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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Genetic algorithms in adaptive fuzzy control

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Karr, C. Lucas↗
NASA NTRSDate not supplied

Application of a Bayesian Framework for Plasticity Model Selection

Interpretable Machine Learning (IML) has performed well when tasked with deriving constitutive material models. However, IML has been shown to prefer models that overfit noise in data, which tends to lead to bloat and a decrease in interpretability. Due to these issues, the ability of IML to reliably derive models that fit the data and are both interpretable and generalizable is limited. A method developed recently has shown promise to improve upon traditional IML by using a Bayesian fitness definition for the evolution of free-form models with non-deterministic parameters. This framework was developed for genetic-programming-based symbolic regression(GPSR) and involves model parameter estimation using Sequential Monte Carlo sampling (SMC).The method has demonstrated a reduction in bloat when dealing with noisy data in comparison to conventional GPSR. The results of this framework applied to stress-strain data for copper show models that more effectively predict the experimental data better than was previously shown with GPSR.

plasticity↗
NASA NTRS2002

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

Kobayashi, Takahisa↗
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 NTRS1998

Radiation-induced instability and its relation to radiation carcinogenesis

PURPOSE: A model that identifies radiation-induced genetic instability as the earliest cellular event in the multi-step sequence leading to radiation-induced cancer was previously proposed. In this paper ongoing experiments are discussed which are designed to test this model and its predictions in mouse mammary epithelial cells. RESULTS: Several lines of evidence are presented that appear to support this model: first, the development of delayed mutations in p53 following irradiation in altered growth variants; secondly, the high frequencies for the induction of both instability and transformation following irradiation in mammary epithelial cells; and finally, the demonstration that susceptibility to the induction of cytogenetic instability is a heritable trait that correlates with susceptibility to transformation and radiation-induced mammary cancer. Mice resistant to transformation and mammary cancer development are also resistant to the development of instability after irradiation. In contrast, mice sensitive to transformation and cancer are also sensitive to the development of cytogenetic instability. CONCLUSIONS: Data from this laboratory and from the studies cited above suggest a specific, and perhaps unique, role for radiation-induced instability as a critical early event associated with initiation of the carcinogenic process.

Review↗
NASA NTRS1990

Weather prediction using a genetic memory

Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.

Rogers, David↗
NASA NTRS2018

Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves

An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment.

Depositio↗
NASA NTRS1997

Hydrothermal hydration of Martian crust: illustration via geochemical model calculations

If hydrothermal Systems existed on Mars, hydration of crustal rocks may have had the potential to affect the water budget of the planet. We have conducted geochemical model calculations to investigate the relative roles of host rock composition, temperature, water-to-rock ratio, and initial fluid oxygen fugacity on the mineralogy of hydrothermal alteration assemblages, as well as the effectiveness of alteration to store water in the crust as hydrous minerals. In order to place calculations for Mars in perspective, models of hydrothermal alteration of three genetically related Icelandic volcanics (a basalt, andesite, and rhyolite) are presented, together with results for compositions based on SNC meteorite samples (Shergotty and Chassigny). Temperatures from 150 degrees C to 250 degrees C, water-to-rock ratios from 0.1 to 1000, and two initial fluid oxygen fugacities are considered in the models. Model results for water-to-rock ratios less than 10 are emphasized because they are likely to be more applicable to Mars. In accord with studies of low-grade alteration of terrestrial rocks, we find that the major controls on hydrous mineral production are host rock composition and temperature. Over the range of conditions considered, the alteration of Shergotty shows the greatest potential for storing water as hydrous minerals, and the alteration of Icelandic rhyolite has the lowest potential.

NASA Discipline Exobiology↗
NASA NTRS2014

Ames Culture Chamber System: Enabling Model Organism Research Aboard the international Space Station

Understanding the genetic, physiological, and behavioral effects of spaceflight on living organisms and elucidating the molecular mechanisms that underlie these effects are high priorities for NASA. Certain organisms, known as model organisms, are widely studied to help researchers better understand how all biological systems function. Small model organisms such as nem-atodes, slime mold, bacteria, green algae, yeast, and moss can be used to study the effects of micro- and reduced gravity at both the cellular and systems level over multiple generations. Many model organisms have sequenced genomes and published data sets on their transcriptomes and proteomes that enable scientific investigations of the molecular mechanisms underlying the adaptations of these organisms to space flight.

culture chamber system↗
NASA NTRS2000

Ceratopteris richardii: a productive model for revealing secrets of signaling and development

Ceratopteris richardii is an aquatic fern grown in tropical and subtropical regions of the world. It is proven to be a productive model system for studies in the genetics, biochemistry, and cell biology of basic biologic processes that occur in early gametophytic development. It provides several advantages to biologists, especially those interested in gravitational biology, polarity development, and in the genetics of sexual development. It is easy to culture, has a relatively short life cycle, and offers an array of attractive features that facilitate genetic studies. The germination and early development of large populations of genetically identical spores are easy to synchronize, and both the direction of polarity development and cell-level gravity responses can be measured and readily manipulated within the first 24 h of spore development. Although there is no reliable transformation system available yet in Ceratopteris, recent studies suggest that the technique of RNA interference can be used to block translation of specific genes in a related fern, Marsilea, and current studies will soon reveal the applicability of this approach, as well as of other transformation approaches, in Ceratopteris. A recently completed expressed sequence tag (EST) sequencing project makes available the partial sequence of more than 2000 cDNAs, representing a significant percentage of the genes being expressed during the first 24 h of spore germination, when many developmentally interesting processes are occurring. A microarray of these ESTs is being constructed, so especially for those scientists interested in basic cellular phenomena that occur early in spore germination, the availability of the ESTs and of the microarray will make Ceratopteris an even more attractive model system.

