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At least 1,423 records · Page 79

ASTRO-2 Spacelab Instrument Pointing System mission performance

This paper reports the performance of the Instrument Pointing System (IPS) that flew on the National Aeronautics and Space Administration (NASA) ASTRO-2 Spacelab mission aboard the Space Shuttle Endeavour in March 1995. The IPS provides a stabilizing platform for the ASTRO-2 instrument payload complement that consists of three main experiments (telescopes). The telescopes observe stellar targets in the universe within the ultraviolet portion of the electromagnetic spectrum that must be observed from beyond the earth's atmospheric filtering effects. The three main experiments for observation are the Hopkins Ultraviolet Telescope (HUT), the Ultraviolet Imaging Telescope (UIT), and the Wisconsin Ultraviolet Photo-Polarimetry Experiment (WUPPE). The HUT uses spectroscopy to obtain the structure and chemical makeup of ultraviolet targets. UIT is responsible for wide field photographing to capture the hidden view of the ultraviolet universe. The WUPPE gathers data on the polarization of the ultraviolet electromagnetic energy coming from the astronomical targets. The capability of IPS enables the experiments to 'see' faint celestial objects. A brief explanation of the IPS is given followed by a review of engineering efforts to improve IPS performance over the ASTRO-1 mission. The main focus of improvements was on enhancing the star acquisition capability through improved guide star selection, lab simulations, computer upgrades, data display systems improvements, and software modifications. A star simulator was developed in the lab to enable IPS to be simulated on the ground pre-mission with flight hardware and software in the loop. The paper concludes with results from the ASTRO-2 mission. The number of targets acquired and the IPS pointing accuracy/stability is reported along with recommendations for the future use of the Instrument Pointing System.

Wessling, Francis C., III↗

The Response of the BATSE LADs to Radiation From the Crab Nebula and Plans for Radioactivity Studies on Space Station

The Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma-Ray Observatory (CGRO) was designed to measure X-rays and gamma rays with energies from about 50 keV to above 2 MeV. As with many scientific investigations, the success of the original experiment lead to additional areas of research interest. In the case of BATSE the ability to observe the radiation from sources down to about 20 keV became readily apparent. This lead to a continuing program of measuring the spectrum of radiation from stellar objects at these lower energies. One of these, the Crab Nebula, has a very steady radiation flux and, thus, has become a "standard candle" for such measurements. The Large Area Detectors (LADS) on BATSE contain a 1.27-cm thick, 25.4-cm radius NaI(Tl) detector behind a 6.35-mm thick polystyrene Charged Particle Detector (CPD) used to "veto" charged particles signals. The detectors have been calibrated with a series of gamma and X-ray sources and the results carefully simulated with a Monte Carlo code. In the calibration process the computer simulation accounts for scattering from material in the counting room as well as the BATSE structure. For an orbiting detector, scattering from the entire spacecraft must be modeled as well as for all covering material over the detectors. Five years after CGRO was launched on April 5, 1991, a large body of observational data has been taken of the Crab Nebula. The technique used for these observations, and for many other X-ray sources, is Earth occultation. From the perspective of the spacecraft, the Earth occults most stellar objects once in orbit, i.e., the signal is lost as the source sets and is regained as the source rises. A careful analysis of the continuing signals from all sources measured allows for an accurate measurement of the spectrum of a given source. An analysis of this data from the Crab has indicated that the LADs are very responsive at energies as low as 20 keV-at energies below the range of calibration. While the model accounts for many of the interactions of the photons with the detectors, the observation of nonstatistical deviations at low energy and at small angles has suggested a need to recalibrate at energies where the attenuation effects are increasing exponentially.

Laird, C. E.↗

End-to-End QoS for Differentiated Services and ATM Internetworking

The Internet was initially design for non real-time data communications and hence does not provide any Quality of Service (QoS). The next generation Internet will be characterized by high speed and QoS guarantee. The aim of this paper is to develop a prioritized early packet discard (PEPD) scheme for ATM switches to provide service differentiation and QoS guarantee to end applications running over next generation Internet. The proposed PEPD scheme differs from previous schemes by taking into account the priority of packets generated from different application. We develop a Markov chain model for the proposed scheme and verify the model with simulation. Numerical results show that the results from the model and computer simulation are in close agreement. Our PEPD scheme provides service differentiation to the end-to-end applications.

Su, Hongjun↗

The effect of digital computing on the performance of a closed-loop control-loading system

A sampled data model of a control loader system for flight simulation was developed and successfully validated. The model accounts for the effects of the central digital simulation computer on the response of the analog control loader system and includes the spring-gradients, bob-weight, and actuator-lag effects of the aircraft. The revelation of a frequency error introduced by the implementation of force feedback through the digital computer that could adversely affect pilot performance in simulated flight has led to a proposed new implementation which will minimize the impact of the frequency problem.

