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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Computer-Aided Systems Engineering for Flight Research Projects Using a Workgroup Database

An online systems engineering tool for flight research projects has been developed through the use of a workgroup database. Capabilities are implemented for typical flight research systems engineering needs in document library, configuration control, hazard analysis, hardware database, requirements management, action item tracking, project team information, and technical performance metrics. Repetitive tasks are automated to reduce workload and errors. Current data and documents are instantly available online and can be worked on collaboratively. Existing forms and conventional processes are used, rather than inventing or changing processes to fit the tool. An integrated tool set offers advantages by automatically cross-referencing data, minimizing redundant data entry, and reducing the number of programs that must be learned. With a simplified approach, significant improvements are attained over existing capabilities for minimal cost. By using a workgroup-level database platform, personnel most directly involved in the project can develop, modify, and maintain the system, thereby saving time and money. As a pilot project, the system has been used to support an in-house flight experiment. Options are proposed for developing and deploying this type of tool on a more extensive basis.

Mizukami, Masahi↗
NASA NTRS2008

From Informal Safety-Critical Requirements to Property-Driven Formal Validation

Most of the efforts in formal methods have historically been devoted to comparing a design against a set of requirements. The validation of the requirements themselves, however, has often been disregarded, and it can be considered a largely open problem, which poses several challenges. The first challenge is given by the fact that requirements are often written in natural language, and may thus contain a high degree of ambiguity. Despite the progresses in Natural Language Processing techniques, the task of understanding a set of requirements cannot be automatized, and must be carried out by domain experts, who are typically not familiar with formal languages. Furthermore, in order to retain a direct connection with the informal requirements, the formalization cannot follow standard model-based approaches. The second challenge lies in the formal validation of requirements. On one hand, it is not even clear which are the correctness criteria or the high-level properties that the requirements must fulfill. On the other hand, the expressivity of the language used in the formalization may go beyond the theoretical and/or practical capacity of state-of-the-art formal verification. In order to solve these issues, we propose a new methodology that comprises of a chain of steps, each supported by a specific tool. The main steps are the following. First, the informal requirements are split into basic fragments, which are classified into categories, and dependency and generalization relationships among them are identified. Second, the fragments are modeled using a visual language such as UML. The UML diagrams are both syntactically restricted (in order to guarantee a formal semantics), and enriched with a highly controlled natural language (to allow for modeling static and temporal constraints). Third, an automatic formal analysis phase iterates over the modeled requirements, by combining several, complementary techniques: checking consistency; verifying whether the requirements entail some desirable properties; verify whether the requirements are consistent with selected scenarios; diagnosing inconsistencies by identifying inconsistent cores; identifying vacuous requirements; constructing multiple explanations by enabling the fault-tree analysis related to particular fault models; verifying whether the specification is realizable.

Cimatti, Alessandro↗
NASA NTRS2021

A Study of Lessons and Experiences of NASA Centers in the Use of Commercial Off the Shelf (COTS) Electronics

The NASA Engineering and Safety Center (NESC) sponsored a Technical Assessment relating to the utilization of commercial-off-the-shelf (COTS) electrical, electronic, and electromechanical (EEE) parts in spaceflight systems at NASA Centers. The assessment had two primary goals. The first was to capture each NASA Centers’ current practices, best practices, lessons learned and Center-proposed recommendations on the use of COTS EEE parts and assemblies in critical ground support equipment (GSE). The second was to provide recommendations on the use of COTS, including a set of current best practices based on the Centers’ current and best practices and the NESC team’s discussions. One key achievement made by the assessment team was the characterization of the term Industry Leading Parts Manufacturers (ILPMs) as parts manufacturer with high volume automatic production facilities and which can provide documented proof of the technology, process and product qualification, and its implementation of the best practices for “zero defects” for parts quality, reliability and workmanship. The assessment concluded with numerous findings, takeaways and recommendations that will be discussed during this presentation.

commercial↗
NASA NTRSDate not supplied

Impact Ice Microstructure Segmentation Using Transfer Learned Model

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods. Results show promise in accuracy as well as a possible improvement in repeatability and consistency. Next steps for improving the model are suggested.

