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At least 127 records · Page 7

Design and Analysis of V-Groove Passive Cryogenic Radiators for Space-borne Telescopes & Instruments

V-groove passive radiators are extremely efficient passive designs to thermally isolate a cryogenic telescope or instrument from warm environments in space, like the Sun, Earth, Moon or Spacecrafts. Compared to traditional multi-layer insulation blankets employed for thermal isolation, the V-Groove radiators provide as much as an order of magnitude improvement. The V-Groove design typically constitutes three low emissivity, lightweight and thin aluminized Mylar/Kapton sheets angled from each other by just few degrees. These successively reflect heat from warmer shields to space via their angular openings, thus minimizing heat flow into the cryogenic system. Thermal analysis of these V-Groove radiators is typically performed by sophisticated thermal software that uses hundreds of thousands of rays to simulate radiative heat flow between successive shields via reflections, which can be very time & resource intensive. We have arrived at very simple closed form equations to predict the thermal behavior of these radiators, that includes their radiative heat transfer factors and temperatures as a function of their basic thermo-optical properties and inter-shield angles. These predictions can be done by hand calculators or in spreadsheet tools like MS-Excel. They compare very well to those from sophisticated computer programs. The ease in the use of these simple equations allow for instantaneous predictions of cryogenic temperatures and their trends for design options and trade studies. A case study of this was utilized for the telescope project that is currently being designed for an all sky spectral survey of the universe. This paper will describe the derivations of these equations, their comparison with computer software results and their applicability for current and future cryogenic space telescope and instrument missions

Bhandari, Pradeep↗

Requirements-Driven Log Analysis Extended Abstract

Imagine that you are tasked to help a project improve their testing effort. In a realistic scenario it will quickly become clear, that having an impact is diffcult. First of all, it will likely be a challenge to suggest an alternative approach which is significantly more automated and/or more effective than current practice. The reality is that an average software system has a complex input/output behavior. An automated testing approach will have to auto-generate test cases, each being a pair (i; o) consisting of a test input i and an oracle o. The test input i has to be somewhat meaningful, and the oracle o can be very complicated to compute. Second, even in case where some testing technology has been developed that might improve current practice, it is then likely difficult to completely change the current behavior of the testing team unless the technique is obviously superior and does everything already done by existing technology. So is there an easier way to incorporate formal methods-based approaches than the full edged test revolution? Fortunately the answer is affirmative. A relatively simple approach is to benefit from possibly already existing logging infrastructure, which after all is part of most systems put in production. A log is a sequence of events, generated by special log recording statements, most often manually inserted in the code by the programmers. An event can be considered as a data record: a mapping from field names to values. We can analyze such a log using formal methods, for example checking it against a formal specification. This separates running the system for analyzing its behavior. It is not meant as an alternative to testing since it does not address the important in- put generation problem. However, it offers a solution which testing teams might accept since it has low impact on the existing process. A single person might be assigned to perform such log analysis, compared to the entire testing team changing behavior.

log analysis↗

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗

Computer Models Simulate Fine Particle Dispersion

Through a NASA Seed Fund partnership with DEM Solutions Inc., of Lebanon, New Hampshire, scientists at Kennedy Space Center refined existing software to study the electrostatic phenomena of granular and bulk materials as they apply to planetary surfaces. The software, EDEM, allows users to import particles and obtain accurate representations of their shapes for modeling purposes, such as simulating bulk solids behavior, and was enhanced to be able to more accurately model fine, abrasive, cohesive particles. These new EDEM capabilities can be applied in many industries unrelated to space exploration and have been adopted by several prominent U.S. companies, including John Deere, Pfizer, and Procter & Gamble.

Source record↗

Petri nets as a modeling tool for discrete concurrent tasks of the human operator

The basic concepts of Petri nets are reviewed as well as their application as the fundamental model of technical systems with concurrent discrete events such as hardware systems and software models of computers. The use of Petri nets is proposed for modeling the human operator dealing with concurrent discrete tasks. Their properties useful in modeling the human operator are discussed and practical examples are given. By means of and experimental investigation of binary concurrent tasks which are presented in a serial manner, the representation of human behavior by Petri nets is demonstrated.

