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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 NTRS2005

Human Adaptation Genetic Response Suites: Toward New Interventions and Countermeasures for Spaceflight

Genetic response suites in human lymphocytes in response to microgravity are important to identify and further study in order to augment human physiological adaptation to novel environments. Emerging technologies, such as DNA micro array profiling, have the potential to identify novel genes that are involved in mediating adaptation to these environments. These genes may prove to be therapeutically valuable as new targets for countermeasures, or as predictive biomarkers of response to these new environments. Human lymphocytes cultured in lg and microgravity analog culture were analyzed for their differential gene expression response. Different groups of genes related to the immune response, cardiovascular system and stress response were then analyzed. Analysis of cells from multiple donors reveals a small shared set that are likely to be essential to adaptation. These three groups focus on human adaptation to new environments. The shared set contains genes related to T cell activation, immune response and stress response to analog microgravity.

Sundaresan, A.↗
NASA NTRS2007

Lunar Habitat Optimization Using Genetic Algorithms

Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts. Transporting the materials and equipment required to build the necessary habitats is costly and difficult. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces; therefore, a habitat wall design tool utilizing genetic algorithms (GAs) has been developed. GAs use a "survival of the fittest" philosophy where the most fit individuals are more likely to survive and reproduce. This habitat design optimization tool is a multiobjective formulation of up-mass, heat loss, structural analysis, meteoroid impact protection, and radiation protection. This Technical Publication presents the research and development of this tool as well as a technique for finding the optimal GA search parameters.

SanScoucie, M. P.↗
NASA NTRS2006

Influence of Space Flight Factors on the Genetic Properties of Streptomyces Lividans 66 (PIJ702)

Gram-positive Streptomyces bacteria display genetic instability in response to external factors. Strain S. lividans 66 harbors the multicopy plasmid pIJ702 with selective and differential marker genes for antibiotic thiostrepton resistance and melanin production. Culture plates of modified ISP agar medium with and without thiostrepton were flown on Foton-M2. Suboptimal flight temperatures, which were simulated for asynchronous ground controls, resulted in slow growth and failure to differentiate and sporulate. Flight samples and asynchronous controls showed a high frequency of failing to express plasmid markers compared to laboratory controls. This was associated with loss of plasmid DNA and likely resulted from suboptimal temperatures for flight cultures and controls. Neither restriction fragment length polymorphism, nor polymerase chain reaction amplification coupled with denaturing gradient gel electrophoresis, revealed differences between pIJ702 DNA from flight vs. control clones. Mutations of the plasmid marker genes resulting from specific spaceflight factors, e.g., microgravity and radiation, were not detected.

Tabakov, V. Yu.↗
NASA NTRS2008

Multidisciplinary Design, Analysis, and Optimization Tool Development using a Genetic Algorithm

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.

Pak, Chan-gi↗
NASA NTRS2009

Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!

Pak, Chan-gi↗
NASA NTRS2009

Stream Flow Prediction by Remote Sensing and Genetic Programming

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

Chang, Ni-Bin↗
NASA NTRS2004

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Kornfeld, Richard P.↗
NASA NTRS2012

Methods for determining the genetic affinity of microorganisms and viruses

Selecting which sub-sequences in a database of nucleic acid such as 16S rRNA are highly characteristic of particular groupings of bacteria, microorganisms, fungi, etc. on a substantially phylogenetic tree. Also applicable to viruses comprising viral genomic RNA or DNA. A catalogue of highly characteristic sequences identified by this method is assembled to establish the genetic identity of an unknown organism. The characteristic sequences are used to design nucleic acid hybridization probes that include the characteristic sequence or its complement, or are derived from one or more characteristic sequences. A plurality of these characteristic sequences is used in hybridization to determine the phylogenetic tree position of the organism(s) in a sample. Those target organisms represented in the original sequence database and sufficient characteristic sequences can identify to the species or subspecies level. Oligonucleotide arrays of many probes are especially preferred. A hybridization signal can comprise fluorescence, chemiluminescence, or isotopic labeling, etc.; or sequences in a sample can be detected by direct means, e.g. mass spectrometry. The method's characteristic sequences can also be used to design specific PCR primers. The method uniquely identifies the phylogenetic affinity of an unknown organism without requiring prior knowledge of what is present in the sample. Even if the organism has not been previously encountered, the method still provides useful information about which phylogenetic tree bifurcation nodes encompass the organism.

