics central data handling facility

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) International Solar-Terrestrial Physics (ISTP) Program is committed to the development of a comprehensive, multi-mission ground data system which will support a variety of national and international scientific missions in an effort to study the flow of energy from the sun through the Earth-space environment, known as the geospace. A major component of the ISTP ground data system is an ISTP-dedicated Central Data Handling Facility (CDHF). Acquisition, development, and operation of the ISTP CDHF were delegated by the ISTP Project Office within the Flight Projects Directorate to the Information Processing Division (IPD) within the Mission Operations and Data Systems Directorate (MO&DSD). The ISTP CDHF supports the receipt, storage, and electronic access of the full complement of ISTP Level-zero science data; serves as the linchpin for the centralized processing and long-term storage of all key parameters generated either by the ISTP CDHF itself or received from external, ISTP Program approved sources; and provides the required networking and 'science-friendly' interfaces for the ISTP investigators. Once connected to the ISTP CDHF, the online catalog of key parameters can be browsed from their remote processing facilities for the immediate electronic receipt of selected key parameters using the NASA Science Internet (NSI), managed by NASA's Ames Research Center. The purpose of this paper is twofold: (1) to describe how the ISTP CDHF was successfully implemented and operated to support initially the Japanese Geomagnetic Tail (GEOTAIL) mission and correlative science investigations, and (2) to describe how the ISTP CDHF has been enhanced to support ongoing as well as future ISTP missions. Emphasis will be placed on how various project management approaches were undertaken that proved to be highly effective in delivering an operational ISTP CDHF to the Project on schedule and within budget. Examples to be discussed include: the development of superior teams; the use of Defect Causal Analysis (DCA) concepts to improve the software development process in a pilot Total Quality Management (TQM) initiative; and the implementation of a robust architecture that will be able to support the anticipated growth in the ISTP Program science requirements with only incremental upgrades to the baseline system. Further examples include the use of automated data management software and the implementation of Government and/or industry standards, whenever possible, into the hardware and software development life-cycle. Finally, the paper will also report on several new technologies (for example, the installation of a Fiber Data Distribution Interface network) that were successfully employed.

Lehtonen, Kenneth↗
NASA NTRS1995

Application of Different Statistical Techniques in Integrated Logistics Support of the International Space Station Alpha

The process to predict the values of the maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle cost spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability, and maintenance support costs. It is the objective of this report to identify the magnitude of the expected enhancement in the accuracy of the results for the International Space Station reliability and maintainability data packages by providing examples. These examples partially portray the necessary information hy evaluating the impact of the said enhancements on the life cycle cost and the availability of the International Space Station.

Sepehry-Fard, F.↗
NASA NTRS2011

Structural health monitoring apparatus and methodology

Disclosed is an apparatus and methodology for structural health monitoring (SHM) in which smart devices interrogate structural components to predict failure, expedite needed repairs, and thus increase the useful life of those components. Piezoelectric wafer active sensors (PWAS) are applied to or integrated with structural components and various data collected there from provide the ability to detect and locate cracking, corrosion, and disbanding through use of pitch-catch, pulse-echo, electro/mechanical impedance, and phased array technology. Stand alone hardware and an associated software program are provided that allow selection of multiple types of SHM investigations as well as multiple types of data analysis to perform a wholesome investigation of a structure.

Giurgiutiu, Victor↗
NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗
NASA NTRSDate not supplied

Space Algae-2 Ground and Lunar Analog Studies in Preparation for Long-Duration Propagation of Cyanobacteria in Spaceflight

There are numerous applications for microalgae in spaceflight missions and on Earth, such as oxygen production, carbon dioxide removal, nutrition, wastewater processing, and biofuel production. Space Algae-2 aims to test the genetic stability of Arthrospira platensis, commonly known as spirulina, during six-months of continuous culture on the International Space Station. Long-duration exposure to ionizing radiation and microgravity may impact growth, nutrient composition, and genetic stability. The high protein, vitamin, antioxidant content, and radiation resistance make spirulina a promising candidate for bioregenerative life support systems. A concept of operations was developed to grow and harvest algal biomass in space. Preflight testing experiments optimized conditions for an extended growth period in a gas permeable bioreactor bag. Preflight and post-harvest storage methods were developed in addition to a novel cryopreservation method. After sample return, multi-omics analysis will be conducted to determine the mutation rate, gene expression, and the protein and metabolite profile. The concept of operations for Space Algae-2 was tested during a lunar mission simulation within a semi-controlled environment. During a six-day lunar analog mission at the Hawai’i Space Exploration Analog and Simulation (HI-SEAS) A. platensis was successfully grown using flight-like hardware. The cyanobacteria were harvested and used to supplement bread as an example of spirulina biomass utilization. Overall, the data collected from Space Algae-2 will inform potential bioengineering of spirulina for space and terrestrial applications.

