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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Determination of the position of Jupiter from radio metric tracking of Voyager 1

The Voyager 1 spacecraft flew by Jupiter on March 5, 1979. Spacecraft navigation was performed with radio tracking data from NASA's Deep Space Network. In the years since then, there has been a great deal of progress in the definition of celestial reference frames and in determining the orbit and orientation of the Earth. Using these improvements, the radio metric range and Doppler data acquired from the Voyager 1 spacecraft near its encounter with Jupiter have been reanalyzed to determine the plane-of-sky position of Jupiter with much greater accuracy than was possible at the time of the encounter. The position of Jupiter at the time of encounter has been determined with an accuracy of 40 nrad in right ascension and 140 nrad in declination with respect to the celestial reference frame defined by the International Earth Rotation Service. This position estimate has been done to improve the ephemeris of Jupiter prior to the upcoming encounter of the Galileo spacecraft with Jupiter.

Folkner, W. M.↗
NASA NTRS1993

Development of a Computer Program for Analyzing Preliminary Aircraft Configurations in Relationship to Emerging Agility Metrics

This paper discusses the development of a FORTRAN computer code to perform agility analysis on aircraft configurations. This code is to be part of the NASA-Ames ACSYNT (AirCraft SYNThesis) design code. This paper begins with a discussion of contemporary agility research in the aircraft industry and a survey of a few agility metrics. The methodology, techniques and models developed for the code are then presented. Finally, example trade studies using the agility module along with ACSYNT are illustrated. These trade studies were conducted using a Northrop F-20 Tigershark aircraft model. The studies show that the agility module is effective in analyzing the influence of common parameters such as thrust-to-weight ratio and wing loading on agility criteria. The module can compare the agility potential between different configurations. In addition, one study illustrates the module's ability to optimize a configuration's agility performance.

Bauer, Brent↗
NASA NTRS1996

Sonic Boom Ocean Penetration: Noise Metric Comparison and Initial Focusing Results

The purpose of the present research is to determine the impact by sonic boom noise penetration into the ocean. Since the 1994 LaRC High Speed Research Program Sonic Boom Workshop several new results have been obtained. This talk reviews these results, and emphasizes the two most important findings. The first major result is an improved understanding of the noise spectra of the penetrating sonic boom. It was determined that weighted sound exposure levels decrease with deeper ocean depths significantly faster than unweighted sound exposure levels. This is because low frequencies penetrate the ocean deeper than high frequencies. Several noise metrics were used including peak, SEL, C-SEL, A-SEL, and PLdB, and results are given for all. These results are important because they show that the sonic boom noise impact on marine life a few meters below the ocean surface may be significantly lower using weighted sound levels than if one were to measure the impact using unweighted levels. The other major finding is the first estimate of the worst case peak levels produced by a penetrating sonic boom being focused by a sinusoidal ocean surface. The method of analysis chosen was computational, a time domain finite difference algorithm. The method is outlined and then example results are presented. For rounded sonic boom waveforms incident on a sinusoidal ocean surface, it is shown that the percentage increase or decrease in pressure is only occasionally larger than 10%, rarely 25%. These fluctuations indicate, under the assumptions already given, that any increase or decrease in sound level underwater due to focusing or defocusing should be small, less than 3 dB.

Sparrow, Victor W.↗
NASA NTRS1998

Reuse Metrics for Object Oriented Software

One way to increase the quality of software products and the productivity of software development is to reuse existing software components when building new software systems. In order to monitor improvements in reuse, the level of reuse must be measured. In this NASA supported project we (1) derived a suite of metrics which quantify reuse attributes for object oriented, object based, and procedural software, (2) designed prototype tools to take these measurements in Ada, C++, Java, and C software, (3) evaluated the reuse in available software, (4) analyzed the relationship between coupling, cohesion, inheritance, and reuse, (5) collected object oriented software systems for our empirical analyses, and (6) developed quantitative criteria and methods for restructuring software to improve reusability.

