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The characteristics and capabilities of existing machine translation systems were examined and procurement recommendations were developed. Four systems, SYSTRAN, GLOBALINK, PC TRANSLATOR, and STYLUS, were determined to meet the NASA requirements for a machine translation system. Initially, four language pairs were selected for implementation. These are Russian-English, French-English, German-English, and Japanese-English.
The primary purpose of this study was to measure the effects of inflow-produced heat turbulence on heat transfer in Stirling machine cylinders. A secondary purpose was to provide new experimental information on heat transfer in gas springs without inflow. The apparatus for the experiment consisted of a varying-volume piston-cylinder space connected to a fixed volume space by an orifice. The orifice size could be varied to adjust the level of inflow-produced turbulence, or the orifice plate could be removed completely so as to merge the two spaces into a single gas spring space. Speed, cycle mean pressure, overall volume ratio, and varying volume space clearance ratio could also be adjusted. Volume, pressure in both spaces, and local heat flux at two locations were measured. The pressure and volume measurements were used to calculate area averaged heat flux, heat transfer hysteresis loss, and other heat transfer-related effects. Experiments in the one space arrangement extended the range of previous gas spring tests to lower volume ratio and higher nondimensional speed. The tests corroborated previous results and showed that analytic models for heat transfer and loss based on volume ratio approaching 1 were valid for volume ratios ranging from 1 to 2, a range covering most gas springs in Stirling machines. Data from experiments in the two space arrangement were first analyzed based on lumping the two spaces together and examining total loss and averaged heat transfer as a function of overall nondimensional parameter. Heat transfer and loss were found to be significantly increased by inflow-produced turbulence. These increases could be modeled by appropriate adjustment of empirical coefficients in an existing semi-analytic model. An attempt was made to use an inverse, parameter optimization procedure to find the heat transfer in each of the two spaces. This procedure was successful in retrieving this information from simulated pressure-volume data with artificially generated noise, but it failed with the actual experimental data. This is evidence that the models used in the parameter optimization procedure (and to generate the simulated data) were not correct. Data from the surface heat flux sensors indicated that the primary shortcoming of these models was that they assumed turbulence levels to be constant over the cycle. Sensor data in the varying volume space showed a large increase in heat flux, probably due to turbulence, during the expansion stroke.
This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.
As far as total automation is not realized, the combination of technical and social components in man-machine systems demands not only contributions from engineers but at least to an equal extent from behavioral scientists. This has been neglected far too long. The psychological, social and cultural aspects of technological innovations were almost totally overlooked. Yet, along with expected safety improvements the institutionalization of human factors is on the way. The introduction of human factors certification of complex man-machine systems will be a milestone in this process.
Machine designed and built for variety of uses involving coating or impregnating ("prepregging") fibers, tows, yarns, or webs or tapes made of such fibrous materials with thermoplastic or thermosetting resins. Prepreg materials produced used to make matrix/fiber composite materials. Comprises modules operated individually, sequentially, or simultaneously, depending on nature of specific prepreg material and prepregging technique used. Machine incorporates number of safety features.
Method of machining on conventional metal lathe devised for precise cutting of axisymmetric contours on honeycomb cores made of composite (matrix/fiber) materials. Wax filling reinforces honeycomb walls against bending and tearing while honeycomb being contoured on lathe. Innovative method of machining on lathe involves preparation in which honeycomb is placed in appropriate fixture and the fixture is then filled with molten water-soluble wax. Number of different commercial waxes have been tried.
The Machine Translation Project consists of several components, two of which, the Project Plan and the Requirements Analysis, have already been delivered. The Project Plan details the overall rationale, objectives and time-table for the project as a whole. The Requirements Analysis compares a number of available machine translation systems, their capabilities, possible configurations, and costs. The Alternatives Analysis has resulted in a number of conclusions and recommendations to the NASA STI program concerning the acquisition of specific MT systems and related hardware and software.
