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At least 91 records · Page 5

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.↗

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.↗

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Rajkumar, T.↗

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.

Long, Jason D.↗

Modeling Leadership Styles in Human-Robot Team Dynamics

The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

Cruz, Gerardo E.↗

Sensorimotor Predictors: Examining the Relationship Between Measures of Post-Landing Sensorimotor Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to Earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study is to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on sensorimotor functional tasks. To date, we have recruited fifteen astronauts who returned from the International Space Station on Soyuz and participated in sensorimotor field tests and/or posturography within one day following long-duration spaceflight. We are specifically utilizing a combination of three quantitative post-flight functional task outcomes(relative to pre-flight baselines): tandem walk, recovery from fall and dynamic posturography, along with a subjective self-rating of post-flight decrements and recovery. The recovery from fall is performed with eyes open on a stable support, allowing the use of vestibular, visual and proprioceptive feedback for task performance. In contrast, the dynamic posturography measures are performed with eyes closed on asway-referenced unstable support, requiring reliance on vestibular feedback for task performance. Tandem walk is performed on a stable surface with eyes open and eyes closed. Fourteen of the 15 subjects performed the field tests. These were nominally performed during three timepoints on the first postflight day, while posturography was performed only once during the third time point after direct return to JSC. More than 20% were unable to complete the initial field testing in the medical tent, while all participants completed testing during the third time point at JSC. As expected, there was considerable variability among all performance outcome measures, with more variability post-flight relative to preflight. Given the variability in all post-flight outcomes, we have been examining the relationships in performance across tasks. While there is a strong association within tests obtained at different landing daytime points, our preliminary findings suggest that by R+24 hrs performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. This underscores the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. We expect that further examining specific behavioral, neuroimaging and genetic sensorimotor biomarkers with post-flight functional task performance will improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

S J Wood↗

Sensorimotor Predictors: Examining the Relationship Between Measures of Post-Landing Sensorimotor Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to Earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study is to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on sensorimotor functional tasks. To date, we have recruited fifteen astronauts who returned from the International Space Station on Soyuz and participated in sensorimotor field tests and/or posturography within one day following long-duration spaceflight. We are specifically utilizing a combination of three quantitative post-flight functional task outcomes(relative to pre-flight baselines): tandem walk, recovery from fall and dynamic posturography, along with a subjective self-rating of post-flight decrements and recovery. The recovery from fall is performed with eyes open on a stable support, allowing the use of vestibular, visual and proprioceptive feedback for task performance. In contrast, the dynamic posturography measures are performed with eyes closed on asway-referenced unstable support, requiring reliance on vestibular feedback for task performance. Tandem walk is performed on a stable surface with eyes open and eyes closed. Fourteen of the 15 subjects performed the field tests. These were nominally performed during three timepoints on the first post flight day, while posturography was performed only once during the third time point after direct return to JSC. More than 20% were unable to complete the initial field testing in the medical tent, while all participants completed testing during the third time point at JSC. As expected, there was considerable variability among all performance outcome measures, with more variability post-flight relative to preflight. Given the variability in all post-flight outcomes, we have been examining the relationships in performance across tasks. While there is a strong association with in tests obtained at different landing daytime points, our preliminary findings suggest that by R+24 hrs performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. This underscores the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. We expect that further examining specific behavioral, neuroimaging and genetic sensorimotor biomarkers with post-flight functional task performance will improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

Yiri De Dios↗

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

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

Non-NASA Center↗

Biological Moleculars: Have Most of Our Problems Already Been Solved?

