Results for “Genetic Engineering” — Page 9

NASA NTRS1998

SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

Akbarzadeh-T, M.-R.↗

NASA NTRS2016

Innovation at the Edge of Space- An Engine for Global Opportunities

Microgravity based commercial opportunities are broad, with applications ranging from fiber optics, device-grade semiconductor crystals, space beads, new materials, cells microencapsulation, 3D tissues and cell cultures, genetic and molecular changes of immune suppression, protein and virus crystal growth, perfume and hair care. To date, primarily the knowledge gained from observing and understanding new end states of systems unraveled in microgravity has been translated into unique technologies and business opportunities on Earth. In some instances existing flight qualified hardware is immediately available for commercial RD for small-scale in-space manufacturing. Overall, products manufactured in microgravity have key properties usually surpassing the best terrestrial counterparts. Commercially, these products have an attractive touch of space which aids in marketing.The talk will addresses the potential benefits of microgravity research for a variety of terrestrial markets by (1) surveying the level of awareness and interest of parties from different commercial sectors (2) assessing the potential of microgravity to stimulate innovation in future product development and (3) formulating a synergistic strategy to use microgravity for economic growth and public benefit.Our findings originating primarily from discussions with 100+ non-aerospace private companies among the high-tech Silicon Valley ecosystem, show that the opportunities and benefits of using the ISS are largely not considered by experts, primarily due to a lack of awareness of the breadth of terrestrial applications that have been enabled or enhanced by microgravity RD. Based on this dialogue, the concept of microgravity verticals is developed to translate the benefits of the microgravity environment into blue ocean business opportunities for various key US commercial sectors.

orbital economy↗

NASA NTRS2017

Engineering, Life Sciences, and Health/Medicine Synergy in Aerospace Human Systems Integration: The Rosetta Stone Project

In the realm of aerospace engineering and the physical sciences, we have developed laws of physics based on empirical and research evidence that reliably guide design, research, and development efforts. For instance, an engineer designs a system based on data and experience that can be consistently and repeatedly verified. This reproducibility depends on the consistency and dependability of the materials on which the engineer works and is subject to physics, geometry and convention. In life sciences and medicine, these apply as well, but individuality introduces a host of variables into the mix, resulting in characteristics and outcomes that can be quite broad within a population of individuals. This individuality ranges from differences at the genetic and cellular level to differences in an individuals personality and abilities due to sex and gender, environment, education, etc.

Medicine↗

NASA NTRS1999

Experimental and Numerical Analysis of Structural Acousticcontrol Interior Noise Reduction

The research results contained in this technical report were performed under the NASA grant entitled "Experimental and Numerical Structural Acoustic Control for Interior Noise Reduction". The report is based essentially on partial progress of the Ph.D. dissertation prepared by Jeffrey S. Bevan under direct guidance of Dr. Chuh Mei. The document presents a finite element formulation and control of sound radiated from cylindrical panels embedded with piezoceramic actuators. The extended MIN6 shallow shell element is fully electrical-structural coupled. A piezoelectric modal actuator participation (PMAP) is defined which indicates the actuator performance to each of the offending modes. Genetic algorithm is also employed to validate the sensor and actuator locations determined by the PMAP criteria. The work was conducted at the Department of Aerospace Engineering, Old Dominion University. Mr. Travis L. Turner, Structural Acoustics Branch, NASA Langley Research Center is the technical monitor.

Mei, Chuh↗

NASA NTRS2010

A Powerful Toolkit for Synthetic Biology: Over 3.8 Billion Years of Evolution

The combination of evolutionary with engineering principles will enhance synthetic biology. Conversely, synthetic biology has the potential to enrich evolutionary biology by explaining why some adaptive space is empty, on Earth or elsewhere. Synthetic biology, the design and construction of artificial biological systems, substitutes bio-engineering for evolution, which is seen as an obstacle. But because evolution has produced the complexity and diversity of life, it provides a proven toolkit of genetic materials and principles available to synthetic biology. Evolution operates on the population level, with the populations composed of unique individuals that are historical entities. The source of genetic novelty includes mutation, gene regulation, sex, symbiosis, and interspecies gene transfer. At a phenotypic level, variation derives from regulatory control, replication and diversification of components, compartmentalization, sexual selection and speciation, among others. Variation is limited by physical constraints such as diffusion, and chemical constraints such as reaction rates and membrane fluidity. While some of these tools of evolution are currently in use in synthetic biology, all ought to be examined for utility. A hybrid approach of synthetic biology coupled with fine-tuning through evolution is suggested