Fox, George E.↗
NASA NTRS2006

Genetic Algorithm for Optimization: Preprocessing with n Dimensional Bisection and Error Estimation

A knowledge of the appropriate values of the parameters of a genetic algorithm (GA) such as the population size, the shrunk search space containing the solution, crossover and mutation probabilities is not available a priori for a general optimization problem. Recommended here is a polynomial-time preprocessing scheme that includes an n-dimensional bisection and that determines the foregoing parameters before deciding upon an appropriate GA for all problems of similar nature and type. Such a preprocessing is not only fast but also enables us to get the global optimal solution and its reasonably narrow error bounds with a high degree of confidence.

Sen, S. K.↗
NASA NTRS2006

Genetic Algorithm for Optimization: Preprocessor and Algorithm

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

Sen, S. K.↗
NASA NTRS2014

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Burt, Adam O.↗
NASA NTRS2014

Modifying the Genetic Regulation of Bone and Cartilage Cells and Associated Tissue by EMF Stimulation Fields and Uses Thereof

An apparatus and method to modify the genetic regulation of mammalian tissue, bone, or any combination. The method may be comprised of the steps of tuning at least one predetermined profile associated with at least one time-varying stimulation field thereby resulting in at least one tuned time-varying stimulation field comprised of at least one tuned predetermined profile, wherein said at least one tuned predetermined profile is comprised of a plurality of tuned predetermined figures of merit and is controllable through at least one of said plurality of tuned predetermined figures of merit, wherein said plurality of predetermined tuned figures of merit is comprised of a tuned B-Field magnitude, tuned rising slew rate, tuned rise time, tuned falling slew rate, tuned fall time, tuned frequency, tuned wavelength, and tuned duty cycle; and exposing mammalian chondrocytes, osteoblasts, osteocytes, osteoclasts, nucleus pulposus, associated tissue, or any combination to said at least one tuned time-varying stimulation field comprised of said at least one tuned predetermined profile for a predetermined tuned exposure time or plurality of tuned exposure time sequences.

Goodwin, Thomas J.↗
NASA NTRS2014

Genetic Algorithm Optimization of a Cost Competitive Hybrid Rocket Booster

Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and later on solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. A remaining issue is the cost of hybrids vs the existing launch propulsion systems. This paper will review the known state of the art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.

Story, George↗
NASA NTRS2015

Genetic Algorithm Optimization of a Cost Competitive Hybrid Rocket Booster

Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. One remaining issue is the cost of hybrids versus the existing launch propulsion systems. This paper will review the known state-of-the-art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.

Story, George↗
NASA NTRS2017

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi↗
NASA NTRS2018

Coalescence of DNA Double Strand Breaks Induced by Galactic Cosmic Radiation is Modulated by Genetics in 15 Inbred Strains of Mice

