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At least 199 records · Page 11

Management issues in systems engineering

When applied to a system, the doctrine of successive refinement is a divide-and-conquer strategy. Complex systems are sucessively divided into pieces that are less complex, until they are simple enough to be conquered. This decomposition results in several structures for describing the product system and the producing system. These structures play important roles in systems engineering and project management. Many of the remaining sections in this chapter are devoted to describing some of these key structures. Structures that describe the product system include, but are not limited to, the requirements tree, system architecture and certain symbolic information such as system drawings, schematics, and data bases. The structures that describe the producing system include the project's work breakdown, schedules, cost accounts and organization.

Shishko, Robert↗

An Engineering Approach to Management of Occupational and Community Noise Exposure at NASA Lewis Research Center

Workplace and environmental noise issues at NASA Lewis Research Center are effectively managed via a three-part program that addresses hearing conservation, community noise control, and noise control engineering. The Lewis Research Center Noise Exposure Management Program seeks to limit employee noise exposure and maintain community acceptance for critical research while actively pursuing engineered controls for noise generated by more than 100 separate research facilities and the associated services required for their operation.

Cooper, Beth A.↗

ESMD Risk Management Workshop: Systems Engineering and Integration Risks

This report has been developed by the National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate (ESMD) Risk Management team in close coordination with the Systems Engineering Team. This document provides a point-in-time, cumulative, summary of key lessons learned derived from the SE RFP Development process. Lessons learned invariably address challenges and risks and the way in which these areas have been addressed. Accordingly the risk management thread is woven throughout the document.

Systems Engineering↗

Development of an Information Fusion System for Engine Diagnostics and Health Management

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Volponi, Allan J.↗

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.

Volponi, Al↗

Intelligent Engine Systems: Thermal Management and Advanced Cooling

The objective is to provide turbine-cooling technologies to meet Propulsion 21 goals related to engine fuel burn, emissions, safety, and reliability. Specifically, the GE Aviation (GEA) Advanced Turbine Cooling and Thermal Management program seeks to develop advanced cooling and flow distribution methods for HP turbines, while achieving a substantial reduction in total cooling flow and assuring acceptable turbine component safety and reliability. Enhanced cooling techniques, such as fluidic devices, controlled-vortex cooling, and directed impingement jets, offer the opportunity to incorporate both active and passive schemes. Coolant heat transfer enhancement also can be achieved from advanced designs that incorporate multi-disciplinary optimization of external film and internal cooling passage geometry.

Bergholz, Robert↗

Sensor Needs for Control and Health Management of Intelligent Aircraft Engines

NASA and the U.S. Department of Defense are conducting programs which support the future vision of "intelligent" aircraft engines for enhancing the affordability, performance, operability, safety, and reliability of aircraft propulsion systems. Intelligent engines will have advanced control and health management capabilities enabling these engines to be self-diagnostic, self-prognostic, and adaptive to optimize performance based upon the current condition of the engine or the current mission of the vehicle. Sensors are a critical technology necessary to enable the intelligent engine vision as they are relied upon to accurately collect the data required for engine control and health management. This paper reviews the anticipated sensor requirements to support the future vision of intelligent engines from a control and health management perspective. Propulsion control and health management technologies are discussed in the broad areas of active component controls, propulsion health management and distributed controls. In each of these three areas individual technologies will be described, input parameters necessary for control feedback or health management will be discussed, and sensor performance specifications for measuring these parameters will be summarized.

