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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Studies of Model Immiscible Systems

The objectives are to use model transparent monotectics to obtain fundamental information applicable to two-phase systems in general, to apply this understanding to materials of interest in the Microgravity Science and Applications program, and to interpret results of flight experimental involving monotectic alloys. A number of model immiscible systems are in use to study various aspects of two-phase behavior within the miscibility gap and during solidification. Particle growth, coalescence and particle motions are under investigation using a holographic microscopy system. The system is capable of working with particle densities up to 10 to the 7th power particles/cubic centimeters through a 100 micron depth and can resolve particles of the order of 2 to 3 micron in diameter throughout the entire cell volume. Particle size, distribution changes with respect to time and temperature are observable from sequential holograms. Initial experiments using diethylene glycol/ethyl salicylate (DEG/ES) have demonstrated the usefulness of the technique. The thermal system controls temperature to at least plus or minus 0.001 K over the course of an experiment. A time-lapse film, made from holograms, of a succinonitrile/water solution shows particle size and number distribution changes with time under isothermal conditions. The observations are consistent with Ostwald ripening theory.

Frazier, D. O.↗
NASA NTRS2011

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Putnam, Williama↗
NASA NTRS2011

Vehicle System Management Modeling in UML for Ares I

The Spacecraft & Vehicle Systems Department of Marshall Space Flight Center is responsible for modeling the Vehicle System Management for the Ares I vehicle which was a part of the now canceled Constellation Program. An approach to generating the requirements for the Vehicle System Management was to use the Unified Modeling Language technique to build and test a model that would fulfill the Vehicle System Management requirements. UML has been used on past projects (flight software) in the design phase of the effort but this was the first attempt to use the UML technique from a top down requirements perspective.

Pearson, Newton W.↗
NASA NTRS1983

Divergence analysis report for the bodies of revolution model support systems

This report documents the sting divergence analyses of nine different model and model support systems that were performed in preparation for a series of wind tunnel tests at the National Transonic Facility at NASA Langley Research Center in Hampton, Virginia. The models were missile shaped bodies of revolution and the model support systems included a force and moment balance and tapered sting sections. The sting divergence results were obtained from a computer program that solved a two-point boundary value problem which used a second order Runge-Kutta integration technique. The computer solution was based on constant section properties between discrete stations along the sting sections, a procedure was developed and included to evaluate the properties for the minimum number of stations along the tapered sections that would produce no more than one half of one percent error in the divergence results. Also included in the report are development of the aerodynamic input data, listings of all input and output computer data, and summary sheets that highlight the input and the critical sting divergence dynamic pressure for each respective configuration.

Rash, Larry C.↗
NASA NTRS2016

NASA Systems Engineering Research Consortium: Defining the Path to Elegance in Systems

The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system exergy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modelling, System Robustness, and Value Modelling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.

Watson, Michael D.↗
NASA NTRS2016

NASA Systems Engineering Research Consortium: Defining the Path to Elegance in Systems

The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system energy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modeling, System Robustness, and Value Modeling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.

Watson, Michael D.↗
NASA NTRS1974

A wind-tunnel investigation of a B-52 model flutter suppression system

Flutter modeling techniques have been successfully extended to the difficult case of the active suppression of flutter. The demonstration was conducted in a transonic dynamics tunnel using a 1/30 scale, elastic, dynamic model of a Boeing B-52 control configured vehicle. The results from the study show that with the flutter suppression system operating there is a substantial increase in the damping associated with the critical flutter mode. The results also show good correlation between the damping characteristics of the model and the aircraft.

Redd, L. T.↗
NASA NTRS1988

Using a simulation assistant in modeling manufacturing systems

Numerous simulation languages exist for modeling discrete event processes, and are now ported to microcomputers. Graphic and animation capabilities were added to many of these languages to assist the users build models and evaluate the simulation results. With all these languages and added features, the user is still plagued with learning the simulation language. Futhermore, the time to construct and then to validate the simulation model is always greater than originally anticipated. One approach to minimize the time requirement is to use pre-defined macros that describe various common processes or operations in a system. The development of a simulation assistant for modeling discrete event manufacturing processes is presented. A simulation assistant is defined as an interactive intelligent software tool that assists the modeler in writing a simulation program by translating the modeler's symbolic description of the problem and then automatically generating the corresponding simulation code. The simulation assistant is discussed with emphasis on an overview of the simulation assistant, the elements of the assistant, and the five manufacturing simulation generators. A typical manufacturing system will be modeled using the simulation assistant and the advantages and disadvantages discussed.