Evolution has resulted in biological machinery that engineers have great reason to envy and at present can only poorly mimic. This is not just a curiosity as biological systems perform many functions that are desired industrial processes. Examples include photosynthesis, chemosynthesis, energy storage, low temperature chemical conversion, reproducible manufacture of chemical compounds, etc. The bases of biological machinery are the proteins and nucleic acids that comprise living organisms. Each molecule functions as a part of a biological machine. In many cases the molecule can be properly regarded as a stand alone machine of its own. Concepts and methods for harnessing the power of biological molecules exist but are often overlooked in the industrial world. Some are old and appear crude but are quite effective, e.g. the fermentation of grains and fruits. Currently, there is a revolution in progress regarding the harnessing biological processes. These include techniques such as genetic manipulation via polymerase chain reaction, forced evolution also known as evolution in a test tube, determination of molecular structure, and combinatorial chemistry. The following is a brief discussion on how these processes are performed and how they may relate to industrial and aerospace processes.

Downey, James P.↗

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Taylor, Jaime R.↗

B Complex 5-Methyltetrahydrofolate, Riboflavin, Pyridoxine, and Methylcobalamin Supplementation as a Non-Mechanical Countermeasure to Mitigate Optic Disc Edema Changes During Strict 6º Head-Down Tilt Bed Rest

A subset of astronauts on International Space Station missions have experienced optic disc edema, part of what is characterized as Spaceflight Associated Neuro-ocular Syndrome (SANS). While the precise cause of SANS is unknown, it is likely that there are multiple contributing factors, including genetic and environmental factors. Our recent work has shown that crewmembers with SANS have higher concentrations of metabolic biomarkers of impairments in the one-carbon metabolic pathway compared to unaffected astronauts - before, during, and after f light (1). B-vitamin status and the presence of one-carbon pathway single nucleotide polymorphism (SNP) variants predicted the incidence of SANS pathologies, including optic disc edema (2). Specifically, the G allele of methionine synthase reductase (MTRR) A66G and the C allele of serine hydroxymethyltransferase-1 (SHMT1) C1420T were associated with increased incidence of SANS pathologies (2). In a recent 30-d bed rest head-down tilt study with 0.5% CO2 exposure, 5 of 11 subjects developed optic disc edema (4) and the same SHMT1 C1420T and MTRR A66G genetic variants were associated with a larger increase in total retina thickness, a quantitative measure of optic disc edema (5). We published a multi-hit hypothesis of how genetics represents an indispensable element of SANS, which is a multifactorial problem (6). In brief: endothelial dysfunction secondary to genetic, biochemical/nutritional, and physiological (e.g., cardiovascular/fluid shift) f actors could lead to optic disc edema and the other ocular changes that occur in SANS. We expanded this hypothesis to include the possibility that genetic effects on B-vitamin status can alter nitric oxide synthesis and oxidative stress in the endothelium. This in turn could alter the turnover of structural components of the sclera, making it more susceptible to pathologic changes when faced with stressors related to the unrelenting headward fluid shift that occurs in weightlessness and strict head-down tilt bed rest (5). If the relationships that we have observed in flight and ground-based research hold true for the SANS Countermeasure Study, these genetic factors could predict who will be more susceptible to the development of SANS, and more importantly could also provide countermeasure options. As has been shown extensively in the literature, vitamin supplementation can serve to overcome genetic hindrances to one-carbon biochemistry and vascular physiology. Thus, based on our findings, publications, and hypotheses, supported by extensive supporting literature, we had hoped to test in the SANS Countermeasure Study the efficacy of a bioactive B-vitamin complex as a countermeasure to optimize function of the one-carbon pathway and prevent or mitigate optic disc edema during strict 6-degree head down tilt bed rest, and ultimately in space f light. While the supplement is no longer planned to be tested in the SANS Countermeasure Study because of laws regulating supplementation studies like this costing much more than initially planned, we will assess the contribution of one-carbon pathway genetics and B-vitamin status to SANS risk.

