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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessing three closed-loop learning algorithms by searching for high-quality quantum control pulses

Designing a high-quality control is crucial for reliable quantum computation. Among the existing approaches, closed-loop leaning control is an effective choice. Its efficiency depends on the learning algorithm employed, thus deserving algorithmic comparisons for its practical applications. Here we assess three representative learning algorithms, including GRadient Ascent Pulse Engineering (GRAPE), improved Nelder-Mead (NMplus), and Differential Evolution (DE), by searching for high-quality control pulses to prepare the Bell state. We first implement each algorithm experimentally in a nuclear magnetic resonance system and then conduct a numerical study considering the impact of some possible significant experimental uncertainties. The experiments report the successful preparation of the high-fidelity target state by the three algorithms, while NMplus converges fastest, and these results coincide with the numerical simulations when potential uncertainties are negligible. However, under certain significant uncertainties, these algorithms possess distinct performance with respect to their resulting precision and efficiency, and DE shows the best robustness. Finally, this study provides insight to aid in the practical application of different closed-loop learning algorithms in realistic physical scenarios.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
NASA NTRS2010

Exploiting Expertise and Knowledge Sharing Online for the Benefit of NASA's GN&C Community of Practice

In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited engineers from sharing their experiences, expertise, ideas, and lessons learned. The necessity to collaborate on complex development projects and the reality of constrained project resources together drove the need for ensuring that personnel at all NASA centers had comparable skill sets and that engineers could find resources in a timely fashion. Mission failures and new directions for the Agency also demanded better collaborative tools for NASA's engineering workforce. In response to these needs, the online NASA Engineering Network (NEN) was formed by the NASA Office of the Chief Engineer to provide a multi-faceted system for overcoming geographic and cultural barriers. NEN integrates communities of practice with a cross-repository search and the Lessons Learned Information System. This paper describes the features of the GN&C engineering discipline CoP site which went live on NEN in May of 2008 as an online means of gathering input and guidance from practitioners. It allows GN&C discipline expertise captured at one field center to be shared in a collaborative way with the larger discipline CoP spread across the entire Agency. The site enables GN&C engineers to find the information they need quickly, to find solutions to questions from experienced engineers, and to connect with other practitioners regardless of geographic location, thus increasing the probability of project success.

control↗
NASA NTRS2012

Moon Search Algorithms for NASA's Dawn Mission to Asteroid Vesta

A moon or natural satellite is a celestial body that orbits a planetary body such as a planet, dwarf planet, or an asteroid. Scientists seek understanding the origin and evolution of our solar system by studying moons of these bodies. Additionally, searches for satellites of planetary bodies can be important to protect the safety of a spacecraft as it approaches or orbits a planetary body. If a satellite of a celestial body is found, the mass of that body can also be calculated once its orbit is determined. Ensuring the Dawn spacecraft's safety on its mission to the asteroid Vesta primarily motivated the work of Dawn's Satellite Working Group (SWG) in summer of 2011. Dawn mission scientists and engineers utilized various computational tools and techniques for Vesta's satellite search. The objectives of this paper are to 1) introduce the natural satellite search problem, 2) present the computational challenges, approaches, and tools used when addressing this problem, and 3) describe applications of various image processing and computational algorithms for performing satellite searches to the electronic imaging and computer science community. Furthermore, we hope that this communication would enable Dawn mission scientists to improve their satellite search algorithms and tools and be better prepared for performing the same investigation in 2015, when the spacecraft is scheduled to approach and orbit the dwarf planet Ceres.

planetary sciences↗
NASA NTRS2009

Liquid Engine Design: Effect of Chamber Dimensions on Specific Impulse

Which assumption of combustion chemistry - frozen or equilibrium - should be used in the prediction of liquid rocket engine performance calculations? Can a correlation be developed for this? A literature search using the LaSSe tool, an online repository of old rocket data and reports, was completed. Test results of NTO/Aerozine-50 and Lox/LH2 subscale and full-scale injector and combustion chamber test results were found and studied for this task. NASA code, Chemical Equilibrium with Applications (CEA) was used to predict engine performance using both chemistry assumptions, defined here. Frozen- composition remains frozen during expansion through the nozzle. Equilibrium- instantaneous chemical equilibrium during nozzle expansion. Chamber parameters were varied to understand what dimensions drive chamber C* and Isp. Contraction Ratio is the ratio of the nozzle throat area to the area of the chamber. L is the length of the chamber. Characteristic chamber length, L*, is the length that the chamber would be if it were a straight tube and had no converging nozzle. Goal: Develop a qualitative and quantitative correlation for performance parameters - Specific Impulse (Isp) and Characteristic Velocity (C*) - as a function of one or more chamber dimensions - Contraction Ratio (CR), Chamber Length (L ) and/or Characteristic Chamber Length (L*). Determine if chamber dimensions can be correlated to frozen or equilibrium chemistry.