Human beings judge images by complex mental processes, whereas computing machines extract features. By reducing scaled human judgments and machine extracted features to a common metric space and fitting them by regression, the judgments of human experts rendered on a sample of images may be imposed on an image population to provide automatic classification.
Micromechanical machining processes are those micro fabrication techniques which directly remove work piece material by either a physical cutting tool or an energy process. These processes are direct and therefore they can help reduce the cost and time for prototype development of micro mechanical components and systems. This is especially true for aerospace applications where size and weight are critical, and reliability and the operating environment are an integral part of the design and development process. The micromechanical machining processes are rapidly being recognized as a complementary set of tools to traditional lithographic processes (such as LIGA) for the fabrication of micromechanical components. Worldwide efforts in the U.S., Germany, and Japan are leading to results which sometimes rival lithography at a fraction of the time and cost. Efforts to develop processes and systems specific to aerospace applications are well underway.
The development of machine vision based pilot aids to help reduce night approach and landing accidents is explored. The techniques developed are motivated by the desire to use the available information sources for navigation such as the airport lighting layout, attitude sensors and Global Positioning System to derive more precise aircraft position and orientation information. The fact that airport lighting geometry is known and that images of airport lighting can be acquired by the camera, has lead to the synthesis of machine vision based algorithms for runway relative aircraft position and orientation estimation. The main contribution of this research is the synthesis of seven navigation algorithms based on two broad families of solutions. The first family of solution methods consists of techniques that reconstruct the airport lighting layout from the camera image and then estimate the aircraft position components by comparing the reconstructed lighting layout geometry with the known model of the airport lighting layout geometry. The second family of methods comprises techniques that synthesize the image of the airport lighting layout using a camera model and estimate the aircraft position and orientation by comparing this image with the actual image of the airport lighting acquired by the camera. Algorithms 1 through 4 belong to the first family of solutions while Algorithms 5 through 7 belong to the second family of solutions. Algorithms 1 and 2 are parameter optimization methods, Algorithms 3 and 4 are feature correspondence methods and Algorithms 5 through 7 are Kalman filter centered algorithms. Results of computer simulation are presented to demonstrate the performance of all the seven algorithms developed.
The NASA Langley Research Center (LARC) participated in a national cooperative evaluation of the Israel Aircraft Industries (IAI) automatic balance calibration machine at Microcraft, San Diego in September 1995. A LaRC-designed six-component strain gauge balance was selected for test and calibration during LaRC's scheduled evaluation period. Eight calibrations were conducted using three selected experimental designs. Raw data were exported to LaRC facilities for reduction and statistical analysis using the techniques outlined in Tripp and Tcheng (1994). This report presents preliminary assessments of the results, and compares IAI calibration results with manual calibration results obtained at the Modern Machine and Tool Co., Inc. (MM & T). Newport News, VA. A more comprehensive report is forthcoming.
It is hypothesized that bone loss experienced by astronauts in zero gravity conditions may be curtailed by appropriate exercise. According to Wolf's law, bone regenerates when muscles produce stresses by pulling on the bone during daily activity and/or exercise on Earth. To use this theory to prevent or decrease bone loss, one needs to quantify musculoskeletal loads and relate them to bone density changes. In the context of the space program, it is desirable to determine musculoskeletal loads during exercise so that one may make similar measurements on Earth and in space. In this manner, load measurements on Earth may be used as reference to generate similar loads during exercise in space. A research project to investigate the effects of high-resistive exercise to decrease bone density loss underzero-gravity conditions is being carried out in Life Sciences Research Laboratories at NASA JSC. The project consists of a bed-rest study whereby subjects remain in horizontal position for seventeen weeks. During the study, a subset of those subjects executes a regime of resistive exercises in the horizontal exercise machine (HEM). The HEM was designed so that subjects remain horizontal while exercising to minimize gravity loading even during exercise. Bone density of each subject is measured throughout the duration of their participation. The objective of the study is to determine if the resistive exercises are effective in diminishing or eliminating bone loss. My participation in this project relates to instrumentation, measurement, and processing of signals from displacement sensors (optical encoders) and load-cells. Measurement of displacements will be used to determine the motion of the body during exercise, and load measurements will be used (along with displacement data) to determine forces and torques exerted on each section of the body during exercise. Further, I have assisted in specifying new sensors to be added to the HEM and to a new prototype resistive exercise machine called the Interim Resistive Exercise Device (IRED). New load cells and encoders should be mounted in these devices to obtain more complete kineto-dynamic information. This report includes a description of the instrumentation that was built to perform measurements in the HEM and the IRED, along with the software that was developed to collect the measurements. It also includes examples of measurements taken in the HEM. Finally, a plan is laid out that describes how these measurements may be used to determine forces exerted by muscles for each exercise.