NASA Discipline Plant Biology↗
NASA NTRS2002

Size distribution of retrovirally marked lineages matches prediction from population measurements of cell cycle behavior

Mechanisms that regulate neuron production in the developing mouse neocortex were examined by using a retroviral lineage marking method to determine the sizes of the lineages remaining in the proliferating population of the ventricular zone during the period of neuron production. The distribution of clade sizes obtained experimentally in four different injection-survival paradigms (E11-E13, E11-E14, E11-E15, and E12-E15) from a total of over 500 labeled lineages was compared with that obtained from three models in which the average behavior of the proliferating population [i.e., the proportion of cells remaining in the proliferative population (P) vs. that exiting the proliferative population (Q)] was quantitatively related to lineage size distribution. In model 1, different proportions of asymmetric, symmetric terminal, and symmetric nonterminal cell divisions coexisted during the entire developmental period. In model 2, the developmental period was divided into two epochs: During the first, asymmetric and symmetric nonterminal cell divisions occurred, but, during the second, asymmetric and symmetric terminal cell divisions occurred. In model 3, the shifts in P and Q are accounted for by changes in the proportions of the two types of symmetric cell divisions without the inclusion of any asymmetric cell divisions. The results obtained from the retroviral experiments were well accounted for by model 1 but not by model 2 or 3. These findings demonstrate that: 1) asymmetric and both types of symmetric cell divisions coexist during the entire period of neurogenesis in the mouse, 2) neuron production is regulated in the proliferative population by the independent decisions of the two daughter cells to reenter S phase, and 3) neurons are produced by both asymmetric and symmetric terminal cell divisions. In addition, the findings mean that cell death and/or tangential movements of cells in the proliferative population occur at only a low rate and that there are no proliferating lineages "reserved" to make particular laminae or cell types. Copyright 2002 Wiley-Liss, Inc.

NASA Discipline Developmental Biology↗
NASA NTRS1975

Petrology of lunar soils

The paper summarizes the physical and petrographic characteristics of the finer-grained fractions (less than 1 cm) of lunar regolith soil in Apollo and Luna samples. Lunar soils are poorly sorted and consist mostly of lithic and mineral debris derived by impact comminution of the underlying bedrock and glass particles formed by impact melting. Agglutinates constitute an important soil component and are key factors in the genetic history of lunar soil. Some models concerning the development of lunar regolith based on soil studies are examined.

Heiken, G.↗
NASA NTRS2002

Low-Shear modeled microgravity alters the Salmonella enterica serovar typhimurium stress response in an RpoS-independent manner

We have previously demonstrated that low-shear modeled microgravity (low-shear MMG) serves to enhance the virulence of a bacterial pathogen, Salmonella enterica serovar Typhimurium. The Salmonella response to low-shear MMG involves a signaling pathway that we have termed the low-shear MMG stimulon, though the identities of the low-shear MMG stimulon genes and regulatory factors are not known. RpoS is the primary sigma factor required for the expression of genes that are induced upon exposure to different environmental-stress signals and is essential for virulence in mice. Since low-shear MMG induces a Salmonella acid stress response and enhances Salmonella virulence, we reasoned that RpoS would be a likely regulator of the Salmonella low-shear MMG response. Our results demonstrate that low-shear MMG provides cross-resistance to several environmental stresses in both wild-type and isogenic rpoS mutant strains. Growth under low-shear MMG decreased the generation time of both strains in minimal medium and increased the ability of both strains to survive in J774 macrophages. Using DNA microarray analysis, we found no evidence of induction of the RpoS regulon by low-shear MMG but did find that other genes were altered in expression under these conditions in both the wild-type and rpoS mutant strains. Our results indicate that, under the conditions of these studies, RpoS is not required for transmission of the signal that induces the low-shear MMG stimulon. Moreover, our studies also indicate that low-shear MMG can be added to a short list of growth conditions that can serve to preadapt an rpoS mutant for resistance to multiple environmental stresses.

