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Space technology transfer is discussed as applied to the field of materials science. Advances made in processing include improved computer techniques, and structural analysis. Technology transfer is shown to have an important impact potential in the overall productivity of the United States.
Spacelab 1 will carry 17 NASA-sponsored research projects. Seven of these investigations will concern the life sciences. Because of NASA's interest in space motion sickness, two vestibular studies will be conducted. Two other experiments will be concerned with the effects of spaceflight on the hematologic system. The fifth life science study will involve nutations in plant organs. The sixth investigation will examine the effects of the Spacelab environment on circadian rhythms in microorganisms. Finally, cosmic radiation inside the Spacelab will be mapped. These seven life science experiments represent both basic and applied areas of research.
The NASA Pilot Land Data System (PLDS) project is intended to enhance the effectiveness of data processing capabilities used by researchers applying remote sensing data in land science research. Two sites in the centerminous U.S. have been selected as study areas scanned by Landsat, Nimbus and GOES instruments. The data will be analyzed by teams of researchers representing different fields of expertise. The PLDS program will explore data management, networking and communications, system access capabilities, land analysis software, special processes and overall systems engineerng. The data will be processed by researchers working interactively through remote supermicrocomputer workstations using a variety of operating systems and on-site software capabilities.
The use of a tethered movable orbiting laboratory for microgravity research is examined. The relation between reduced microgravity carriers and acceleration levels, and the effects of acceleration levels on in-orbit experiments are studied. The tuning of the gravity level at a space laboratory by employing a tether is described. The applications of the variable gravity environment to research in fluids and materials sciences, life sciences, separative techniques, and physical and applied chemistry are discussed.
The Institute conducts unclassified basic research in applied mathematics, numerical analysis, and computer science in order to extend and improve problem-solving capabilities in science and engineering, particularly in aeronautics and space. The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers. ICASE reports are considered to be primarily preprints of manuscripts that have been submitted to appropriate research journals or that are to appear in conference proceedings.
The NASA-UVA Light Aerospace Alloy and Structures Technology (LA(2)ST) Program continues a high level of activity, with projects being conducted by graduate students and faculty advisors in the Departments of Materials Science and Engineering, Civil Engineering and Applied Mechanics, and Mechanical and Aerospace Engineering at the University of Virginia. This work is funded by the NASA-Langley Research Center under Grant NAG-1-745. We report on progress achieved between July 1 and December 31, 1992. The objective of the LA(2)ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement advances; and critically, a pool of educated graduate students for aerospace technologies.
Advances in computer, navigation and wireless telecommunication technologies are enabling better electronic devices at reduced costs. Individually, these devices have been applied to increase the performance of many common systems, such as desktop computers, surveying equipment, and modems. However, we believe the convergence of these three technologies will create a product that simultaneously lowers life cycle costs while increasing operational effectiveness. Space Systems/Loral (SS/L) is developing portions of this product, known as the Telestation, for both terrestrial and orbital applications. The Telestation consists of an advanced microprocessor for command and data handling; a GPS receiver for position, time, and attitude information; and a Globalstar Transceiver for two-way digital communications. The Telestation provides the user with real-time command and control of globally distributed hardware elements. This capability can be applied terrestrially for gathering information (e.g., science, environmental, etc.) in remote or inhospitable locations, or where logistical support is inadequate. An in-orbit version can be used for spacecraft or payload operations, allowing principal investigators instant access to their payloads during all phases of a mission. This paper describes some cost effectiveness metrics of the Telestation, its development status, and its utility in both terrestrial and orbital applications.
SEDSAT-1 is designed to be a low cost scientific satellite which is to be used to perform a minimum of five tasks which include: (1) the acquisition of a number of important parameters associated with the tethering processes from the payloads perspective (such as accelerations incurred and imaging data of the tether during deployment), (2) to act as a remote sensing platform for making measurements of the Earth's Atmosphere (allowing research to be performed in such areas as vertical lightning observation, visible light spectrography, and cloud cover studies, (3) to act as a general purpose amateur radio communication satellite relaying information back to earth, (4) to demonstrate the feasibility of the deployment in low earth orbit of advanced technology such as the Gallium Arsenide Solar Cells, Nickel Metal Hydride batteries, and multi-chip module technology and, (5) to support student's active participation in applying the disciplines of engineering and science to space-based hardware platforms. The project includes the Three-axis Accelerometer System, TAS, Experiment which is designed to report the accelerations that the satellite undergoes during the tethering operations and during the second phase of the mission when the free floating satellite comes in contact with orbit debris. The SEASIS (SEDS Earth, Atmosphere, and Space Imaging System) is another SEDSAT experiment designed to provide images of the tether during its deployment and the earth during the second phase of the mission. To control these experiments and virtually all other satellite operations the Command Data System, CDS is employed. This system utilizes a moderate complexity micro-controller controlled by tasks operating under a real-time operating system to dynamically monitor and control the satellite. The scope of this researchers efforts has been in the general area of coordinating and assisting the student researchers with the development of the CDS and ground station interfaces. This included the low level CDS hardware design and the formulization of a general software plan and schedule for both the CDS and ground station portions of the project.