In this manuscript we address the challenges associated with the ability to predict radiation sensitivity associated with exposure to either cosmic radiation or X-rays in a population study, by monitoring DNA damage sensing protein 53BP1 forming small nuclear radiation-induced foci (RIF) as a surrogate biomarker of DNA double strand breaks (DSB). 76 primary skin fibroblasts were isolated from 10 collaborative cross strains and five reference inbred mice (C57Bl/6, BALB/CByJ, B6C3, C3H and CBA/CaJ) and exposed to three different charged nuclei of increasing LET (350 MeV/n Si, 350 MeV/n Ar and 600 MeV/n Fe) and X-ray. Our data brings strong evidence against the classic "contact-first" model where DSBs are assumed to be immobile and repaired at the lesion site. In contrast, our model suggests nearby DSBs move into single repair unit characterized by large RIF before the repair machinery kicks in. Such model has the advantage of being much more efficient molecularly but is poorly suited to deal with cosmic radiation, where energy is concentrated along the particle trajectory, inducing a large density of DSBs along each particle track. In accordance with this model, RIF quantification after X-ray exposition showed a saturated dose response for early time points post-irradiation for all strains. Similarly, the high-LET response showed that RIF number matched the number of track per cell, not the number of expected DSB per cell (1). At the temporal level, we noted that the percentage of unrepaired high-LET tracks over a 48 hour time-course increased with LET, confirming that the DNA repair process becomes more difficult as more DSB coalesce into single RIF. There was also good agreement between persistent RIF levels measured in-vitro in the primary skin cultures and survival levels of T-cells and B-cells collected in blood samples from 10 CC strains 24 hours after 0.1 Gy whole-body dose of X-ray. This suggests that persistent RIF 24 hour post-IR is a good surrogate in-vitro biomarker for in-vivo radiation toxicity. Finally, at the genomic level, large differences in repair rates between strains for high-LET allowed us to identify suggestive genetic loci associated with radiation sensitivity. Interestingly, the two highest LETs provided the most strain variation with a common locus on Chromosome 10 highly enriched for DNA repair associated genes we discussed in detail.

Radiation-Induced Foci↗
NASA NTRS2018

Genetic Regulation of Bone and Cells by Electromagnetic Stimulation Fields and Uses Thereof

The present invention provides methods to modify the genetic regulation of mammalian tissue, bone, cells or any combination thereof by preferential activation, up-regulation and/or down-regulation. The method comprises steps of tuning the predetermined profiles of one or more time-varying stimulation fields by manipulating the B-Field magnitude, rising slew rate, rise time, falling slew rate, fall time, frequency, wavelength, and duty cycle, and exposing mammalian cells or tissues to one or more tuned time-varying stimulation fields with predetermined profiles. Examples of mammalian cells or tissues are chondrocytes, osteoblasts, osteocytes, osteoclasts, nucleus pulposus, associated tissue, or any combination. The resulted modification on gene regulation of these cells, tissues or bones may promote the retention, repair of and reduction of compromised mammalian cartilage, bone, and associated tissue.

Goodwin, Thomas J.↗
NASA NTRS2019

Fine-Grained, Spinel-Rich Ca-Al-Rich Inclusions From The Reduced CV3 Chondrite Efremovka: A Genetic Link To Wark-Lovering Rims?

Fine-grained, spinel-rich Ca-Al-rich inclusions (FGIs) in carbonaceous chondrites, mostly CV3 chondrites, are interpreted as aggregates of nebular gas-solid condensates that escaped significant melting [1]. Multiple lines of evidence suggest a condensation origin for FGIs, including their layered structures and irregular shapes and the fine grain size of numerous spinel-cored nodules [e.g., 2,3], and the distinctive volatility-fractionated group II rare earth element patterns of bulk inclusions and their mineral constituents [e.g., 4,5]. The origin and nature of FGIs are poorly constrained because of their fine grain sizes and intimate intergrowths of refractory phases, combined with their susceptibility to secondary parent body alteration processes, making detailed mineralogical and petrologic characterizations difficult using scanning electron microscope (SEM) and electron microprobe techniques. In this study, we present preliminary transmission electron microscope (TEM) analyses of pristine FGIs from the reduced CV3 chondrite Efremovka in order to provide the detailed characterization of their micrometer- to nanometer-scale textures and chemical compositions. Our goals are to better understand the formation processes and conditions of FGIs in the early solar nebula and to explore their possible genetic relationship with other early-formed refractory inclusions and their rims.

Keller, L. P.↗