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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 NTRS1990

Vehicle processing operations database

The Vehicle Processing Operations Data base (VPOD) has been designed and constructed to enable the collection and preliminary analysis of data relative to the processing of planetary exploration vehicles in low Earth orbit. VPOD has the capability to hierarchically store the events, assemblies, and equipment data needed for performing vehicle processing analysis, to whatever level of detail available. This permits some analysis to be performed even during the very early phases of vehicle and mission design. As more data about the events, assemblies, or equipment become available, the analysis can then be refined using the increased level of detail. VPOD output is based on a mission defined by selecting from the VPOD Events data base the events that are required to perform the desired tasks. The outputs available include total crew time, crew skill requirements, equipment needed, assemblies worked per event, to any available level of detail. The VPOD design is structured to interface with an operations simulation capability which is currently in the requirements definition phase. The simulator will use information from the VPOD to perform operations analysis for missions being conducted in low Earth orbit. VPOD information, along with information from the science missions operations data base and a Space Station configuration data base, will be used by the simulator to provide a capability to study total system operations and resources requirements.

Ganoe, George G.↗
NASA NTRS1993

The National Launch System Advanced Development Program: A brief overview

A broad-based Advanced Development Program is being conducted to modernize the technological base and support the systems design of the National Launch System. While the principal concentration of efforts has been in propulsion, significant work is being accomplished in all of the disciplinary areas associated with space launch. Tasks are selected that offer reduced costs, increased reliability, and enhanced operability with anticipated task completion times which are consistent with NLS development.

Battenburg, J. A.↗
NASA NTRS1992

An expert system for integrated structural analysis and design optimization for aerospace structures

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

Source record↗
NASA NTRS1994

An intelligent robot for helping astronauts

This paper describes the development status of a prototype supervised intelligent robot for space application for purposes of (1) helping the crew of a spacecraft such as the Space Station with various tasks, such as holding objects and retrieving/replacing tools and other objects from/into storage, and (2) for purposes of retrieving detached objects, such as equipment or crew, that have become separated from their spacecraft. In addition to this set of tasks in this low-Earth-orbiting spacecraft environment, it is argued that certain aspects of the technology can be viewed as generic in approach, thereby offering insight into intelligent robots for other tasks and environments. Candidate software architectures and their key technical issues which enable real work in real environments to be accomplished safely and robustly are addressed. Results of computer simulations of grasping floating objects are presented. Also described are characterization results on the usable reduced gravity environment in an aircraft flying parabola (to simulate weightlessness) and results on hardware performance there. These results show it is feasible to use that environment for evaluative testing of dexterous grasping based on real-time vision of freely rotating and translating objects.

Erickson, J. D.↗
NASA NTRS1994

Rocketdyne Safety Algorithm: Space Shuttle Main Engine Fault Detection

The Rocketdyne Safety Algorithm (RSA) has been developed to the point of use on the TTBE at MSFC on Task 4 of LeRC contract NAS3-25884. This document contains a description of the work performed, the results of the nominal test of the major anomaly test cases and a table of the resulting cutoff times, a plot of the RSA value vs. time for each anomaly case, a logic flow description of the algorithm, the algorithm code, and a development plan for future efforts.

