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This paper summarizes the justification and technical approach of an experimental plan for landmark recognition and tracking from the Advanced Technology Laboratory (ATL). The primary experimental approach is that of near real-time pattern recognition by means of coherent optical techniques. An experiment development plan would lead to a flight test in 1981.
The applications of meteorological satellite data to both summer and winter weather modification programs are addressed. Appraisals of the capability of satellites to assess seedability, to provide real-time operational support, and to assist in the post-experiment analysis of a seeding experiment led to the incorporation of satellite observing systems as a major component in the Bureau of Reclamations weather modification activities. Satellite observations are an integral part of the South Park Area cumulus experiment (SPACE) which aims to formulate a quantitative hypothesis for enhancing precipitation from orographically induced summertime mesoscale convective systems (orogenic mesoscale systems). Progress is reported in using satellite observations to assist in classifying the important mesoscale systems, and in defining their frequency and coverage, and potential area of effect. Satellite studies of severe storms are also covered.
A revue of experimental investigations of lubricant behaviour in highly stressed situations shows that a Newtonian model for lubricant rheology is insufficient for explanation of traction behaviour. The oil film build-up, on the other hand, is fairly well predicted using a Newtonian lubricant model except at high slide to roll ratios and at very high loads, where the non-Newtonian behaviour starts to be important already outside the Hertzian contact area. Two main types of experiments are reported: static and dynamic. In static experiments the pressure is typically applied to the lubricant more than a million times longer than in an EHD contact. Depending on the pressure-temperature history of the experiment the lubricant will become a crystallized or amorphous solid at high pressures. In dynamic experiments, where the pressure is applied as short time as in real EHD contacts, the oil is in an amorphous solid state. Depending on the viscosity, time-scale, elasticity of the oil and the bearing surfaces, the oil film pressure, shear strain rate and the type of lubricant, different properties of the oil are important for prediction of shear stresses in the oil. This can be seen from the different proposed models for the lubricant, where it is described as being for instance a Newtonian liquid, an elastic liquid, a plastic liquid and an elastic-plastic solid.
Real time analysis of data can reduce the time involved in exploring dynamic systems. The failure of the data acquisition system at the Princeton Dynamic Model Track prompted its replacement with a real time data acquisition system. Data can be obtained from an experiment and analyzed during and immediately following a data run. The new system employs high speed analog to digital conversion and a small computer to collect data. Sampling rates of 1000 hertz over 44 channels (44,000 words/sec) are obtainable. The data can be accessed as it enters the computer's environment where it may be displayed or stored for later processing. The system was tested on a helicopter rotor steep descent experiment. The data collected compares with previous data from a similar experiment.
The purpose of the workshop was to further explore and define the earth sciences requirements for the Information Sciences Experiment System (ISES), a proposed onboard data processor with real-time communications capability intended to support the Earth Observing System (Eos). A review of representative Eos instrument types is given and a preliminary set of real-time data needs has been established. An executive summary is included.
The science and application of remote sensing is flourishing in the digital age. Geographical information systems can provide a broad range of information tailored to the specific needs of disaster managers. Recent advances in airborne platforms, sensors and information technologies have come together provide the ability to put geo-registered, multispectral imagery on the web in near real-time. Highlights of a demonstration of NASA's First Response Experiment (FiRE) will be presented.
The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.
The Pore Formation and Mobility Investigation (PFMI) and the In-Space Soldering Investigation (ISSI) were conducted aboard the International Space Station (ISS) with the intent of promoting our understanding of materials processing in a low-gravity environment. The numerous experiments were conducted by telescience with the results evaluated by real time video and subsequently returned tapes and samples. In addition to discussing the experimental results and analysis the presentation will include an account of the ISS facilities (Microgravity Science Glovebox and Maintenance Work Area) used as well as some lessons-learned comments.
GSI, NICT, OSO, and MRO have been engaged in Ultra-rapid dUT1 experiments since 2007 aiming at the technological possibility of real-time dUT1 results using the e-VLBI technique. We have already successfully determined dUT1 in less than four minutes after the end of an experimental Intensive session in 2008, and at present we routinely get the results within 30 minutes for regular Intensives. In 2009 we applied the technique to 24-hour sessions and continuously obtained dUT1 values by processing and analyzing Tsukuba Onsala data in near real-time. It showed a detailed behavior of UT1 variations, which could be very valuable for scientific study as well as for precise prediction of UT1-UTC.