Schroer, Bernard J.↗
NASA NTRS1992

A component modes projection and assembly model reduction methodology for articulated, multi-flexible body structures

A two-stage model reduction methodology, combining the classical Component Mode Synthesis (CMS) method and the newly developed Enhanced Projection and Assembly (EP&A) method is proposed in this research. The first stage of this methodology, called COmponent Mode Projection and Assembly model REduction (COMPARE) method, involves the generations of CMS mode sets, such as the MacNeal-Rubin mode sets. These mode sets are then used to reduce the order of each component model in the Rayleigh-Ritz sense. The resultant component models are then combined to generate reduced-order system models at various system configurations. A composite mode set which retains important system modes at all system configurations is then selected from these reduced-order system models. In the second stage, the EP&A model reduction method is employed to reduce further the order of the system model generated in the first stage. The effectiveness of the COMPARE methodology has been successfully demonstrated on a high-order, finite-element model of the cruise-configured Galileo spacecraft.

Lee, Allan Y.↗
NASA NTRS1993

A component modes projection and assembly model reduction methodology for articulated, multi-flexible body structures

A two-stage model reduction methodology, combining the classical Component Mode Synthesis (CMS) method and the newly developed Enhanced Projection and Assembly (EP&A) method, is proposed in this research. The first stage of this methodology, called the COmponent Modes Projection and Assembly model REduction (COMPARE) method, involves the generation of CMS mode sets, such as the MacNeal-Rubin mode sets. These mode sets are then used to reduce the order of each component model in the Rayleigh-Ritz sense. The resultant component models are then combined to generate reduced-order system models at various system configurations. A composite mode set which retains important system modes at all system configurations is then selected from these reduced-order system models. In the second stage, the EP&A model reduction method is employed to reduce further the order of the system model generated in the first stage. The effectiveness of the COMPARE methodology has been successfully demonstrated on a high-order, finite-element model of the cruise-configured Galileo spacecraft.

Lee, Allan Y.↗
NASA NTRS1992

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Pan, Jianqiang↗
NASA NTRS2005

Achieving control and interoperability through unified model-based systems and software engineering

Control and interoperation of complex systems is one of the most difficult challenges facing NASA's Exploration Systems Mission Directorate. An integrated but diverse array of vehicles, habitats, and supporting facilities, evolving over the long course of the enterprise, must perform ever more complex tasks while moving steadily away from the sphere of ground support and intervention.

control↗
NASA NTRS1991

Improved large perturbation propulsion models for control system design (1988-1989) and large perturbation models of high velocity propulsion systems (1989-1990) and reduced order propulsion models for control system design (1990-1991)

Methods for modeling high speed propulsion systems will be discussed. Included in this category are internal flow propulsion systems without rotating machinery, such as inlets, ramjets, and scramjets. Among the modeling topics discussed are modeling of linear isentropic flow, heat exchange, gasdynamics, lumped parameter systems, and infinite dimensional systems. Furthermore, a generalized overview of modeling high speed propulsion systems is presented in this collection of papers.

Hartley, Tom T.↗
NASA NTRS2016

Effort to Accelerate MBSE Adoption and Usage at JSC

This paper describes the authors' experience in adopting Model Based System Engineering (MBSE) at the NASA/Johnson Space Center (JSC). Since 2009, NASA/JSC has been applying MBSE using the Systems Modeling Language (SysML) to a number of advanced projects. Models integrate views of the system from multiple perspectives, capturing the system design information for multiple stakeholders. This method has allowed engineers to better control changes, improve traceability from requirements to design and manage the numerous interactions between components. As the project progresses, the models become the official source of information and used by multiple stakeholders. Three major types of challenges that hamper the adoption of the MBSE technology are described. These challenges are addressed by a multipronged approach that includes educating the main stakeholders, implementing an organizational infrastructure that supports the adoption effort, defining a set of modeling guidelines to help engineers in their modeling effort, providing a toolset that support the generation of valuable products, and providing a library of reusable models. JSC project case studies are presented to illustrate how the proposed approach has been successfully applied.

Wang, Lui↗
NASA NTRS1990

Projection and assembly method for multibody component model reduction

The problem addressed is that of obtaining reduced-order component models for use in simulating the dynamics of a multibody system. In certain cases, nonlinear system models may be constructed using linear dynamic models for each component, but allowing large angle motion between components. Without some form of model reduction, system models constructed in this manner may be too large for use in control system design and simulation trades. This paper analyzes one method of component model reduction that allows systems level requirements (e.g., capturing the effect of body 1 reaction wheel noise on body 2 camera pointing) to aid in the selection of the reduced-order component models. Briefly stated, important modes are selected at the system level and projected onto the components, and reduced-order components are then assembled into a reduced-order system model that retains the projected modes.

Bernard, Douglas E.↗