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Results for “evolutionary computation”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

The fueling of active galaxies

Collisions of galaxies are often invoked to explain violent phenomena in the universe. The dynamics of interacting galaxies is intrinsically three-dimensional and involves both gas and stellar dynamics. In general, a computational approach is needed to model galactic collisions. Galaxy encounters are studied using a hybrid N-body/hydrodynamics code, capable of integrating systems of stars, gas, and dark matter in a fully self-consistent manner. These experiments demonstrate that gravitational coupling between gas and stars in galactic interactions can drive most of the gas throughout a galaxy into the nucleus of a merger remnant. The high densities in these gas concentrations are likely to result in strong bursts of star formation. Hence, this process may explain the nuclear starbursts in some systems of interacting galaxies. Further collapse of these gas concentrations can trigger even more intense activity if some gas is eventually accreted by a supermassive black hole. Such an evolutionary sequence may account for some quasars and active galactic nuclei.

Hernquist, Lars↗
DOE OSTI2020

Standardized phylogenetic and molecular evolutionary analysis applied to species across the microbial tree of life

There is growing interest in reconstructing phylogenies from the copious amounts of genome sequencing projects that target related viral, bacterial or eukaryotic organisms. To facilitate the construction of standardized and robust phylogenies for disparate types of projects, we have developed a complete bioinformatic workflow, with a web-based component to perform phylogenetic and molecular evolutionary (PhaME) analysis from sequencing reads, draft assemblies or completed genomes of closely related organisms. Furthermore, the ability to incorporate raw data, including some metagenomic samples containing a target organism (e.g. from clinical samples with suspected infectious agents), shows promise for the rapid phylogenetic characterization of organisms within complex samples without the need for prior assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Reinforcement learning in discrete action space applied to inverse defect design

Abstract Reinforcement learning (RL) algorithms that include Monte Carlo Tree Search (MCTS) have found tremendous success in computer games such as Go, Shiga and Chess. Such learning algorithms have demonstrated super-human capabilities in navigating through an exhaustive discrete action search space. Motivated by their success in computer games, we demonstrate that RL can be applied to inverse materials design problems. We deploy RL for a representative case of the optimal atomic scale inverse design of extended defects via rearrangement of chalcogen (e.g. S) vacancies in 2D transition metal dichalcogenides (e.g. MoS 2 ). These defect rearrangements and their dynamics are important from the perspective of tunable phase transition in 2D materials i.e. 2H (semi-conducting) to 1T (metallic) in MoS 2 . We demonstrate the ability of MCTS interfaced with a reactive molecular dynamics simulator to efficiently sample the defect phase space and perform inverse design—starting from randomly distributed S vacancies, the optimal defect rearrangement of defects corresponds a line defect of S vacancies. We compare MCTS performance with evolutionary optimization i.e. genetic algorithms and show that MCTS converges to a better optimal solution (lower objective) and in fewer evaluations compared to GA. We also comprehensively evaluate and discuss the effect of MCTS hyperparameters on the convergence to solution. Overall, our study demonstrates the effectives of using RL approaches that operate in discrete action space for inverse defect design problems.

