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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 775 records · Page 43

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Alston, D. W.↗

Steady-state fuel performance analyses for the preliminary fuel concept of general atomics fast modular reactor

Here this manuscript presents the fuel performance analysis results of the General Atomics Fast Modular Reactor (FMR) based on an axi-symmetric (2D-RZ) geometry. Three fuel performance model sets that fit the FMR fuel specifications best, i.e., a BISON baseline model set, a BISON diffusion enhancement model set, and a BISON-FASTGRASS model set, were identified and evaluated against a series of relevant experimental cases featuring high burnup and low irradiation temperature conditions. The three BISON-based model sets were then utilized to conduct a comprehensive fuel performance analysis of the FMR fuel under normal operation including the shutdown/restarting periods for refueling. The evaluation of the fuel performance parameters, represented by temperature, internal pressure, stress, and strain, shows that the FMR fuel maintains its thermal and mechanical integrity during normal operation. Technology gaps and limitations are also discussed to guide future efforts for extending the performance analysis to transient scenarios as well as improving the fuel performance evaluation through experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparative analysis of techniques for evaluating the effectiveness of aircraft computing systems

Performability analysis is a technique developed for evaluating the effectiveness of fault-tolerant computing systems in multiphase missions. Performability was evaluated for its accuracy, practical usefulness, and relative cost. The evaluation was performed by applying performability and the fault tree method to a set of sample problems ranging from simple to moderately complex. The problems involved as many as five outcomes, two to five mission phases, permanent faults, and some functional dependencies. Transient faults and software errors were not considered. A different analyst was responsible for each technique. Significantly more time and effort were required to learn performability analysis than the fault tree method. Performability is inherently as accurate as fault tree analysis. For the sample problems, fault trees were more practical and less time consuming to apply, while performability required less ingenuity and was more checkable. Performability offers some advantages for evaluating very complex problems.

Hitt, E. F.↗

Approaches to Cycle Analysis and Performance Metrics

The following notes were prepared as part of an American Institute of Aeronautics and Astronautics (AIAA) sponsored short course entitled Air Breathing Pulse Detonation Engine (PDE) Technology. The course was presented in January of 2003, and again in July of 2004 at two different AIAA meetings. It was taught by seven instructors, each of whom provided information on particular areas of PDE research. These notes cover two areas. The first is titled Approaches to Cycle Analysis and Performance Metrics. Here, the various methods of cycle analysis are introduced. These range from algebraic, thermodynamic equations, to single and multi-dimensional Computational Fluid Dynamic (CFD) solutions. Also discussed are the various means by which performance is measured, and how these are applied in a device which is fundamentally unsteady. The second topic covered is titled PDE Hybrid Applications. Here the concept of coupling a PDE to a conventional turbomachinery based engine is explored. Motivation for such a configuration is provided in the form of potential thermodynamic benefits. This is accompanied by a discussion of challenges to the technology.

Parson, Daniel E.↗

Computational Reproducibility of Scientific Workflows at Extreme Scales

We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use cases: scientific reproducibility of results in the ACME climate simulations and performance reproducibility in molecular dynamics workflows on HPC computing platforms.

provenance, Reproducibility, Climate & Earth Syste↗

Subsonic wind-tunnel performance

Analysis of conditional sampling averages for turbulent flows shows how conditional averages can be related to conventional averages incorporated into existing flow models. Technique allows vast quantities of data generated by conditional sampling to be analyzed in coherent way.

Eckert, W. T.↗

Quantitative Electroluminescence Imaging Analysis for Performance Estimation of PID-Influenced PV Modules

An empirical method for estimating relative power losses caused by potential-induced degradation (PID) for p-type solar cells and modules using quantitative electroluminescence (EL) analysis (QELA) is presented. First, EL images are corrected for camera- and perspective distortion. The relative power loss map is then calculated from the logarithmic ratio of two EL images, taken either before and after PID degradation or at different applied currents. Only the cell average of the resulting power loss map is evaluated. The highest power loss across each string is averaged to obtain the overall power loss. Consequently, for modules with three strings, three cells are averaged. The resulting power loss depends on the current applied. The conversion to equivalent irradiance allows for comparison of measured and estimated device performance. The analysis of roughly 2000 EL images and related current-voltage (I-V) curves indicates a good agreement between flash-test-measured and performance estimated using QELA. A relative root mean square error of 1-3% can be achieved.

