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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Hybrid Inverse Parameter Identification of Fully Coupled Ductile Damage Model for Steel Sheet DP600 with Two Different Algorithms: Trust Region and Genetic Algorithms

Ductile damage model has been widely regarded as a valuable method to predict the failure of sheet metal. Based on the thermodynamic theory and continuum damage mechanics, the fully coupled ductile damage model can be developed, which also can better predict the initiation and growth of the fracture. But the identifications of model parameters with theoretical methodology are difficult due to the complex coupling relationships existing among all state variables. The inverse methodology is regarded as a good method to resolve the problem. In this paper, the recently proposed fully coupled ductile damage model is chosen to investigate the deformation behavior of DP600 steel, in which the mixed saturation isotropic and kinematic hardenings are taken into account and fully coupled with the ductile damage. During the identification process, the least square formula of the error between experimental and numerical results is selected as the target function. The trust region algorithm and genetic algorithm are used with the help of MATLAB for the identification of three damage parameters. Finally, by comparing the experimental and numerical results, the validations of two algorithms are proved. The efficiency of the optimization process with trust region algorithm is higher, but with lower accuracy. Meanwhile, the optimization process is greatly affected by the chosen initial values of the ductile damage parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Functional coding and non-coding variants in human BRCA1 gene and their use in genetic screening

BRCA1 is involved in double-strand DNA damage repair pathways, and mutations in the gene are associated with hereditary breast and ovarian cancers. With great help of the development of high-throughput DNA sequencing techniques numerous single-nucleotide polymorphisms (SNPs) and insertion deletion (Indel) mutations are detected on both coding and non-coding/regulatory regions of the BRCA1. Mutations may cause pathogenic or benign changes on the protein function or affect its expression. In the last decade, use of genetic screening tests to detect mutations on such genes has become greatly popular. However, it is very important to know the effect of the detected mutations, which is mostly possible by the use of predictive softwares, and also the related family history to be able to correctly analyse the screening results and to inform the patient. Therefore, use of in silico and in vitro techniques to score the pathogenicity of detected variants on genes like BRCA1 is now of great importance. Otherwise, results obtained from screening tests and family history cannot be analysed precisely.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

New approach based on group technology for the consolidation problem in cloud computing-mathematical model and genetic algorithm

Resource management is a hotspot issue in distributed systems like cloud computing (CC). It means how to prepare the computational resources, i.e., servers and virtual machines (VMS), to execute the tasks. This paper offers a new approach based on Group Technology (GT)—known as a powerful philosophy for the resource management in cellular manufacturing systems—to deal with the resource management problem in CC. We develop a mathematical model to optimally consolidate the VMs, servers and tasks simultaneously to control several important factors such as task migrations and server load variation, as well as the number of VMs. To test the validity of our proposed model, several small problems are generated randomly and solved by LINGO 9 software. Furthermore, to cope with larger problems, which cannot be solved optimally, a genetic algorithm is proposed. We, finally, compare our methods with the most well-known algorithms in this context, round robin (RR) and first-come, first-served (FCFS) algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2019

Process design and economics for production of advanced biofuels from genetically modified lipid-producing sorghum

This study evaluates the potential for making advanced biofuels from genetically modified (GM) lipid–producing sorghum. A biodiesel coproduction process is developed to extract, purify, and upgrade lipids to diesel fuel while carbohydrates are utilized for making ethanol through acid thermal pretreatment, enzymatic hydrolysis, and fermentation. To assess the advantages of coproducing biodiesel from GM–sorghum, process economics are compared to a cellulosic ethanol biorefinery receiving non-GM sorghum. Minimum ethanol selling prices (MESP) that reach a breakeven point after 30 years of service life are calculated as an economic index to compare the two processes. Results indicate that biodiesel coproduction improves the economics by lowering the MESP from 3.08/gal for the ethanol-only process to 2.46/gal. Sensitivity analyses reveal that increasing sorghum’s lipid content, increasing the lipid extraction efficiency, and reducing the solvent-to-solids ratio in lipid extraction columns are the most important process parameters to further enhance technoeconomics. Analyses indicate that a lipid content above 13 wt% (dry basis) or a biomass price less than 65/Mg (dry basis) will result in a 2014 ethanol wholesale price of 2.25/gal for the coproduction process.