S R Zwart↗

Rhodoferax antarcticus sp. nov., a moderately psychrophilic purple nonsulfur bacterium isolated from an Antarctic microbial mat

A new species of purple nonsulfur bacteria isolated from an Antarctic microbial mat is described. The organism, designated strain ANT.BR, was mildly psychrophilic, growing optimally at 15-18 degrees C with a growth temperature range of 0-25 degrees C. Cells of strain ANT.BR were highly motile curved rods and spirals, contained bacteriochlorophyll a, and showed a multicomponent in vivo absorption spectrum. A specific phylogenetic relationship was observed between strain ANT.BR and the purple bacterium Rhodoferax fermentans FR2T, and the two organisms shared several physiological and other phenotypic properties, with the notable exception of growth temperature optimum. Tests of genomic DNA hybridization, however, showed Rfx. fermentans FR2T and strain ANT.BR to be genetically distinct bacteria. Because of its unique set of properties, especially its requirement for low growth temperatures, we propose to recognize strain ANT.BR as a new species of the genus Rhodoferax, Rhodoferax antarcticus, named for its known habitat, the Antarctic.

NASA Discipline Exobiology↗

Testing A Concept of Operations for the Space Algae-2 Spaceflight Experiment

Algae has abundant potential spaceflight applications to enable future crewed missions and habitation beyond low-Earth orbit, including production of essential nutrients, oxygen, and biofuels. Implementing algae production in space requires understanding how different algae species respond to spaceflight stressors such as microgravity and radiation over a realistic production time course. Space Algae-2 is focusing on Arthrospira platensis, a filamentous cyanobacteria commonly known as Spirulina. A. platensis is a human nutritional supplement on Earth that is a good source of essential amino acids, β-carotene, thiamin, riboflavin, and antioxidants. The Space Algae-2 experiment plans to grow and passage A. platensis continuously aboard the International Space Station for six months. The algae produced will be analyzed with multi-omics profiling to monitor for genetic and phenotype stability in the spaceflight environment. This presentation will report the results from pre-flight science verification tests of the concept of operations for Space Algae-2. The purpose of these tests was to determine if the proposed crew operations for serial passages, sample collection, and sample preservation are feasible to meet science requirements for axenic culturing and preservation of DNA, RNA, protein, and nutritional metabolites.

Microalgae↗

Scheduling Earth Observing Satellites with Evolutionary Algorithms

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

Globus, Al↗

Bionutrients-1, On-Demand Production of Nutrients in Space

Future long-duration missions face significant challenges maintaining crew health. A critical area is supplying adequate nutrition, as certain vitamins and nutrients in supplied foods and supplements demonstrate substantial degradation during extended storage. To address this issue, we are developing and flight-testing a platform technology that demonstrates in situ microbial production of targeted nutrients over extended mission durations. This 5-year experiment, known as BioNutrients-1, was started on the International Space Station in May 2019. It involves two components: an on-orbit hydration and production experiment; and the development of space-compatible, key bio-manufacturing microorganisms. On-orbit testing utilizes a small “production pack” system that encloses sterile edible growth substrate and desiccated Saccharomyces cerevisiae strains genetically engineered to produce the nutrients beta-carotene or zeaxanthin. On hydration and mixing of the production pack, the organisms revive and grow until limited by the depletion of growth media, hypothetically leading to consistent amounts of biomass and nutrients. In eventual mission applications, the packet contents would be heat treated to inactivate the microorganisms prior to consumption. For these flight experiments, the packet will not be heat treated, but will instead be frozen for return to Earth for analyses. In addition to the production pack trials, 14 different microorganisms/treatments were also delivered to ISS for long-duration storage. These samples will be intermittently returned to Earth and analyzed to determine survival rates and genomics. For this presentation, initial data from returned samples and ground controls will be discussed.