Parrish, R. V.↗

Separability of Mesh Bias and Parametric Uncertainty for a Full System Thermal Analysis

When making computational simulation predictions of multiphysics engineering systems, sources of uncertainty in the prediction need to be acknowledged and included in the analysis within the current paradigm of striving for simulation credibility. A thermal analysis of an aerospace geometry was performed at Sandia National Laboratories. Here, for this analysis, a verification, validation, and uncertainty quantification (VVUQ) workflow provided structure for the analysis, resulting in the quantification of significant uncertainty sources including spatial numerical error and material property parametric uncertainty. It was hypothesized that the parametric uncertainty and numerical errors were independent and separable for this application. This hypothesis was supported by performing uncertainty quantification (UQ) simulations at multiple mesh resolutions, while being limited by resources to minimize the number of medium and high resolution simulations. In conclusion, based on this supported hypothesis, a prediction including parametric uncertainty and a systematic mesh bias is used to make a margin assessment that avoids unnecessary uncertainty obscuring the results and optimizes use of computing resources.

42 ENGINEERING↗

Cathode to Target Simulations for Scorpius: I. Simulation Codes and Models

The new Scorpius linear induction electron accelerator is under development for multi-pulse flash radiography of large, explosively-driven hydrodynamic experiments. Beam physics from the cathode to the target was examined with computer simulations, including envelope, ray-trace, and particle-in cell (PIC) codes. Beam instabilities investigated included beam breakup (BBU), image displacement, diocotron, parametric envelope, ion hose, and the resistive wall instability. Beam corkscrew motion and emittance growth from beam mismatch were also studied. The results of these simulations is documented in a series of reports. In this report the computer codes and physical models used for these simulations are described. The conclusion of this study is that Scorpius will produce and accelerate a beam with radiographic quality equivalent to the present accelerators at Los Alamos National Laboratory if the same engineering standards and construction details are upheld.

43 PARTICLE ACCELERATORS↗

RAS Protein Molecular Dynamics Simulations

This dataset contains 6401 files that describe parameters and other inputs for running molecular dynamics computer simulations of Ras proteins associated with a lipid-based cell membrane model in water, as well as resulting time-trajectories of atomic motion in these simulations. Specifically, the content includes: (a) 21 files containing generalized force field parameters, and (b) 22 files of similar format and content for each of 290 separate molecular dynamics simulations (22 ´ 290 = 6,380). The total size of this data set is 1.0 TB.

59 BASIC BIOLOGICAL SCIENCES↗

Development of the reentry flight dynamics simulator for evaluation of space shuttle orbiter entry systems

A nonlinear, six degree of freedom, digital computer simulation of a vehicle which has constant mass properties and whose attitudes are controlled by both aerodynamic surfaces and reaction control system thrusters was developed. A rotating, oblate Earth model was used to describe the gravitational forces which affect long duration Earth entry trajectories. The program is executed in a nonreal time mode or connected to a simulation cockpit to conduct piloted and autopilot studies. The program guidance and control software used by the space shuttle orbiter for its descent from approximately 121.9 km to touchdown on the runway.

Rowell, L. F.↗

Flight dynamics analysis and simulation of heavy lift airships. Volume 1: Executive summary

A generic, yet comprehensive mathematical model and computer simulation of the HLA flight dynamics over its entire flight envelope was developed. Implicit in this simulation development are the data reviews and analyses which support the equations of motion and the calculation of forces and moments acting on the vehicle. The simulation, HYBRDS, is addressed to the broad requirements and is intended for use as a synthesis and analysis tool for the evaluation of competing HLA design concepts.

Ringland, R. F.↗

Improving the Spacelab mass memory unit tape layout with a simulation model

A tape drive called the Mass Memory Unit (MMU) stores software used by Spacelab computers. MMU tape motion must be minimized during typical flight operations to avoid a loss of scientific data. A projection of the tape motion is needed for evaluation of candidate tape layouts. A computer simulation of the scheduled and unscheduled MMU tape accesses is developed for this purpose. This simulation permits evaluations of candidate tape layouts by tracking and summarizing tape movements. The factors that affect tape travel are investigated and a heuristic is developed to find a good tape layout. An improved tape layout for Spacelab I is selected after the evaluation of fourteen candidates. The simulation model will provide the ability to determine MMU layouts that substantially decrease the tape travel on future Spacelab flights.

