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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Nashman, Marilyn↗
NASA NTRS2003

Small Aircraft Transportation System Simulation Analysis of the HVO and ERO Concepts

It is acknowledged that the aviation and aerospace industries are primary forces influencing the industrial development and economic well being of the United States and many countries around the world. For decades the US national air transportation system has been the model of success - safely and efficiently moving people, cargo, goods and services and generating countless benefits throughout the global community; however, the finite nature of the system and many of its components is becoming apparent. Without measurable increases in the capacity of the national air transportation system, delays and service delivery failures will eventually become intolerable. Although the recent economic slowdown has lowered immediate travel demands, that trend is reversing and cargo movement remains high. Research data indicates a conservative 2.5-3.0% annual increase in aircraft operations nationwide through 2017. Such growth will place additional strains upon a system already experiencing capacity constraints. The stakeholders of the system will continue to endure ever-increasing delays and abide lesser levels of service to many lower population density areas of the country unless more efficient uses of existing and new transportation resources are implemented. NASA s Small Aircraft Transportation System program (SATS) is one of several technologies under development that are aimed at using such resources more effectively. As part of this development effort, this report is the first in a series outlining the findings and recommendations resulting from a comprehensive program of multi-level analyses and system engineering efforts undertaken by NASA Langley Research Center s Systems Analysis Branch (SAB). These efforts are guided by a commitment to provide systems-level analysis support for the SATS program. Subsequent efforts will build upon this early work to produce additional analyses and benefits studies needed to provide the technical and economic basis for national investment and policy decisions related to further development and potential deployment of a small aircraft transportation system. This report primarily serves two purposes. First, it presents results attained from an initial evaluation and analysis of the Higher Volume Operations (HVO) and EnRoute Operations (ERO) concepts - both designated operational capabilities within the SATS Program s Concept of Operations (CONOPS) document. It further outlines areas of the concepts that would benefit from follow-on analyses and system engineering efforts. It is intended that these processes will aid continued maturation of the concepts and promote additional studies of their effects and influences in combination with other designated CONOPS currently under development. In essence, it establishes a baseline of data upon which subsequent analyses and studies can be built and identifies performance characteristics the concept must exhibit in order to provide, at minimum, levels of safety and usage equal to or better than the current system.

Millsaps, Gary D.↗
NASA NTRS2013

Towards Requirements in Systems Engineering for Aerospace IVHM Design

Health management (HM) technologies have been employed for safety critical system for decades, but a coherent systematic process to integrate HM into the system design is not yet clear. Consequently, in most cases, health management resorts to be an after-thought or 'band-aid' solution. Moreover, limited guidance exists for carrying out systems engineering (SE) on the subject of writing requirements for designs with integrated vehicle health management (IVHM). It is well accepted that requirements are key to developing a successful IVHM system right from the concept stage to development, verification, utilization, and support. However, writing requirements for systems with IVHM capability have unique challenges that require the designers to look beyond their own domains and consider the constraints and specifications of other interlinked systems. In this paper we look at various stages in the SE process and identify activities specific to IVHM design and development. More importantly, several relevant questions are posed that system engineers must address at various design and development stages. Addressing these questions should provide some guidance to systems engineers towards writing IVHM related requirements to ensure that appropriate IVHM functions are built into the system design.

Requirements↗
NASA NTRS2013

SpaceCube Version 1.5

SpaceCube 1.5 is a high-performance and low-power system in a compact form factor. It is a hybrid processing system consisting of CPU (central processing unit), FPGA (field-programmable gate array), and DSP (digital signal processor) processing elements. The primary processing engine is the Virtex- 5 FX100T FPGA, which has two embedded processors. The SpaceCube 1.5 System was a bridge to the SpaceCube 2.0 and SpaceCube 2.0 Mini processing systems. The SpaceCube 1.5 system was the primary avionics in the successful SMART (Small Rocket/Spacecraft Technology) Sounding Rocket mission that was launched in the summer of 2011. For SMART and similar missions, an avionics processor is required that is reconfigurable, has high processing capability, has multi-gigabit interfaces, is low power, and comes in a rugged/compact form factor. The original SpaceCube 1.0 met a number of the criteria, but did not possess the multi-gigabit interfaces that were required and is a higher-cost system. The SpaceCube 1.5 was designed with those mission requirements in mind. The SpaceCube 1.5 features one Xilinx Virtex-5 FX100T FPGA and has excellent size, weight, and power characteristics [4×4×3 in. (approx. = 10×10×8 cm), 3 lb (approx. = 1.4 kg), and 5 to 15 W depending on the application]. The estimated computing power of the two PowerPC 440s in the Virtex-5 FPGA is 1100 DMIPS each. The SpaceCube 1.5 includes two Gigabit Ethernet (1 Gbps) interfaces as well as two SATA-I/II interfaces (1.5 to 3.0 Gbps) for recording to data drives. The SpaceCube 1.5 also features DDR2 SDRAM (double data rate synchronous dynamic random access memory); 4- Gbit Flash for storing application code for the CPU, FPGA, and DSP processing elements; and a Xilinx Platform Flash XL to store FPGA configuration files or application code. The system also incorporates a 12 bit analog to digital converter with the ability to read 32 discrete analog sensor inputs. The SpaceCube 1.5 design also has a built-in accelerometer. In addition, the system has 12 receive and transmit RS- 422 interfaces for legacy support. The SpaceCube 1.5 processor card represents the first NASA Goddard design in a compact form factor featuring the Xilinx Virtex- 5. The SpaceCube 1.5 incorporates backward compatibility with the Space- Cube 1.0 form factor and stackable architecture. It also makes use of low-cost commercial parts, but is designed for operation in harsh environments.