Designed in 1964 and erected in 1966, the mission of the Gilmore Load Cell Machine was to provide highly accurate calibrations for large capacity load cells in support of NASA's Apollo Program. Still in use today, the Gilmore Machine is a national treasure with no equal.
Many optical MEMS device designs involve large arrays of thin (0.5 to 1 micron components subjected to high stresses due to cyclic loading. These devices are fabricated from a variety of materials, and the properties strongly depend on size and processing. Our objective is to develop standard and convenient test methods that can be used to measure the properties of large numbers of witness samples, for every device we build. In this work we explore a variety of fracture test configurations for 0.5 micron thick silicon nitride membranes machined using the Reactive Ion Etching (RIE) process. Testing was completed using an FEI 620 dual focused ion beam milling machine. Static loads were applied using a probe. and dynamic loads were applied through a piezo-electric stack mounted at the base of the probe. Results from the tests are presented and compared, and application for predicting fracture probability of large arrays of devices are considered.
Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.
Recent computational efforts at NASA Ames Research Center and computation and experiment elsewhere suggest that a nanotechnology of machine phase functionalized fullerenes may be synthetically accessible and of great interest. We have computationally demonstrated that molecular gears fashioned from (14,0) single-walled carbon nanotubes and benzyne teeth should operate well at 50-100 gigahertz. Preliminary results suggest that these gears can be cooled by a helium atmosphere and a laser motor can power fullerene gears if a positive and negative charge have been added to form a dipole. In addition, we have unproven concepts based on experimental and computational evidence for support structures, computer control, a system architecture, a variety of components, and manufacture. Combining fullerene machines with the remarkable mechanical properties of carbon nanotubes, there is some reason to believe that a focused effort to develop fullerene nanotechnology could yield materials with tremendous properties.
Fullerenes possess remarkable properties and many investigators have examined the mechanical, electronic and other characteristics of carbon SP2 systems in some detail. In addition, C-60 can be functionalized with many classes of molecular fragments and we may expect the caps of carbon nanotubes to have a similar chemistry. Finally, carbon nanotubes have been attached to t he end of scanning probe microscope (Spill) tips. Spills can be manipulated with sub-angstrom accuracy. Together, these investigations suggest that complex molecular machines made of fullerenes may someday be created and manipulated with very high accuracy. We have studied some such systems computationally (primarily functionalized carbon nanotube gears and computer components). If such machines can be combined appropriately, a class of materials may be created that can sense their environment, calculate a response, and act. The implications of such hypothetical materials are substantial.
This study used Support Vector Machines to classify multiangle POLDER data. Boreal wetland ecosystems cover an estimated 90 x 10(exp 6) ha, about 36% of global wetlands, and are a major source of trace gases emissions to the atmosphere. Four to 20 percent of the global emission of methane to the atmosphere comes from wetlands north of 4 degrees N latitude. Large uncertainties in emissions exist because of large spatial and temporal variation in the production and consumption of methane. Accurate knowledge of the areal extent of open water and inundated vegetation is critical to estimating magnitudes of trace gas emissions. Improvements in land cover mapping have been sought using physical-modeling approaches, neural networks, and active microwave, examples that demonstrate the difficulties of separating open water, inundated vegetation and dry upland vegetation. Here we examine the feasibility of using a support vector machine to classify POLDER data representing open water, inundated vegetation and dry upland vegetation.