42 ENGINEERING↗
DOE OSTI2024

Novel Z-DNA binding domains in giant viruses

Z-nucleic acid structures play vital roles in cellular processes and have implications in innate immunity due to their recognition by Zα domains containing proteins (Z-DNA/Z-RNA binding proteins, ZBPs). Although Zα domains have been identified in six proteins, including viral E3L, ORF112, and I73R, as well as, cellular ADAR1, ZBP1, and PKZ, their prevalence across living organisms remains largely unexplored. In this study, we introduce a computational approach to predict Zα domains, leading to the revelation of previously unidentified Zα domain-containing proteins in eukaryotic organisms, including non-metazoan species. Our findings encompass the discovery of new ZBPs in previously unexplored giant viruses, members of the Nucleocytoviricota phylum. Through experimental validation, we confirm the Zα functionality of select proteins, establishing their capability to induce the B-to-Z conversion. Additionally, we identify Zα-like domains within bacterial proteins. While these domains share certain features with Zα domains, they lack the ability to bind to Z-nucleic acids or facilitate the B-to-Z DNA conversion. Our findings significantly expand the ZBP family across a wide spectrum of organisms and raise intriguing questions about the evolutionary origins of Zα-containing proteins. Moreover, our study offers fresh perspectives on the functional significance of Zα domains in virus sensing and innate immunity and opens avenues for exploring hitherto undiscovered functions of ZBPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Wormholes Within: A Study of 1, 3, 5–Triamino–2, 4, 6–Trinitrobenzene Crystal Morphology by Micro and Nano–Scale X–Ray Computed Tomography and its Effects Upon the Shock Sensitivity of Detonation

We report that we understand heterogeneous-explosive detonation only to the extent that we can first measure the salient chemical and microstructural features. Barring an inordinate amount of trial and error, we can tailor the detonation properties of our HE formulations only to the extent that we understand (at least qualitatively) the same effects. As an insensitive high explosive, 1, 3, 5-triamino-2, 4, 6-trinitrobenzene (TATB) burns more heterogeneously than conventional high explosives, making its detonation properties sensitive to microstructure. The Benziger route can produce various grain morphologies depending on the amount of water used in the amination step. So-called dry-aminated (DA) TATB crystals are riddled with a void structure called wormholes, which are washed out ammonium chloride (NH4Cl) inclusions that form during synthesis. So-called wet-aminated (WA) TATB crystals do not contain NH 4 Cl inclusions but possess a very convoluted external structure. Using both micro and nano-scale CT, we explore three DA-TATB lots that reflect evolutionary processing changes, plus one WA-TATB material. Micro CT imaged crystal collections show the exterior grain structure, revealing its roughness and providing a crude particle size measurement. The DA-TATB lots that test most sensitively in the LANL ECOT corner-turning test are roughest, having the appearance of being “corroded”. Nano-scale CT reveals both internal NH 4 Cl inclusions and void structures. The DA-TATB lots that tested intermediate and high sensitivity in ECOT exhibited similar wormhole structures, which were more extensive than that of the low-sensitivity lot. The least sensitive DA-TATB lot also retained more NH 4 Cl, consistent with reduced connectivity of voids to the surface.

1, 3, 5-triamino-2,4↗
DOE OSTI2022

Implementing the donor–acceptor approach in electronically conducting copolymers via electropolymerization

Electropolymerization has become a convenient method for synthesizing and characterizing complex organic copolymers having intrinsic electronic conductivity, including the donor (D)–acceptor (A) class of electronically conducting polymers (ECPs). This review begins with an introduction to the electrosynthesis of common second-generation ECPs. The information obtainable from electroanalytical studies, charge carriers such as polarons (positive and negative) and bipolarons (positive and negative) and doping will be discussed. The evolutionary chain of ECPs is then presented. ECPs comprising electron-rich D and electron-deficient A moieties have been shown to possess intrinsic electronic conductivity and unique optical and electronic properties. They are third generation ECPs and electropolymerization of mixtures of D and A leads to stoichiometrically controlled block copolymers. These D–A type ECPs are discussed on the basis of selected representative materials. Since the discovery of electropolymerization as a powerful tool to synthesize copolymers of conjugated monomers with a pre-determined ratio of D and A repeat units present in the polymer, the field of D–A type ECPs has grown considerably and the literature available since 2004 to 2021 is summarized and tabulated. Electronic and optical properties of the materials determined by computational chemistry are presented. The data obtained from electrochemical and optical methods are compared with those obtained from computational methods and reasons for discrepancies are given. The literature on the concept of electropolymerization extended to synthesizing triblock and many-block copolymers is reviewed. Finally, applications of D–A polymers in optoelectronic devices (organic solar cells and field-effect transistors) and in bio-imaging are explained quoting appropriate examples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Tomography Analysis of Orion Artemis 1 Heatshield Sample

