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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Model for the computation of self-motion in biological systems

A technique is presented by which direction- and speed-tuned cells, such as those commonly found in the middle temporal region of the primate brain, can be utilized to analyze the patterns of retinal image motion that are generated during observer movement through the environment. The developed model determines heading by finding the peak response in a population of detectors or neurons each tuned to a particular heading direction. It is suggested that a complex interaction of multiple cell networks is required for the solution of the self-motion problem in the primate brain.

Perrone, John A.↗
NASA NTRS2002

Using CONFIG for Simulation of Operation of Water Recovery Subsystems for Advanced Control Software Evaluation

A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center

Malin, Jane T.↗
NASA NTRS2008

Water-Based Coating Simplifies Circuit Board Manufacturing

The Structures and Materials Division at Glenn Research Center is devoted to developing advanced, high-temperature materials and processes for future aerospace propulsion and power generation systems. The Polymers Branch falls under this division, and it is involved in the development of high-performance materials, including polymers for high-temperature polymer matrix composites; nanocomposites for both high- and low-temperature applications; durable aerogels; purification and functionalization of carbon nanotubes and their use in composites; computational modeling of materials and biological systems and processes; and developing polymer-derived molecular sensors. Essentially, this branch creates high-performance materials to reduce the weight and boost performance of components for space missions and aircraft engine components. Under the leadership of chemical engineer, Dr. Michael Meador, the Polymers Branch boasts world-class laboratories, composite manufacturing facilities, testing stations, and some of the best scientists in the field.

Source record↗
NASA NTRS1999

An Inherited Efficiencies Model of Non-Genomic Evolution

A model for the evolution of biological systems in the absence of a nucleic acid-like genome is proposed and applied to model the earliest living organisms -- protocells composed of membrane encapsulated peptides. Assuming that the peptides can make and break bonds between amino acids, and bonds in non-functional peptides are more likely to be destroyed than in functional peptides, it is demonstrated that the catalytic capabilities of the system as a whole can increase. This increase is defined to be non-genomic evolution. The relationship between the proposed mechanism for evolution and recent experiments on self-replicating peptides is discussed.

New, Michael H.↗
NASA NTRS2018

Pilot Study on the Investigation of Tear Fluid Biomarkers as an Indicator of Ocular, Neurological, and Immunological Health in Astronauts

The purpose of this pilot study is to investigate the collection, preparation, and analysis of tear biomarkers as a means of assessing ocular, neurological, and immunological health. At present, no published data exists on the cytokine profiles of tears from astronauts exposed to long periods of microgravity and space irradiations. In addition, no published data exist on cytokine (biomarker) profiles of tears that have been collected from irradiated non-human biological systems (primates and other animal models). A goal for the proposed pilot study is to discover novel tear biomarkers which can help inform researchers, clinicians, epidemiologist and healthcare providers about the health status of a living biological system, as well as informing them when a disease state is triggered. This would be done via analysis of the onset of expression of pro-inflammatory cytokines, leading up to the full progression of a disease (i.e. cancer, loss of vision, radiation-induced oxidative stress, cardiovascular disorders, fibrosis in major organs, bone loss). Another goal of this pilot study is to investigate the state of disease against proposed medical countermeasures, in order to determine whether the countermeasures are efficacious in preventing or mitigating these injuries. An example of an up and coming tear biomarker technology, Ascendant Dx, a clinical stage diagnostic company, is developing a screening test to detect breast cancer using proteins from tears. The team utilized Liquid Chromatography -Mass Spectrometry with Mass analysis (LC MS/MS) as a discovery platform followed by validation with ELISA to come up with a panel of protein biomarkers that can differentiate breast cancer samples from control ("cancer free") samples with results far surpassing the results of imaging techniques in use today. Continued research into additional proteins is underway to increase the sensitivity and specificity of the test and development efforts are on the way to transfer the test onto a fast, accurate and inexpensive point of care platform. In conclusion, the expected results from this proposed pilot study are to: a) establish an SOP for retrieving/storing/transporting tear fluid samples from multicentre sites b) establish a normal range for relevant biomarkers in tears; and c) establish a database (biobank) of tears of space naïve versus veteran astronauts, to establish a personal baseline for long-term ocular health monitoring

Morton, Stephen↗
NASA NTRS1999

Protein machines and self assembly in muscle organization

The remarkable order of striated muscle is the result of a complex series of protein interactions at different levels of organization. Within muscle, the thick filament and its major protein myosin are classical examples of functioning protein machines. Our understanding of the structure and assembly of thick filaments and their organization into the regular arrays of the A-band has recently been enhanced by the application of biochemical, genetic, and structural approaches. Detailed studies of the thick filament backbone have shown that the myosins are organized into a tubular structure. Additional protein machines and specific myosin rod sequences have been identified that play significant roles in thick filament structure, assembly, and organization. These include intrinsic filament components, cross-linking molecules of the M-band and constituents of the membrane-cytoskeleton system. Muscle organization is directed by the multistep actions of protein machines that take advantage of well-established self-assembly relationships. Copyright 1999 John Wiley & Sons, Inc.