With the help of Small Business Innovation Research (SBIR) funding from NASA's Goddard Space Flight Center, of Greenbelt, Maryland, Clearwater Instrumentation, of Watertown, Massachusetts, created the ClearSat-Autonomous Drifting Ocean Station (ADOS). The multi-sensor array ocean drifting station was developed to support observations of Earth by NASA satellites. It is a low-cost device for gathering an assortment of data necessary to the integration of present and future satellite measurements of biological and physical processes. Clearwater Instrumentation developed its ADOS technology based on Goddard's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project, but on a scale that is practical for commercial use. ADOS is used for the in situ measuring of ocean surface layer properties such as ocean color, surface thermal structure, and surface winds. Thus far, multiple ADOS units have been sold to The Scripps Institution of Oceanography, where they are being applied in the field of academic science research. Fisheries can also benefit, because ADOS can locate prime cultivation conditions for this fast-growing industry.
The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.
Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.
Magnetic microsystems in the form of magneto-resistive (MR) sensors are firmly established in automobiles and industrial applications. They are used to measure travel, angle, electrical current, or magnetic fields. MR technology opens up new sensor possibilities in space applications and can be an enabling technology for optimal performance, high robustness and long lifetime at reasonable costs. In some science missions, the technology is already applied, however, the designs are proprietary and case specific, for instance in case of the angular sensors used for JPL/NASA's Mars rover Curiosity [1]. Since 2013 HTS GmbH and Sensitec GmbH have teamed up to develop and qualify a standardized yet flexible to use MR angular sensor for space mechanisms. Starting with a first assessment study and market survey performed under ESA contract, a very strong industry interest in novel, contactless position measurement means was found. Currently a detailed and comprehensive development program is being performed by HTS and Sensitec. The objective of this program is to advance the sensor design up to Engineering Qualification Model level and to perform qualification testing for a representative space application. The paper briefly reviews the basics of magneto-resistive effects and possible sensor applications and describes the key benefits of MR angular sensors with reference to currently operational industrial and space applications. The key applications and specification are presented and the preliminary baseline mechanical and electrical design will be discussed. An outlook on the upcoming development and test stages as well as the qualification program will be provided.
This paper originates from the joint efforts of an aeroelastic study team in the Applied Vehicle Technology Panel from NATO Science and Technology Organization, with the Task Group number AVT-191, titled "Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design." We present aeroelastic uncertainty quantification studies using the SemiSpan Supersonic Transport wind tunnel model at the NASA Langley Research Center. The aeroelastic study team decided treat both structural and aerodynamic input parameters as uncertain and represent them as samples drawn from statistical distributions, propagating them through aeroelastic analysis frameworks. Uncertainty quantification processes require many function evaluations to asses the impact of variations in numerous parameters on the vehicle characteristics, rapidly increasing the computational time requirement relative to that required to assess a system deterministically. The increased computational time is particularly prohibitive if high-fidelity analyses are employed. As a remedy, the Istanbul Technical University team employed an Euler solver in an aeroelastic analysis framework, and implemented reduced order modeling with Polynomial Chaos Expansion and Proper Orthogonal Decomposition to perform the uncertainty propagation. The NASA team chose to reduce the prohibitive computational time by employing linear solution processes. The NASA team also focused on determining input sample distributions.
This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with an assumed vehicle aerodynamic model. The approach utilizes the full navigation state of the vehicle (position, velocity, and attitude) to recast the vehicle aerodynamic model to be a function solely of the atmospheric state (density, pressure, and winds). Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman-Schmidt filter to estimate the atmospheric conditions. The new method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the new estimation algorithm are compared with results from a Flush Air Data Sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the new proposed estimation method provides estimates consistent with the air data measurements, without the use of pressure measurements. Implications for future missions such as the Mars 2020 entry capsule are described.
This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with a vehicle aerodynamic model. The approach uses the navigation state of the vehicle to recast the vehicle aerodynamic model to be a function solely of the atmospheric state. Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman–Schmidt filter to estimate the atmospheric conditions. The method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the estimation algorithm are compared with results from a flush air data sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the proposed method provides estimates consistent with the air data measurements, without the use of pressure transducers. Implications for future missions such as the Mars 2020 entry capsule are described.
We reexamine mass flow in a superfluid gyroscope containing a superfluid Josephson weak link. We introduce a frequency-dependent hydrodynamic inductance to account for an oscillatory flow of the normal fluid component in the sensing loop. With this hydrodynamic inductance, we derive the thermal phase noise, and hence the thermal rotational noise of the gyroscope. We examine the thermodynamic stability of the system based on an analysis of the free energy. We derive a quantum phase noise, which is analogous to the zero-point motion of a simple harmonic oscillator. The configuration of the studied gyroscope is analogous to a conventional superconducting RF SQUID. We show that the gyroscope has very low intrinsic noise (1.9x10(-13) rad s(-1)/root Hz), and it can potentially be applied to study general relativity, Earth science, and to improve global positioning systems (GPS).
Paired measurements of phytoplankton absorption and backscatter, the inherent optical properties central to the interpretation of ocean colour remote sensing data, are notoriously rare. We present a dataset of Chlorophyll a (Chl a) -specific phytoplankton absorption, scatter and backscatter for 17 different phytoplankton groups, derived from first principles using measured in vivo pigment absorption and a well-validated semi-analytical coated sphere model which simulates the full suite of biophysically consistent phytoplankton optical properties. The optical properties of each simulated phytoplankton cell are integrated over an entire size distribution and are provided at high spectral resolution. The model code is additionally included to enable user access to the complete set of wavelength-dependent, angularly resolved volume scattering functions. This optically coherent dataset of hyperspectral optical properties for a set of globally significant phytoplankton groups has potential for use in algorithm development towards the optimal exploitation of the new age of hyperspectral satellite radiometry.
Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.