Simon, Donald L.↗

Space systems engineering and risk management - joined at the hip

This paper explores the separate skills and capabilities practiced until now, and the powerful coupling to be achieved, practically and effectively, in implementing a space mission, from inception (pre-phase A) to the end of Operations (phase E). The use of risk assessment techniques in balancing cost risk against performance risk, and the application of the systems engineering team in these trades, is the key to achieving this new implementation paradigm.

systems engineering↗

Intelligent Engine Systems: Thermal Management and Advanced Cooling

The objective of the Advanced Turbine Cooling and Thermal Management program is to develop intelligent control and distribution methods for turbine cooling, while achieving a reduction in total cooling flow and assuring acceptable turbine component safety and reliability. The program also will develop embedded sensor technologies and cooling system models for real-time engine diagnostics and health management. Both active and passive control strategies will be investigated that include the capability of intelligent modulation of flow quantities, pressures, and temperatures both within the supply system and at the turbine component level. Thermal management system concepts were studied, with a goal of reducing HPT blade cooling air supply temperature. An assessment will be made of the use of this air by the active clearance control system as well. Turbine component cooling designs incorporating advanced, high-effectiveness cooling features, will be evaluated. Turbine cooling flow control concepts will be studied at the cooling system level and the component level. Specific cooling features or sub-elements of an advanced HPT blade cooling design will be downselected for core fabrication and casting demonstrations.

Bergholz, Robert↗

Model-Based Systems Engineering Approach to Managing Mass Margin

When designing a flight system from concept through implementation, one of the fundamental systems engineering tasks ismanaging the mass margin and a mass equipment list (MEL) of the flight system. While generating a MEL and computing a mass margin is conceptually a trivial task, maintaining consistent and correct MELs and mass margins can be challenging due to the current practices of maintaining duplicate information in various forms, such as diagrams and tables, and in various media, such as files and emails. We have overcome this challenge through a model-based systems engineering (MBSE) approach within which we allow only a single-source-of-truth. In this paper we describe the modeling patternsused to capture the single-source-of-truth and the views that have been developed for the Europa Habitability Mission (EHM) project, a mission concept study, at the Jet Propulsion Laboratory (JPL).

cloud comu↗

A History of Space Shuttle Main Engine (SSME) Redline Limits Management

The Space Shuttle Main Engine (SSME) has several "redlines", which are operational limits designated to preclude a catastrophic shutdown of the SSME. The Space Shuttle Orbiter utilizes a combination of hardware and software to enable or disable the automated redline shutdown capability. The Space Shuttle is launched with the automated SSME redline limits enabled, but there are many scenarios which may result in the manual disabling of the software by the onboard crew. The operational philosophy for manually enabling and disabling the redline limits software has evolved continuously throughout the history of the Space Shuttle Program, due to events such as SSME hardware changes and updates to Space Shuttle contingency abort software. In this paper, the evolution of SSME redline limits management will be fully reviewed, including the operational scenarios which call for manual intervention, and the events that triggered changes to the philosophy. Following this review, improvements to the management of redline limits for future spacecraft will be proposed.

Arnold, Thomas M.↗

Knowledge management in the engineering design environment

The Aerospace and Defense industry is experiencing an increasing loss of knowledge through workforce reductions associated with business consolidation and retirement of senior personnel. Significant effort is being placed on process definition as part of ISO certification and, more recently, CMMI certification. The process knowledge in these efforts represents the simplest of engineering knowledge and many organizations are trying to get senior engineers to write more significant guidelines, best practices and design manuals. A new generation of design software, known as Product Lifecycle Management systems, has many mechanisms for capturing and deploying a wider variety of engineering knowledge than simple process definitions. These hold the promise of significant improvements through reuse of prior designs, codification of practices in workflows, and placement of detailed how-tos at the point of application.

designs↗

Reusable Rocket Engine Turbopump Health Management System

A health monitoring expert system software architecture has been developed to support condition-based health monitoring of rocket engines. Its first application is in the diagnosis decisions relating to the health of the high pressure oxidizer turbopump (HPOTP) of Space Shuttle Main Engine (SSME). The post test diagnostic system runs off-line, using as input the data recorded from hundreds of sensors, each running typically at rates of 25, 50, or .1 Hz. The system is invoked after a test has been completed, and produces an analysis and an organized graphical presentation of the data with important effects highlighted. The overall expert system architecture has been developed and documented so that expert modules analyzing other line replaceable units may easily be added. The architecture emphasizes modularity, reusability, and open system interfaces so that it may be used to analyze other engines as well.

