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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 NTRS2017

Developing Model Benchtop Systems for Microbial Experimental Evolution

Understanding how microbes impact an ecosystem has improved through advances of molecular and genetic tools, but creating complex systems that emulate natural biology goes beyond current technology. In fact, many chemical, biological, and metabolic pathways of even model organisms are still poorly characterized. Even then, standard laboratory techniques for testing microbial impact on environmental change can have many drawbacks; they are time-consuming, labor intensive, and are at risk of contamination. By having an automated process, many of these problems can be reduced or even eliminated. We are developing a benchtop system that can run for long periods of time without the need for human intervention, involve multiple environmental stressors at once, perform real-time adjustments of stressor exposure based on current state of the population, and minimize contamination risks. Our prototype device allows operators to generate an analogue of real world micro-scale ecosystems that can be used to model the effects of disruptive environmental change on microbial ecosystems. It comprises of electronics, mechatronics, and fluidics based systems to control, measure, and evaluate the before and after state of microbial cultures from exposure to environmental stressors. Currently, it uses four parallel growth chambers to perform tests on liquid cultures. To measure the population state, optical sensors (LED/photodiode) are used. Its primary selection pressure is UV-C radiation, a well-studied stressor known for its cell- and DNA-damaging effects and as a mutagen. Future work will involve improving the current growth chambers, as well as implementing additional sensors and environmental stressors into the system. Full integration of multiple culture testing will allow inter-culture comparisons. Besides the temperature and OD sensors, other types of sensors can be integrated such as conductivity, biomass, pH, and dissolved gasses such as CO and O. Additional environmental stressor systems like temperature (extreme heat or cold), metal toxicity, and other forms of radiation will increase the scale and testing range.

Developing↗
NASA NTRS1987

USSR Space Life Sciences Digest, issue 11

This is the eleventh issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 54 papers recently published in Russian language periodicals and bound collections and of four new Soviet monographs. Selected abstracts are illustrated. Additional features include the translation of a paper presented in Russian to the United Nations, a review of a book on space ecology, and report of a conference on evaluating human functional capacities and predicting health. Current Soviet Life Sciences titles available in English are cited. The materials included in this issue have been identified as relevant to 30 areas of aerospace medicine and space biology. These areas are: adaptation, aviation physiology, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, cosmonaut training, developmental biology, endocrinology, enzymology, equipment and instrumentation, gastrointestinal systems, group dynamics, genetics, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, and radiobiology.

Hooke, Lydia Razran↗
NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗
NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗
NASA NTRS2004

High Efficiency Thermoelectric Radioisotope Power Systems

The work performed and whose results presented in this report is a joint effort between the University of New Mexico s Institute for Space and Nuclear Power Studies (ISNPS) and the Jet Propulsion Laboratory (JPL), California Institute of Technology. In addition to the development, design, and fabrication of skutterudites and skutterudites-based segmented unicouples this effort included conducting performance tests of these unicouples for hundreds of hours to verify theoretical predictions of the conversion efficiency. The performance predictions of these unicouples are obtained using 1-D and 3-D models developed for that purpose and for estimating the actual performance and side heat losses in the tests conducted at ISNPS. In addition to the performance tests, the development of the 1-D and 3-D models and the development of Advanced Radioisotope Power systems for Beginning-Of-Life (BOM) power of 108 We are carried out at ISNPS. The materials synthesis and fabrication of the unicouples are carried out at JPL. The research conducted at ISNPS is documented in chapters 2-5 and that conducted at JP, in documented in chapter 5. An important consideration in the design and optimization of segmented thermoelectric unicouples (STUs) is determining the relative lengths, cross-section areas, and the interfacial temperatures of the segments of the different materials in the n- and p-legs. These variables are determined using a genetic algorithm (GA) in conjunction with one-dimensional analytical model of STUs that is developed in chapter 2. Results indicated that when optimized for maximum conversion efficiency, the interfacial temperatures between various segments in a STU are close to those at the intersections of the Figure-Of-Merit (FOM), ZT, curves of the thermoelectric materials of the adjacent segments. When optimizing the STUs for maximum electrical power density, however, the interfacial temperatures are different from those at the intersections of the ZT curves, but close to those at the intersections the characteristic power, CP, curves of the thermoelectric materials of the adjacent segments (CP = T(sup 2)Zk and has a unit of W/m). Results also showed that the number of the segments in the n- and p-legs of the STUs optimized for maximum power density are generally fewer than when the same unicouples are optimized for maximum efficiency. These results are obtained using the 1-D optimization model of STUs that is detailed in chapter 2. A three-dimensional model of STUs is developed and incorporated into the ANSYS commercial software (chapter 3). The governing equations are solved, subject to the prescribed