Schumacher, W.↗

Computer-Aided Modeling and Analysis of Power Processing Systems (CAMAPPS), phase 1

The large-signal behaviors of a regulator depend largely on the type of power circuit topology and control. Thus, for maximum flexibility, it is best to develop models for each functional block a independent modules. A regulator can then be configured by collecting appropriate pre-defined modules for each functional block. In order to complete the component model generation for a comprehensive spacecraft power system, the following modules were developed: solar array switching unit and control; shunt regulators; and battery discharger. The capability of each module is demonstrated using a simplified Direct Energy Transfer (DET) system. Large-signal behaviors of solar array power systems were analyzed. Stability of the solar array system operating points with a nonlinear load is analyzed. The state-plane analysis illustrates trajectories of the system operating point under various conditions. Stability and transient responses of the system operating near the solar array's maximum power point are also analyzed. The solar array system mode of operation is described using the DET spacecraft power system. The DET system is simulated for various operating conditions. Transfer of the software program CAMAPPS (Computer Aided Modeling and Analysis of Power Processing Systems) to NASA/GSFC (Goddard Space Flight Center) was accomplished.

Kim, S.↗

Performance of Reynolds Averaged Navier-Stokes Models in Predicting Separated Flows: Study of the Hump Flow Model Problem

Separation can be seen in most aerodynamic flows, but accurate prediction of separated flows is still a challenging problem for computational fluid dynamics (CFD) tools. The behavior of several Reynolds Averaged Navier-Stokes (RANS) models in predicting the separated ow over a wall-mounted hump is studied. The strengths and weaknesses of the most popular RANS models (Spalart-Allmaras, k-epsilon, k-omega, k-omega-SST) are evaluated using the open source software OpenFOAM. The hump ow modeled in this work has been documented in the 2004 CFD Validation Workshop on Synthetic Jets and Turbulent Separation Control. Only the baseline case is treated; the slot flow control cases are not considered in this paper. Particular attention is given to predicting the size of the recirculation bubble, the position of the reattachment point, and the velocity profiles downstream of the hump.

Cappelli, Daniele↗

Staffing implications of software productivity models

The attributes of software project staffing and productivity implied by equating the effects of two popular software models in a small neighborhood of a given effort-duration point are investigated. The first model presupposes that organizational productivity decreases as a function of the project staff size due to interfacing and intercommunication. The second, the so-called software equation, relates the product size to effort and duration through a power law tradeoff formula. The conclusions that may be reached by assuming that both of these describe project behavior, the former as a global phenomenon and the latter as a localized effect in a small neighborhood of a given effort duration point, are that (1) there is a calculable maximum effective staff level, which, if exceeded, reduces the project production rate, (2) there is a calculable maximum extent to which effort and time may be traded effectively, (3) it becomes ineffective in a practical sense to expend more than an additional 25 to 50% of resources in order to reduce delivery time, and (4) the team production efficiency can be computed directly from the staff level, the slope of the intercommunication loss function, and the ratio of exponents in the software equation.

Tausworthe, R. C.↗

PIE: A Dynamic Failure-Based Technique

This paper presents a dynamic technique for statistically estimating three program characteristics that affect a program's computational behavior: (1) the probability that a particular section of a program is executed, (2) the probability that the particular section affects the data state, and (3) the probability that a data state produced by that section has an effect on program output. These three characteristics can be used to predict whether faults are likely to be uncovered by software testing. Index Terms: Software testing, data state, fault, failure, testability. 1 Introduction

Voas, Jeffrey M.↗

The role of reliability graph models in assuring dependable operation of complex hardware/software systems

The complexity of computer systems currently being designed for critical applications in the scientific, commercial, and military arenas requires the development of new techniques for utilizing models of system behavior in order to assure 'ultra-dependability'. The complexity of these systems, such as Space Station Freedom and the Air Traffic Control System, stems from their highly integrated designs containing both hardware and software as critical components. Reliability graph models, such as fault trees and digraphs, are used frequently to model hardware systems. Their applicability for software systems has also been demonstrated for software safety analysis and the analysis of software fault tolerance. This paper discusses further uses of graph models in the design and implementation of fault management systems for safety critical applications.