Norman, Arnold M., Jr.↗
NASA NTRS1996

The Integrated Mode Management Interface

Mode management is the processes of understanding the character and consequences of autoflight modes, planning and selecting the engagement, disengagement and transitions between modes, and anticipating automatic mode transitions made by the autoflight system itself. The state of the art is represented by the latest designs produced by each of the major airframe manufacturers, the Boeing 747-400, the Boeing 777, the McDonnell Douglas MD-11, and the Airbus A320/A340 family of airplanes. In these airplanes autoflight modes are selected by manipulating switches on the control panel. The state of the autoflight system is displayed on the flight mode annunciators. The integrated mode management interface (IMMI) is a graphical interface to autoflight mode management systems for aircraft equipped with flight management computer systems (FMCS). The interface consists of a vertical mode manager and a lateral mode manager. Autoflight modes are depicted by icons on a graphical display. Mode selection is accomplished by touching (or mousing) the appropriate icon. The IMMI provides flight crews with an integrated interface to autoflight systems for aircraft equipped with flight management computer systems (FMCS). The current version is modeled on the Boeing glass-cockpit airplanes (747-400, 757/767). It runs on the SGI Indigo workstation. A working prototype of this graphics-based crew interface to the autoflight mode management tasks of glass cockpit airplanes has been installed in the Advanced Concepts Flight Simulator of the CSSRF of NASA Ames Research Center. This IMMI replaces the devices in FMCS equipped airplanes currently known as mode control panel (Boeing), flight guidance control panel (McDonnell Douglas), and flight control unit (Airbus). It also augments the functions of the flight mode annunciators. All glass cockpit airplanes are sufficiently similar that the IMMI could be tailored to the mode management system of any modern cockpit. The IMMI does not replace the functions of the FMCS control and display unit. The purpose of the INMI is to provide flight crews with a shared medium in which they can assess the state of the autoflight system, take control actions on it, reason about its behavior, and communicate with each other about its behavior. The design is intended to increase mode awareness and provide a better interface to autoflight mode management. This report describes the IMMI, the methods that were used in designing and developing it, and the theory underlying the design and development processes.

Hutchins, Edwin↗
NASA NTRS2000

Improved Anvil Forecasting

This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

Lambert, Winifred C.↗
NASA NTRS2001

Avionics Simulation, Development and Software Engineering

This monthly report summarizes the work performed under contract NAS8-00114 for Marshall Space Flight Center in the following tasks: 1) Purchase Order No. H-32831D, Task Order 001A, GPB Program Software Oversight; 2) Purchase Order No. H-32832D, Task Order 002, ISS EXPRESS Racks Software Support; 3) Purchase Order No. H-32833D, Task Order 003, SSRMS Math Model Integration; 4) Purchase Order No. H-32834D, Task Order 004, GPB Program Hardware Oversight; 5) Purchase Order No. H-32835D, Task Order 005, Electrodynamic Tether Operations and Control Analysis; 6) Purchase Order No. H-32837D, Task Order 007, SRB Command Receiver/Decoder; and 7) Purchase Order No. H-32838D, Task Order 008, AVGS/DART SW and Simulation Support

Francis, Ronald C.↗
NASA NTRS2004

Monitoring and Testing the Parts Cleaning Stations, Abrasive Blasting Cabinets, and Paint Booths

I have the opportunity to work in the Environmental Management Office (EMO) this summer. One of the EMO's tasks is to make sure the Environmental Management System is implemented to the entire Glenn Research Center (GRC). The Environmental Management System (EMS) is a policy or plan that is oriented toward minimizing an organization's impact to the environment. Our EMS includes the reduction of solid waste regeneration and the reduction of hazardous material use, waste, and pollution. With the Waste Management Team's (WMT) help, the EMS can be implemented throughout the NASA Glenn Research Center. The WMT is responsible for the disposal and managing of waste throughout the GRC. They are also responsible for the management of all chemical waste in the facility. My responsibility is to support the waste management team by performing an inventory on parts cleaning stations, abrasive cabinets, and paint booths through out the entire facility. These booths/stations are used throughout the center and they need to be monitored and tested for hazardous waste and material. My job is to visit each of these booths/stations, take samples of the waste, and analyze the samples.

Jordan, Tracee M.↗
NASA NTRS2004

Software Quality Assurance Metrics

Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.

McRae, Kalindra A.↗
NASA NTRS2005

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Jones, Kennie H.↗
NASA NTRS2014

An Ergonomic Evaluation of the Extravehicular Mobility Unit (EMU) Space Suit Hard Upper Torso (HUT) Size Effect on Metabolic, Mobility, and Strength Performance

The objective of this project was to assess the performance differences between a nominally sized Extravehicular Mobility Unit (EMU) space suit and a nominal +1 (plus) sized EMU. Method: This study evaluated suit size conditions by using metabolic cost, arm mobility, and arm strength as performance metrics. Results: Differences between the suit sizes were found only in shoulder extension strength being 15.8% greater for the plus size. Discussion: While this study was able to identify motions and activities that were considered to be practically or statistically different, it does not signify that use of a plus sized suit should be prohibited. Further testing would be required that either pertained to a particular mission critical task or better simulates a microgravity environment that the EMU suit was designed to work in.