Rothschild, Lynn J.↗

NASA NTRS2018

Design of Distributed Mail-Slot Propulsion System on a Hybrid Wingbody Aircraft

This paper deals with designing a thrust distribution strategy when a Turboelectric Distributed Propulsion (TeDP) system of 16 embedded propulsors is installed on an aerodynamically optimized hybrid wing-body configuration. This HWB previously designed to satisfy conditions of trim, longitudinally static stability and specific cargo space is employed as the baseline configuration for the current study of seeking an optimal propulsion/power system. According to the nature of the entrance flow condition for each distributed propulsion passage in hybrid wing-body aircraft, the ingested boundary layer thickness differs and results in different propulsive reaction. An optimal distribution of thrust and power output is determined by how the system utilizes the propulsive characteristics of each passage. The design space and the number of design variables are selected and described accordingly. An actuator disk model is employed to model thrust generation and shaft power from the propulsor. To carry out the optimization of the propulsion/power system on a computationally expensive CFD model, a Kriging method in conjunction with a Genetic Algorithm (GA) is applied. Throughout the design process, the propulsion performances of the sampled propulsion/power system are analyzed and compared to those of a clean flow engine. The performance metrics includes mass flow rate, fan pressure ratio besides the thrust and shaft power. Minimization of total shaft power from the distributed engine is performed at multiple thrust levels. The benefit of boundary layer ingestion propulsion system is quantified via comparison of thrust equivalent, shaft power and mass flow equivalent clean flow engines with CFD based system design.

Hybrid Wingbody↗

NASA NTRSDate not supplied

3D Construction of Biologically Derived Materials

System for the 3D Construction of Biologically Derived Materials, Structures, and Parts NASA has developed a novel approach for macroscale biomaterial production by combining synthetic biology with 3D printing. Cells are biologically engineered to deposit desired materials, such as proteins or metals, derived from locally available resources. The bioengineered cells build different materials in a specified 3D pattern to produce novel microstructures with precise molecular composition, thickness, print pattern, and shape. Scaffolds and reagents can be used for further control over material product. This innovation provides modern design and fabrication techniques for custom-designed organic or organic-inorganic composite biomaterials produced from limited resources. Benefits Conserves resources. Few raw or bulk starting materials needed Enables custom design of diverse materials Fast, portable, macroscale, on-demand manufacturing High-fidelity microstructures Uses commercially available parts Applications Biomaterials, biotechnology Organic-inorganic composite materials On-demand manufacturing In situ resource utilization Space stations Military Infrastructure materials The Technology Once genes for a desired material type, delivery mode, control method and affinity have been chosen, assembling the genetic components and creating the cell lines can be done with well-established synthetic biology techniques. A 3D microdeposition system is used to make a 3D array of these cells in a precise, microstructure pattern and shape. The engineered cells are suspended in a printable 'ink'. The 3D microdeposition system deposits minute droplets of the cells onto a substrates surface in a designed print pattern. Additional printer passes thicken the material. The cell array is fed nutrients and reagents to activate the engineered genes within the cells to create and deposit the desired molecules. These molecules form the designed new material. If desired, the cells may be removed by flushing. The end product is thus a 3D composite microstructure comprising the novel material. This innovation provides a fast, controlled production of natural, synthetic, and novel biomaterials with minimum resource overhead and reduced pre- and post-processing requirements.

3D↗

NASA NTRS2005

Launch Vehicle Propulsion Design with Multiple Selection Criteria

The approach and techniques described herein define an optimization and evaluation approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system. The method uses Monte Carlo simulations, genetic algorithm solvers, a propulsion thermo-chemical code, power series regression curves for historical data, and statistical models in order to optimize a vehicle system. The system, including parameters for engine chamber pressure, area ratio, and oxidizer/fuel ratio, was modeled and optimized to determine the best design for seven separate design weight and cost cases by varying design and technology parameters. Significant model results show that a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Other key findings show the sensitivity of propulsion parameters, technology factors, and cost factors and how these parameters differ when cost and weight are optimized separately. Each of the three key propulsion parameters; chamber pressure, area ratio, and oxidizer/fuel ratio, are optimized in the seven design cases and results are plotted to show impacts to engine mass and overall vehicle mass.

Shelton, Joey D.↗

NASA NTRS2004

Tissue Engineering and Cellular Regeneration at NASA Report to Regenetech SAB

A project overview describing three dimensional tissue models is shown. The topics include: 1) cellular regeneration; 2) haemopoietic replacement; 3) novel vaccine development; 4) pharmacology and toxicology interventions; 5) development of synthetic viruses; and 6) molecular genetics and proteomics of recapitulated models.