Patterson-Hine, F. A.↗

Person-like intelligent systems architectures for robotic shared control and automated operations

An approach to rendering robotic systems as 'personlike' as possible to achieve needed capabilities is outlined. Human characteristics such as knowledge, motivation, know-how, performance, achievement and individual differences corresponding to propensities and abilities can be supplied, within limits, with computing software and hardware to robotic systems provided with sufficiently rich sensory configurations. Pushing these limits is the developmental path for more and more personlike robotic systems. The portions of the Person Concept that appear to be most directly relevant to this effort are described in the following topics: reality concepts (the state-of-affairs system and descriptive formats, behavior as intentional action, individual persons (person characteristics), social patterns of behavior (social practices), and boundary conditions (status maxims). Personlike robotic themes and considerations for a technical development plan are also discussed.

Erickson, Jon D.↗

Improving Vacuum Cleaners

Under a Space Act Agreement between the Kirby company and Lewis Research Center, NASA technology was applied to a commercial vacuum cleaner product line. Kirby engineers were interested in advanced operational concepts, such as particle flow behavior and vibration, critical factors to improve vacuum cleaner performance. An evaluation of the company 1994 home care system, the Kirby G4, led to the refinement of the new G5 and future models. Under the cooperative agreement, Kirby had access to Lewis' holography equipment, which added insight into how long a vacuum cleaner fan would perform, as well as advanced computer software that can simulate the flow of air through fans. The collaboration resulted in several successes including fan blade redesign and continuing dialogue on how to improve air-flow traits in various nozzle designs.

Source record↗

Uncertainty Analysis for a Jet Flap Airfoil

An analysis of variance (ANOVA) study was performed to quantify the potential uncertainties of lift and pitching moment coefficient calculations from a computational fluid dynamics code, relative to an experiment, for a jet flap airfoil configuration. Uncertainties due to a number of factors including grid density, angle of attack and jet flap blowing coefficient were examined. The ANOVA software produced a numerical model of the input coefficient data, as functions of the selected factors, to a user-specified order (linear, 2-factor interference, quadratic, or cubic). Residuals between the model and actual data were also produced at each of the input conditions, and uncertainty confidence intervals (in the form of Least Significant Differences or LSD) for experimental, computational, and combined experimental / computational data sets were computed. The LSD bars indicate the smallest resolvable differences in the functional values (lift or pitching moment coefficient) attributable solely to changes in independent variable, given just the input data points from selected data sets. The software also provided a collection of diagnostics which evaluate the suitability of the input data set for use within the ANOVA process, and which examine the behavior of the resultant data, possibly suggesting transformations which should be applied to the data to reduce the LSD. The results illustrate some of the key features of, and results from, the uncertainty analysis studies, including the use of both numerical (continuous) and categorical (discrete) factors, the effects of the number and range of the input data points, and the effects of the number of factors considered simultaneously.

Green, Lawrence L.↗

Rotor CFD Analysis at Terrestrial and Martian Atmospheric Densities

Much effort has been made to enhance exploration on Mars. In addition to a rover and Mars-orbiting satellites, a Mars helicopter (MH) was proposed in order to augment planetary research. Computational Fluid Dynamics (CFD) simulations have been performed to have a better understanding of the behavior and performance of vertical lift Planetary Aerial Vehicles (PAV). Due to the large differences in atmospheric conditions between Mars and Earth, predicting and testing rotorcraft performance is a complex task. The goal of this project is to understand the capability of the mid-fidelity CFD software RotCFD to predict rotor performance in terms of thrust at 1013.25 milibar and 14 milibar corresponding to Terrestrial and Martian conditions, respectively. Also, in order to characterize the wind tunnel wall effects free field and wind tunnel simulations were performed, analyzed and compared. Different analytical tools have been used in order to aid with the design process for the future vertical lift planetary aerial vehicles. One of them includes experimental tests performed on a rotor in the Aeolian Wind Tunnel (AWT) facility at NASA Ames Research Center under different pressure conditions ranging from Terrestrial to Martian atmospheric conditions. Other software was used as well in order to capture the aerodynamic coefficients of the corresponding rotor sections based on the Mach and Reynolds numbers used for the experimental tests. The aerodynamic coefficients were input into RotCFD, and various simulations were performed under Terrestrial and Martian conditions in order to mimic the experimental test. Then, the obtained results from RotCFD were compared with the AWT collected data.