The Orion spacecraft, under NASA's Artemis program, is an integral step in humanity's ambitions of deep space exploration, including our return to the Moon and subsequent mission to Mars. The performance of Orion's heatshield is central to ensuring the safety and success of such missions. This presentation offers a comprehensive overview of the process used in and findings derived from tomography scans of an Artemis 1 heatshield sample executed at the Lawrence Berkeley National Laboratory's Advanced Light Source. These tomography scans captured high-resolution X-Ray images of the heatshield's microstructure, allowing advanced imaging to be employed for 3D image segmentation and visualization of the sample. The Porous Media Analysis (PuMA) software stands central to our analysis, offering robust computational algorithms and methodologies to digitally compute properties of the heatshield material. The presentation discusses the following derived metrics: - Volume fractions, representing the spatial distribution and amounts of various components throughout the heatshield’s depth. - Porosity and crack distributions, offering insights into the void space within the material, critical for understanding the heatshield's structural integrity. - Fiber orientation, detailing the alignment and arrangement of fibers, significant for material orthotropy. - Permeability estimates, quantifying the passage of gas through the material, relevant for re-entry conditions and pyrolysis gasses. One distinctive feature of this study is the comparative evaluation against data obtained from tomography scans of the Exploration Flight Test-1 (EFT-1) heatshield. Such a comparison offers multiple insights, including evaluation of the consistency and repeatability of manufacturing processes as well as understanding of any evolutionary changes in heatshield design or material properties.

Micro-tomography↗
NASA NTRS2021

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Zishuo Zeng↗
DOE OSTI2025

A dynamic likelihood approach to filtering transport processes: advection-diffusion dynamics

A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems –waves–, and in this paper, it is extended via a split step formulation, to handle advection-diffusion problems. In the dynamic likelihood approach, observations and their statistics are used to propagate probabilities along characteristics, evolving the likelihood in time. The estimate posterior thus inherits phase information. For advection-diffusion the advective part of the time evolution is handled on the basis of observations alone, while the diffusive part is informed through the model as well as observations. We expect, and indeed show here, that in advection-dominated problems, the DLF approach produces better estimates than other assimilation approaches, particularly when the observations are sparse and have low uncertainty. The added computational expense of the method is cubic in the total number of observations over time, which is on the same order of magnitude as a standard Kalman filter and can be mitigated by bounding the number of forward propagated observations, discarding the least informative data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

Entropy Splitting and Numerical Dissipation

A rigorous stability estimate for arbitrary order of accuracy of spatial central difference schemes for initial-boundary value problems of nonlinear symmetrizable systems of hyperbolic conservation laws was established recently by Olsson and Oliger (1994) and Olsson (1995) and was applied to the two-dimensional compressible Euler equations for a perfect gas by Gerritsen and Olsson (1996) and Gerritsen (1996). The basic building block in developing the stability estimate is a generalized energy approach based on a special splitting of the flux derivative via a convex entropy function and certain homogeneous properties. Due to some of the unique properties of the compressible Euler equations for a perfect gas, the splitting resulted in the sum of a conservative portion and a non-conservative portion of the flux derivative. hereafter referred to as the "Entropy Splitting." There are several potential desirable attributes and side benefits of the entropy splitting for the compressible Euler equations that were not fully explored in Gerritsen and Olsson. The paper has several objectives. The first is to investigate the choice of the arbitrary parameter that determines the amount of splitting and its dependence on the type of physics of current interest to computational fluid dynamics. The second is to investigate in what manner the splitting affects the nonlinear stability of the central schemes for long time integrations of unsteady flows such as in nonlinear aeroacoustics and turbulence dynamics. If numerical dissipation indeed is needed to stabilize the central scheme, can the splitting help minimize the numerical dissipation compared to its un-split cousin? Extensive numerical study on the vortex preservation capability of the splitting in conjunction with central schemes for long time integrations will be presented. The third is to study the effect of the non-conservative proportion of splitting in obtaining the correct shock location for high speed complex shock-turbulence interactions. The fourth is to determine if this method can be extended to other physical equations of state and other evolutionary equation sets. If numerical dissipation is needed, the Yee, Sandham, and Djomehri (1999) numerical dissipation is employed. The Yee et al. schemes fit in the Olsson and Oliger framework.

