Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms
This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing.
Mars↗
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Results for “Genetic”
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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Thermal Conductivity Estimation from Transient Test Data with Embedded Thermocouples using Genetic Algorithm Optimization
Inverse heat transfer methodology previously developed to estimate thermal properties of high temperature fibrous insulation from embedded thermocouples was applied to the thermoplastic polymer, polyether-ether-ketone (PEEK). A small experimental setup was utilized to test the PEEK sample between temperatures of 300 K and 525 K at atmospheric pressure. Cylindrical plugs of PEEK with three thermocouples embedded at various depths were incorporated in the test sample. The experimental PEEK thermocouple data were used as the boundary and initial conditions of a one-dimensional numerical thermal model to predict the internal temperatures of the material. The thermal conductivity of PEEK was estimated with the Continuous Genetic Algorithm optimization technique by searching for the coefficients of a functional form of thermal conductivity that minimized the difference between the experimentally measured and model predicted internal temperature values. The thermal testing, one-dimensional numerical thermal model, optimization algorithm, analysis, and results are presented.
Thermal Properties↗
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.
G F Bomarito↗
Surface Cancellation in Wideband Ground Penetrating Radar Employing Genetic Algorithm AI for Waveform Synthesis
This paper presents a wideband 600-1200 MHz ground penetrating radar (GPR) system for sub-surface exploration of the moon and other planetary bodies. The presented radar system uses an arbitrary waveform generator (AWG) to directly produce the frequency-modulated continuous wave (FMCW) chirp waveform. To address the key challenges of Tx-to-Rx leakage and surface reflections, the system uses a second AWG channel coupled directly to the receiver that provides a cancellation waveform to mitigate the unwanted signals. The system also uses a genetic algorithm AI engine which assesses the radar IF and iteratively improves the parameters of the cancellation waveform injected at the receiver.
Chang, Frank↗
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-tRNAsyn-thetases, 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↗
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↗
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.
60 APPLIED LIFE 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, 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↗
Real time selective harmonic minimization for multilevel inverters using genetic algorithm and artifical neural network angle generation
The work developed here proposes a methodology for calculating switching angles for varying DC sources in a multilevel cascaded H-bridges converter. In this approach the required fundamental is achieved, the lower harmonics are minimized, and the system can be implemented in real time with low memory requirements. Genetic algorithm (GA) is the stochastic search method to find the solution for the set of equations where the input voltages are the known variables and the switching angles are the unknown variables. With the dataset generated by GA, an artificial neural network (ANN) is trained to store the solutions without excessive memory storage requirements. This trained ANN then senses the voltage of each cell and produces the switching angles in order to regulate the fundamental at 120 V and eliminate or minimize the low order harmonics while operating in real time.
Filho, Faete J↗
Developing Highly Sensitive Micro-Biosensors for in-situ Monitoring Mercury and Chromium(IV) Contaminants by Genetically-evolving and Computer-designing Metal-binding Proteins
Mercury has been well known as an environmental pollutant to the environment and to cause serious effects on human health for several decades. To effectively control mercury pollution and reduce mercury damages, the sensitive determination of mercury is essential. Currently, many different types of sensor-based assays have been developed, while the whole-cell biosensor has been gaining increasingly attentions due to its easy reproducibility and the possibility to greatly reduce the cost. However, significant improvements on the specificity, sensitivity, stability and simplicity of the whole-cell biosensor are still needed prior to its eventual commercialization. Sponsored by US Department of Energy under the contract agreement DE-FG02-07ER64410, we applied the special synthetic biology and directed evolution strategies to improve the effectiveness and performance of whole-cell biosensors. We have constructed different whole-cell biosensors for the mercuric ion and methylmercury detection with metalloregulator MerR, fluorescent protein mCherry and organomercurial lyase MerB. By introducing the mercuric transporter MerT, we were able to increase the detection sensitivity of whole-cell biosensors by at least one fold. By introducing the bio-amplification genetic circuit based on the gene cascade expression system of $P_{RM-}cI$ from bacteriophage λ and Pm-XylS2 from Pseudomonas putida, we have increased the detection sensitivity of whole-cell biosensors by 1~2 folds in our tested conditions. With the directed evolution of MerR and subsequent high-throughput screening via color assay and microplate screening, we have dramatically increased the detection sensitivity by up to 10 folds at low concentration of mercury (II) of 1-10nM. Structural modeling and computational analysis of the mutated MerR showed that many mutations could cause the change of a loop to helix, which could be responsible for the increased mercury sensitivity.
02 PETROLEUM↗
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↗
Mutations and genetic targets for enhanced L-tyrosine production
The invention relates to identification of mutations and genetic targets for enhanced L-tyrosine production, and bacterial strains capable of L-tyrosine production.
59 BASIC BIOLOGICAL SCIENCES↗