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NASA NTRS1976

Evolutionary problems of Cepheids and other giants investigated with new radiative opacities

Comparison of evolutionary tracks, pulsation constants, and linearized pulsational-stability coefficients for stellar models applicable to the problems of classical Cepheids, whose structures were calculated using the Cox-Stewart (1965) opacities and a recently computed set of opacities. The latter are based on the hot 'Thomas-Fermi' statistical model of the atom for all elements heavier than hydrogen and helium; they contain larger helium and metals contributions, but a smaller hydrogen contribution than the former ones for the same chemical composition. The difference in metals contribution affects mainly the location and shape of the evolutionary tracks on the H-R diagram, while the difference in hydrogen and helium contributions has its greatest effect on the pulsational properties of the Cepheid models. From the comparison of evolutionary tracks it is concluded that: (1) the theoretical M/L relation for evolved giants is changed very little by using the second set of opacities; (2) Q-values for the fundamental mode of radial pulsation in Cepheid envelope models increase if the second set is used, but the classical mass discrepancy remains; and (3) the second set leads to pulsational-instability.

Carson, T. R.↗

NASA NTRS1987

Evolutionary models of interstellar chemistry

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Prasad, Sheo S.↗

NASA NTRS1988

Evolutionary period changes in the rapidly oscillating Ap stars

Preliminary computations of the asymptotic p-mode frequency spacings, and their time derivatives, are presented for a grid of evolutionary models of the rapidly oscillating Ap ('roAp') stars. It is shown how the frequency spacings depend on stellar mass, metallicity, and evolutionary stage. The frequency spacings observed in two of the roAp stars indicate that they either are main-sequence objects or have evolved off of the main sequence, depending on how the pulsation spectrum is interpreted. A way to remove this ambiguity is suggested: secular evolutionary changes in the pulsation frequencies may be measurable if the roAp stars have evolved off of the main sequence. In principle, this determination may be made for the roAp star HR 1217 with existing data.

Heller, Clayton H.↗

NASA NTRS1990

Evolutionary tree reconstruction

It is described how Minimum Description Length (MDL) can be applied to the problem of DNA and protein evolutionary tree reconstruction. If there is a set of mutations that transform a common ancestor into a set of the known sequences, and this description is shorter than the information to encode the known sequences directly, then strong evidence for an evolutionary relationship has been found. A heuristic algorithm is described that searches for the simplest tree (smallest MDL) that finds close to optimal trees on the test data. Various ways of extending the MDL theory to more complex evolutionary relationships are discussed.

Cheeseman, Peter↗

NASA NTRS2002

Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.

Globus, Al↗

NASA NTRS2002

Evolutionary Design and Simulation of a Tube Crawling Inspection Robot

The Space Robotics Assembly Team Simulation (SpaceRATS) is an expansive concept that will hopefully lead to a space flight demonstration of a robotic team cooperatively assembling a system from its constitutive parts. A primary objective of the SpaceRATS project is to develop a generalized evolutionary design approach for multiple classes of robots. The portion of the overall SpaceRats program associated with the evolutionary design and simulation of an inspection robot's morphology is the subject of this paper. The vast majority of this effort has concentrated on the use and modification of Darwin2K, a robotic design and simulation software package, to analyze the design of a tube crawling robot. This robot is designed for carrying out inspection duties in relatively inaccessible locations within a liquid rocket engine similar to the SSME. A preliminary design of the tube crawler robot was completed, and the mechanical dynamics of the system were simulated. An evolutionary approach to optimizing a few parameters of the system was utilized, resulting in a more optimum design.

Craft, Michael↗

NASA NTRS2003

Aerodynamic Shape Optimization Using Evolutionary Algorithms

A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem, both single and two-objective variations, is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.

Holst, Terry L.↗

NASA NTRS2003

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

Lohn, Jason↗

NASA NTRS2003

Aerodynamic Shape Optimization using an Evolutionary Algorithm

A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem-both single and two-objective variations is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.

Hoist, Terry L.↗

NASA NTRS2000

Automated Hardware Design via Evolutionary Search

The goal of this research is to investigate the application of evolutionary search to the process of automated engineering design. Evolutionary search techniques involve the simulation of Darwinian mechanisms by computer algorithms. In recent years, such techniques have attracted much attention because they are able to tackle a wide variety of difficult problems and frequently produce acceptable solutions. The results obtained are usually functional, often surprising, and typically "messy" because the algorithms are told to concentrate on the overriding objective and not elegance or simplicity. advantages. First, faster design cycles translate into time and, hence, cost savings. Second, automated design techniques can be made to scale well and hence better deal with increasing amounts of design complexity. Third, design quality can increase because design properties can be specified a priori. For example, size and weight specifications of a device, smaller and lighter than the best known design, might be optimized by the automated design technique. The domain of electronic circuit design is an advantageous platform in which to study automated design techniques because it is a rich design space that is well understood, permitting human-created designs to be compared to machine- generated designs. developed for circuit design was to automatically produce high-level integrated electronic circuit designs whose properties permit physical implementation in silicon. This process entailed designing an effective evolutionary algorithm and solving a difficult multiobjective optimization problem. FY 99 saw many accomplishments in this effort.