Yee, H. C.↗
NASA NTRS1990

Aerothermodynamics and transition in high-speed wind tunnels at NASA Langley

The evolutionary development of subsonic, supersonic, and hypersonic wind tunnels for the study of aerodynamic, aerothermodynamic, and fluid-dynamic characteristics of the flow about models, including transition from laminar to turbulent boundary layers, is discussed. Currently, three supersonic and seven hypersonic wind tunnels are operational at Langley, and two additional tunnels are scheduled to become operational by 1990. In the present work, an effort is made to provide a 'tour'of selected supersonic and hypersonic wind tunnels at NASA-Langley used for aerodynamic and aerothermodynamic testing of models, and to present the evolution of quiet-tunnel technology at this facility over the last decade. It is noted that upgrades to the hypersonic facilities complex are underway in order to provide the high flow quality and improved data accuracy required to calibrate advanced computational fluid-dynamic computer codes. Also to be provided are increased productivity required for configuration development and improved reliability to support major hypersonic programs in an efficient and timely manner.

Beckwith, I. E.↗
NASA NTRS1992

Development of NASA/DOE NTP System Performance Models

A critical enabling technology in the evolutionary development of Nuclear Thermal Propulsion (NTP) is the ability to predict the system performance under a variety of operating conditions. The ability to predict the system performance is critical for mission analysis and for control subsystem testing, as well as for the modeling of various failure modes. Performance must be accurately predicted during steady-state and transient operation, such as start-up, shut-down and after-cooling. The development and application of verified and validated system models has the potential to reduce testing, cost and time required for the technology to again reach flight-ready status. An integrated NASA/DOE team was formed in late 1991 to develop and implement a strategy for modeling NTP systems. It is the intent of the interagency team to develop several levels of computer programs, which vary in detail, to simulate NTP systems based on either prismatic, particle or advanced fuel forms. This paper presents an overview of the models under development by the interagency team. In addition, the status of the development and validation efforts for the Level 1 steady-state parametric model is discussed.

Walton, James T.↗
NASA NTRS2008

Toward Optimal Transport Networks

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Alexandrov, Natalia↗
NASA NTRS2007

Fragmentation hierarchy of bright sungrazing comets and the birth and orbital evolution of the Kreutz System. II. the case for cascading fragmentation

We examine the process of cascading fragmentation for the Kreutz sungrazer system to continue our exploration of its birth, orbital evolution, and temporal clumping. We modify and broaden the two-superfragment model from Paper I to include clusters of ~30 bright comets spanning four centuries and 1000 SOHO sungrazers from 1996 to 2006. The spectacular parent sungrazer X/1106 C1 is assumed to have tidally split shortly after perihelion into a train of major protofragments immersed in a cloud of particulate debris, which at larger heliocentric distances were breaking up nontidally over and over again. We describe potential evolutionary paths for the Kreutz system by linking X/1106 C1 in subgroup I-type orbit with the comet of February 423 in one scenario or with the comet of February 467 in another. The latter scenario accounts for sungrazer clusters in as early as the 16th century, suggests that the progenitor object may have been observed as the comet of 214 BCE, is quite consistent with the orbital distribution of the SOHO sungrazers that sample the central filament of the Kreutz system between the clusters of major sungrazers, and predicts future clusters until ~2120. Comet X/1106 C1 and the common parent of C/1882 R1 and C/1965 S1 were two first-generation fragments of the progenitor that split nontidally on the way to its 5th century perihelion, reminiscent of the superfragments in Paper I. We provide computational tools needed for solving the problem of the Kreutz system’s orbital evolution, but no unique scenarios are presented for the individual comets. Another cluster of bright sungrazers is expected to arrive in the coming decades, its earliest member possibly just several years from now.