09 BIOMASS FUELS↗
DOE OSTI2022

Artificial intelligence based analysis of nanoindentation load–displacement data using a genetic algorithm

In this work, we developed an automated tool, Nanoindentation Neo package for the analysis of nanoindentation load–displacement curves using a Genetic Algorithm (GA) applied to the Oliver-Pharr method (Oliver et al.,1992). For some materials, such as polycrystalline isotropic graphites, Least Squares Fitting (LSF) of the unload curve can produce unrealistic fit parameters. These graphites exhibit sharply peaked unloading curves not easily fit using the LSF, which tends to overestimate the indenter tip geometry parameter. To tackle this problem, we extended our general materials characterization tool Neo for EXAFS analysis (Terry et al., 2021) to fit nanoindentation data. Nanoindentation Neo automatically processes and analyzes nanoindentation data with minimal user input while producing meaningful fit parameters. GA, a robust metaheuristic method, begins with a population of temporary solutions using model parameters called chromosomes; from these we evaluate a fitness value for each solution, and select the best solutions to mix with random solutions producing the next generation. A mutation operator then modifies existing solutions by random perturbations, and the optimal solution is selected. We tested the GA method using Silica and Al reference standards. We fit samples of graphite and a high entropy alloy (HEA) consisting of BCC and FCC phases.

42 ENGINEERING↗
DOE OSTI2025

Developing a robust strength model using physically-informed genetic programming

The strength of materials is influenced by a range of external conditions, such as temperature and deformation rate. Consequently, materials that demonstrate substantial variations in their mechanical behavior due to fluctuations in temperature and strain rate require complex strength models to accurately predict material performance in real-world applications. To predict such complex behavior, a robust and flexible strength model is necessary. In this work, we utilize genetic programming-based symbolic regression (GPSR) to develop data-driven strength models that accurately represent the measured stress–strain responses of tin across a wide range of strain, strain rate and temperature regimes. The GPSR models are constrained by physically-informed conditions, which leads to significant improvement in extrapolation. The best model is integrated into a multi-physics code to perform Taylor impact simulations, validating the model’s accuracy and robustness. In conclusion, the model predictions showed excellent agreement with experimental results, particularly when compared to predictions using traditional strength models.

Genetic programming↗
DOE OSTI2017

Optimization of Type 4 composite pressure vessels using genetic algorithms and simulated annealing

We propose and demonstrate two methodologies for weight minimization of Type 4 (plastic lined, fiber wrapped) compressed hydrogen pressure vessels: genetic algorithms and simulated annealing. We consider 70 MPa vessels with a safety factor of 2.25, and analyze the vessels with classical laminate theory. We propose an objective function based on Tsai-Wu criterion, composite thickness, a safety factor, and a penalization factor. Here, the optimum results are analyzed and compared by a high resolution finite element model. Computer simulations show that the proposed methodology produces more efficient designs by reducing the weight by up to 9.8% and 11.2% when compared to previously published vessel optimization research.

08 HYDROGEN↗
DOE OSTI2022

Ancestral archaea expanded the genetic code with pyrrolysine

The pyrrolysyl-tRNA synthetase (PylRS) facilitates the cotranslational installation of the 22nd amino acid pyrrolysine. Owing to its tolerance for diverse amino acid substrates, and its orthogonality in multiple organisms, PylRS has emerged as a major route to install noncanonical amino acids into proteins in living cells. Recently, a novel class of PylRS enzymes was identified in a subset of methanogenic archaea. Enzymes within this class (ΔPylSn) lack the N-terminal tRNA-binding domain that is widely conserved amongst PylRS enzymes, yet remain active and orthogonal in bacteria and eukaryotes. In this study, we use biochemical and in vivo UAG-readthrough assays to characterize the aminoacylation efficiency and substrate spectrum of a ΔPylSn class PylRS from the archaeon Candidatus Methanomethylophilus alvus. We show that, compared with the full-length enzyme from Methanosarcina mazei, the Ca. M. alvus PylRS displays reduced aminoacylation efficiency but an expanded amino acid substrate spectrum. To gain insight into the evolution of ΔPylSn enzymes, we performed molecular phylogeny using 156 PylRS and 105 pyrrolysine tRNA (tRNA Pyl ) sequences from diverse archaea and bacteria. This analysis suggests that the PylRS•tRNA Pyl pair diverged before the evolution of the three domains of life, placing an early limit on the evolution of the Pyl-decoding trait. Furthermore, our results document the coevolutionary history of PylRS and tRNA Pyl and reveal the emergence of tRNA Pyl sequences with unique A73 and U73 discriminator bases. The orthogonality of these tRNA Pyl species with the more common G73-containing tRNA Pyl will enable future efforts to engineer PylRS systems for further genetic code expansion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Optimization of the magnetic horn for the nuSTORM non-conventional neutrino beam using the genetic algorithm