Bieman, James M.↗
NASA NTRS1997

A Metric to Evaluate Mobile Satellite Systems

The concept of a "cost per billable minute" methodology to analyze mobile satellite systems is reviewed. Certain assumptions, notably those about the marketplace and regulatory policies, may need to be revisited. Fading and power control assumptions need to be tested. Overall, the metric would seem to have value in the design phase of a system and for comparisons between and among alternative systems.

Young, Elizabeth L.↗
NASA NTRS1998

Development of Technology Transfer Economic Growth Metrics

The primary objective of this project is to determine the feasibility of producing technology transfer metrics that answer the question: Do NASA/MSFC technical assistance activities impact economic growth? The data for this project resides in a 7800-record database maintained by Tec-Masters, Incorporated. The technology assistance data results from survey responses from companies and individuals who have interacted with NASA via a Technology Transfer Agreement, or TTA. The goal of this project was to determine if the existing data could provide indications of increased wealth. This work demonstrates that there is evidence that companies that used NASA technology transfer have a higher job growth rate than the rest of the economy. It also shows that the jobs being supported are jobs in higher wage SIC codes, and this indicates improvements in personal wealth. Finally, this work suggests that with correct data, the wealth issue may be addressed.

Mastrangelo, Christina M.↗
NASA NTRS1995

Object-Oriented Software Metrics for Predicting Reusability and Estimating Size

As object-oriented software development methods come into more widespread use, basic questions of software quality assurance must be reconsidered. We will highlight efforts now underway at NASA's Jet Propulsion Laboratory to both assess the quality of software systems developed using object oriented technology and develop guidelines for future development of such systems. The current focus is on design and code reusability., and system size estimation. A number of metrics are proposed and two software systems measured and analyzed. The preliminary results reported here should be useful to software development and quality assurance personnel working in C++ implementation environment.

Sanderson, D. Peter↗
NASA NTRS1999

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Mog, Robert A.↗
NASA NTRS1995

Metrics and Benchmarks for Visualization

What is a "good" visualization? How can the quality of a visualization be measured? How can one tell whether one visualization is "better" than another? I claim that the true quality of a visualization can only be measured in the context of a particular purpose. The same image generated from the same data may be excellent for one purpose and abysmal for another. A good measure of visualization quality will correspond to the performance of users in accomplishing the intended purpose, so the "gold standard" is user testing. As a user of visualization software (or at least a consultant to such users) I don't expect visualization software to have been tested in this way for every possible use. In fact, scientific visualization (as distinct from more "production oriented" uses of visualization) will continually encounter new data, new questions and new purposes; user testing can never keep up. User need software they can trust, and advice on appropriate visualizations of particular purposes. Considering the following four processes, and their impact on visualization trustworthiness, reveals important work needed to create worthwhile metrics and benchmarks for visualization. These four processes are (1) complete system testing (user-in-loop), (2) software testing, (3) software design and (4) information dissemination. Additional information is contained in the original extended abstract.

Uselton, Samuel P.↗
NASA NTRS2002

Alternative Metrics for Evaluating the Resilence of Advanced Life Support Systems

Ensuring the safety of the crew is a key performance requirement of a life support system. However, a number of conceptual and practical difficulties arise when devising metrics to concretely measure the ability of a life support system to maintain critical functions in the presence of anticipated and unanticipated faults. Resilience is a dynamic property of a life support system that depends on the complex interactions between faults, controls and system hardware. We review some of the approaches to understanding the robustness or resilience of complex systems being developed in diverse fields such as ecology, software engineering and cell biology and discuss their applicability to regenerative life support systems. We also consider how approaches to measuring resilience vary depending on system design choices such as the definition and choice of the nominal operating regime. Finally, we explore data collection and implementation issues such as the key differences between the instantaneous or conditional and average or overall measures of resilience. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data are used to consider alternative measures of resilience as predictors of the system's ability to recover from component-level faults.