Chodas, Paul W.↗
DOE OSTI2025

GenomeFace v1.0

GenomeFace is meta-genome binning software. Metagenomic binning, the process of grouping DNA sequences into taxonomic units, is critical for understanding the functions, interactions, and evolutionary dynamics of microbial communities. We propose a deep learning approach to binning using two neural networks, one based on composition and another on environmental abundance, dynamically weighting the contribution of each based on characteristics of the input data. Trained on over 43,000 prokaryotic genomes, our network for composition-based binning is inspired by metric learning techniques used for facial recognition. Using a task-specific, multi-GPU accelerated algorithm to cluster the embeddings produced by our network, our binner leverages marker genes observed to be universally present in nearly all taxa to grade and select optimal clusters of sequences from a hierarchy of candidates. We evaluate our approach on four simulated datasets with known ground truth. Our linear time integration of marker genes recovers more near complete genomes than state of the art but computationally infeasible solutions using them, while being over an order of magnitude faster. Finally, we demonstrate the scalability and acuity of our approach by testing it on three of the largest metagenome assemblies ever performed. Compared to other binners, we produced 47%-183% more near complete genomes. From these datasets, we find over the genomes of over 3000 new candidate species which have never been previously cataloged, representing a potential 4% expansion of the known bacterial tree of life.

Lettich, Richard [Lawrence Berkeley National Labor↗
DOE OSTI2020

Software classification using phylogenetic techniques

Software, such as malware, may be classified using phylogenetic techniques. An evolutionary history of a representative set of software programs may be reconstructed to generate a reference phylogeny. Dynamic traces of the representative software programs may be obtained. The dynamic traces may include time-ordered sequences of execution commands extracted from running software binaries. Metrics may be developed using the dynamic traces. One or more unknown software programs may then be classified against the reference phylogeny using the metrics developed using the dynamic traces of the representative set of software programs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Star formation and evolution in spiral galaxies.

Evolutionary models for regions of M31 and M33 and the solar neighborhood are based on a stellar birthrate suggested by the dynamics of spiral structure: we assume that stars are formed very efficiently until the gas content reaches equilibrium at its present value, which takes about 1 b.y.; thereafter, the birthrate just equals the rate at which gas enters the system from stellar mass-loss or infall of intergalactic matter. Each model represents an average around a cylindrical-shell-shaped region, which is homogeneous and closed except for possible infall. The disk and spiral-arm populations only are considered. Each star is followed in the H-R diagram from the main sequence to death as an invisible remnant. Integrated magnitudes, colors, mass-to-light ratio (M/L), gas content, helium and metal abundance (Z), are computed in steps of 1 b.y.

Quirk, W. J.↗
NASA NTRS1998

Automatic Molecular Design using Evolutionary Techniques

Molecular nanotechnology is the precise, three-dimensional control of materials and devices at the atomic scale. An important part of nanotechnology is the design of molecules for specific purposes. This paper describes early results using genetic software techniques to automatically design molecules under the control of a fitness function. The fitness function must be capable of determining which of two arbitrary molecules is better for a specific task. The software begins by generating a population of random molecules. The population is then evolved towards greater fitness by randomly combining parts of the better individuals to create new molecules. These new molecules then replace some of the worst molecules in the population. The unique aspect of our approach is that we apply genetic crossover to molecules represented by graphs, i.e., sets of atoms and the bonds that connect them. We present evidence suggesting that crossover alone, operating on graphs, can evolve any possible molecule given an appropriate fitness function and a population containing both rings and chains. Prior work evolved strings or trees that were subsequently processed to generate molecular graphs. In principle, genetic graph software should be able to evolve other graph representable systems such as circuits, transportation networks, metabolic pathways, computer networks, etc.

Globus, Al↗