Noneman, S. R.↗

Simulations of satellite Doppler wind observations

This study will involve two objectives: (1) to develop, through computer simulations, optimal satellite-based sensor scanning techniques for direct measurement of tropospheric winds on the meso- and synoptic scales; and (2) to construct simulations of remotely measured wind fields for assessing impact of such fields on the diagnosis and prognosis of atmospheric phenomena through the use of Observing System Simulation Experiments (OSSE). Using the LAWS Simulation Model (LSM), various global coverage scenarios have been investigated as part of an effort to define the optimal orbit, configuration and sampling strategies for observations of winds for use in global circulation models. Simulated data sets have been provided to GSFC, FSU and several LAWS team members. Particular emphasis has been on providing realistic cloud cover, cirrus backscatter, aerosol distribution and wind variance on scales less than 600 km. Progress is currently being made to incorporate other remote sensors (AIRS/AMSU, STIKSCAT) into the global OSSEs.

Emmitt, George D.↗

Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages

This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling of convection phenomena in Bridgman-Stockbarger crystal growth

Thermal convection phenomena in a vertically oriented Bridgman-Stockbarger apparatus were modeled by computer simulations for different gravity conditions, ranging from earth conditions to extremely low gravity, approximate space conditions. The modeling results were obtained by the application of a state-of-the art, transient, multi-dimensional, completely densimetrically coupled, discrete-element computational model which was specifically developed for the simulation of flow, temperature, and species concentration conditions in two-phase (solid-liquid) systems. The computational model was applied to the simulation of the flow and the thermal conditions associated with the convection phenomena in a modified Germanium-Silicon charge enclosed in a stationary fused-silica ampoule. The results clearly indicated that the gravitational field strength influences the characteristics of the coherent vortical flow patterns, interface shape and position, maximum melt velocity, and interfacial normal temperature gradient.

Carlson, F. M.↗

Software for Simulating Air Traffic

Future Air Traffic Management Concepts Evaluation Tool (FACET) is a system of software for performing computational simulations for evaluating advanced concepts of advanced air-traffic management. FACET includes a program that generates a graphical user interface plus programs and databases that implement computational models of weather, airspace, airports, navigation aids, aircraft performance, and aircraft trajectories. Examples of concepts studied by use of FACET include aircraft self-separation for free flight; prediction of air-traffic-controller workload; decision support for direct routing; integration of spacecraft-launch operations into the U.S. national airspace system; and traffic- flow-management using rerouting, metering, and ground delays. Aircraft can be modeled as flying along either flight-plan routes or great-circle routes as they climb, cruise, and descend according to their individual performance models. The FACET software is modular and is written in the Java and C programming languages. The architecture of FACET strikes a balance between flexibility and fidelity; as a consequence, FACET can be used to model systemwide airspace operations over the contiguous U.S., involving as many as 10,000 aircraft, all on a single desktop or laptop computer running any of a variety of operating systems. Two notable applications of FACET include: (1) reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administration s nationally deployed, real-time, operational systems; and (2) the licensing and integration of FACET with the commercially available Flight Explorer, which is an Internet- based, real-time flight-tracking system.

Sridhar, Banavar↗

Active Subspace Methods for Data-Intensive Inverse Problems (Final Report)

Fostered by advances in computing, simulation and data science have emerged as the third and fourth paradigms enabling scientific discovery. Many mathematical challenges arise when integrating these paradigms to produce new knowledge. One of the most important challenges is the inverse or calibration problem: find the inputs of a simulation such that its outputs agree with a given set of measurements. As both the cost of the complex simulations and the volume of measurement data sets increase, intuition-driven trial-and-error methods for calibration quickly become untenable; modern scientists need more computationally efficient and mathematically rigorous methods. When measurements and simulated predictions contain uncertainty, the Bayesian perspective on statistical inference provides a popular mathematical framework for developing computational methods to solve inverse problems. Markov chain Monte Carlo (MCMC) methods are a mainstay of this framework; they characterize a probability distribution on the space of model inputs that is conditioned on the given measurements. However, despite recent advances, MCMC methods remain impractical for expensive simulations with more than a handful of inputs. At its heart, MCMC searches the space of inputs for corresponding outputs that match measurements, and so it is afflicted with the curse of dimensionality. Additionally, MCMC methods become less efficient as the volume of the measurement data increases, particularly if the measurements are redundant. To make MCMC—and Bayesian methods, in general—amenable to today’s computer models with millions of inputs and terabytes of measurement data, one must devise methods to reduce the dimension of both the simulation inputs and the measurements. For many models used in practice, the outputs vary primarily on a low-dimensional manifold of the nominally high-dimensional input space. Recently developed active subspace methods discover this low-dimensional manifold and exploit it to enable analyses typically suited for low-dimensional settings (e.g., statistical inversion of complex systems). We hypothesize that active subspace methods can provide the necessary dimension reduction, enabling existing Bayesian methods to find solutions for a large class of otherwise intractable statistical inverse problems. We will test the hypothesis with a series of mathematical analyses and computational experiments that will proceed along three research veins: (i) integrating active subspace methods into methods for statistical inversion, (ii) addressing current challenges in active subspace methods, and (iii) incorporating methods for nonlinear dimensionality reduction into active subspace methods. We will apply the methods we develop to real inverse problems in chemical kinetics and turbulent flame modeling. Our team combines expertise in methods for inverse problems, dimension reduction, and reduced order modeling. With a history of active collaboration and thoughtful engagement, we bring enthusiasm and fresh perspectives to a well studied subject. We are excited by the potential opportunity to work together to extend and apply active subspace methods to data-intensive inverse problems.

