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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA Commercial Crew Program and Medical Operational Challenges

BACKGROUND: NASA embarked on the Commercial Crew Program to launch astronauts into low-earth orbit from US soil and dock with the International Space Station (ISS). The eventual industry providers selected were SpaceX (SpX) and Boeing. These commercial transportation systems are vital to ensure crew availability on ISS for research and discovery. OVERVIEW: NASA/SpaceX Demo-2 (DM2) mission launched from the Kennedy Space Center in 2020 as the historic first crewed test-flight of the Crew Dragon spacecraft with two NASA Astronauts onboard. DM2 represented the first flight in 9-years from US soil since STS-135 in 2011. The 63-day mission ended with splashdown in the Gulf of Mexico, the first US water recovery in 45-years since Apollo-Soyuz. Validation of system hardware and operations allowed four-person crews to launch on subsequently missions (Crew-1, Crew-2, Crew-3, Crew-4, Crew-5 to date), which included International Partner crewmembers. DISCUSSION: A multitude of operational, training, medical, and technical issues needed to be addressed between NASA Medical Operations, the commercial provider SpaceX, and the Department of Defense. These included Flight rule development, occupant protection, pressurized suit testing, communication plans during mission phases, and emergency simulations for supporting Flight Surgeons and Biomedical Engineers. In providing crew experience with expected launch and entry G-force profile, Centrifuge training was established. Preventive health measures via the Health Stabilization Program were especially vital during the global COVID-19 pandemic. Unique aspects arise for SpX Dragon parachute splashdown and shipboard recovery operations in the Atlantic Ocean and Gulf of Mexico. The new Commercial Crew Program is indeed a wonderfully challenging and exciting era for human spaceflight.

Joseph P Dervay↗
NASA NTRS2024

Biomedical Research for Human Spaceflight

This invited presentation will offer an overview of the biomedical research – both from a biomedical sciences and engineering perspective – of human physiology and performance during spaceflight. Focused on the unique expertise within the Biomedical Sciences Branch, NASA Johnson Space Center, the talk will elucidate the critical role of biomedical laboratories in synergistic activities in clinical sciences, space physiology, applied research, technology development, and operational support for human space exploration. Together, the efforts within this branch play a crucial role in supporting astronauts' health, performance, and safety. The branch Scientists, Researchers, and Engineers conduct biomedical research in flight on board the International Space Station and on-earth space environment analogs. This dual approach allows for a nuanced understanding of the effects of micro- and planetary gravitation fields on human physiology and the assessment of potential clinical and biomedical interventions (countermeasures) to mitigate astronaut clinical and performance decrements. The talk aims to underscore the synergistic collaborative efforts of biomedical engineers, physiologists, clinicians, and computational researchers, emphasizing these experts' pivotal role in advancing human spaceflight's frontiers.

Biomedical Research↗
NASA NTRS2006

Technological Innovations from NASA

The challenge of human space exploration places demands on technology that push concepts and development to the leading edge. In biotechnology and biomedical equipment development, NASA science has been the seed for numerous innovations, many of which are in the commercial arena. The biotechnology effort has led to rational drug design, analytical equipment, and cell culture and tissue engineering strategies. Biomedical research and development has resulted in medical devices that enable diagnosis and treatment advances. NASA Biomedical developments are exemplified in the new laser light scattering analysis for cataracts, the axial flow left ventricular-assist device, non contact electrocardiography, and the guidance system for LASIK surgery. Many more developments are in progress. NASA will continue to advance technologies, incorporating new approaches from basic and applied research, nanotechnology, computational modeling, and database analyses.

