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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Bright field illumination system

A Bright Field Illumination system for inspecting a range of characteristically different kinds of defects, depressions, and ridges in a selected material surface. The system has an illumination source placed near a first focus of an elliptical reflector. In addition, a camera facing the inspected area is placed near the illumination source and the first focus. The second focus of the elliptical reflector is located at a distance approximately twice the elliptical reflector's distance above the inspected surface. The elliptical reflector directs the light from the source onto the inspected surface. Due to the shape of the elliptical reflector, light that is specularly reflected from the inspected surface is directed into the camera is which located at the position of the reflected second focus of the ellipse. This system creates a brightly lighted background field against which damage sites appear as high contrast dark objects which can be easily detected by a person or an automated inspection system. In addition, the Bright Field Illumination system and method can be used in combination with a vision inspection system providing for multiplexed illumination and data handling of multiple kinds of surface characteristics including abrupt and gradual surface variations and differences between measured characteristics of different kinds and prior instruments.

Huber, Edward D.↗
NASA NTRS2023

The Design of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV)

This discussion will involve the design and architecture of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV). It will describe the structure and modular design of the RV, expounding on its various subsystems, including power and commanding, data handling and recovery, instrumentation, the inflation system, and the aeroshell. The unique launch vehicle architecture for the LOFTID mission, as a massive rideshare payload, required the development of supporting flight systems, including the Payload Adapter Separation System (PASS) and the Reentry Vehicle Payload Adapter Interface Ring (RVPAIR). To do no harm to the primary mission, the LOFTID team also designed and delivered a flightworthy Mass Simulator as risk reduction in the event the RV was not ready in time for the primary mission launch date. Various challenges and design trades will be discussed, along with a brief description of the RV performance in flight.

R J Bodkin↗
NASA NTRSDate not supplied

The Design of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV)

This discussion will involve the design and architecture of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV). It will describe the structure and modular design of the RV, expounding on its various subsystems, including power and commanding, data handling and recovery, instrumentation, the inflation system, and the aeroshell. The unique launch vehicle architecture for the LOFTID mission, as a massive rideshare payload, required the development of supporting flight systems, including the Payload Adapter Separation System (PASS) and the Reentry Vehicle Payload Adapter Interface Ring (RVPAIR). To do no harm to the primary mission, the LOFTID team also designed and delivered a flightworthy Mass Simulator as risk reduction in the event the RV was not ready in time for the primary mission launch date. Various challenges and design trades will be discussed, along with a brief description of the RV performance in flight.

R J Bodkin↗
NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗
NASA NTRS1981

OAO-3 end of mission tests report

Twelve engineering type tests were performed on several subsystems and experiment(s) of the OAO 3 spacecraft near its end of mission. The systems tested include: Princeton experiment package (PEP), fine error system guidance, inertial reference unit, star trackers, heat pipes, thermal control coatings, command and data handling, solar array; batteries, and onboard processor/power boost regulator. Generally, the systems performed well for the 8 1/2 years life of OAO 3, although some degradation was noted in the sensitivity of PEP and in the absorptivity of the skin coatings. Battery life was prolonged during the life of the mission in large part by carefully monitoring the charge-discharge cycle with careful attention not to overcharge.

Kalil, F.↗
NASA NTRS1991

Integrated Analysis Capability Program

Integrated Analysis Capability (IAC) software system intended to provide highly effective, interactive analysis tool for integrated design of large structures. Supports needs of engineering analysis groups concerned with interdisciplinary problems. Developed to serve as software interface between computer programs from fields of structures, thermodynamics, controls, and dynamics of systems on one hand and executive software system and data base on other hand to yield highly efficient multi-disciplinary system. Special attention given to such users' requirements as handling data and online assistance with operational features and ability to add new modules of user's choice at future date. Written in FORTRAN 77.

Vos, R. G.↗
NASA NTRS1994

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complete database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful, and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications, and has produced real, published results.

Djorgovski, S. George↗
NASA NTRS1994

Multivariate Statistical Analysis Software Technologies for Astrophysical Research Involving Large Data Bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complex database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects of the SKICAT system, and of some of the scientific results achieved to date. We also developed a user-friendly package for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications and has produced real, published results.

Djorgovski, S. G.↗
DOE OSTI2025

Modular Autonomous Experimentation for Biological Applications

The Modular Autonomous Research System (MARS) was created to address a key challenge in scientific discovery: experiments are often slow, require significant manual labor, and generate data that is not easily integrated across different tools. This limits how quickly scientists can explore new materials, processes, and chemical reactions. Our motivation was to design a system that makes research faster, more reliable, and adaptable by combining automation with artificial intelligence. By doing so, we aimed to reduce human error, accelerate discovery, and allow researchers to quickly test many possibilities that would otherwise take months or years. Our approach was to build a flexible platform that connects laboratory robots, measurement instruments, and a central data system, all guided by artificial intelligence. MARS integrates liquid handling robots, robotic arms, and plate readers with an intelligent decision-making system that chooses the most informative experiments to run next. This creates a closed loop where experiments are performed automatically, the data is analyzed in real time, and new conditions are immediately tested. Through this work, we demonstrated that MARS can carry out multiple experiments with little or no human intervention, adapt to different scientific problems, and handle uncertain or noisy measurements in a robust way. The results show that modular and intelligent automation can significantly accelerate the pace of discovery, providing a model for future self-driving laboratories. This approach addresses the growing scientific need for adaptable, data-driven research platforms that can keep up with the complexity and scale of modern science.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