Bell, Ann Maria↗
NASA NTRS2003

Using Technology Readiness Level (TRL), Life Cycle Cost (LCC), and Other Metrics to Supplement Equivalent System Mass (ESM) in Advanced Life Support (ALS)

The ALS project plan goals are reducing cost, improving performance, and achieving flight readiness. ALS selects projects to advance the mission readiness of low cost, high performance technologies. The role of metrics is to help select good projects and report progress. The Equivalent Mass (EM) of a system is the sum of the estimated mass of the hardware, of its required materials and spares, and of the pressurized volume, power supply, and cooling system needed to support the hardware in space. EM is the total payload launch mass needed to provide and support a system. EM is directly proportional to the launch cost.

Jones, Harry↗
NASA NTRS2005

Metrics for More than Two Points at Once

The conventional definition of a topological metric over a space specifies properties that must be obeyed by any measure of "how separated" two points in that space are. Here it is shown how to extend that definition, and in particular the triangle inequality, to concern arbitrary numbers of points. Such a measure of how separated the points within a collection are can be bootstrapped, to measure "how separated" from each other are two (or more) collections. The measure presented here also allows fractional membership of an element in a collection. This means it directly concerns measures of "how spread out" a probability distribution over a space is. When such a measure is bootstrapped to compare two collections, it allows us to measure how separated two probability distributions are, or more generally, how separated a distribution of distributions is.

Wolpert, David H.↗
NASA NTRS2005

Cognition in Space Workshop: Metrics and Models - 1

"Cognition in Space Workshop I: Metrics and Models" was the first in a series of workshops sponsored by NASA to develop an integrated research and development plan supporting human cognition in space exploration. The workshop was held in Chandler, Arizona, October 25-27, 2004. The participants represented academia, government agencies, and medical centers. This workshop addressed the following goal of the NASA Human System Integration Program for Exploration: to develop a program to manage risks due to human performance and human error, specifically ones tied to cognition. Risks range from catastrophic error to degradation of efficiency and failure to accomplish mission goals. Cognition itself includes memory, decision making, initiation of motor responses, sensation, and perception. Four subgoals were also defined at the workshop as follows: (1) NASA needs to develop a human-centered design process that incorporates standards for human cognition, human performance, and assessment of human interfaces; (2) NASA needs to identify and assess factors that increase risks associated with cognition; (3) NASA needs to predict risks associated with cognition; and (4) NASA needs to mitigate risk, both prior to actual missions and in real time. This report develops the material relating to these four subgoals.

Woolford, Barbara↗
NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗
NASA NTRS2003

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.↗
NASA NTRS2007

A New Sea Ice Model: Pancakes to Metrics

We are developing, testing, and validating a new sea ice dynamics model that treats the ice cover as an elastic/decohesive material in the permanent pack and includes the correct frazil/pancake behavior in the marginal zone. Two salient features of present ice dynamics models are that they do not: 1) reproduce the oriented fracture patterns of openings and closings in the pack ice, and 2) accurately model the effects of frazil/pancake ice formation in the ice margin. These poorly modeled areas account for a substantial portion of the ice growth, turbulent heat flux to the atmosphere, salt flux to the ocean, and energy dissipation due to slippage, ridging, and rafting, in the Arctic. Existing sea ice models have shown limited success in predicting the degree to which a lead will open for prescribed or observed forcing conditions. An important aspect of the new model we are developing is that the existence of cracks, along with their orientation, opening, and closing, is predicted. To put this effort in perspective a short history of ice dynamics modeling and data collection is presented. The RGPS data set is used to validate the model. As part of the testing and validation of the model, we are working on a new metric for comparing linear features (leads and ridges) in the data and model to be used in data assimilation for this model. The model framework is presented as well as some results showing the creation and development of leads in a simulation of ice dynamics in the Beaufort Sea. Other presentations by the authors will show other results from this effort.

Coon, M.↗