Surko, Pamela↗

Hybrid Power Management

An engineering discipline denoted as hybrid power management (HPM) has emerged from continuing efforts to increase energy efficiency and reliability of hybrid power systems. HPM is oriented toward integration of diverse electric energy-generating, energy-storing, and energy-consuming devices in optimal configurations for both terrestrial and outer-space applications. The basic concepts of HPM are potentially applicable at power levels ranging from nanowatts to megawatts. Potential applications include terrestrial power-generation, terrestrial transportation, biotechnology, and outer-space power systems. Instances of this discipline at prior stages of development were reported (though not explicitly labeled as HPM) in three prior NASA Tech Briefs articles: "Ultracapacitors Store Energy in a Hybrid Electric Vehicle"(LEW-16876), Vol. 24, No. 4 (April 2000), page 63; "Photovoltaic Power Station With Ultracapacitors for Storage" (LEW-17177), Vol. 27, No. 8 (August 2003), page 38; and "Flasher Powered by Photovoltaic Cells and Ultracapacitors" (LEW-17246), Vol. 24, No. 10 (October 2003), page 37. As the titles of the cited articles indicate, the use of ultracapacitors as energy-storage devices lies at the heart of HPM. An ultracapacitor is an electrochemical energy-storage device, but unlike in a conventional rechargeable electrochemical cell or battery, chemical reactions do not take place during operation. Instead, energy is stored electrostatically at an electrode/electrolyte interface. The capacitance per unit volume of an ultracapacitor is much greater than that of a conventional capacitor because its electrodes have much greater surface area per unit volume and the separation between the electrodes is much smaller. Power-control circuits for ultracapacitors can be simpler than those for batteries, for two reasons: (1) Because of the absence of chemical reactions, charge and discharge currents can be greater than those in batteries, limited only by the electrical resistances of conductors; and (2) whereas the charge level of a battery depends on voltage, temperature, age, and load condition, the charge level of an ultracapacitor, like that of a conventional capacitor, depends only on voltage.

Eichenberg, Dennis↗

Repository-Based Software Engineering Program: Working Program Management Plan

Repository-Based Software Engineering Program (RBSE) is a National Aeronautics and Space Administration (NASA) sponsored program dedicated to introducing and supporting common, effective approaches to software engineering practices. The process of conceiving, designing, building, and maintaining software systems by using existing software assets that are stored in a specialized operational reuse library or repository, accessible to system designers, is the foundation of the program. In addition to operating a software repository, RBSE promotes (1) software engineering technology transfer, (2) academic and instructional support of reuse programs, (3) the use of common software engineering standards and practices, (4) software reuse technology research, and (5) interoperability between reuse libraries. This Program Management Plan (PMP) is intended to communicate program goals and objectives, describe major work areas, and define a management report and control process. This process will assist the Program Manager, University of Houston at Clear Lake (UHCL) in tracking work progress and describing major program activities to NASA management. The goal of this PMP is to make managing the RBSE program a relatively easy process that improves the work of all team members. The PMP describes work areas addressed and work efforts being accomplished by the program; however, it is not intended as a complete description of the program. Its focus is on providing management tools and management processes for monitoring, evaluating, and administering the program; and it includes schedules for charting milestones and deliveries of program products. The PMP was developed by soliciting and obtaining guidance from appropriate program participants, analyzing program management guidance, and reviewing related program management documents.

Source record↗

Software Engineering Guidebook

The Software Engineering Guidebook describes SEPG (Software Engineering Process Group) supported processes and techniques for engineering quality software in NASA environments. Three process models are supported: structured, object-oriented, and evolutionary rapid-prototyping. The guidebook covers software life-cycles, engineering, assurance, and configuration management. The guidebook is written for managers and engineers who manage, develop, enhance, and/or maintain software under the Computer Software Services Contract.

Connell, John↗