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A small mobile bed-side computer system is described that is capable of performing phonoangiographic analyses as well as many other common data analysis tasks in a hospital. The clinical application of phonoangiography is found to be greatly facilitated by the computer-provided availability of data acquisition and analysis capabilities.
It is pointed out that significant redirection has occurred in the U.S. Department of Energy (DOE) Photovoltaics Program, and thus in the Flat-Plate Solar Array Project (FSA), since the 3rd European Communities Conference. The Silicon Materials Task has now the objective to sponsor theoretical and experimental research on silicon material refinement technology suitable for photovoltaic flat-plate solar arrays. With respect to the hydrochlorination reaction, a process proof of concept was completed through definition of reaction kinetics, catalyst, and reaction characteristics. In connection with the dichlorosilane chemical vapor desposition process, a preliminary design was completed of an experimental process system development unit with a capacity of 100 to 200 MT/yr of Si.Attention is also given to the silicon-sheet formation research area, environmental isolation research, the cell and module formation task, the engineering sciences area, and the module performance and failure analysis area.
The effects of spatially displaced visual feedback on the operation of a camera viewed remote manipulation task are analyzed. A remote manipulation task is performed by operators exposed to the following different viewing conditions: direct view of the work site; normal camera view; reversed camera view; inverted/reversed camera view; and inverted camera view. The task completion performance times are statistically analyzed with a repeated measures analysis of variance, and a Newman-Keuls pairwise comparison test is administered to the data. The reversed camera view is ranked third out of four camera viewing conditions, while the normal viewing condition is found significantly slower than the direct viewing condition. It is shown that generalization to remote manipulation applications based upon the results of direct manipulation studies are quite useful, but they should be made cautiously.
A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.
An assessment was conducted to determine the maximum LH2 tank stretch capability based on the constraints of the manufacturing, tooling and facilities at the Michoud Assembly Facility in New Orleans, Louisiana. The maximum tank stretch was determined to be 5 ft. with minor or no modifications, a stretch of 11 ft. with some possible facility modifications and beyond 11 ft. significant new facilities are required. A cost analysis was performed to evaluate the impacts for various stretch lengths. Tasks that were defined to perform trades and studies regarding the best approach to meet requirements for the National Launch System Avionics are also discussed.
With a pilots' increasing use of visual cue augmentation, much requiring extensive pre-processing, there is a need to establish criteria for new avionics/display design. The timeliness and synchronization of the augmented cues is vital to ensure the performance quality required for precision mission task elements (MTEs) where augmented cues are the primary source of information to the pilot. Processing delays incurred while transforming sensor-supplied flight information into visual cues are unavoidable. Relationships between maximum control system delays and associated flying qualities levels are documented in MIL-F-83300 and MIL-F-8785. While cues representing aircraft status may be just as vital to the pilot as prompt control response for operations in instrument meteorological conditions, presently, there are no specification requirements on avionics system latency. To produce data relating avionics system latency to degradations in flying qualities, the Navy conducted two simulation investigations. During the investigations, flying qualities and performance data were recorded as simulated avionics system latency was varied. Correlated results of the investigation indicates that there is a detrimental impact of latency on flying qualities. Analysis of these results and consideration of key factors influencing their application indicate that: (1) Task performance degrades and pilot workload increases as latency is increased. Inconsistency in task performance increases as latency increases. (2) Latency reduces the probability of achieving Level 1 handling qualities with avionics system latency as low as 70 ms. (3) The data suggest that the achievement of desired performance will be ensured only at display latency values below 120 ms. (4) These data also suggest that avoidance of inadequate performance will be ensured only at display latency values below 150 ms.
As control systems become more complex, the use of automated control has increased. At the same time, the role of the human operator has changed from primary system controller to supervisor or monitor. Safe design of the human computer interaction becomes more difficult. In this paper, we present a visual task modeling language that can be used by system designers to model human-computer interactions. The visual models can be translated into SpecTRM-RL, a blackbox specification language for modeling the automated portion of the control system. The SpecTRM-RL suite of analysis tools allow the designer to perform formal and informal safety analyses on the task model in isolation or integrated with the rest of the modeled system.