El-Genk, Mohamed↗
NASA NTRS2003

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

Burchett, Bradley T.↗
NASA NTRS2001

Prediction of Unsteady Aerodynamic Coefficients at High Angles of Attack

The nonlinear indicial response method is used to model the unsteady aerodynamic coefficients in the low speed longitudinal oscillatory wind tunnel test data of the 0.1 scale model of the F-16XL aircraft. Exponential functions are used to approximate the deficiency function in the indicial response. Using one set of oscillatory wind tunnel data and parameter identification method, the unknown parameters in the exponential functions are estimated. The genetic algorithm is used as a least square minimizing algorithm. The assumed model structures and parameter estimates are validated by comparing the predictions with other sets of available oscillatory wind tunnel test data.

Pamadi, Bandu N.↗
NASA NTRS1990

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Karr, C. L.↗
NASA NTRS2014

Learning the Task Management Space of an Aircraft Approach Model

Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.

Validation↗
NASA NTRS1998

Genetically Engineered Nanostructure Devices

Material variations on an atomic scale enable the quantum mechanical functionality of devices such as resonant tunneling diodes (RTDs), quantum well infrared photodetectors (QWIPs), quantum well lasers, and heterostructure field effect transistors (HFETs).

NEMO↗
NASA NTRS1991

Catalysis and biocatalysis program

The annual report presents the fiscal year (FY) 1990 research activities and accomplishments for the Catalysis and Biocatalysis Program of the Advanced Industrial Concepts Division (AICD), Office of Industrial Technologies of the Department of Energy (DOE). The mission of the AICD is to create a balanced program of high risk, long term, directed interdisciplinary research and development that will improve energy efficiency and enhance fuel flexibility in the industrial sector. The Catalysis and Biocatalysis Program's technical activities were organized into five work elements: the Molecular Modeling and Catalysis by Design element; the Applied Microbiology and Genetics element; the Bioprocess Engineering element; the Separations and Novel Chemical Processes element; and the Process Design and Analysis element.

Source record↗
NASA NTRS1995

ISSOL Meeting, Barcelona, Spain, 1993

Topics in a conference on the origins of life and the evolution of the biosphere include the origin of chirality, prebiotic chemistry of small biomolecules, primitive polymer formation, RNA regulation and control. Early origins of life and the ecology of hydrothermal systems such as ocean floor vents and their simple organisms are examined. The process of mineral catalysis in Montmorillonite as a model for early metabolism is used. The origin of the genetic code and the development of branching in molecular structures of amino acids is described. Studies are reported of the effects of meteorite impact on early Earth life.

Ferris, James P.↗
NASA NTRS2013

NASA Tech Briefs, December 2013

Topics include: Microwave Kinetic Inductance Detector With; Selective Polarization Coupling; Flexible Microstrip Circuits for; Superconducting Electronics; CFD Extraction Tool for TecPlot From DPLR Solutions; RECOVIR Software for Identifying Viruses; Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model; Orbital Debris Engineering Model (ORDEM) v.3; Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation; Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response; Hermetic Seal Designs for Sample Return Sample Tubes; Silicon Alignment Pins: An Easy Way To Realize a Wafer-to-Wafer Alignment; Positive-Buoyancy Rover for Under Ice Mobility; Electric Machine With Boosted Inductance to Stabilize Current Control; International Space Station-Based Electromagnetic Launcher for Space Science Payloads; Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems; Data Quality Screening Service.

Source record↗
NASA NTRS2011

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗
NASA NTRS2016

IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

global warming↗
NASA NTRS1996

CI Controls for Energy and Environment

Computational intelligence (CI) is a rapidly evolving field that utilizes life imitating metaphors for guiding model building including, but not limited to neural networks, fuzzy logic, genetic algorithms, artificial life, and hybrid CI paradigms. Although the boundaries between artificial intelligence (AI) and CI are not distinct, their research communities are separate and distinct. CI researchers tend to focus on processing numerical data from sensors, while the AI community generally relies on symbolic computing to capture human knowledge. In both areas, there is a great deal of interest and activity in hybrid systems that can offset the limitations of individual methods, extend their capabilities, and create new capabilities. Examples of the benefits that can accrue from hybrid systems are contained.

Biondo, Samuel J.↗