Machine learning↗
NASA NTRS1998

Development and Testing of Automatically Generated ACS Flight Software for the MAP Spacecraft

By integrating the attitude determination and control system (ACS) analysis and design, flight software development, and flight software testing processes, it is possible to improve the overall spacecraft development cycle, as well as allow for more thorough software testing. One of the ways to achieve this integration is to use code-generation tools to automatically generate components of the ACS flight software directly from a high-fidelity (HiFi) simulation. In the development of the Microwave Anisotropy Probe (MAP) spacecraft, currently underway at the NASA Goddard Space Flight Center, approximately 1/3 of the ACS flight software was automatically generated. In this paper, we will examine each phase of the ACS subsystem and flight software design life cycle: analysis, design, and testing. In the analysis phase, we scoped how much software we would automatically generate and created the initial interface. The design phase included parallel development of the HiFi simulation and the hand-coded flight software components. Everything came together in the test phase, in which the flight software was tested, using results from the HiFi simulation as one of the bases of comparison for testing. Because parts of the spacecraft HiFi simulation were converted into flight software, more care needed to be put into its development and configuration control to support both the HiFi simulation and flight software. The components of the HiFi simulation from which code was generated needed to be designed based on the fact that they would become flight software. This process involved such considerations as protecting against mathematical exceptions, using acceptable module and parameter naming conventions, and using an input/output interface compatible with the rest of the flight software. Maintaining good configuration control was an issue for the HiFi simulation and the flight software, and a way to track the two systems was devised. Finally, an integrated test approach was devised to support flight software testing at both the unit- and build-test levels using the HiFi simulation to generate data for performance verification. Another benefit of the simulation and code-generation application used on the MAP project is that it supported bringing flight software and test data into the HiFi simulation environment. It was possible to integrate parts of the hand-coded flight software into the HiFi simulation, and also possible to import flight software test data for comparison and performance verification. This capability was used to incorporate the flight software Kalman filter into the HiFi simulation. This enabled us to greatly increase the amount of testing that could be done on the filter, because we could exert a greater degree of control over the software-only simulation than over the flight software test environment. Also, since the simulation could be used to run the Kalman filter faster than real time, our testing efficiency was greatly increased. We will conclude our discussion with a summary of the lessons learned thus far using automatically- generated code for the MAP project, and the spacecraft status as we work towards our scheduled launch in the year 2000.

ODonnell, James R., Jr.↗
NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗
NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗
NASA NTRS1987

On the next generation of reliability analysis tools

The current generation of reliability analysis tools concentrates on improving the efficiency of the description and solution of the fault-handling processes and providing a solution algorithm for the full system model. The tools have improved user efficiency in these areas to the extent that the problem of constructing the fault-occurrence model is now the major analysis bottleneck. For the next generation of reliability tools, it is proposed that techniques be developed to improve the efficiency of the fault-occurrence model generation and input. Further, the goal is to provide an environment permitting a user to provide a top-down design description of the system from which a Markov reliability model is automatically constructed. Thus, the user is relieved of the tedious and error-prone process of model construction, permitting an efficient exploration of the design space, and an independent validation of the system's operation is obtained. An additional benefit of automating the model construction process is the opportunity to reduce the specialized knowledge required. Hence, the user need only be an expert in the system he is analyzing; the expertise in reliability analysis techniques is supplied.

