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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 541 records · Page 30

Implementing Effective Mission Systems Engineering Practices During Early Project Formulation Phases

Developing and implementing a plan for a NASA space mission can be a complicated process. The needs, goals, and objectives of any proposed mission or technology must be assessed early in the Project Life Cycle. The key to successful development of a space mission or flight project is the inclusion of systems engineering in early project formulation, namely during Pre-phase A, Phase A, and Phase B of the NASA Project Life Cycle. When a space mission or new technology is in pre-development, or "pre-Formulation", feasibility must be determined based on cost, schedule, and risk. Inclusion of system engineering during project formulation is key because in addition to assessing feasibility, design concepts are developed and alternatives to design concepts are evaluated. Lack of systems engineering involvement early in the project formulation can result in increased risks later in the implementation and operations phases of the project. One proven method for effective systems engineering practice during the pre-Formulation Phase is the use of a mission conceptual design or technology development laboratory, such as the Mission Design Lab (MDL) at NASA's Goddard Space Flight Center (GSFC). This paper will review the engineering process practiced routinely in the MDL for successful mission or project development during the pre-Formulation Phase.

Processes↗

Reliability and Probabilistic Risk Assessment - How They Play Together

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

Safie, Fayssal↗

Development of a Multilevel Optimization Approach to the Design of Modern Engineering Systems

A general algorithm is proposed which carries out the design process iteratively, starting at the top of the hierarchy and proceeding downward. Each subproblem is optimized separately for fixed controls from higher level subproblems. An optimum sensitivity analysis is then performed which determines the sensitivity of the subproblem design to changes in higher level subproblem controls. The resulting sensitivity derivatives are used to construct constraints which force the controlling subproblems into chosing their own designs so as to improve the lower levels subproblem designs while satisfying their own constraints. The applicability of the proposed algorithm is demonstrated by devising a four-level hierarchy to perform the simultaneous aerodynamic and structural design of a high-performance sailplane wing for maximum cross-country speed. Finally, the concepts discussed are applied to the two-level minimum weight structural design of the sailplane wing. The numerical experiments show that discontinuities in the sensitivity derivatives may delay convergence, but that the algorithm is robust enough to overcome these discontinuities and produce low-weight feasible designs, regardless of whether the optimization is started from the feasible space or the infeasible one.

Barthelemy, J. F. M.↗

Tensoral: A system for post-processing turbulence simulation data

Many computer simulations in engineering and science -- and especially in computational fluid dynamics (CFD) -- produce huge quantities of numerical data. These data are often so large as to make even relatively simple post-processing of this data unwieldy. The data, once computed and quality-assured, is most likely analyzed by only a few people. As a result, much useful numerical data is under-utilized. Since future state-of-the-art simulations will produce even larger datasets, will use more complex flow geometries, and will be performed on more complex supercomputers, data management issues will become increasingly cumbersome. My goal is to provide software which will automate the present and future task of managing and post-processing large turbulence datasets. My research has focused on the development of these software tools -- specifically, through the development of a very high-level language called 'Tensoral'. The ultimate goal of Tensoral is to convert high-level mathematical expressions (tensor algebra, calculus, and statistics) into efficient low-level programs which numerically calculate these expressions given simulation datasets. This approach to the database and post-processing problem has several advantages. Using Tensoral the numerical and data management details of a simulation are shielded from the concerns of the end user. This shielding is carried out without sacrificing post-processor efficiency and robustness. Another advantage of Tensoral is that its very high-level nature lends itself to portability across a wide variety of computing (and supercomputing) platforms. This is especially important considering the rapidity of changes in supercomputing hardware.

Dresselhaus, Eliot↗

Developing a Medical System Foundation for Level of Care IV: Short-Duration Lunar Orbit

The Human Research Program (HRP) Exploration Medical Capability (ExMC) element has developed a Medical System Foundation for Level of Care IV, as defined by NASA’s space flight human-system standards, for short-duration lunar orbit missions by employing a systems engineering approach using model-based systems engineering tools. This Foundation includes a concept of operations, medical system architecture, associated functional and non-functional requirements and rationales, and medical conditions, capabilities, and resources. Collectively, these serve as a starting point (“Foundation”) for a medical system that meets the Level of Care IV requirement. The Foundation also includes traces to the current versions of NASA standards documents and lower (e.g., sub-system) and higher (e.g., vehicle system) level requirements. Stakeholders can use the Foundation to analyze the traces between medical capabilities, medical conditions, medical resources, and requirements; identify medical system interfaces with other vehicle systems/subsystems; and as a basis for performing trades on risks vs. medical system mass and volume allocation. To facilitate communication of the Foundation to stakeholders who do not have access to the modeling tools used, an HTML representation of the Foundation was created. This discussion will focus on the processes through which the Medical System Foundation was developed, how the Foundation builds a bridge between the medical and engineering domains and facilitates communication between these communities, and how these processes can be applied more broadly to a crew health and performance system and other system domains.