Algae↗
NASA NTRS1983

Analysis of the economics of photovoltaic-diesel-battery energy systems for remote applications

Computer simulations were conducted to analyze the performance and operating cost of a photovoltaic energy source combined with a diesel generator system and battery storage. The simulations were based on the load demand profiles used for the design of an all photovoltaic energy system installed in the remote Papago Indian Village of Schuchuli, Arizona. Twenty year simulations were run using solar insolation data from Phoenix SOLMET tapes. Total energy produced, energy consumed, operation and maintenance costs were calculated. The life cycle and levelized energy costs were determined for a variety of system configurations (i.e., varying amounts of photovoltaic array and battery storage).

Brainard, W. A.↗
NASA NTRS1994

Re-engineering the mission life cycle with ABC and IDEF

The theory behind re-engineering a business process is to remove the non-value added activities thereby lowering the process cost. In order to achieve this, one must be able to identify where the non-value added elements are located which is not a trivial task. This is because the non-value added elements are often hidden in the form of overhead and/or pooled resources. In order to be able to isolate these non-value added processes from among the other processes, one must first decompose the overall top level process into lower layers of sub-processes. In addition, costing data must be assigned to each sub-process along with the value the sub-process adds towards the final product. IDEF0 is a Federal Information Processing Standard (FIPS) process-modeling tool that allows for this functional decomposition through structured analysis. In addition, it illustrates the relationship of the process and the value added to the product or service. The value added portion is further defined in IDEF1X which is an entity relationship diagramming tool. The entity relationship model is the blueprint of the product as it moves along the 'assembly line' and therefore relates all of the parts to each other and the final product. It also relates the parts to the tools that produce the product and all of the paper work that is used in their acquisition. The use of IDEF therefore facilitates the use of Activity Based Costing (ABC). ABC is an essential method in a high variety, product-customizing environment, to facilitate rapid response to externally caused change. This paper describes the work being done in the Mission Operations Division to re-engineer the development and operation life cycle of Mission Operations Centers using these tools.

Mandl, Daniel↗
NASA NTRS1978

Exobiology and the origin of life

Research supported wholly or in part by NASA is summarized, Topics covered include the molecular analysis of ultraviolet-photoproduced organic solids synthesized under simulated Jovian conditions; the molecular analysis of organic solids produced by electrical discharge in reducing atmospheres; the organic chemistry of interstellar grains; the spectra of possible organic solids present as aerosols in planetary atmospheres; far infrared studies of organic polymers of possible astrophysical interest; organic dust synthesized in reducing environments by ultraviolet radiation or electric discharge; the diffusion of galactic civilizations; eavesdropping on galactic civilizations; Lander imaging as a detector of life on Mars; and continuing puzzles about Mars. Bibliographic data is included for four additional publications not supported by NASA grant, but related to the objectives of the program.

Sagan, C.↗
NASA NTRS1982

Special report on the data collection programs for the ground based nitrogen washout experiment. Volume 1: User's guide

The Nitrogen Washout System measures nitrogen elimination on a breath basis from the body tissues of a subject breathing pure oxygen. The system serves as a prototype for a Space Shuttle Life Sciences experiment and in the Environmental Physiology Laboratory. Typically, a subject washes out body nitrogen for three hours while breathing oxygen from a mask enclosed in a positive-pressure oxygen tent. A nitrogen washout requires one test operator and the test subject. A DEC LSI-11/02 computer is used to (1) control and calibrate the mass spectrometer and Skylab spirometer, (2) gather and store experimental data and (3) provide limited real time analysis and more extensive post-experiment analysis. Five programs are used to gather and store the experimental data and perform all the real time control and analysis.

Bueker, P. A.↗
NASA NTRS1986

Controlled Ecological Life Support Systems (CELSS) conceptual design option study

Results are given of a study to explore options for the development of a Controlled Ecological Life Support System (CELSS) for a future Space Station. In addition, study results will benefit the design of other facilities such as the Life Sciences Research Facility, a ground-based CELSS demonstrator, and will be useful in planning longer range missions such as a lunar base or manned Mars mission. The objectives were to develop weight and cost estimates for one CELSS module selected from a set of preliminary plant growth unit (PGU) design options. Eleven Space Station CELSS module conceptual PGU designs were reviewed, components and subsystems identified and a sensitivity analysis performed. Areas where insufficient data is available were identified and divided into the categories of biological research, engineering research, and technology development. Topics which receive significant attention are lighting systems for the PGU, the use of automation within the CELSS system, and electric power requirements. Other areas examined include plant harvesting and processing, crop mix analysis, air circulation and atmosphere contaminant flow subsystems, thermal control considerations, utility routing including accessibility and maintenance, and nutrient subsystem design.