During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.
The basic approach for analyzing hydrostatic bearing flows at the Marshall Space Flight Center (MSFC) is briefly discussed. The Hydrostatic Bearing Team has responsibility for assessing and evaluating flow codes; evaluating friction, ignition, and galling effects; evaluating wear; and performing tests. The Office of Aerospace and Exploration Technology Turbomachinery Seals Tasks consist of tests and analysis. The MSFC in-house analyses utilize one-dimensional bulk-flow codes. Computational fluid dynamics (CFD) analysis is used to enhance understanding of bearing flow physics or to perform parametric analysis that are outside the bulk flow database. As long as the bulk flow codes are accurate enough for most needs, they will be utilized accordingly and will be supported by CFD analysis on an as-needed basis.
The operations required to support the on-orbit Space Station Freedom activities planned or being studied will be complex. Operational capability to perform tasks will be dependent on many factors such as manpower availability, logistics, other tasks being worked and Space Station configuration. This effort uses information available about these and other factors to perform operations analysis for given missions and determine the feasibility of target configuration concepts to support those missions. Studies have been conducted to determine processing requirements for a number of potential evolutionary missions on the Space Station Freedom. These studies have identified the need for growth of the Space Station in various ways. Some of the studies have dealt with the operational needs for the particular mission that they are concerned with, but none have looked at the total evolutionary operations requirement. In order to pursue the subject of overall on-orbit operations to any appreciable level of detail, data bases of operational on-orbit tasks need to be compiled, and an analysis tool is needed to assist the analyst. A number of existing operations tools have been reviewed, and none have been found to satisfactorily perform the functions needed to analyze integrated operations requirements for the evolutionary Space Station Freedom. However, during the tool review, some existing applications were found to provide subsets of the required functionality, and these are being considered for incorporation into the analysis tool.
The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.
This paper descibes a knowledge-based system for performing real-time monitoring and analysis of telemetry data from the NASA Hubble Space Telescope (HST). In order to handle asynchronous inputs and perform in real time the system consists of three or more separate processes, which run concurrently and communicate via a message passing scheme. The data management process gathers, compresses, and scales the incoming telemetry data befoe sending it to the other tasks. The inferencing process uses the incoming data to perform a real-time analysis of the state and health of the Space Telescope. The I/O process receives telemetry monitors from the data management process, updates its graphical displays in real time, and acts as the interface to the console operator. The three processes may run on the same or different computers. This system is currently under development and is being used to monitor testcases produced by the Bass Telemetry System in the Hardware/Software Integration Facility at Lockheed Missile and Space Co. in Sunnyvale, California.
The present investigation is concerned with the development of a better pilot modelling technique via optimal control theory, taking into account concepts concerning 'pilot rating' considered by Neal and Smith (1970). The investigation conducted by Neal and Smith had the objective to provide data on the effects of Flight Control System dynamics and to develop a design criterion capable of pinpointing pilot problem areas encountered in performing a given task. Neal and Smith devised a 'pilot-in-the-loop' analysis capable of showing problem areas in pitch attitude tracking. Unfortunately the employed method has some drawbacks. The current investigation attempts, therefore, to provide an alternate approach which makes use of an optimal-control pilot model. An optimal control model (OCM) had been discussed by Kleinman et al. (1970). It is shown that the alternate approach, based on the OCM, offers some distinct advantages.
In the last few years, teleoperated tasks have been the subject of extensive research to determine the best combination of control modalities according to specific criteria. The operator's performance were compared on the basis of task completion time and of force and torque measurements during the tasks. This paper proposes a procedure for the spectral analysis of force and torque signals generated during teleoperation experiments. There are two main reasons for examining teleoperation data in the frequency domain: a spectral analysis of different tasks can validate the assumptions made in the design of the teleoperator, and a task's frequency signature can be a valuable measure of the operator's performance.