S. Lumpkins↗

Rapid Modeling and Analysis Tools: Evolution, Status, Needs and Directions

Advanced aerospace systems are becoming increasingly more complex, and customers are demanding lower cost, higher performance, and high reliability. Increased demands are placed on the design engineers to collaborate and integrate design needs and objectives early in the design process to minimize risks that may occur later in the design development stage. High performance systems require better understanding of system sensitivities much earlier in the design process to meet these goals. The knowledge, skills, intuition, and experience of an individual design engineer will need to be extended significantly for the next generation of aerospace system designs. Then a collaborative effort involving the designer, rapid and reliable analysis tools and virtual experts will result in advanced aerospace systems that are safe, reliable, and efficient. This paper discusses the evolution, status, needs and directions for rapid modeling and analysis tools for structural analysis. First, the evolution of computerized design and analysis tools is briefly described. Next, the status of representative design and analysis tools is described along with a brief statement on their functionality. Then technology advancements to achieve rapid modeling and analysis are identified. Finally, potential future directions including possible prototype configurations are proposed.

Knight, Norman F., Jr.↗

The IPAC Image Subtraction and Discovery Pipeline for the Intermediate Palomar Transient Factory

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by approximately equal to 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of approximately equal to 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

methods: analytical – methods: data analysis –↗

Forced response testing of an axi-centrifugal turboshaft engine

Dynamic data from tests of a T55-L-712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗

Forced Response Testing of an Axi-Centrifugal Turboshaft Engine

Dynamic data from tests of a T55-L,712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗

CASIS Fact Sheet: Hardware and Facilities

Vencore is a proven information solutions, engineering, and analytics company that helps our customers solve their most complex challenges. For more than 40 years, we have designed, developed and delivered mission-critical solutions as our customers' trusted partner. The Engineering Services Contract, or ESC, provides engineering and design services to the NASA organizations engaged in development of new technologies at the Kennedy Space Center. Vencore is the ESC prime contractor, with teammates that include Stinger Ghaffarian Technologies, Sierra Lobo, Nelson Engineering, EASi, and Craig Technologies. The Vencore team designs and develops systems and equipment to be used for the processing of space launch vehicles, spacecraft, and payloads. We perform flight systems engineering for spaceflight hardware and software; develop technologies that serve NASA's mission requirements and operations needs for the future. Our Flight Payload Support (FPS) team at Kennedy Space Center (KSC) provides engineering, development, and certification services as well as payload integration and management services to NASA and commercial customers. Our main objective is to assist principal investigators (PIs) integrate their science experiments into payload hardware for research aboard the International Space Station (ISS), commercial spacecraft, suborbital vehicles, parabolic flight aircrafts, and ground-based studies. Vencore's FPS team is AS9100 certified and a recognized implementation partner for the Center for Advancement of Science in Space (CASIS

Solomon, Michael R.↗

Generative engineering databases - Toward expert systems

Engineering data management, incorporating concepts of optimization with data representation, is receiving increasing attention as the amount and complexity of information necessary for performing engineering operations increases and the need to coordinate its representation and use increases. Research in this area promises advantages for a wide variety of engineering applications, particularly those which seek to use data in innovative ways in the engineering process. This paper presents a framework for a comprehensive, relational database management system that combines a knowledge base of design constraints with a database of engineering data items in order to achieve a 'generative database' - one which automatically generates new engineering design data according to the design constraints stored in the knowledge base. The representation requires a database that is able to store all of the data normally associated with engineering design and to accurately represent the interactions between constraints and the stored data while guaranteeing its integrity. The representation also requires a knowledge base that is able to store all the constraints imposed upon the engineering design process.

Rasdorf, W. J.↗

Automation of Shuttle Tile Inspection - Engineering methodology for Space Station

The Space Systems Integration and Operations Research Applications (SIORA) Program was initiated in late 1986 as a cooperative applications research effort between Stanford University, NASA Kennedy Space Center, and Lockheed Space Operations Company. One of the major initial SIORA tasks was the application of automation and robotics technology to all aspects of the Shuttle tile processing and inspection system. This effort has adopted a systems engineering approach consisting of an integrated set of rapid prototyping testbeds in which a government/university/industry team of users, technologists, and engineers test and evaluate new concepts and technologies within the operational world of Shuttle. These integrated testbeds include speech recognition and synthesis, laser imaging inspection systems, distributed Ada programming environments, distributed relational database architectures, distributed computer network architectures, multimedia workbenches, and human factors considerations.