Atmospheric Pressures↗

Active optics simulation system

The active optics simulation system (AOSS) is a set of computer programs and associated software to be used in the development, design, and evaluation of a primary mirror control system for a large space telescope, (e.g., the tentatively proposed 3-meter telescope). The mathematical models of component subsystems and the solution of the physical processes that occur within the mirror surface control system were obtained, and based on these models AOSS simulates the behavior of the entire mirror surface control system as well as the behavior of the component subsystems. The program has a modular structure so that any subsystem module can be replaced or modified with minimum disruption of the rest of the simulation program.

Chi, C. H.↗

Intelligent fault management for the Space Station active thermal control system

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Hill, Tim↗

A Change Impact Analysis to Characterize Evolving Program Behaviors

Change impact analysis techniques estimate the potential effects of changes made to software. Directed Incremental Symbolic Execution (DiSE) is an intraprocedural technique for characterizing the impact of software changes on program behaviors. DiSE first estimates the impact of the changes on the source code using program slicing techniques, and then uses the impact sets to guide symbolic execution to generate path conditions that characterize impacted program behaviors. DiSE, however, cannot reason about the flow of impact between methods and will fail to generate path conditions for certain impacted program behaviors. In this work, we present iDiSE, an extension to DiSE that performs an interprocedural analysis. iDiSE combines static and dynamic calling context information to efficiently generate impacted program behaviors across calling contexts. Information about impacted program behaviors is useful for testing, verification, and debugging of evolving programs. We present a case-study of our implementation of the iDiSE algorithm to demonstrate its efficiency at computing impacted program behaviors. Traditional notions of coverage are insufficient for characterizing the testing efforts used to validate evolving program behaviors because they do not take into account the impact of changes to the code. In this work we present novel definitions of impacted coverage metrics that are useful for evaluating the testing effort required to test evolving programs. We then describe how the notions of impacted coverage can be used to configure techniques such as DiSE and iDiSE in order to support regression testing related tasks. We also discuss how DiSE and iDiSE can be configured for debugging finding the root cause of errors introduced by changes made to the code. In our empirical evaluation we demonstrate that the configurations of DiSE and iDiSE can be used to support various software maintenance tasks

Rungta, Neha Shyam↗

Performance of Coupled Physics Solvers for Multidisciplinary Hypersonic Flow Simulations on Several Classes of Computer Architectures

The application of hypersonic flow simulation tools to realistic flight scenarios will require the coupling of multiple physical effects to the baseline fluid dynamics. Such multiphysics effects can include the aerooelastic response of the airframe or engine components, dynamic transport of atmospheric particles, the deformation of solid-fluid interfaces that can ablate, pyrolyze, or erode, as well as a host of other processes, all of which are governed by unique sets of physical equations and models. Coupling multiple (and potentially disparate) physics solvers to a robust compressible flow solver poses additional challenges related to the stability, performance and scalability of the combined solver. The choices made during the software design process can therefore lead to a variation in simulation efficiency across different computer architectures. In this paper, we will consider two representative multiphysics hypersonic flow scenarios: the interaction of solid particulates with the flow field created by a hypersonic lifting body and the aerooelastic deformation of a model airframe under high-Mach-number flow conditions. For these simulations we explore the behavior of several hypersonic simulation tools, including Kestrel, FUN3D, US3D, and JENRE multiphysics framework, on several high performance computing systems containing various CPU and GPU architectures.

architecture↗