Geist, Alessandro↗
NASA NTRS1981

Low cost solar aray project: Experimental process system development unit for producing semiconductor-grade silicon using the silane-to-silicon process

This phase consists of the engineering design, fabrication, assembly, operation, economic analysis, and process support R&D for an Experimental Process System Development Unit (EPSDU). The mechanical bid package was issued and the bid responses are under evaluation. Similarly, the electrical bid package was issued, however, responses are not yet due. The majority of all equipment is on order or has been received at the EPSDU site. The pyrolysis/consolidation process design package was issued. Preparation of process and instrumentation diagram for the free-space reactor was started. In the area of melting/consolidation, Kayex successfully melted chunk silicon and have produced silicon shot. The free-space reactor powder was successfully transported pneumatically from a storage bin to the auger feeder twenty-five feet up and was melted. The fluid-bed PDU has successfully operated at silane feed concentrations up to 21%. The writing of the operating manual has started. Overall, the design phase is nearing completion.

Source record↗
NASA NTRS1999

National Cycle Program (NCP) Common Analysis Tool for Aeropropulsion

Through the NASA/Industry Cooperative Effort (NICE) agreement, NASA Lewis and industry partners are developing a new engine simulation, called the National Cycle Program (NCP), which is the initial framework of NPSS. NCP is the first phase toward achieving the goal of NPSS. This new software supports the aerothermodynamic system simulation process for the full life cycle of an engine. The National Cycle Program (NCP) was written following the Object Oriented Paradigm (C++, CORBA). The software development process used was also based on the Object Oriented paradigm. Software reviews, configuration management, test plans, requirements, design were all apart of the process used in developing NCP. Due to the many contributors to NCP, the stated software process was mandatory for building a common tool intended for use by so many organizations. The U.S. aircraft and airframe companies recognize NCP as the future industry standard for propulsion system modeling.

Follen, G.↗
NASA NTRS1991

Structured prototyping as risk management

A methodology is presented for integrating the systems-engineering management recommendation of prototyping into the traditional project-management process for developing large-scale systems. The suggested methodology begins with the identification of life-cycle risk areas, outlines the structure and conduct of the prototyping process, and defines the composition of the prototyping team. The methodology includes a step-by-step procedure for creating, executing, and documenting a prototyping test plan to evaluate design alternatives. It is argued that managers who adopt this methodology and apply it rigorously will increase the likelihood that the systems they build will be operationally effective and will be accepted by the intended users.

Hornstein, Rhoda SH.↗
NASA NTRS2016

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↗
NASA NTRS1994

TARGET's role in knowledge acquisition, engineering, validation, and documentation

We investigate the use of the TARGET task analysis tool for use in the development of rule-based expert systems. We found TARGET to be very helpful in the knowledge acquisition process. It enabled us to perform knowledge acquisition with one knowledge engineer rather than two. In addition, it improved communication between the domain expert and knowledge engineer. We also found it to be useful for both the rule development and refinement phases of the knowledge engineering process. Using the network in these phases required us to develop guidelines that enabled us to easily translate the network into production rules. A significant requirement for TARGET remaining useful throughout the knowledge engineering process was the need to carefully maintain consistency between the network and the rule representations. Maintaining consistency not only benefited the knowledge engineering process, but also has significant payoffs in the areas of validation of the expert system and documentation of the knowledge in the system.

Levi, Keith R.↗
NASA NTRS2015

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↗
NASA NTRS1983

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.↗
NASA NTRS1993

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↗
NASA NTRSDate not supplied

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↗
NASA NTRS2002

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.↗
NASA NTRS2016

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 –↗
NASA NTRS1996

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↗
NASA NTRS1996

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↗