Goodwin, Thomas J.↗

NASA NTRS2014

Characterization of Plastic Degrading Bacteria from Environmental Samples by Genetic and Biochemical Analysis

Plastic is the major waste-product during NASA space missions, recycling this waste-stream to produce other beneficial materials would decrease upmass. Bacterial called plastisomes have been demonstrated to metabolize non-biodegradable plastics such as polyethylene and polystyrene. Characterization and engineering of these bacteria, and their eventual incorporation as life support systems would enable space flight beyond lower earth orbit. We will utilize molecular techniques to identify and isolate the most productive plastisome. Environmental samples obtained from locations known to be rich in plastic will be cultured in a laboratory defined-media supplemented with plastic as the sole carbon source. Cultures will be monitored for growth over time. Ribosomal DNA will be amplified from cultures that exhibit growth using PCR. These amplified fragments will be sequenced to determine the identity of the consortia in the cultures. We will then perform bioinformatics analysis on the data to identify the plastisomes and generate phylogenetic trees. Morphological and physiological profile of the plastisomes will also be conducted by microscopy and biochemical tests. Our results would reveal a bacterial strain that can break down plastics efficiently. The implication for this project would not only benefit space exploration but also make a major impact towards sustainability development on Earth.

plastic conversion↗

NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Dhawan, Atam P.↗

NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Dhawan, Atam P.↗

NASA NTRS2012

Nemesis Autonomous Test System

A generalized framework has been developed for systems validation that can be applied to both traditional and autonomous systems. The framework consists of an automated test case generation and execution system called Nemesis that rapidly and thoroughly identifies flaws or vulnerabilities within a system. By applying genetic optimization and goal-seeking algorithms on the test equipment side, a "war game" is conducted between a system and its complementary nemesis. The end result of the war games is a collection of scenarios that reveals any undesirable behaviors of the system under test. The software provides a reusable framework to evolve test scenarios using genetic algorithms using an operation model of the system under test. It can automatically generate and execute test cases that reveal flaws in behaviorally complex systems. Genetic algorithms focus the exploration of tests on the set of test cases that most effectively reveals the flaws and vulnerabilities of the system under test. It leverages advances in state- and model-based engineering, which are essential in defining the behavior of autonomous systems. It also uses goal networks to describe test scenarios.

Barltrop, Kevin J.↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗

NASA NTRS2015

Biomaterials Out of Thin Air: in Situ, On-Demand Printing of Advanced Biocomposites

Upmass is the single most significant limitation of our current space mission capability. Although biomaterials and biocomposites have mass, strength, flexibility, and self-healing properties that could significantly reduce upmass, their use is limited by the following drawbacks: Expensive, specific production. Many biomaterials can only be produced as part of significant support ecosystem; Inaccessible functional customization. The grain of wood, the porosity of bone, and so on are an integral part of the materials' desired mechanical properties, but are not deterministic when the material is naturally grown; Limited compositions. Most biomaterials (unlike metal, plastic, etc.) cannot be easily combined or modified to produce new materials. This project builds on recent advances in: Synthetic biology. Libraries of standardized genetic parts which can be used for controlled cellular material production, delivery, and binding; 3D printing. Commercial off-the-shelf components which can be used to make of a pico- to nanoliter cell deposition system; Tissue engineering. Proven cell-compatible support hydrogels and scaffolds can be modified to bind the deposited biomaterials of interest. Objectives: Feasibility and benefit analysis. Two mission contexts span the concept's scope (see below); Proof-of-concept demonstration. A simple grid of two proteins, fluorescent for easy detection, to validate the core technology concept; Proposed implementations for follow-on work. Avenues for future work on each core component (host cell, production control, material delivery, material binding, etc.); Complementary studies exploration. A survey of other emerging areas (in situ resource utilization, protein engineering, etc.) with the potential to multiply our technology's impact. Potential Impacts: This application could dramatically expand manufacturing capabilities on Earth and in space: In situ resource utilization. A far greater range of materials and products will be available from the limited palette offered by in situ resource extraction techniques; Reduced equipment and material upmass for off-Earth habitats. Ready- to-use highly specialized construction materials (radiation hardened, compressive/tensile, light or dense) from an extremely low starting mass; Structured biomaterial production. New ready-to-use macro, micro, and molecular manufacturing techniques for traditional biomaterials such as wood, bone and shell; New and novel biocomposite creation. The ability to create completely novel material composites from any base material that cells can be engineered to produce. Suggested Mission Contexts: ISS part manufacturing. A 'minimal working example' making a finished biomaterial part aboard the International Space Station; A long-term Mars habitat. 'Cradle-to-grave' use at a hypothetical Mars habitat, covering everything from tools to construction materials. Alternate Abstract: Imagine being able to print anything from tools and composite building materials to food and human tissues. Imagine being on Mars with the ability to replace any broken part, whether it's a part of your spacesuit, your habitat, or your own body. We propose a technique that would allow just that. By printing 3D arrays of cells engineered to secrete the necessary materials, the abundant in situ resources of atmosphere and regolith become organic, inorganic, or organic-inorganic composite materials. Such materials include novel, biologically derived materials not previously possible to fabricate.