Wiskerchen, M. J.↗

The Montana ALE (Autonomous Lunar Excavator) Systems Engineering Report

On May 2 1-26, 20 12, the third annual NASA Lunabotics Mining Competition will be held at the Kennedy Space Center in Florida. This event brings together student teams from universities around the world to compete in an engineering challenge. Each team must design, build and operate a robotic excavator that can collect artificial lunar soil and deposit it at a target location. Montana State University, Bozeman, is one of the institutions selected to field a team this year. This paper will summarize the goals of MSU's lunar excavator project, known as the Autonomous Lunar Explorer (ALE), along with the engineering process that the MSU team is using to fulfill these goals, according to NASA's systems engineering guidelines.

Lars Osborne↗

Stage Separation Performance Analysis Project

Stage separation process is an important phenomenon in multi-stage launch vehicle operation. The transient flowfield coupled with the multi-body systems is a challenging problem in design analysis. The thermodynamics environment with burning propellants during the upper-stage engine start in the separation processes adds to the complexity of the-entire system. Understanding the underlying flow physics and vehicle dynamics during stage separation is required in designing a multi-stage launch vehicle with good flight performance. A computational fluid dynamics model with the capability to coupling transient multi-body dynamics systems will be a useful tool for simulating the effects of transient flowfield, plume/jet heating and vehicle dynamics. A computational model using generalize mesh system will be used as the basis of this development. The multi-body dynamics system will be solved, by integrating a system of six-degree-of-freedom equations of motion with high accuracy. Multi-body mesh system and their interactions will be modeled using parallel computing algorithms. Adaptive mesh refinement method will also be employed to enhance solution accuracy in the transient process.

Chen, Yen-Sen↗

NEXT Single String Integration Tests in Support of the Double Asteroid Redirection Test Mission

A system integration test has been performed utilizing a prototype model NEXT ion thruster, an engineering model power processing unit, and a laboratory model command and data handling system. The objectives of the test were to: a) verify that the integrated system meets performance requirements, b) demonstrate that the integrated system is functional across the anticipated thermal, power processor, and Xe propellant ranges for the DART mission, and to c) evaluate fault detection and operation of the command and data handling system. Measurements made during this test included: thruster performance, PPU input voltages, PPU electrical and thermal telemetry, software states, and fault flags. Additionally, a far-field electrostatic probe diagnostic was used to infer relative changes in the thrust vector across the various propellant flow splits. This manuscript presents the results of these tests, which include integrated ion propulsion system demonstrations of performance, details on the execution of DART flight algorithms, and software fault handling.

Thomas, Robert E.↗

NEXT Single String Integration Tests in Support of the Double Asteroid Redirection Test Mission

A system integration test has been performed utilizing a prototype model NEXT ion thruster, an engineering model power processing unit, and a laboratory model command and data handling system. The objectives of the test were to: a) verify that the integrated system meets performance requirements, b) demonstrate that the integrated system is functional across the anticipated thermal, power processor, and Xe propellant ranges for the DART mission, and to c) evaluate fault detection and operation of the command and data handling system. Measurements made during this test included: thruster performance, PPU input voltages, PPU electrical and thermal telemetry, software states, and fault flags. Additionally, a far-field electrostatic probe diagnostic was used to infer relative changes in the thrust vector across the various propellant flow splits. This manuscript presents the results of these tests, which include integrated ion propulsion system demonstrations of performance, details on the execution of DART flight algorithms, and software fault handling.

Thomas, Robert↗

Development of a NASA Integrated Technical Workforce Career Development Model Entitled Requisite Occupation Competencies and Knowledge -- the ROCK

This paper shares the findings of NASA's Integrated Learning and Development Program (ILDP) in its effort to reinvigorate the HANDS-ON practice of space systems engineering and project/program management through focused coursework, training opportunities, on-the job learning and special assignments. Prior to March 2005, NASA responsibility for technical workforce development (the program/project manager, systems engineering, discipline engineering, discipline engineering and associated communities) was executed by two parallel organizations. In March 2005 these organizations merged. The resulting program-ILDP-was chartered to implement an integrated competency-based development model capable of enhancing NASA's technical workforce performance as they face the complex challenges of Earth science, space science, aeronautics and human spaceflight missions. Results developed in collaboration with NASA Field Centers are reported on. This work led to definition of the agency's first integrated technical workforce development model known as the Requisite Occupation Competence and Knowledge (the ROCK). Critical processes and products are presented including: 'validation' techniques to guide model development, the Design-A-CUrriculuM (DACUM) process, and creation of the agency's first systems engineering body-of-knowledge. Findings were validated via nine focus groups from industry and government, validated with over 17 space-related organizations, at an estimated cost exceeding $300,000 (US). Masters-level programs and training programs have evolved to address the needs of these practitioner communities based upon these results. The ROCK reintroduced rigor and depth to the practitioner's development in these critical disciplines enabling their ability to take mission concepts from imagination to reality.

Menrad, Robert J.↗