NASA Discipline Musculoskeletal↗
NASA NTRS2015

Spaceflight Causes Increased Virulence of Serratia Marcescens on a Drosophila Melanogaster Host

Drosophila melanogaster, or the fruit fly, has long been an important organism for Earth-based research, and is now increasingly utilized as a model system to understand the biological effects of spaceflight. Studies in Drosophila melanogaster have shown altered immune responses in 3rd instar larvae and adult males following spaceflight, changes similar to those observed in astronauts. In addition, spaceflight has also been shown to affect bacterial physiology, as evidenced by studies describing altered virulence of Salmonella typhimurium following spaceflight and variation in biofilm growth patterns for the opportunistic pathogen Pseudomonas aeruginosa during flight. We recently sent Serratia marcescens Db11, a Drosophila pathogen and an opportunistic human pathogen, to the ISS on SpaceX-5 (Fruit Fly Lab-01). S. marcescens samples were stored at 4degC for 24 days on-orbit and then allowed to grow for 120 hours at ambient station temperature before being returned to Earth. Upon return, bacteria were isolated and preserved in 50% glycerol or RNAlater. Storage, growth, and isolation for ground control samples were performed using the same procedures. Spaceflight and ground samples stored in 50% glycerol were diluted and injected into 5-7-day-old ground-born adult D. melanogaster. Lethality was significantly greater in flies injected with the spaceflight samples compared to those injected with ground bacterial samples. These results indicate a shift in the virulence profile of the spaceflight S. marcescens Db11 and will be further assessed with molecular biological analyses. Our findings strengthen the conclusion that spaceflight impacts the virulence of bacterial pathogens on model host organisms such as the fruit fly. This research was supported by NASA's ISS Program Office (ISSPO) and Space Life and Physical Sciences Research and Applications (SLPSRA).

Serratia marcescens↗
NASA NTRS1999

Growing wheat in Biosphere 2 under elevated CO2: observations and modeling

Spring wheat (Triticum aestivum L., cv. Yecora Rojo) was grown in the intensive agricultural biome (IAB) of Biosphere 2 during the l995-l996 winter/spring season. Environmental conditions were characterized by a day/night temperature regime of 27/17 degrees C, relative humidity (RH) levels around 45%, mean atmospheric CO2 concentration of 450 ppmv, and natural light conditions with mean intensities about half of outside levels. Weekly samples of above-ground plant matter were collected throughout the growing season and phenological events recorded. A computer model, CERES-Wheat, previously tested under both field and controlled conditions, was used to simulate the observed crop growth and to help in data analysis. We found that CERES-Wheat simulated the data collected at Biosphere 2 to within 10% of observed, thus suggesting that wheat growth inside the IAB was comparable to that documented in other environments. The model predicts phenological stages and final dry matter (DM) production within l0% of the observed data. Measured DM production rates, normalized for light absorbed by the crop. suggested photosynthetic efficiencies intermediate between those observed under optimal field conditions and those recorded in NASA-Controlled Ecological Life-Support Systems (CELSS). We suggest that such a difference can be explained primarily in terms of low light levels inside the IAB, with additional effects due to elevated CO2 concentrations and diffuse light fractions.

Non-NASA Center↗
NASA NTRS1996

Evaluation of Cyanothece sp. ATCC 51142 as a candidate for inclusion in a CELSS

Controlled ecological life support systems (CELSS) have been proposed to make long-duration manned space flights more cost-effective. Higher plants will presumably provide food and a breathable atmosphere for the crew. It has been suggested that imbalances between the CO2/O2 gas exchange ratios of the heterotrophic and autotrophic components of the system will inevitably lead to an unstable system, and the loss of O2 from the atmosphere. Ratio imbalances may be corrected by including a second autotroph with an appropriate CO2/O2 gas exchange ratio. Cyanothece sp. ATCC 51142 is a large unicellular N2-fixing cyanobacterium, exhibiting high growth rates under diverse physiological conditions. A rat-feeding study showed the biomass to be edible. Furthermore, it may have a CO2/O2 gas exchange ratio that theoretically can compensate for ratio imbalances. It is suggested that Cyanothece spp. could fulfill several roles in a CELSS: supplementing atmosphere recycling, generating fixed N from the air, providing a balanced protein supplement, and protecting a CELSS in case of catastrophic crop failure.

Non-NASA Center↗
NASA NTRS2014

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This optimized composite set of SeaUVSeaUVc algorithms will provide the optical community with improved ability to quantify the role of solar UV radiation in photochemical and photobiological processes in the ocean.

UV↗
NASA NTRS1979

The terrestrial radiation environment and EVA's: Prediction requirements, model improvements, and warning systems

The total medical-biological impact of the Earth's space radiation environment on humans is a function of combined EVA and non-EVA exposure. In either case, the correct assessment of the eventual health risk to crew members is crucial to the success and viability of a project or mission. Aside from the medical-biological aspect itself, the validity of any assessment depends entirely on the existence of good and reliable models providing the high quality data that is needed for such evaluations, which should contain time histories of storm and substorm events, their intensities, their frequency of occurence, and their duration. Prediction requirements, advantageous and desirable model developments and improvements, and systems that need to be designed and tested, which would alert space crews and maintenance personnel about impending radiation danger are outlined.

Stassinopoulos, E. G.↗
NASA NTRS2009

Complexity for Survival of Living Systems

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Zak, Michail↗
NASA NTRS2001

Adjustable Autonomy Testbed

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Malin, Jane T.↗
NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗
NASA NTRS2002

A model for plant lighting system selection

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

NASA Center KSC↗
NASA NTRS1998

Radial Distribution of Electron Spectra from High-Energy Ions

The average track model describes the response of physical and biological systems using radial dose distribution as the key physical descriptor. We report on an extension of this model to describe the average distribution of electron spectra as a function of radial distance from an ion. We present calculations of these spectra for ions of identical linear energy transfer (LET), but dissimilar charge and velocity to evaluate the differences in electron spectra from these ions. To illustrate the usefulness of the radial electron spectra for describing effects that are not described by electron dose, we consider the evaluation of the indirect events in microdosimetric distributions for ions. We show that folding our average electron spectra model with experimentally determined frequency distributions for photons or electrons provides a good representation of radial event spectra from high-energy ions in 0.5-2 micrometer sites.

Cucinotta, Francis A.↗