This paper describes the strategy for optimizing the magnetic horn for the neutrinos from STORed Muons (nuSTORM) facility. The nuSTORM magnetic horn is the primary collection device for the secondary particles generated by bombarding a solid target with 120 GeV protons. As a consequence of the non-conventional beamline designed for nuSTORM, the requirements on the horn are different from those for a conventional neutrino beamline. At nuSTORM, muons decay while circulating in the storage ring, and the detectors are placed downstream of the production straight so as to be exposed to the neutrinos from muon decay. nuSTORM aims at precisely measuring the neutrino cross sections, and providing a definitive statement about the existence of sterile neutrinos. The nuSTORM horn aims at focusing the pions into a certain phase space so that more muons from pion decay can be accepted by the decay ring. The paper demonstrates a numerical method that was developed to optimize the horn design to gain higher neutrino flux from the circulating muons. A Genetic Algorithm (GA) was applied to the simultaneous optimization of the two objectives in this study. In conclusion, the application of the technique discussed in this paper is not limited to either the nuSTORM facility or muon based facilities, but can be used for other neutrino facilities that use magnetic horns as collection devices.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

RF design of APEX2 two-cell continuous-wave normal conducting photoelectron gun cavity based on multi-objective genetic algorithm

High brightness, high repetition rate electron beams are key components for optimizing the performance of next generation scientific instruments, such as MHz-class X-ray Free Electron Laser (XFEL) and Ultra-fast Electron Diffraction/Microscopy (UED/UEM). In the Advanced Photo-injector EXperiment (APEX)at Berkeley Lab, a photoelectron gun based on a 185.7 MHz normal conducting re-entrant RF cavity, has been proven to be a feasible solution to provide high brightness, high repetition rate electron beam for both XFEL and UED/UEM. Based on the success of APEX, a new electron gun system, named APEX2, has been under development to further improve the electron beam brightness. For APEX2, we have designed a new 162.5 MHz two-cell photoelectron gun and achieved a significant increase on the cathode launching field and the beam exit energy. For a fixed charge per bunch, these improvements will allow for the emittance reduction and hence to an increased beam brightness. The design of APEX2 gun cavity is a complex problem with multiple design goals and restrictions, some even competing each other. In conclusion, for a systematic and comprehensive search for the optimized cavity geometry, we have developed and implemented a novel optimization method based on the Multi-Objective Genetic Algorithm (MOGA).

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Genetic algorithm prediction of crystal structure of metastable Si-IX phase

We performed genetic algorithm search for the atomic structure of the long Lime unsolved Si-IX phase. We found two new structures with space groups of P4(2)/m and P-4, respectively, which have lattice parameters in excellent agreement with the experimental data. The phonon calculations showed that the P4(2)/m structure exhibits a soft phonon mode, while the P-4 structure is dynamically stable. Our calculation also showed that the P-4 structure is a meta-stable structure in a pressure range from 0 to 40 GPa, The Si-IX phase could be a mixed phase consisting of the P4(2)/m and the P-4 structures. Published by Elsevier Ltd.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Small bimetallic clusters Agn-1M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15): Density functional theory and genetic algorithm

We investigated the effect of size and composition on the properties of bimetallic nanoclusters. The geometric structures, stabilities, and electronic properties of size-selected Ag n-1 M (M = Au, Co, Cu, Ni, Pd, Pt; n = 3, 9, 15) bimetallic nanoclusters are systematically analyzed using spin-polarized density functional theory (DFT) within the generalized gradient approximation (GGA). We determine the most stable geometries for these clusters using a genetic algorithm (GA) in combination with DFT. Our results show that doping pure silver clusters with an M atom (transition metal), referred to as a “guest atom”, increases the stability as compared to pure Ag n (n = 3, 9, 15) clusters. The results for various properties including formation energy per atom, electronic structure, magnetic moments, and vibrational density of states (VDOS) are evaluated as a function of both size and composition of the system. The adsorption of selected bimetallic clusters on hydroxylated alumina substrate shows weak binding and minor changes in geometric properties except for Ag 8 Pt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Genetic characterization of an adapted pandemic 2009 H1N1 influenza virus that reveals improved replication rates in human lung epithelial cells