Pellis, Neal R.↗
NASA NTRS1965

Space-based centrifuge

Engineering and biomedical studies of therapeutic and training potential of space-based centrifuge

TRAINING↗
NASA NTRS2001

Ultrasonic wave propagation in trabecular bone predicted by the stratified model

The objective of this study was to investigate ultrasound propagation in trabecular bone by considering the wave reflection and transmission in a multilayered medium. The use of ultrasound to identify those at risk of osteoporosis is a promising diagnostic method providing a measure of bone mineral density (BMD). A stratified model was proposed to study the effect of transmission and reflection of ultrasound wave within the trabecular architecture on the relationship between ultrasound and BMD. The results demonstrated that ultrasound velocity in trabecular bone was highly correlated with the bone apparent density (r=0.97). Moreover, a consistent pattern of the frequency dependence of ultrasound attenuation coefficient has been observed between simulation using this model and experimental measurement of trabecular bone. The normalized broadband ultrasound attenuation (nBUA) derived from the simulation results revealed that nBUA was nonlinear with respect to trabecular porosity and BMD. The curve of the relationship between nBUA and BMD was parabolic in shape, and the peak magnitude of nBUA was observed at approximately 60% of bone porosity. These results agreed with the published experimental data and demonstrated that according to the stratified model, reflection and transmission were important factors in the ultrasonic propagation through the trabecular bone.

Non-NASA Center↗
NASA NTRS1990

Earth benefits from space life sciences

Contributions of space exploration which are widely recognized are those dealing with the impact of space technology on public health and medical services in both urban and remote rural areas. Telecommunications, image enhancement, 3-dimensional image reconstructions, miniaturization, automation, and data analysis, have transformed the delivery of medical care and have brought about a new impetus to the field of biomedicine. Many areas of medical care and biological research have been affected. These include technological breakthroughs in such areas as: (1) diagnosis, treatment, and prevention of cardiovascular diseases, (2) new approaches to the understanding of osteoporosis, (3) early detection of genetic birth defects, (4) emergency medical care, and (5) treatment of chronic metabolic disorders. These are but a few examples where technology originally developed to support space medicine or space research has been applied to solving medical and health care delivery problems on Earth.

NASA Center HQS↗
NASA NTRS2001

Use of a genetic algorithm for the analysis of eye movements from the linear vestibulo-ocular reflex

It is common in vestibular and oculomotor testing to use a single-frequency (sine) or combination of frequencies [sum-of-sines (SOS)] stimulus for head or target motion. The resulting eye movements typically contain a smooth tracking component, which follows the stimulus, in which are interspersed rapid eye movements (saccades or fast phases). The parameters of the smooth tracking--the amplitude and phase of each component frequency--are of interest; many methods have been devised that attempt to identify and remove the fast eye movements from the smooth. We describe a new approach to this problem, tailored to both single-frequency and sum-of-sines stimulation of the human linear vestibulo-ocular reflex. An approximate derivative is used to identify fast movements, which are then omitted from further analysis. The remaining points form a series of smooth tracking segments. A genetic algorithm is used to fit these segments together to form a smooth (but disconnected) wave form, by iteratively removing biases due to the missing fast phases. A genetic algorithm is an iterative optimization procedure; it provides a basis for extending this approach to more complex stimulus-response situations. In the SOS case, the genetic algorithm estimates the amplitude and phase values of the component frequencies as well as removing biases.

Non-NASA Center↗
NASA NTRS2001

Shear stress reduces protease activated receptor-1 expression in human endothelial cells

Shear stress has been shown to regulate several genes involved in the thrombotic and proliferative functions of endothelial cells. Thrombin receptor (protease-activated receptor-1: PAR-1) increases at sites of vascular injury, which suggests an important role for PAR-1 in vascular diseases. However, the effect of shear stress on PAR-1 expression has not been previously studied. This work investigates effects of shear stress on PAR-1 gene expression in both human umbilical vein endothelial cells (HUVECs) and microvascular endothelial cells (HMECs). Cells were exposed to different shear stresses using a parallel plate flow system. Northern blot and flow cytometry analysis showed that shear stress down-regulated PAR-1 messenger RNA (mRNA) and protein levels in both HUVECs and HMECs but with different thresholds. Furthermore, shear-reduced PAR-1 mRNA was due to a decrease of transcription rate, not increased mRNA degradation. Postshear stress release of endothelin-1 in response to thrombin was reduced in HUVECs and HMECs. Moreover, inhibitors of potential signaling pathways applied during shear stress indicated mediation of the shear-decreased PAR-1 expression by protein kinases. In conclusion, shear stress exposure reduces PAR-1 gene expression in HMECs and HUVECs through a mechanism dependent in part on protein kinases, leading to altered endothelial cell functional responses to thrombin.