Hoggard, Lindsay↗
NASA NTRS1972

Study of inducer load and stress, volume 2

A program of analysis, design, fabrication and testing has been conducted to develop computer programs for predicting rocket engine turbopump inducer hydrodynamic loading, stress magnitude and distribution, and vibration characteristics. Methods of predicting blade loading, stress, and vibration characteristics were selected from a literature search and used as a basis for the computer programs. An inducer, representative of typical rocket engine inducers, was designed, fabricated, and tested with special instrumentation selected to provide measurements of blade surface pressures and stresses. Data from the tests were compared with predicted values and the computer programs were revised as required to improve correlation. For Volume 1 see N71-20403. For Volume 2 see N71-20404.

Source record↗
NASA NTRS1994

The chemical reactivity of the Martian soil and implications for future missions

Possible interpretations of the results of the Viking Biology Experiments suggest that greater than 1 ppm of a thermally labile oxidant, perhaps H2O2, and about 10 ppm of a thermally stable oxidant are present in the martian soil. We reexamine these results and discuss implications for future missions, the search for organics on Mars, and the possible health and engineering effects for human exploration. We conclude that further characterization of the reactivity of the martian regolith materials is warrented-although if our present understanding is correct the oxidant does not pose a hazard to humans. There are difficulties in explaining the reactivity of the Martian soil by oxidants. Most bulk phase compounds that are capable of oxidizing H2O to O2 per the Gas Exchange Experiment (GEx) are thermally labile or unstable against reduction by atmospheric CO2. Models invoking trapped O2 or peroxynitrates (NOO2(-)) require an unlikely geologic history for the Viking Lander 2 site. Most suggested oxidants, including H2O2, are expected to decompose rapidly under martian UV. Nonetheless, we conclude that the best model for the martian soil contains oxidants produced by heterogeneous chemical reactions with a photochemically produced atmospheric oxidant. The GEx results may be due to catalytic decomposition of an unstable oxidizing material by H2O. We show that interfacial reaction sites covering less than 1% of the available soil surfaces could explain the Viking Biology Experiments results.

Zent, Aaron P.↗
NASA NTRS2000

A Matrix Approach to Software Process Definition

The Software Engineering Laboratory (SEL) is currently engaged in a Methodology and Metrics program for the Information Systems Center (ISC) at Goddard Space Flight Center (GSFC). This paper addresses the Methodology portion of the program. The purpose of the Methodology effort is to assist a software team lead in selecting and tailoring a software development or maintenance process for a specific GSFC project. It is intended that this process will also be compliant with both ISO 9001 and the Software Engineering Institute's Capability Maturity Model (CMM). Under the Methodology program, we have defined four standard ISO-compliant software processes for the ISC, and three tailoring criteria that team leads can use to categorize their projects. The team lead would select a process and appropriate tailoring factors, from which a software process tailored to the specific project could be generated. Our objective in the Methodology program is to present software process information in a structured fashion, to make it easy for a team lead to characterize the type of software engineering to be performed, and to apply tailoring parameters to search for an appropriate software process description. This will enable the team lead to follow a proven, effective software process and also satisfy NASA's requirement for compliance with ISO 9001 and the anticipated requirement for CMM assessment. This work is also intended to support the deployment of sound software processes across the ISC.

Schultz, David↗
NASA NTRS2005

NASA Tech Briefs, March 2005

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.

Source record↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16833-DND

Semantic Infrastructure is central to realizing the first goal of the ASDC's Strategic Plan: expanding the ASDC's customer base by improving access to ASDC data. ASDC data comprises a widely heterogeneous set of complex products which presents two significant challenges in data access: Helping customers discover, among many available options, the most suitable data products for their purpose; and Guiding customers to easily and appropriately use products. Data products differ significantly in terms of how the data was collected and processed, even with similar subject matter. Understanding differences is critical to using data effectively. To reach a broader customer range, the ASDC must provide prospective users with enough information to quickly and meaningfully compare and evaluate data products. Data formats and structures also differ among products. Applications displaying and analyzing data need access to federated and semantically disambiguated data. Semantic technologies offer functionality for addressing this issue. Ontologies can provide robust, stable domain models serving as common schema for discovering, evaluating, comparing, and integrating data from disparate products. Reasoning engines and triple stores can leverage ontologies to support intelligent search applications allowing users to discover, query, retrieve, and easily reformat data from a broad spectrum of sources.