habitats↗

NASA NTRS2015

Biomaterials Out of Thin Air: in Situ, On-demand Printing of Advanced Biocomposites

Upmass is the single most significant limitation of our current space mission capability. Although biomaterials and biocomposites have mass, strength, flexibility, and self-healing properties that could significantly reduce upmass, their use is limited by the following drawbacks: Expensive, specific production. Many biomaterials can only be produced as part of significant support ecosystem; Inaccessible functional customization. The grain of wood, the porosity of bone, and so on are an integral part of the materials' desired mechanical properties, but are not deterministic when the material is naturally grown; Limited compositions. Most biomaterials (unlike metal, plastic, etc.) cannot be easily combined or modified to produce new materials. This project builds on recent advances in: Synthetic biology. Libraries of standardized genetic parts which can be used for controlled cellular material production, delivery, and binding; 3D printing. Commercial off-the-shelf components which can be used to make of a pico- to nanoliter cell deposition system; Tissue engineering. Proven cell-compatible support hydrogels and scaffolds can be modified to bind the deposited biomaterials of interest. Objectives: Feasibility and benefit analysis. Two mission contexts span the concept's scope (see below); Proof-of-concept demonstration. A simple grid of two proteins, fluorescent for easy detection, to validate the core technology concept; Proposed implementations for follow-on work. Avenues for future work on each core component (host cell, production control, material delivery, material binding, etc.); Complementary studies exploration. A survey of other emerging areas (in situ resource utilization, protein engineering, etc.) with the potential to multiply our technology's impact. Potential Impacts: This application could dramatically expand manufacturing capabilities on Earth and in space: In situ resource utilization. A far greater range of materials and products will be available from the limited palette offered by in situ resource extraction techniques; Reduced equipment and material upmass for off-Earth habitats. Ready- to-use highly specialized construction materials (radiation hardened, compressive/tensile, light or dense) from an extremely low starting mass; Structured biomaterial production. New ready-to-use macro, micro, and molecular manufacturing techniques for traditional biomaterials such as wood, bone and shell; New and novel biocomposite creation. The ability to create completely novel material composites from any base material that cells can be engineered to produce. Suggested Mission Contexts: ISS part manufacturing. A 'minimal working example' making a finished biomaterial part aboard the International Space Station; A long-term Mars habitat. 'Cradle-to-grave' use at a hypothetical Mars habitat, covering everything from tools to construction materials. Alternate Abstract: Imagine being able to print anything from tools and composite building materials to food and human tissues. Imagine being on Mars with the ability to replace any broken part, whether it's a part of your spacesuit, your habitat, or your own body. We propose a technique that would allow just that. By printing 3D arrays of cells engineered to secrete the necessary materials, the abundant in situ resources of atmosphere and regolith become organic, inorganic, or organic-inorganic composite materials. Such materials include novel, biologically derived materials not previously possible to fabricate.

habitats↗

NASA NTRS2023

Uncovering Unique Molecular Adaptations in the Arabidopsis Thaliana Cvi-0 Ecotype

This research proposal aims to investigate the unique molecular adaptations exhibited by Arabidopsis Thaliana, specifically focusing on the Cape Verde Islands (Cvi-0) ecotype, in response to microgravity conditions. The study examines data from NASA’s Open Science Data Repository and applies a multifaceted RNAseq analysis pipeline using tools in the UseGalaxy.org open platform. Through transcriptomic analysis, differential gene expression patterns were identified in Cvi-0, revealing an absence of heat shock protein (HSP) upregulation and an upregulation of Rubisco Activase (RCA) and chloroplast-related pathways. To test the hypothesis that these adaptations may contribute to Cvi-0’s increased adaptability in microgravity, a three-fold experimental design is proposed. Four experimental groups will be cultivated under simulated microgravity and ground control conditions, including Cvi-0, Col-0, and genetically modified Col-0 with silenced HSP genes, and genetically modified Col-0 with upregulated RCA gene. Growth parameters will be measured to assess plant resilience, and RNA sequencing will provide transcriptomic data for pathway analysis. Anticipated outcomes include improved markers of plant health (mass, growth, etc.) of Cvi-0 in simulated microgravity and enhanced resilience in genetically altered Col-0 variants, providing insights into potential mechanisms of adaptation. This research would bear significance for space agriculture, nutrition for extended space missions, and sustainable terrestrial crop enhancement. Moreover, the insights gained could reshape crop engineering on Earth, enhancing robustness to climate induced stresses and bolstering global food security. The proposal’s trajectory blends scientific curiosity with practical applicability, forging a path towards sustainable food production and improving human exploration beyond our planet.

GL4HS↗