Non-NASA Center↗
NASA NTRS1998

Influence of gravity on cardiac performance

Results obtained by the investigators in ground-based experiments and in two parabolic flight series of tests aboard the NASA KC-135 aircraft with a hydraulic simulator of the human systemic circulation have confirmed that a simple lack of hydrostatic pressure within an artificial ventricle causes a decrease in stroke volume of 20%-50%. A corresponding drop in stroke volume (SV) and cardiac output (CO) was observed over a range of atrial pressures (AP), representing a rightward shift of the classic CO versus AP cardiac function curve. These results are in agreement with echocardiographic experiments performed on space shuttle flights, where an average decrease in SV of 15% was measured following a three-day period of adaptation to weightlessness. The similarity of behavior of the hydraulic model to the human system suggests that the simple physical effects of the lack of hydrostatic pressure may be an important mechanism for the observed changes in cardiac performance in astronauts during the weightlessness of space flight.

NASA Discipline Cardiopulmonary↗
NASA NTRS1998

Evaluation of dual-tip micromanometers during 21-day implantation in goats

Investigative research efforts using a cardiovascular model required the determination of central circulatory haemodynamic and arterial system parameters for the evaluation of cardiovascular performance. These calculations required continuous beat-to-beat measurement of pressure within the four chambers of the heart and great vessels. Sensitivity and offset drift, longevity, and sources of error for eight 3F dual-tipped micromanometers were determined during 21 days of implantation in goats. Subjects were instrumented with pairs of chronically implanted fluid-filled access catheters in the left and right ventricles, through which dual-tipped (test) micromanometers were chronically inserted and single-tip (standard) micromanometers were acutely inserted. Acutely inserted sensors were calibrated daily and measured pressures were compared in vivo to the chronically inserted sensors. Comparison of the pre- and post-gain calibration of the chronically inserted sensors showed a mean sensitivity drift of 1.0 +/- 0.4% (99% confidence, n = 9 sensors) and mean offset drift of 5.0 +/- 1.5 mmHg (99% confidence, n = 9 sensors). Potential sources of error for these drifts were identified, and included measurement system inaccuracies, temperature drift, hydrostatic column gradients, and dynamic pressure changes. Based upon these findings, we determined that these micromanometers may be chronically inserted in high-pressure chambers for up to 17 days with an acceptable error, but should be limited to acute (hours) insertions in low-pressure applications.

Non-NASA Center↗
NASA NTRS1998

Electrical signal transmission in a bone cell network: the influence of a discrete gap junction

A refined electrical cable model is formulated to investigate the role of a discrete gap junction in the intracellular transmission of electrical signals in an electrically coupled system of osteocytes and osteoblasts in an osteon. The model also examines the influence of the ratio q between the membrane's electrical time constant and the characteristic time of pore fluid pressure, the circular, cylindrical geometry of the osteon, and key simplifying assumptions in our earlier continuous cable model (see Zhang, D., S. C. Cowin, and S. Weinbaum. Electrical signal transmission and gap junction regulation in a bone cell network: A cable model for an osteon. Ann. Biomed. Eng. 25:379-396, 1997). Using this refined model, it is shown that (1) the intracellular potential amplitude at the osteoblastic end of the osteonal cable retains the character of a combination of a low-pass and a high-pass filter as the corner frequency varies in the physiological range; (2) the presence of a discrete gap junction near a resting osteoblast can lead to significant modulation of the intracellular potential and current in the osteoblast for measured values of the gap junction coupling strength; and (3) the circular, cylindrical geometry of the osteon is well simulated by the beam analogy used in Zhang et al.