TEQUEL: The query language of SADDLE

A relational database management system is presented that is tailored for engineering applications. A wide variety of engineering data types are supported and the data definition language (DDL) and data manipulation language (DML) are extended to handle matrices. The system can be used either in the standalone mode or through a FORTRAN or PASCAL application program. The query language is of the relational calculus type and allows the user to store, retrieve, update and delete tuples from relations. The relational operations including union, intersect and differ facilitate creation of temporary relations that can be used for manipulating information in a powerful manner. Sample applications are shown to illustrate the creation of data through a FORTRAN program and data manipulation using the TEQUEL DML.

Rajan, S. D.↗
NASA NTRS1975

Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River basin

The author has identified the following significant results. The full potential of high quality data is achieved only with the application of efficient and effective interpretation techniques. An excellent operating system for handling, processing, and interpreting ERTS-1 and other MSS data was achieved. Programs for processing digital data are implemented on a large nondedicated general purpose computer. Significant results were attained in mapping land use, agricultural croplands, forest resources, and vegetative cover. Categories of land use classified and mapped depend upon the geographic location, the detail required, and the types of lands use of interest. Physiographic and structural provinces are spectacularly displayed on ERTS-1 MSS image mosaics. Geologic bedrock structures show up well and formation contacts can sometimes be traced for hundreds of kilometers. Large circular structures and regional features, previously obscured by the detail of higher resolution data, can be seen. Environmental monitoring was performed in three areas: coal strip mining, coal refuse problems, and damage to vegetation caused by insects and pollution.

Mcmurtry, G. J.↗
NASA NTRS2006

Balloon Support Systems Performance for the Cosmic Rays Energetics and Mass Mission

The Ballooncraft Support Systems were developed by NASA Wallops Flight Facility for use on ULDB class balloon missions. The support systems have now flown two missions supporting the Cosmic Rays Energetics and Mass (CREAM) experiment. The first, CREAM I, flown in December 2004, was for a record breaking 41 days, 21 hours, and the second, flown in December 2005, was for 28 days, 9 hours. These support systems provide CREAM with power, telecommunications, command and data handling ioc!uding Plight computers, mechanical structures, thermal management and attitude control to help ensure a successful scientific mission. This paper will address the performance and success of these support systems over the two missions.

Tompson, Linda D.↗
NASA NTRS1972

Modularized instrument system for turbojet engine test facilities

A modular instrument system is being developed to handle the many data channels encountered in turbojet engine testing. Each module contains a group of transducers and all the signal conditioning multiplexing, and digitizing electronics necessary for direct interface with a digital computer. The digital interface within each module is the same for all modules; in addition, each module provides a controlled environment for its contents. A minicomputer in the control room gathers the data, performs on-line calculation and display, and interfaces with a shared recording and computing system. The advantages of this system are: (1) reduced manpower for system installation, setup, and checkout; (2) standardized equipment interfaces; (3) increased reliability through automatic system testing and minimization of manual adjustments; and (4) reduced cost through minimization of wiring and simplification of control room display.

Nieberding, W. C.↗
NASA NTRS2001

Advanced Communication Architectures and Technologies for Missions to the Outer Planets

Missions to the outer planets would be considerably enhanced by the implementation of a future space communication infrastructure that utilizes relay stations placed at strategic locations in the solar system. These relay stations would operate autonomously and handle remote mission command and data traffic on a prioritized demand access basis. Such a system would enhance communications from that of the current direct communications between the planet and Earth. The system would also provide high rate data communications to outer planet missions, clear communications paths during times when the sun occults the mission spacecraft as viewed from Earth, and navigational "lighthouses" for missions utilizing onboard autonomous operations. Additional information is contained in the original extended abstract.

Bhasin, K.↗
DOE OSTI2025

Evaluate data lake design for the accelerator control system

Increasing precision in automation for modern particle accelerators not only creates a requirement to gather data from all devices but also demands scalable and high-performance data infrastructure with the capability of handling vast incoming device data. A well architected data lake is suitable for such a system which integrates real-time data acquisition, transient data caching, and long-term storage. This paper evaluates data lake architecture for an Accelerator Control System (ACS), focusing on two critical components of a data lake, data cache and long-term storage.

Jaikar, Amol [Fermilab]↗
NASA NTRS1981

NASA tracking and data acquisition in the 1990s - High earth orbit and planetary spacecraft support

It is pointed out that during the decade of the 1980's the Deep Space Network (DSN) and the ground stations of the Ground Spaceflight Tracking Data Network (GSTDN) will have been consolidated into one ground-based network to provide services for tracking and data acquisition for NASA deep space probes and highly elliptical earth orbiters. The Tracking and Data Relay Satellite System (TDRSS) will have been implemented to handle low earth orbiters. Anticipated solar system exploration missions of the 1990's are discussed, and a description is presented of the new tracking and data acquisition requirements for supporting these missions. The technology options needed to meet these new requirements are identified, and the impact of these technology options on the consolidated DSN is discussed. Attention is given to the evolution of the DSN of the 1980's into the DSN of the year 2000.

Smith, J. G.↗