Reid, Christopher↗
NASA NTRS2015

Numerical Analysis of Incipient Separation on 53 Deg Swept Diamond Wing

A systematic analysis of incipient separation and subsequent vortex formation from moderately swept blunt leading edges is presented for a 53 deg swept diamond wing. This work contributes to a collective body of knowledge generated within the NATO/STO AVT-183 Task Group titled 'Reliable Prediction of Separated Flow Onset and Progression for Air and Sea Vehicles'. The objective is to extract insights from the experimentally measured and numerically computed flow fields that might enable turbulence experts to further improve their models for predicting swept blunt leading-edge flow separation. Details of vortex formation are inferred from numerical solutions after establishing a good correlation of the global flow field and surface pressure distributions between wind tunnel measurements and computed flow solutions. From this, significant and sometimes surprising insights into the nature of incipient separation and part-span vortex formation are derived from the wealth of information available in the computational solutions.

Frink, Neal T.↗
NASA NTRSDate not supplied

Predicting Adverse Events and their Precursors in Aviation Using Multi-Class Multiple-Instance Learning

In recent years, there has been a rapid growth in the application of machine learning techniques that leverage aviation data collected from commercial airline operations to improve safety. Anomaly detection and predictive maintenance have been the main targets for machine learning applications. However, this paper focuses on the identification of precursors, which is a relatively newer application. Precursors are events correlated with adverse events that happen prior to the adverse event itself. Therefore, precursor mining provides many benefits including understanding the reasons behind a safety incident and the ability to identify signatures, which can be tracked throughout a flight to alert the operators of an potential upcoming adverse event. This work proposes using the multiple-instance learning (MIL) framework, a weakly supervised learning task, combined with a carefully designed Multi-Head Convolutional Neural Networks-Recurrent Neural Networks (MHCNN-RNN) architecture to predict different type of adverse events for any given flights and identify their precursors with little to no post-processing.Results obtained show that the MHCNN-RNN is able to accurately forecast high speed and high path angle events during the approach, and that it is also capable of determining the aircraft’s parameters that are correlated to these events. These parameters can be considered precursors to the events.

multiple instance learning↗
NASA NTRS1993

Direct Broadcast Satellite-Radio, Receiver Development

This paper reports on the status of the ongoing Direct Broadcast Satellite-Radio (DBS-R) Receiver Development Task being performed at the Jet Propulsion Laboratory, California Institute of Technology (JPL). This work is sponsored by the Voice of America/U.S Information Agency through an agreement with NASA.

Radio↗
NASA NTRSDate not supplied

Simplifying Requirements Formalization for Resource-Constrained Mission-Critical Software

Developing critical software requires adherence to rigorous software development practices, such as formal requirement specification and verification. Despite their importance, such practices are often considered as complex and challenging tasks that require a strong formal methods background. In this paper, we present our work on simplifying the formal requirements specification experience for resource-constrained mission critical software through the use of structured natural language. To this end, we connect NASA’s FRET, a formal requirement elicitation and authoring tool with the Shelley model checking framework for MicroPython code. We report our experience on using these tools to specify requirements and analyze code from the NASA Ames PHALANX exploration concept.

PHALANX exploration concept↗
DOE OSTI2015

David Blackwell’s Forty Years in the Idaho Desert, The Foundation for 21st Century Geothermal Research

Dr. David Blackwell has had a profound influence on geo-thermal exploration and R&D in Idaho. Forty years have elapsed since the first Southern Methodist University (SMU) temperature logging truck rolled onto the high desert in Southern Idaho, yet even after so much time has elapsed, most recent and ongoing geothermal R&D can trace its roots to the foundational temperature studies led by Dr. Blackwell. We believe that the best way to honor any scientist is to see their work carried forward by others. As this paper demonstrates, it has been an easy task to find a host of Idaho researchers and students eager to contribute to this tribute paper. We organize this paper by ongoing or recent projects that continue to benefit left to Idaho by Dr. David Blackwell.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Prediction Models for Dynamic Demand Response

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2 R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2 R, which we address in this paper. Our first contribution is the formal definition of D 2 R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2 R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2 R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2 R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2 R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions, simplifying the complexity of big data challenge associated with D 2 R.

Aman, Saima↗