Oleson, Melvin↗
NASA NTRS2019

Development of a Point of Care Technology for Military Medical Applications in Austere Environments

NASA, Lawrence Livermore National Laboratory (LLNL) and the Department of Defense (DoD) share a common interest in compact medical diagnostic technologies—also known as “point of care testing” (POCT) technologies. For NASA, the need is to take care of astronauts on deep space missions. For LLNL, the focus is on technologies needed to support homeland security applications. For DoD, the need is to support warfighters in military theaters of operation, especially for prolonged field care and en route care. A recently patented technology, “Portable Medical Diagnosis Instrument” (U.S. Patent 9824870), co-invented by NASA and LLNL, is being developed further in a partnership between NASA, LLNL and Travis Air Force Base, with a focus on military applications. This instrument, the NASA-LLNL Medical Tricorder, can be used for a wide range of clinical samples including breath, saliva and blood. One component of the Tricorder is the NASA E-Nose, a carbon nanotube-based chemical sensor, integrated into a hand-held smart phone, that can detect and measure “breath biomarkers” in the gas phase of exhaled breath. The response of the NASA E-Nose is rapid, which makes it possible to detect various gas-phase substances in real time. The NASA E-Nose, with modification, can also be used for breath condensate analysis. Another component of the Tricorder is a miniaturized microfluidic analyzer, under development by LLNL, that does not require any pumps. The microfluidic analyzer can detect and measure biomarkers in liquid samples, such as blood, saliva and breath condensate. This microfluidic system requires small quantities of liquid sample and can perform analysis very rapidly (seconds to minutes), which makes it possible to detect relevant biomarkers in near real time in the field. The Clinical Investigation Facility (CIF) at Travis Air Force Base is currently conducting research with the goal to develop improved field-able technologies and procedures for the emergency response to life threatening injuries soldiers may receive in theater. This work includes experimental large animal systems and comprehensive collection of clinical specimens and physiological data. NASA and LLNL are partnering with Travis to test and further develop the Tricorder technology for high priority military applications, initially focused on lung injury models and traumatic brain injury.

Loftus, David J.↗
NASA NTRS2017

A Science-Driven Mission Concept to An Exoplanet

A concept for a science-driven robotic mission to an exoplanet was developed by a team of scientists and engineers from NASA and academia. The concept and scope were based on key mission and science requirements designed to address the question: “What makes a flight mission to an exoplanet compelling, in terms of science return, compared to what we will be able to learn in the next few decades with large near-Earth telescopes or other remote sensing techniques such as a telescope at the Solar Gravity Lens Focus?” By thinking systematically through mission and science goals and objectives, key requirements were developed that would drive technology developments in all necessary aspects, not just on propulsion. Unique science measurements would be performed en route to the exoplanet, including exploring the environment in the outer regions of our solar system, the Oort Cloud, the local interstellar medium, and the astrospheric environment around the host star. One of the key mission science objectives, and one that addresses why a mission to an exoplanet is compelling, was to confirm and characterize life. This objective is fundamental and drives the need for a precursor exoplanet characterization program to search for Earth-centric biosignatures and also drives key aspects of the mission concept. The team concluded that a direct confirmation of life would require in situ observations and measurements which cannot be performed on a fast (~10% of the speed of light) flyby; thus, the mission would require a method to slow down, orbit, or send a probe to the exoplanet’s surface. This capability drives a trade between interstellar travel velocity, trip duration, and propulsion architecture, as well as a high level of onboard autonomy, including adaptive science data collection, on-board data processing, and analysis. This paper describes our mission concept, the key requirements, and open trades.

Bennett, Gary↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
NASA NTRS2024

Space Algae-2 Ground and Lunar Analog Studies in Preparation for Long-Duration Propagation of Cyanobacteria in Spaceflight

There are numerous applications for microalgae in spaceflight missions and on Earth, such as oxygen production, carbon dioxide removal, nutrition, wastewater processing, and biofuel production. Space Algae-2 aims to test the genetic stability of Arthrospira platensis, commonly known as spirulina, during six-months of continuous culture on the International Space Station. Long-duration exposure to ionizing radiation and microgravity may impact growth, nutrient composition, and genetic stability. The high protein, vitamin, antioxidant content, and radiation resistance make spirulina a promising candidate for bioregenerative life support systems. A concept of operations was developed to grow and harvest algal biomass in space. Preflight testing experiments optimized conditions for an extended growth period in a gas permeable bioreactor bag. Preflight and post-harvest storage methods were developed in addition to a novel cryopreservation method. After sample return, multi-omics analysis will be conducted to determine the mutation rate, gene expression, and the protein and metabolite profile. The concept of operations for Space Algae-2 was tested during a lunar mission simulation within a semi-controlled environment. During a six-day lunar analog mission at the Hawai’i Space Exploration Analog and Simulation (HI-SEAS) A. platensis was successfully grown using flight-like hardware. The cyanobacteria were harvested and used to supplement bread as an example of spirulina biomass utilization. Overall, the data collected from Space Algae-2 will inform potential bioengineering of spirulina for space and terrestrial applications.

Algae↗