97 MATHEMATICS AND COMPUTING↗

Active Subspace Methods for Data-Intensive Inverse Problems

Fostered by advances in computing, simulation and data science have emerged as the third and fourth paradigms enabling scientific discovery. Many mathematical challenges arise when integrating these paradigms to produce new knowledge. One of the most important challenges is the inverse or calibration problem: find the inputs of a simulation such that its outputs agree with a given set of measurements. As both the cost of the complex simulations and the volume of measurement data sets increase, intuition-driven trial-and-error methods for calibration quickly become untenable; modern scientists need more computationally efficient and mathematically rigorous methods. When measurements and simulated predictions contain uncertainty, the Bayesian perspective on statistical inference provides a popular mathematical framework for developing computational methods to solve inverse problems. Markov chain Monte Carlo (MCMC) methods are a mainstay of this framework; they characterize a probability distribution on the space of model inputs that is conditioned on the given measurements. However, despite recent advances, MCMC methods remain impractical for expensive simulations with more than a handful of inputs. At its heart, MCMC searches the space of inputs for corresponding outputs that match measurements, and so it is afflicted with the curse of dimensionality. Additionally, MCMC methods become less efficient as the volume of the measurement data increases, particularly if the measurements are redundant. To make MCMC—and Bayesian methods, in general—amenable to today’s computer models with millions of inputs and terabytes of measurement data, one must devise methods to reduce the dimension of both the simulation inputs and the measurements. For many models used in practice, the outputs vary primarily on a low-dimensional manifold of the nominally high-dimensional input space. Recently developed active subspace methods discover this low-dimensional manifold and exploit it to enable analyses typically suited for low-dimensional settings (e.g., statistical inversion of complex systems). We hypothesize that active subspace methods can provide the necessary dimension reduction, enabling existing Bayesian methods to find solutions for a large class of otherwise intractable statistical inverse problems. We will test the hypothesis with a series of mathematical analyses and computational experiments that will proceed along three research veins: (i) integrating active subspace methods into methods for statistical inversion, (ii) addressing current challenges in active subspace methods, and (iii) incorporating methods for nonlinear dimensionality reduction into active subspace methods. We will apply the methods we develop to real inverse problems in chemical kinetics and turbulent flame modeling. Our team combines expertise in methods for inverse problems, dimension reduction, and reduced order modeling. With a history of active collaboration and thoughtful engagement, we bring enthusiasm and fresh perspectives to a well studied subject. We are excited by the potential opportunity to work together to extend and apply active subspace methods to data-intensive inverse problems.

97 MATHEMATICS AND COMPUTING↗

Predicting Chemical Reaction Barriers with a Machine Learning Model

In the past few decades, tremendous advances have been made in the understanding of catalysis at solid surfaces. Despite this, most discoveries of materials for improved catalytic performance are made by a slow trial and error process in an experimental laboratory. Computational simulations have begun to provide a way to rationally design materials for optimizing catalytic performance, but due to the high computational expense of calculating transition state energies, simulations cannot adequately screen the phase space of materials. In this work, we attempt to mitigate this expense by using a machine learning approach to predict the most expensive and most important parameter in a catalyst’s affinity for a reaction: the reaction barrier. Previous methods which used the step reaction energy as the only parameter in a linear regression had a mean absolute error (MAE) on the order of 0.4 eV, too high to be used predictively. Here in our work, we achieve a MAE of about 0.22 eV, a marked improvement towards the goal of computational prediction of catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A method of testing attitude control systems during the development phase

A technique, utilized on the Space Telescope Program, and used for testing satellite attitude pointing and control systems during the engineering and development phases is presented. The technique verifies the hardware models used in design phase computer simulations, verifies the interface between the flight hardware and flight software, and uncovers hardware/software switching or mode logic problems. The testing is accomplished in two phases: a dynamic hardware simulator phase using hardware electronic simulators and an electronic vehicle motion simulator; and a second real hardware phase utilizing engineering model gyros and reaction wheels on an airbearing table. Both phases use an engineering model of the flight computer, flight algorithms and software, and a breadboard data management and computer hardware interface for timing simulations. The purpose of each test and the test phases are described, and examples of closed loop test results for both attitude hold and maneuvering models are given.

Besonis, A.↗