The 2009 influenza pandemic originated from a swine-origin H1N1 virus, which, although less pathogenic than anticipated, may acquire additional virulence-associated mutations in the future. To estimate the potential risk, we sequentially passaged the isolate A/Hamburg/04/2009 in A549 human lung epithelial cells. After passage 6, we observed a 100-fold increased replication rate. High-throughput sequencing of viral gene segments identified five dominant mutations, whose contribution to the enhanced growth was analyzed by reverse genetics. The increased replication rate was pinpointed to two mutations within the hemagglutinin (HA) gene segment (HA{sub 1} D130E, HA{sub 2} I91L), near the receptor binding site and the stem domain. The adapted virus also replicated more efficiently in mice in vivo. Enhanced replication rate correlated with increased fusion pH of the HA protein and a decrease in receptor affinity. Our data might be relevant for surveillance of pre-pandemic strains and development of high titer cell culture strains for vaccine production. - Highlights: • We observed a spontaneous mutation of a 2009-pandemic H1N1 influenza virus in vitro. • The adaptation led to a 100-fold rise in replication rate in human A549 cells. • Adaptation was caused by two mutations in the HA gene segment. • Adaptation correlates with increased fusion pH and decreased receptor affinity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Acoustic cloaking: Geometric transform, homogenization and a genetic algorithm

A general process is proposed to experimentally design anisotropic inhomogeneous metamaterials obtained through a change of coordinates in the Helmholtz equation. The method is applied to the case of a cylindrical transformation that allows cloaking to be performed. To approximate such complex metamaterials we apply results of the theory of homogenization and combine them with a genetic algorithm. To illustrate the power of our approach, we design three types of cloaks composed of isotropic concentric layers structured with three types of perforations: curved rectangles, split rings and crosses. These cloaks have parameters compatible with existing technology and they mimic the behavior of the transformed material. Numerical simulations have been performed to qualitatively and quantitatively study the cloaking efficiency of these metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Implication of rare genetic variants of NODAL and ACVR1B in congenital heart disease patients from Indian population

Highlights: • Screening of 300 CHD patients revealed two rare missense variants (p.P51L & p.D327E) in NODAL. • A novel missense variation p.M345I was identified in ACVR1B. • Bioinformatic analyses suggested that these variants could have deleterious role. • Three-dimensional modelling suggested conformation changes in the mutated proteins compared to wild-type. • In vitro studies demonstrated that missense variants affect the function of NODAL and ACVR1B. NODAL signaling plays an essential role in vertebrate embryonic patterning and heart development. Accumulating evidences suggest that genetic mutations in TGF-β/NODAL signaling pathway can cause congenital heart disease in humans. To investigate the implication of NODAL signaling in isolated cardiovascular malformation, we have screened 300 non-syndromic CHD cases and 200 controls for NODAL and ACVR1B by Sanger sequencing and identified two rare missense (c.152C > T; p.P51L and c.981 T > A; p.D327E) variants in NODAL and a novel missense variant c.1035G > A; p.M345I in ACVR1B. All these variants are absent in 200 controls. Three-dimensional protein-modelling demonstrates that both p.P51L and p.D327E variations of NODAL and p.M345I mutation of ACVR1B, affect the tertiary structure of respective proteins. Variants of NODAL (p.P51L and p.D327E) and ACVR1B (p.M345I), significantly reduce the transactivation of AR3-Luc, (CAGA){sub 12}-Luc and (SBE){sub 4}-Luc promoters. Moreover, qRT-PCR results have also deciphered a reduction in the expression of cardiac-enriched transcription factors namely Gata4, Nkx2-5, and Tbx5 in both the mutants of NODAL. Decreased expression of, Gata4, Nkx2-5, Tbx5, and lefty is observed in p.M345I mutant of ACVR1B as well. Additionally, reduced phosphorylation of SMAD2/3 in response to these variants, suggests impaired NODAL signaling and possibly responsible for defective cell fate decision and differentiation of cardiomyocytes leading to CHD phenotype.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways

Gas fermentation by autotrophic bacteria, such as clostridia, offers a sustainable path to numerous bioproducts from a range of local, highly abundant, waste and low-cost feedstocks, such as industrial flue gases or syngas generated from biomass or municipal waste. Unfortunately, designing and engineering clostridia remains laborious and slow. The ability to prototype individual genetic part function, gene expression patterns, and biosynthetic pathway performance in vitro before implementing designs in cells could help address these bottlenecks by speeding up design. Unfortunately, a high-yielding cell-free gene expression (CFE) system from clostridia has yet to be developed. Here in this paper, we report the development and optimization of a high-yielding (236 ± 24 μg/mL) batch CFE platform from the industrially relevant anaerobe, Clostridium autoethanogenum. A key feature of the platform is that both circular and linear DNA templates can be applied directly to the CFE reaction to program protein synthesis. We demonstrate the ability to prototype gene expression, and quantitatively map aerobic cell-free metabolism in lysates from this system. We anticipate that the C. autoethanogenum CFE platform will not only expand the protein synthesis toolkit for synthetic biology, but also serve as a platform in expediting the screening and prototyping of gene regulatory elements in non-model, industrially relevant microbes.

59 BASIC BIOLOGICAL SCIENCES↗