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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 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRS1988

Mission Report on the Orbiter Camera Payload System (OCPS) Large Format Camera (LFC) and Attitude Reference System (ARS)

The Orbiter Camera Payload System (OCPS) is an integrated photographic system which is carried into earth orbit as a payload in the Space Transportation System (STS) Orbiter vehicle's cargo bay. The major component of the OCPS is a Large Format Camera (LFC), a precision wide-angle cartographic instrument that is capable of producing high resolution stereo photography of great geometric fidelity in multiple base-to-height (B/H) ratios. A secondary, supporting system to the LFC is the Attitude Reference System (ARS), which is a dual lens Stellar Camera Array (SCA) and camera support structure. The SCA is a 70-mm film system which is rigidly mounted to the LFC lens support structure and which, through the simultaneous acquisition of two star fields with each earth-viewing LFC frame, makes it possible to determine precisely the pointing of the LFC optical axis with reference to the earth nadir point. Other components complete the current OCPS configuration as a high precision cartographic data acquisition system. The primary design objective for the OCPS was to maximize system performance characteristics while maintaining a high level of reliability compatible with Shuttle launch conditions and the on-orbit environment. The full-up OCPS configuration was launched on a highly successful maiden voyage aboard the STS Orbiter vehicle Challenger on October 5, 1984, as a major payload aboard mission STS 41-G. This report documents the system design, the ground testing, the flight configuration, and an analysis of the results obtained during the Challenger mission STS 41-G.

Mollberg, Bernard H.↗

NASA NTRS1991

A knowledge-based system design/information tool for aircraft flight control systems

Research aircraft have become increasingly dependent on advanced electronic control systems to accomplish program goals. These aircraft are integrating multiple disciplines to improve performance and satisfy research objective. This integration is being accomplished through electronic control systems. Systems design methods and information management have become essential to program success. The primary objective of the system design/information tool for aircraft flight control is to help transfer flight control system design knowledge to the flight test community. By providing all of the design information and covering multiple disciplines in a structured, graphical manner, flight control systems can more easily be understood by the test engineers. This will provide the engineers with the information needed to thoroughly ground test the system and thereby reduce the likelihood of serious design errors surfacing in flight. The secondary object is to apply structured design techniques to all of the design domains. By using the techniques in the top level system design down through the detailed hardware and software designs, it is hoped that fewer design anomalies will result. The flight test experiences are reviewed of three highly complex, integrated aircraft programs: the X-29 forward swept wing; the advanced fighter technology integration (AFTI) F-16; and the highly maneuverable aircraft technology (HiMAT) program. Significant operating technologies, and the design errors which cause them, is examined to help identify what functions a system design/informatin tool should provide to assist designers in avoiding errors.

Mackall, Dale A.↗

NASA NTRS1993

An expert system shell for inferring vegetation characteristics: Prototype help system (Task 1)

The NASA Vegetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. A prototype of the VEG subgoal HELP.SYSTEM has been completed and the Help System has been added to the VEG system. It is loaded when the user first clicks on the HELP.SYSTEM option in the Tool Box Menu. The Help System provides a user tool to support needed user information. It also provides interactive tools the scientist may use to develop new help messages and to modify existing help messages that are attached to VEG screens. The system automatically manages system and file operations needed to preserve new or modified help messages. The Help System was tested both as a help system development and a help system user tool.

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NASA NTRS1995

Technical report series on global modeling and data assimilation. Volume 4: Documentation of the Goddard Earth Observing System (GEOS) data assimilation system, version 1