Non-NASA Center↗
NASA NTRS1992

Biodiversity: molecular biological domains, symbiosis and kingdom origins

The number of extant species of organisms is estimated to be from fewer than 3 to more than 30 x 10(6) (May, 1992). Molecular biology, comparative genetics and ultrastructural analyses provide new insights into evolutionary relationships between these species, including increasingly precise ideas of how species and higher taxa have evolved from common ancestors. Accumulation of random mutations and large macromolecular sequence change in all organisms since the Proterozoic Eon has been importantly supplemented by acquisition of inherited genomes ('symbiogenesis'). Karyotypic alterations (polyploidization and karyotypic fissioning) have been added to these other mechanisms of species origin in plants and animals during the Phanerozoic Eon. The new evolution concepts (coupled with current rapid rates of species extinction and ignorance of the extent of biodiversity) prompted this analysis of the field of systematic biology and its role in the reorganization of extant species into higher taxa. Two superkingdoms (= Domains: Prokaryotae and Eukaryotae) and five kingdoms (Monera = Procaryotae or Bacteria; Protoctista: algae, amoebae, ciliates, foraminifera, oomycetes, slime molds, etc.; Mychota: 'true' fungi; Plantae: one phylum (division) of bryophytes and nine phyla of tracheophytes; and Animalia) are recognized. Two subkingdoms comprise the monera: the great diverse lineages are Archaebacteria and Eubacteria. The criteria for classification using molecular, ultrastructural and genetic data for this scheme are mentioned. For the first time since the nineteenth century, logical, technical definitions for each group are given with their time of appearance as inferred from the fossil record in the primary scientific literature. This classification scheme, which most closely reflects the evolutionary history, molecular biology, genetics and ultrastructure of extant life, requires changes in social organization of biologists, many of whom as botanists and zoologists, still behave as if there were only two important kingdoms (plants and animals).

Non-NASA Center↗
NASA NTRS2002

Radiation Effect on Human Tissue

Predicting the occurrence of human cancer following exposure of an epidemiologic population to any agent causing genetic damage is a difficult task. To an approximation, this is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within clinically normal individuals. This situation begs the need for alternate controlled experimental models that are predictive for the development of human cancer following exposures to agents causing genetic damage. Such models historically have not been of substantial proven value. It is more recently encouraging, however, that developments in molecular and cell biology have led to an expanded knowledge of human carcinogenesis, and of molecular markers associated with that process. It is therefore appropriate to consider new laboratory models developed to accomodate that expanded knowledge in order to assess the cancer risks associated with exposures to genotoxic agents. When ionizing radiation of space is the genotoxic agent, then a series of additional considerations for human cancer risk assessment must also be applied. These include the dose of radiation absorbed by tissue at different locations in the body, the quality of the absorbed radiation, the rate at which absorbed dose accumulates in tissue, the way in which absorbed dose is measured and calculated, and the alterations in incident radiation caused by shielding materials. It is clear that human cancer risk assessment for damage caused by ionizing radiation is a multidisciplinary responsibility, and that within this responsibility no single discipline can hold disproportionate sway if a risk assessment model of radiation-induced human cancer is to be developed that has proven value. Biomolecular and cellular markers from the work reported here are considered for use in assessing human cancer risk related to exposure to space radiation. This potential use must be integrated within the specified multidisciplinary context in order to create a new tool of molecular epidemiology that can hopefully then realistically assess this cancer risk.

Richmond, Robert C.↗
NASA NTRS1996

Soft Computing Methods in Design of Superalloys

Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modelled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.

Cios, K. J.↗
NASA NTRS1995

Soft computing methods in design of superalloys

Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modeled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.

Cios, K. J.↗
NASA NTRS2002

Heat Transfer in High-Temperature Fibrous Insulation

The combined radiation/conduction heat transfer in high-porosity, high-temperature fibrous insulations was investigated experimentally and numerically. The effective thermal conductivity of fibrous insulation samples was measured over the temperature range of 300-1300 K and environmental pressure range of 1.33 x 10(exp -5)-101.32 kPa. The fibrous insulation samples tested had nominal densities of 24, 48, and 72 kilograms per cubic meter and thicknesses of 13.3, 26.6 and 39.9 millimeters. Seven samples were tested such that the applied heat flux vector was aligned with local gravity vector to eliminate natural convection as a mode of heat transfer. Two samples were tested with reverse orientation to investigate natural convection effects. It was determined that for the fibrous insulation densities and thicknesses investigated no heat transfer takes place through natural convection. A finite volume numerical model was developed to solve the governing combined radiation and conduction heat transfer equations. Various methods of modeling the gas/solid conduction interaction in fibrous insulations were investigated. The radiation heat transfer was modeled using the modified two-flux approximation assuming anisotropic scattering and gray medium. A genetic-algorithm based parameter estimation technique was utilized with this model to determine the relevant radiative properties of the fibrous insulation over the temperature range of 300-1300 K. The parameter estimation was performed by least square minimization of the difference between measured and predicted values of effective thermal conductivity at a density of 24 kilograms per cubic meters and at nominal pressures of 1.33 x 10(exp -4) and 99.98 kPa. The numerical model was validated by comparison with steady-state effective thermal conductivity measurements at other densities and pressures. The numerical model was also validated by comparison with a transient thermal test simulating reentry aerodynamic heating conditions.

Daryabeigi, Kamran↗