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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 1,009 records · Page 56

Genetic Optimization of Planetary Gearboxes Based on Analytical Gearing Equations

Electric and hybrid electric vertical takeoff and landing vehicles will require high performance electric motor driven propulsion systems to enable fuel burn and emissions benefits over traditional liquid fuel powered rotorcraft. One key to the design of a high performance electric motor driven propulsion systems is to be able to estimate the mass and efficiency of a gearbox at various motor and propellor operating speeds. Knowing how gearbox mass and efficiency trade with motor and propellor rotational speed, allows motor and propellor RPM to be traded in an overall optimization of the propulsion system. In this paper, a genetic optimization tool for estimating the mass and efficiency of gearboxes is presented. Example results from the tool are presented and compared to existing correlations in use by NASA aircraft design codes.

Thomas Tallerico↗

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

Uncertainty quantification↗

Genetic Relationships and the Nucleosynthetic Heritage of the Asteroid Bennu

The OSIRIS-REx sample return mission visited the B-type asteroid Bennu and delivered 121.6 gof pristine material to Earth in September 2023. Genetic links between this pristine material and different meteorite groups can be determined using nucleosynthetic isotope variations. These variations reflect the heterogeneous distribution of isotopically distinct dust from different stellar environments within the protoplanetary disk. They can therefore be used to constrain different formation locations of parent asteroids [e.g., 1]. In addition, isotope variations are powerful tracers to establish the nucleosynthetic heritage of returned samples [e.g., 2] and to evaluate mixing and reservoir formation within the disk. Here we present nucleosynthetic Ti and Fe isotope data for samples from Bennu and several carbonaceous chondrites. We also report the Ti isotope composition of hand-picked matrix fractions from CR and CV meteorites.

M Rüfenacht↗

Development of Genetic Countermeasures for Enhancing Cellular Stress Tolerance on a Lunar Surface Mission

The Lunar Explorer Instrument for space biology Applications (LEIA) LEIA investigates the response to partial gravity and ionizing radiation of: Different DNA damage and stress response pathways and Bioproduction of antioxidants LEIA utilizes: Various strains of the yeast Saccharomyces cerevisiae, which will be desiccated in fluidic cards and rehydrated on the lunar surface LEIA develops: Genetic countermeasures to improve tolerance to the desiccation process and the constraints associated with long duration missions beyond low Earth orbit (LEO)

Neha Lingam↗

Unnatural reactive amino acid genetic code additions

This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

59 BASIC BIOLOGICAL SCIENCES↗

Twenty-Seventh Fungal Genetics Conference, Asilomar, CA, March 12-17, 2013

This meeting brings together ~900 international scientists to discuss the latest research on fungal genetics. Sessions of particular relevance to DOE include lignocellulose degradation, cellulose conversion to fermentable sugars, fermentation of sugars to fuel molecules. Other sessions cover fungal diseases of biomass crops (miscanthus, corn, switchgrass, etc.).

09 BIOMASS FUELS↗

Genetic algorithms and their applications in accelerator physics

Multi-objective optimization techniques are widely used in an extremely broad range of fields. Genetic optimization for multi-objective optimization was introduced in the accelerator community in relatively recent times and quickly spread becoming a fundamental tool in multi-dimensional optimization problems. This discussion introduces the basics of the technique and reviews applications in accelerator problems.

43 PARTICLE ACCELERATORS↗

Unnatural reactive amino acid genetic code additions

This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

59 BASIC BIOLOGICAL SCIENCES↗

Expanding the eukaryotic genetic code

This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic Algorithms and Classification Trees in Feature Discovery: Diabetes and the NHANES database

This paper presents a feature selection methodology that can be applied to datasets containing a mixture of continuous and categorical variables. Using a Genetic Algorithm (GA), this method explores a dataset and selects a small set of features relevant for the prediction of a binary (1/0) response. Binary classification trees and an objective function based on conditional probabilities are used to measure the fitness of a given subset of features. The method is applied to health data in order to find factors useful for the prediction of diabetes. Results show that our algorithm is capable of narrowing down the set of predictors to around 8 factors that can be validated using reputable medical and public health resources.

Heredia-Langner, Alejandro↗

Utilizing Genetic Programming to Identify Failures in ICS Networks

Previously, researchers have attempted to apply machine learning techniques to network anomaly detection problems. Due to the staggering amount of variety that can occur in normal networks, the results have often been underwhelming. These challenges are far less pronounced when considering industrial control system (ICS) networks. The recurrent nature of these networks results in less noise and more consistent patterns for a machine learning algorithm to recognize. Here, we propose a method of evolving decision trees through genetic programming (GP) in order to detect network anomalies, such as device outages. Our approach extracts over a dozen features from network packet captures and netflows, normalizes them, and relates them in decision trees using fuzzy logic operators. Furthermore, the trees were used to detect three specific network events from three different points on the network across a statistically significant number of runs and achieved 100% accuracy on five of the nine experiments. When the trees attempted to detect more challenging events at points of presence further from the occurrence, the accuracy averaged to above 98%. Finally, using our method, all of the evolutionary cycles of the GP algorithm are computed a-priori, allowing the best resultant trees to be deployed as semi-real-time sensors with little overhead.

97 MATHEMATICS AND COMPUTING↗

Expanding the eukaryotic genetic code

This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

59 BASIC BIOLOGICAL SCIENCES↗

Unnatural reactive amino acid genetic code additions

This invention provides compositions and methods for producing translational components that expand the number of genetically encoded amino acids in eukaryotic cells. The components include orthogonal tRNAs, orthogonal aminoacyl-tRNA synthetases, orthogonal pairs of tRNAs/synthetases and unnatural amino acids. Proteins and methods of producing proteins with unnatural amino acids in eukaryotic cells are also provided.

59 BASIC BIOLOGICAL SCIENCES↗

Constructs and methods for genome editing and genetic engineering of fungi and protists

Provided herein are constructs for genome editing or genetic engineering in fungi or protists, methods of using the constructs and media for use in selecting cells. The construct include a polynucleotide encoding a thymidine kinase operably connected to a promoter, suitably a constitutive promoter; a polynucleotide encoding an endonuclease operably connected to an inducible promoter; and a recognition site for the endonuclease. The constructs may also include selectable markers for use in selecting recombinations.

59 BASIC BIOLOGICAL SCIENCES↗

Development Of A Novel Genetic Algorithm-based Optimization Method For Design Of Nuclear Criticality Experiments

A new evaluation of isotopic molybdenum total neutron cross section data based on measurements performed at Rensselaer Polytechnic Institute prompted researchers at Rensselaer and Los Alamos National Laboratory (LANL) to design a nuclear criticality experiment for the validation of the data. A novel approach of criticality experiment design employing a genetic algorithm-based optimization technique was developed. The method produced a critical experiment with a cross section sensitivity that exceeded target specifications by an order of magnitude.

59 BASIC BIOLOGICAL SCIENCES↗