This report describes the analysis component of the Goddard Earth Observing System, Data Assimilation System, Version 1 (GEOS-1 DAS). The general features of the data assimilation system are outlined, followed by a thorough description of the statistical interpolation algorithm, including specification of error covariances and quality control of observations. We conclude with a discussion of the current status of development of the GEOS data assimilation system. The main components of GEOS-1 DAS are an atmospheric general circulation model and an Optimal Interpolation algorithm. The system is cycled using the Incremental Analysis Update (IAU) technique in which analysis increments are introduced as time independent forcing terms in a forecast model integration. The system is capable of producing dynamically balanced states without the explicit use of initialization, as well as a time-continuous representation of non- observables such as precipitation and radiational fluxes. This version of the data assimilation system was used in the five-year reanalysis project completed in April 1994 by Goddard's Data Assimilation Office (DAO) Data from this reanalysis are available from the Goddard Distributed Active Center (DAAC), which is part of NASA's Earth Observing System Data and Information System (EOSDIS). For information on how to obtain these data sets, contact the Goddard DAAC at (301) 286-3209, EMAIL daac@gsfc.nasa.gov.

Suarez, Max J.↗

NASA NTRS1998

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Larson, Jay W.↗

NASA NTRS2005

Meeting the Challenges of Exploration Systems: Health Management Technologies for Aerospace Systems With Emphasis on Propulsion

The constraints of future Exploration Missions will require unique Integrated System Health Management (ISHM) capabilities throughout the mission. An ambitious launch schedule, human-rating requirements, long quiescent periods, limited human access for repair or replacement, and long communication delays all require an ISHM system that can span distinct yet interdependent vehicle subsystems, anticipate failure states, provide autonomous remediation, and support the Exploration Mission from beginning to end. NASA Glenn Research Center has developed and applied health management system technologies to aerospace propulsion systems for almost two decades. Lessons learned from past activities help define the approach to proper ISHM development: sensor selection- identifies sensor sets required for accurate health assessment; data qualification and validation-ensures the integrity of measurement data from sensor to data system; fault detection and isolation-uses measurements in a component/subsystem context to detect faults and identify their point of origin; information fusion and diagnostic decision criteria-aligns data from similar and disparate sources in time and use that data to perform higher-level system diagnosis; and verification and validation-uses data, real or simulated, to provide variable exposure to the diagnostic system for faults that may only manifest themselves in actual implementation, as well as faults that are detectable via hardware testing. This presentation describes a framework for developing health management systems and highlights the health management research activities performed by the Controls and Dynamics Branch at the NASA Glenn Research Center. It illustrates how those activities contribute to the development of solutions for Integrated System Health Management.

Melcher, Kevin J.↗

NASA NTRS2012

System-of-Systems Technology-Portfolio-Analysis Tool

Advanced Technology Life-cycle Analysis System (ATLAS) is a system-of-systems technology-portfolio-analysis software tool. ATLAS affords capabilities to (1) compare estimates of the mass and cost of an engineering system based on competing technological concepts; (2) estimate life-cycle costs of an outer-space-exploration architecture for a specified technology portfolio; (3) collect data on state-of-the-art and forecasted technology performance, and on operations and programs; and (4) calculate an index of the relative programmatic value of a technology portfolio. ATLAS facilitates analysis by providing a library of analytical spreadsheet models for a variety of systems. A single analyst can assemble a representation of a system of systems from the models and build a technology portfolio. Each system model estimates mass, and life-cycle costs are estimated by a common set of cost models. Other components of ATLAS include graphical-user-interface (GUI) software, algorithms for calculating the aforementioned index, a technology database, a report generator, and a form generator for creating the GUI for the system models. At the time of this reporting, ATLAS is a prototype, embodied in Microsoft Excel and several thousand lines of Visual Basic for Applications that run on both Windows and Macintosh computers.