14 SOLAR ENERGY↗

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗

High-performance parallel analysis of coupled problems for aircraft propulsion

Applications are described of high-performance parallel, computation for the analysis of complete jet engines, considering its multi-discipline coupled problem. The coupled problem involves interaction of structures with gas dynamics, heat conduction and heat transfer in aircraft engines. The methodology issues addressed include: consistent discrete formulation of coupled problems with emphasis on coupling phenomena; effect of partitioning strategies, augmentation and temporal solution procedures; sensitivity of response to problem parameters; and methods for interfacing multiscale discretizations in different single fields. The computer implementation issues addressed include: parallel treatment of coupled systems; domain decomposition and mesh partitioning strategies; data representation in object-oriented form and mapping to hardware driven representation, and tradeoff studies between partitioning schemes and fully coupled treatment.

Felippa, C. A.↗

Performance requirements analysis for payload delivery from a space station

Operations conducted from a space station in low Earth orbit which have different constraints and opportunities than those conducted from direct Earth launch were examined. While a space station relieves many size and performance constraints on the space shuttle, the space station's inertial orbit has different launch window constraints from those associated with customary Earth launches which reflect upon upper stage capability. A performance requirements analysis was developed to provide a reference source of parametric data, and specific case solutions and upper stage sizing trade to assist potential space station users and space station and upper stage developers assess the impacts of a space station on missions of interest.

Friedlander, A. L.↗

The Development of a Handbook for Astrobee F Performance and Stability Analysis

An astrobee F performance and stability analysis is presented, for use by the NASA Sounding Rocket Division. The performance analysis provides information regarding altitude, mach number, dynamic pressure, and velocity as functions of time since launch. It is found that payload weight has the greatest effect on performance, and performance prediction accuracy was calculated to remain within 1%. In addition, to assure sufficient flight stability, a predicted rigid-body static margin of at least 8% of the total vehicle length is required. Finally, fin cant angle predictions are given in order to achieve a 2.5 cycle per second burnout roll rate, based on obtaining 75% of the steady roll rate. It is noted that this method can be used by flight performance engineers to create a similar handbook for any sounding rocket series.

Wolf, R. S.↗

RF coverage analysis and performance for Shuttle communication links

This paper describes the current work at NASA/Johnson Space Center in the area of RF coverage analysis and performance-assessment for the Space Shuttle Program communication and tracking radio links. Trajectories, antenna data, ground station and Shuttle hardware performance characteristics and RF link math models were assimilated to generate RF link performance predictions for the three basic mission phases - ascent, on-orbit, and descent. Results identify some earlier deficiencies that required re-configuration of the ground station. Overall performance is currently satisfactory.

Loh, Y.-C.↗

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

Schlagheck, R. A.↗

Near-term hybrid vehicle program, phase 1. Appendix A: Mission analysis and performance specification studies report

Results of a study leading to the preliminary design of a five passenger hybrid vehicle utilizing two energy sources (electricity and gasoline/diesel fuel) to minimize petroleum usage on a fleet basis are presented. The study methodology is described. Vehicle characterizations, the mission description, characterization, and impact on potential sales, and the rationale for the selection of the reference internal combustion engine vehicle are presented. Conclusions and recommendations of the mission analysis and performance specification report are included.

Source record↗

Mini-apps for high performance data analysis

Scaling-up scientific data analysis and machine learning algorithms for data-driven discovery is a grand challenge that we face today. Despite the growing need for analysis from science domains that are generating `Big Data' from instruments and simulations, building high-performance analytical workflows of data-intensive algorithms have been daunting because: (i) the `Big Data' hardware and software architecture landscape is constantly evolving, (ii) newer architectures impose new programming models, and (iii) data-parallel kernels of analysis algorithms and their performance facets on different architectures are poorly understood. To address these problems, we have: (i) identified scalable data-parallel kernels of popular data analysis algorithms, (ii) implemented `Mini-Apps' of those kernels using different programming models (e.g. Map Reduce, MPI, etc.), (iii) benchmarked and validated the performance of the kernels in diverse architectures. In this paper, we discuss two of those Mini-Apps and show the execution of principal component analysis built as a workflow of the Mini-Apps. We show that Mini-Apps enable scientists to (i) write domain-specific data analysis code that scales on most HPC hardware and (ii) and offers the ability (most times with over a 10x speed-up) to analyze data sizes 100 times the size of what off-the-shelf desktop/workstations of today can handle.

Sukumar, Sreenivas R.↗