Hindupur, Aditya↗

BioNutrients-1: On-Demand Production of Nutrients in Space

Future long-duration missions face significant challenges maintaining crew health. A critical area is supplying adequate nutrition, as certain vitamins and nutrients in supplied foods and supplements demonstrate substantial degradation during extended storage. To address this issue, we are developing and flight-testing a platform technology that demonstrates in situ microbial production of targeted nutrients over extended mission durations. This 5-year experiment, known as BioNutrients-1, was started on the International Space Station in May 2019. It involves two components: an on-orbit hydration and production experiment; and the development of space-compatible, key bio-manufacturing microorganisms. On-orbit testing utilizes a small "production pack" system that encloses sterile edible growth substrate and desiccated Saccharomyces cerevisiae strains genetically engineered to produce the nutrients beta-carotene or zeaxanthin. On hydration and mixing of the production pack, the organisms revive and grow until limited by the depletion of growth media, hypothetically leading to consistent amounts of biomass and nutrients. In eventual mission applications, the packet contents would be heat treated to inactivate the microorganisms prior to consumption. For these flight experiments, the packet will not be heat treated, but will instead be frozen for return to Earth for analyses. In addition to the production pack trials, 14 different microorganisms/treatments were also delivered to ISS for long-duration storage. These samples will be intermittently returned to Earth and analyzed to determine survival rates and genomics. For this presentation, initial data from returned samples and ground controls will be discussed.

Hindupur, Aditya↗

Diversity Buffers Winegrowing Regions from Climate Change Losses

Agrobiodiversity—the variation within agricultural plants, animals, and practices—is often suggested as a way to mitigate the negative impacts of climate change on crops [S. A. Wood et al., Trends Ecol. Evol. 30, 531–539 (2015)]. Recently, increasing research and attention has focused on exploiting the intraspecific genetic variation within a crop [Hajjar et al., Agric. Ecosyst. Environ. 123, 261–270 (2008)], despite few relevant tests of how this diversity modifies agricultural forecasts. Here, we quantify how intraspecific diversity, via cultivars, changes global projections of growing areas. We focus on a crop that spans diverse climates, has the necessary records, and is clearly impacted by climate change: winegrapes (predominantly Vitis vinifera subspecies vinifera). We draw on long-term French records to extrapolate globally for 11 cultivars (varieties) with high diversity in a key trait for climate change adaptation—phenology. We compared scenarios where growers shift to more climatically suitable cultivars as the climate warms or do not change cultivars. We find that cultivar diversity more than halved projected losses of current winegrowing areas under a 2 °C warming scenario, decreasing areas lost from 56 to 24%. These benefits are more muted at higher warming scenarios, reducing areas lost by a third at 4 °C (85% versus 58%). Our results support the potential of in situ shifting of cultivars to adapt agriculture to climate change—including in major winegrowing regions—as long as efforts to avoid higher warming scenarios are successful.

Morales-Castilla, Ignacio↗

Polymorphic Electronic Circuits

Polymorphic electronics is a nascent technological discipline that involves, among other things, designing the same circuit to perform different analog and/or digital functions under different conditions. For example, a circuit can be designed to function as an OR gate or an AND gate, depending on the temperature (see figure). Polymorphic electronics can also be considered a subset of polytronics, which is a broader technological discipline in which optical and possibly other information- processing systems could also be designed to perform multiple functions. Polytronics is an outgrowth of evolvable hardware (EHW). The basic concepts and some specific implementations of EHW were described in a number of previous NASA Tech Briefs articles. To recapitulate: The essence of EHW is to design, construct, and test a sequence of populations of circuits that function as incrementally better solutions of a given design problem through the selective, repetitive connection and/or disconnection of capacitors, transistors, amplifiers, inverters, and/or other circuit building blocks. The evolution is guided by a search-and-optimization algorithm (in particular, a genetic algorithm) that operates in the space of possible circuits to find a circuit that exhibits an acceptably close approximation of the desired functionality. The evolved circuits can be tested by computational simulation (in which case the evolution is said to be extrinsic), tested in real hardware (in which case the evolution is said to be intrinsic), or tested in random sequences of computational simulation and real hardware (in which case the evolution is said to be mixtrinsic).

Stoica, Adrian↗