O'Neil, Daniel↗

NASA NTRS2012

Cognitive Systems Modeling and Analysis of Command and Control Systems

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Norlander, Arne↗

NASA NTRS2014

System Engineering of Photonic Systems for Space Application

The application of photonics in space systems requires tight integration with the spacecraft systems to ensure accurate operation. This requires some detailed and specific system engineering to properly incorporate the photonics into the spacecraft architecture and to guide the spacecraft architecture in supporting the photonics devices. Recent research in product focused, elegant system engineering has led to a system approach which provides a robust approach to this integration. Focusing on the mission application and the integration of the spacecraft system physics incorporation of the photonics can be efficiently and effectively accomplished. This requires a clear understanding of the driving physics properties of the photonics device to ensure proper integration with no unintended consequences. The driving physics considerations in terms of optical performance will be identified for their use in system integration. Keywords: System Engineering, Optical Transfer Function, Optical Physics, Photonics, Image Jitter, Launch Vehicle, System Integration, Organizational Interaction

Watson, Michael D.↗

NASA NTRS2017

The Use of a Satellite Communications System for Command and Control of the National Aeronautics and Space Administration Surrogate Unmanned Aerial System Research Aircraft

The NASA Langley Research Center has transformed a Cirrus Design SR22 general aviation (GA) aircraft into an Unmanned Aerial Systems (UAS) Surrogate research aircraft which has served for several years as a platform for unmanned systems research and development. The aircraft is manned with a Safety Pilot and a Research Systems Operator (RSO) that allows for flight operations almost any-where in the national airspace system (NAS) without the need for a Federal Aviation Administration (FAA) Certificate of Authorization (COA). The UAS Surrogate can be remotely controlled from a modular, transportable ground control station (GCS) like a true UAS. Ground control of the aircraft is accomplished by the use of data links that allow the two-way passage of the required data to control the aircraft and provide the GCS with situational awareness. The original UAS Surrogate data-link system was composed of redundant very high frequency (VHF) data radio modems with a maximum range of approximately 40 nautical miles. A new requirement was developed to extend this range beyond visual range (BVR). This new requirement led to the development of a satellite communications system that provided the means to command and control the UAS Surrogate at ranges beyond the limits of the VHF data links. The system makes use of the Globalstar low earth orbit (LEO) satellite communications system. This paper will provide details of the development, implementation, and flight testing of the satellite data communications system on the UAS Surrogate research aircraft.

Howell, Charles T.↗

NASA NTRS2017

Thermal System Modeling for Lunar and Martian Surface Regenerative Fuel Cell Systems

The Advanced Exploration Systems (AES) Advanced Modular Power Systems (AMPS) Project is investigating different power systems for various lunar and Martian mission concepts. The AMPS Fuel Cell (FC) team has created two system-level models to evaluate the performance of regenerative fuel cell (RFC) systems employing different fuel cell chemistries. Proton Exchange Membrane fuel cells PEMFCs contain a polymer electrolyte membrane that separates the hydrogen and oxygen cavities and conducts hydrogen cations (protons) across the cell. Solid Oxide fuel cells (SOFCs) operate at high temperatures, using a zirconia-based solid ceramic electrolyte to conduct oxygen anions across the cell. The purpose of the modeling effort is to down select one fuel cell chemistry for a more detailed design effort. Figures of merit include the system mass, volume, round trip efficiency, and electrolyzer charge power required. PEMFCs operate at around 60 degrees Celsius versus SOFCs which operate at temperatures greater than 700 degrees Celsius. Due to the drastically different operating temperatures of the two chemistries the thermal control systems (TCS) differ. The PEM TCS is less complex and is characterized by a single pump cooling loop that uses deionized water coolant and rejects heat generated by the system to the environment via a radiator. The solid oxide TCS has its own unique challenges including the requirement to reject high quality heat and to condense the steam produced in the reaction. This paper discusses the modeling of thermal control systems for an extraterrestrial RFC that utilizes either a PEM or solid oxide fuel cell.

thermal modeling↗

NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Removal Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide removal systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide removal systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗

NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Reduction Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide reduction systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide reduction systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System

NASA↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model Based Engineering

Model Based Engineering↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model-Based Engineering (REV B)

The emergence of model-based engineering is transforming design and analysis methodologies. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses, GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System Safety Engineering for NASA if adequate modeling processes and environment are established.

NASA↗

DOE OSTI2015

Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), a systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.

Bucknor, Matthew↗

DOE OSTI2016

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens of thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.

25 ENERGY STORAGE↗