Non-NASA Center↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRS1991

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

Frisch, Harold P.↗
NASA NTRS2000

Development of Countermeasures and Exercise Protocols to Reduce the Effects of Microgravity

I have helped scientists at NASA-JSC in analyzing data from many projects. Some of the major ones are: (1) cardiovascular responses to lower body negative pressure (LBNP) following bed rest, (2) the effects of dietary sodium, (3) in-flight cycle exercise mitigates reduced oxygen consumption at submaximal heart rates following space flight, (4) exercise thermoregulation after 13 days of head down bed rest, and (5) bed rest induced orthostatic intolerance. Many of the projects have now been completed and some of them are in the process of being published and others have been presented at national meetings. These projects have helped me be a true statistician and given me a real-life perspective of how interesting and complicated data can be. As a by-product of of these involvements I have been able to write and publish some methodological research that have applications in NASA and elsewhere. For instance, while I was at JSC, I happened to meet Dr. Al Feiveson and got into a discussion of the Space Shuttle Reliability. This led us to rethink about the way the data on the accelerated life testing of space shuttle pressure vessels had been analyzed. This has resulted in a major statistical paper and the paper has appeared in one of the top journals in the field of Statistics. A review of the paper by the editor of the journal was published in AmStatNews, a copy is attached with this report. I have presented these findings at the national/international statistics conference and at other places. I have also written another paper on reliability and a paper on calibration techniques that have applications in the engineering and the biomedical branches of NASA. Further, I am currently in the process of writing at least two more papers that have direct applications in NASA related studies.

Kulkarni, Pandurang M.↗
NASA NTRSDate not supplied

Investigating Biological Responses to Deep Space Radiation for Missions Beyond Low Earth Orbit (LEO) using Yeast

To enable long-term spaceflight missions and establish habitation on the Moon and Mars, we require a comprehensive understanding of the effects of chronic deep space radiation exposure on humans. BioSentinel is NASA’s first biological CubeSat to venture beyond Low Earth Orbit (LEO). It utilizes Saccharomyces cerevisiae (budding yeast) as a model organism to study biological responses to deep space radiation. Yeast share significant genetic homology with humans, including basic cellular metabolism and DNA repair mechanisms. In addition, unlike human cell cultures, yeast can survive the duration and constraints of a deep space mission. BioSentinel measures biological responses using an optical system and alamarBlue oxidation-reduction (redox) dye. Two strains of yeast are studied - a wild-type and a rad51 mutant strain that is deficient in DNA repair. Changes in metabolism and growth are monitored throughout the nominal 6-month mission. Preliminary tests indicate a significant change in the alamarBlue response to low-dose ionizing radiation (IR). Additionally, rad51 cells have shown an IR dose-dependent decrease in glucose uptake and accumulation of oxidized NADH (NAD+). These biomolecules are involved in reactions responsible for basic cell processes, including growth and development, signaling, and respiration. The current study expanded upon previous data by exposing yeast to deep space-relevant radiation. Glucose and NADH/NAD+ assays were conducted on yeast subjected to varying dosages of high-energy Fe-56 and simulated galactic cosmic rays (GCRs). The resulting data was analyzed using Excel and GraphPad Prism. A particular focus was to identify biomolecules resulting from aerobic respiration, which requires the presence of oxygen, or anaerobic processes. As long-term spaceflight missions draw near, it is increasingly important to characterize biological processes affected by the conditions of deep space. Studying biomolecular damage caused by deep space radiation may enable the development of engineering controls or biomedical therapeutics that mitigate health complications for future astronauts.

Kyra Keenan↗