The analytical tools (analysis and computer simulation) needed to explain and predict the dynamic operation of air cushion landing systems (ACLS) is described. The following tasks were performed: the development of improved analytical models for the fan and the trunk; formulation of a heave pitch roll analysis for the complete ACLS; development of a general purpose computer simulation to evaluate landing and taxi performance of an ACLS equipped aircraft; and the verification and refinement of the analysis by comparison with test data obtained through lab testing of a prototype cushion. Demonstration of simulation capabilities through typical landing and taxi simulation of an ACLS aircraft are given. Initial results show that fan dynamics have a major effect on system performance. Comparison with lab test data (zero forward speed) indicates that the analysis can predict most of the key static and dynamic parameters (pressure, deflection, acceleration, etc.) within a margin of a 10 to 25 percent.
For a variety of reasons, condition monitoring of the Space Shuttle Main Engine (SSME) has become an important concern for both ground tests and in-flight operation. The complexities of the SSME suggest that active, real-time condition monitoring should be performed to avoid large-scale or catastrophic failure of the engine. In 1986, the SSME became the subject of a plume emission spectroscopy project at NASA's Marshall Space Flight Center (MSFC). Since then, plume emission spectroscopy has recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to develop the Optical Plume Anomaly Detection (OPAD) system. The OPAD system is designed to provide condition monitoring of the SSME during ground-level testing. The operational health of the engine is achieved through the acquisition of spectrally resolved plume emissions and the subsequent identification of abnormal emission levels in the plume indicative of engine erosion or component failure. Eventually, OPAD, or a derivative of the technology, could find its way on to an actual space vehicle and provide in-flight engine condition monitoring. This technology step, however, will require miniaturized hardware capable of processing plume spectral data in real-time. An objective of OPAD condition monitoring is to determine how much of an element is present in the SSME plume. The basic premise is that by knowing the element and its concentration, this could be related back to the health of components within the engine. For example, an abnormal amount of silver in the plume might signify increased wear or deterioration of a particular bearing in the engine. Once an anomaly is identified, the engine could be shut down before catastrophic failure occurs. Currently, element concentrations in the plume are determined iteratively with the help of a non-linear computer code called SPECTRA, developed at the USAF Arnold Engineering Development Center. Ostensibly, the code produces intensity versus wavelength plots (i.e., spectra) when inputs such as element concentrations, reaction temperature, and reaction pressure are provided. However, in order to provide a higher-level analysis, element concentration is not specified explicitly as an input. Instead, two quantum variables, number density and broadening parameter, are used. Past experience with OPAD data analysis has revealed that the region of primary interest in any SSME plume spectrum lies in the wavelength band of 3300 A to 4330 A. Experience has also revealed that some elements, such as iron, cobalt and nickel, cause multiple peaks over the chosen wavelength range whereas other elements (magnesium, for example) have a few, relatively isolated peaks in the chosen wavelength range. Iteration with SPECTRA as a part of OPAD data analysis is an incredibly labor intensive task and not one to be performed by hand. What is really needed is the "inverse" of the computer code but the mathematical model for the inverse mapping is tenuous at best. However, building generalized models based upon known input/output mappings while ignoring details of the governing physical model is possible using neural networks. Thus the objective of the research project described herein was to quickly and accurately predict combustion temperature and element concentrations (i.e., number density and broadening parameter) from a given spectrum using a neural network. In other words, a neural network had to be developed that would provide a generalized "inverse" of the computer code SPECTRA.
Situation awareness is presented as a fundamental requirement for good airmanship, forming the basis for pilot decision making and performance. To develop a better understanding of the role of situation awareness in flying, an analysis was performed to determine the specific situation awareness information requirements for commercial aircraft pilots. This was conducted as a goal-directed task analysis in which pilots' major goals, subgoals, decisions, and associated situation awareness information requirements were delineated based on elicitation from experienced commercial airline pilots. A determination of the major situation awareness information requirements for visual and instrument flight was developed from this analysis, providing a foundation for future system development which seeks to enhance pilot situation awareness and provide a basis for the development of situation awareness measures for commercial flight.
Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.