Babcock, Philip S., IV↗
NASA NTRS1978

Collection, processing and dissemination of data for the national solar demonstration program

A national solar data system developed for the DOE by IBM provides for automatic gathering, conversion, transfer, and analysis of demonstration site data. NASA requirements for this system include providing solar site hardware, engineering, data collection, and analysis. The specific tasks include: (1) solar energy system design/integration; (2) developing a site data acquisition subsystem; (3) developing a central data processing system; (4) operating the test facility at Marshall Space Flight Center; (5) collecting and analyzing data. The systematic analysis and evaluation of the data from the National Solar Data System is reflected in a monthly performance report and a solar energy system performance evaluation report.

Day, R. E.↗
NASA NTRS2003

Processing Digital Imagery to Enhance Perceptions of Realism

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Woodell, Glenn A.↗
NASA NTRS2021

Features and Characteristics of the New NASA MicroPuLse NETwork (MPLNET) Automatic Rain Detection Algorithm

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics.

S. Lolli↗
NASA NTRS1975

The analysis of the pilot's cognitive and decision processes

Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.

Curry, R. E.↗
NASA NTRS1979

Wind tunnel real-time data acquisition system

The hardware configuration is described for the data acquisition system (DAS) which consists of an analog front end that can process up to 260 channels of data, a multichannel analog-to-digital subsystem that can process up to 50,000 samples of data per second, and a digital computer with standard and nonstandard devices, including graphics capability. Also described are the software configuration of the DAS and complex hardware/software interfaces providing, for example, automatic amplifier gain and offset adjustment for each data channel. Specific DAS applications are summarized, including the real time processing of dynamic deflection data, unsteady pressure measurements, and flutter and buffet data.

Cole, P.↗
NASA NTRS1999

Visualization Co-Processing of a CFD Simulation

OVERFLOW, a widely used CFD simulation code, is combined with a visualization system, pV3, to experiment with an environment for simulation/visualization co-processing on a SGI Origin 2000 computer(O2K) system. The shared memory version of the solver is used with the O2K 'pfa' preprocessor invoked to automatically discover parallelism in the source code. No other explicit parallelism is enabled. In order to study the scaling and performance of the visualization co-processing system, sample runs are made with different processor groups in the range of 1 to 254 processors. The data exchange between the visualization system and the simulation system is rapid enough for user interactivity when the problem size is small. This shared memory version of OVERFLOW, with minimal parallelization, does not scale well to an increasing number of available processors. The visualization task takes about 18 to 30% of the total processing time and does not appear to be a major contributor to the poor scaling. Improper load balancing and inter-processor communication overhead are contributors to this poor performance. Work is in progress which is aimed at obtaining improved parallel performance of the solver and removing the limitations of serial data transfer to pV3 by examining various parallelization/communication strategies, including the use of the explicit message passing.

Vaziri, Arsi↗
NASA NTRS1975

AMPS data management concepts

Five typical AMPS experiments were formulated to allow simulation studies to verify data management concepts. Design studies were conducted to analyze these experiments in terms of the applicable procedures, data processing and displaying functions. Design concepts for AMPS data management system are presented which permit both automatic repetitive measurement sequences and experimenter-controlled step-by-step procedures. Extensive use is made of a cathode ray tube display, the experimenters' alphanumeric keyboard, and the computer. The types of computer software required by the system and the possible choices of control and display procedures available to the experimenter are described for several examples. An electromagnetic wave transmission experiment illustrates the methods used to analyze data processing requirements.

Metzelaar, P. N.↗
NASA NTRS1972

Some new techniques for processing remotely obtained images by self-generated spectral masks.

An extension of a new technique that makes possible parallel, simultaneous processing of remotely obtained images is presented. The technique holds out promise for automatic onboard classification of data. The central feature involves the generation of binary masks, directly from the image, based on object reflectance data, that group objects into equivalence classes. These masks, called equivalence class masks, can be used in various logical combinations to isolate classes of objects with a priori known reflectance or radiance signatures. Experimental verification of the technique is furnished for simple scenes. A computational scheme, based on a sequence of integrated irradiance measurements on the image, that makes it possible to identify objects within an equivalence class is suggested.

Stark, H.↗