Beth Huffer↗
NASA NTRS1988

Expert system validation in prolog

An overview of the Expert System Validation Assistant (EVA) is being implemented in Prolog at the Lockheed AI Center. Prolog was chosen to facilitate rapid prototyping of the structure and logic checkers and since February 1987, we have implemented code to check for irrelevance, subsumption, duplication, deadends, unreachability, and cycles. The architecture chosen is extremely flexible and expansible, yet concise and complementary with the normal interactive style of Prolog. The foundation of the system is in the connection graph representation. Rules and facts are modeled as nodes in the graph and arcs indicate common patterns between rules. The basic activity of the validation system is then a traversal of the connection graph, searching for various patterns the system recognizes as erroneous. To aid in specifying these patterns, a metalanguage is developed, providing the user with the basic facilities required to reason about the expert system. Using the metalanguage, the user can, for example, give the Prolog inference engine the goal of finding inconsistent conclusions among the rules, and Prolog will search the graph intantiations which can match the definition of inconsistency. Examples of code for some of the checkers are provided and the algorithms explained. Technical highlights include automatic construction of a connection graph, demonstration of the use of metalanguage, the A* algorithm modified to detect all unique cycles, general-purpose stacks in Prolog, and a general-purpose database browser with pattern completion.

Stock, Todd↗
NASA NTRS1999

Improvement of Space Shuttle Main Engine Low Frequency Acceleration Measurements

The noise floor of low frequency acceleration data acquired on the Space Shuttle Main Engines is higher than desirable. Difficulties of acquiring high quality acceleration data on this engine are discussed. The approach presented in this paper for reducing the acceleration noise floor focuses on a search for an accelerometer more capable of measuring low frequency accelerations. An overview is given of the current measurement system used to acquire engine vibratory data. The severity of vibration, temperature, and moisture environments are considered. Vibratory measurements from both laboratory and rocket engine tests are presented.

Stec, Robert C.↗
DOE OSTI2022

Understanding Proton Movement in [Fe-Fe] Hydrogenases

Nature uses specialized metalloenzymes to carry out small molecule activation reactions, including CO 2 fixation, O 2 activation, and proton reduction, with unparalleled efficiency, rates, and selectivity. The latter reactions are performed by hydrogenases, protein metallo-complexes that interconverts H 2 to protons and electrons (H 2 oxidation) and the reverse reaction (H 2 production) with incredibly low energy input and amazingly fast kinetics. Reproducing both the activity and efficiency of metalloenzymes in sustainable anthropogenic systems remains one of the “holy grails” of inorganic chemistry. However, identifying the precise molecular components responsible for these desirable properties has been challenging in the natural metalloenzymes, hindering efforts to develop analogous processes in synthetic compounds. Considering the inherent complexity of a metalloenzyme and the many interactions, both strong and weak, that contribute to the function of an enzyme, we have elected to model natural metalloenzymes on a biochemical platform. Towards this end, we have a developed structural, functional, and mechanistic mimic of the [Ni-Fe] hydrogenases within a robust protein scaffold, rubredoxin, to understand the influence of the secondary coordination environment on the metal center. This involved preparing a series of three rubredoxin constructs containing a single point mutation at Val positions and making the NMR chemical shift assignments for the paramagnetic (nickel-substituted) and non-paramagnetic (zinc-substituted) form. These physical studies were complemented with in silico molecular dynamic studies on proteins with [Fe-S] clusters to engineer new proton channels to test in vitro . To assist our search for new natural metalloprotein scaffolds within the vast number of sequenced genomes, we created a neural network-based program to identify proteins with specific metal-binding sites. These computational and physical studies with metalloenzymes provide direct insight into the fundamental chemical principles driving the natural systems and offer design principles for developing catalysts that utilize analogous principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Information technology aided exploration of system design spaces

We report on a practical application of information technology techniques to aid system engineers effectively explore large design spaces. We make use of heuristic search, visualization and data mining, the combination of which we have implemented wtihin a risk management tool in use at JPL and NASA.

requirements prioritization↗
NASA NTRS1990

Search for near-Earth asteroids with the spacewatch camera

The Spacewatch Program began as an engineering development of the discovery of near-earth asteroids and comets, with the firs observations starting in 1983, using an RCA charge coupled device (CCD) that has 320 x 512 pixels. Extensive software was written to scan the sky and learn how to do astrometry for precise orbits of newly discovered objects. The merit of the concept was proven, with many observations reported and comets recovered. The precision of astrometric observations for comets and asteroids was improved. For efficient scanning and discovery of new objects, a Tektronix 2048 x 2048 CCD was obtained and is now permanently on the Spacewatch Telescope. Other aspects of the Spacewatch Program are briefly discussed.

Gehrels, T.↗
NASA NTRS1989

Searching the PASCAL database - A user's perspective

The operation of PASCAL, a bibliographic data base covering broad subject areas in science and technology, is discussed. The data base includes information from about 1973 to the present, including topics in engineering, chemistry, physics, earth science, environmental science, biology, psychology, and medicine. Data from 1986 to the present may be searched using DIALOG. The procedures and classification codes for searching PASCAL are presented. Examples of citations retrieved from the data base are given and suggestions are made concerning when to use PASCAL.

Jack, Robert F.↗