Lohn, Jason D.↗

NASA NTRS1998

Bell-Curve Based Evolutionary Optimization Algorithm

The paper presents an optimization algorithm that falls in the category of genetic, or evolutionary algorithms. While the bit exchange is the basis of most of the Genetic Algorithms (GA) in research and applications in America, some alternatives, also in the category of evolutionary algorithms, but use a direct, geometrical approach have gained popularity in Europe and Asia. The Bell-Curve Based Evolutionary Algorithm (BCB) is in this alternative category and is distinguished by the use of a combination of n-dimensional geometry and the normal distribution, the bell-curve, in the generation of the offspring. The tool for creating a child is a geometrical construct comprising a line connecting two parents and a weighted point on that line. The point that defines the child deviates from the weighted point in two directions: parallel and orthogonal to the connecting line, the deviation in each direction obeying a probabilistic distribution. Tests showed satisfactory performance of BCB. The principal advantage of BCB is its controllability via the normal distribution parameters and the geometrical construct variables.

Sobieszczanski-Sobieski, J.↗

NASA NTRS2004

Taking evolutionary circuit design from experimentation to implementation: some useful techniques and a silicon demonstration

Current techniques in evolutionary synthesis of analogue and digital circuits designed at transistor level have focused on achieving the desired functional response, without paying sufficient attention to issues needed for a practical implementation of the resulting solution. No silicon fabrication of circuits with topologies designed by evolution has been done before, leaving open questions on the feasibility of the evolutionary circuit design approach, as well as on how high-performance, robust, or portable such designs could be when implemented in hardware. It is argued that moving from evolutionary 'design-for experimentation' to 'design-for-implementation' requires, beyond inclusion in the fitness function of measures indicative of circuit evaluation factors such as power consumption and robustness to temperature variations, the addition of certain evaluation techniques that are not common in conventional design. Several such techniques that were found to be useful in evolving designs for implementation are presented; some are general, and some are particular to the problem domain of transistor-level logic design, used here as a target application. The example used here is a multifunction NAND/NOR logic gate circuit, for which evolution obtained a creative circuit topology more compact than what has been achieved by multiplexing a NAND and a NOR gate. The circuit was fabricated in a 0.5 mum CMOS technology and silicon tests showed good correspondence with the simulations.

digital circuits designs↗

NASA NTRS2008

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

Schnell, Andrew R.↗

NASA NTRS2009

Evolutionary Computing Methods for Spectral Retrieval

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

Terrile, Richard↗

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.↗

DOE OSTI2024

Extending evolutionary forecasts across bacterial species

Improving evolutionary forecasting requires progressing from studying repeated evolution of a single genotype under identical conditions to formulating broad principles. These principles should enable predictions of how similar species will adapt to similar selective pressures. Evolve-and-resequence experiments with multiple species allow testing forecasts on different biological levels and elucidating the causes for failed predictions. Here, we show that forecasts for adaptation to static culture conditions can be extended to multiple species by testing previous predictions for Pseudomonas syringae and Pseudomonas savastanoi. In addition to sequence divergence, these species differ in their repertoire of biofilm regulatory genes and structural components. Consistent with predictions, both species repeatedly produced biofilm mutants with a wrinkly spreader phenotype. Predominantly, mutations occurred in the wsp operon, with less frequent promoter mutations near uncharacterized diguanylate cyclases. However, mutational patterns differed on the gene level, which was explained by a lack of conservation in relative fitness of mutants between more divergent species. The same mutation was the most frequent for both species suggesting that conserved mutation hotspots can increase parallel evolution. This study shows that evolutionary forecasts can be extended across species, but that differences in the genotype–phenotype–fitness map and mutational biases limit predictability on a detailed molecular level.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

The Radiata and the evolutionary origins of the bilaterian body plan

The apparent conservation of cellular and molecular developmental mechanisms observed in a handful of bilaterian metazoans has spawned a "race" to reconstruct the bilaterian ancestor. Knowledge of this ancestor would permit us to reconstruct the evolutionary changes that have occurred along specific bilaterian lineages. However, comparisons among extant bilaterians provide an unnecessarily limited view of the ancestral bilaterian. Since the original bilaterians are believed by many to be derived from a radially symmetrical ancestor, additional evidence might be obtained by examining present-day radially symmetrical animals. We briefly review pertinent features of the body plans of the extant radial eumetazoan phyla, the Cnidaria, and Ctenophora, in the context of revealing potential evolutionary links to the bilaterians.

NASA Discipline Evolutionary Biology↗

NASA NTRS2005

Evolutionary Computing for Low-thrust Navigation

The development of new mission concepts requires efficient methodologies to analyze, design and simulate the concepts before implementation. New mission concepts are increasingly considering the use of ion thrusters for fuel-efficient navigation in deep space. This paper presents parallel, evolutionary computing methods to design trajectories of spacecraft propelled by ion thrusters and to assess the trade-off between delivered payload mass and required flight time. The developed methods utilize a distributed computing environment in order to speed up computation, and use evolutionary algorithms to find globally Pareto-optimal solutions. The methods are coupled with two main traditional trajectory design approaches, which are called direct and indirect. In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. In the indirect approach, a thrust control problem is transformed into a costate control problem, and the initial values of the costate vector are optimized. The developed methods are applied to two problems: 1) an orbit transfer around the Earth and 2) a transfer between two distance retrograde orbits around Europa, the closest to Jupiter of the icy Galilean moons. The optimal solutions found with the present methods are comparable to other state-of-the-art trajectory optimizers and to analytical approximations for optimal transfers, while the required computational time is several orders of magnitude shorter than other optimizers thanks to an intelligent design of control vector discretization, advanced algorithmic parameterization, and parallel computing.

optimization↗