The primary reason for monitoring air quality aboard the International Space Station (ISS) is to determine whether air pollutants have collectively reached a concentration where the crew could experience adverse health effects. These effects could be near-real-time (e.g. headache, respiratory irritation) or occur late in the mission or even years later (e.g. cancer, liver toxicity). Secondary purposes for monitoring include discovery that a potentially harmful compound has leaked into the atmosphere or that air revitalization system performance has diminished. Typical ISS atmospheric trace pollutants consist of alcohols, aldehydes, aromatic compounds, halo-carbons, siloxanes, and silanols. Rarely, sulfur-containing compounds and alkanes are found at trace levels. Spacecraft Maximum Allowable Concentrations (SMACs) have been set in cooperation with a subcommittee of the National Research Council Committee on Toxicology. For each compound and time of exposure, the limiting adverse effect(s) has been identified. By factoring the analytical data from the Air Quality Monitor (AQM), which is in use as a prototype instrument aboard the ISS, through the array of compounds and SMACs, the risk of 16 specific adverse effects can be estimated. Within each adverse-effect group, we have used an additive model proportioned to each applicable 180-day SMAC to estimate risk. In the recent past this conversion has been performed using archival data, which can be delayed for months after an air sample is taken because it must be returned to earth for analysis. But with the AQM gathering in situ data each week, NASA is in a position to follow toxic-effect groups and correlate these with any reported crew symptoms. The AQM data are supplemented with data from real-time CO2 instruments aboard the ISS and from archival measurements of formaldehyde, which the AQM cannot detect.
Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.
At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.
The Burst and Transient Source Experiment (BATSE) for the Gamma Ray Observatory (GRO) consists of eight detector modules that provide full-sky coverage for gamma-ray bursts and other transient phenomena such as solar flares. Each detector module has a thin, large-area scintillation detector (2025 sq cm) for high time-resolution studies, and a thicker spectroscopy detector (125 sq cm) to extend the energy range and provide better spectral resolution. The total energy range of the system is 15 keV to 100 MeV. These 16 detectors and the associated onboard data system should provide unprecedented capabilities for observing rapid spectral changes and gamma-ray lines from solar flares. The presence of a solar flare can be detected in real-time by BATSE; a trigger signal is sent to two other experiments on the GRO. The launch of the GRO is scheduled for June 1990, so that BATSE can be an important component of the Max '91 campaign.
The evaluation of available medical data to determine the health status of the Skylab 3 crew members is discussed. The utilization of raw data from medical experiments during the course of the mission as a source of near-real time criteria for monitoring crew health is described. The percentage change of selected metabolic parameters, including calorie intake, Na intake, K intake, urine output, water intake, and body weight, from their pre-flight values, vectorcardiographic data, and results of the lower body negative pressure experiment provided a core of information upon which clinical judgements could be made. Minor clinical problems occurring during the mission are outlined.
NASA's Superfluid Helium On-Orbit Transfer (SHOOT) project is a Shuttle-based experiment designed to acquire data on the properties of superfluid helium in micro-gravity. Aft Flight Deck Computer Software for the SHOOT experiment is comprised of several monitoring programs which give the astronaut crew visibility into SHOOT systems and a rule based system which will provide process control, diagnosis and error recovery for a helium transfer without ground intervention. Given present Shuttle manifests, this software will become the first expert system to be used in space. The SHOOT Command and Monitoring System (CMS) software will provide a near real time highly interactive interface for the SHOOT principal investigator to control the experiment and to analyze and display its telemetry. The CMS software is targeted for all phases of the SHOOT project: hardware development, pre-flight pad servicing, in-flight operations, and post-flight data analysis.
The Skylab food system, waste management system, operational bioinstrumentation, personal hygiene provisions, in-flight medical support system, and the cardiovascular counterpressure garment worn during reentry are described. The medical experiments program provided scientific data and also served as the basis for real-time decisions on flight duration. Premission support, in-flight operational support, and postflight medical activities are surveyed. Measures devised to deal with possible food spoilage, medical instrument damage, and toxic atmosphere caused by the initial failures on the Orbital Workshop (OWS) are discussed. The major medical experiments performed in flight allowed the study of physiological changes as a function of exposure to weightless flight. The experiments included studies of the cardiovascular system, musculoskeletal and fluid/electrolyte balance, sleep, blood, vestibular system, and time and motion studies.
The Control/Structure Interaction Program is a technology development program for spacecraft that exhibit interactions between the control system and structural dynamics. The program objectives include development and verification of new design concepts - such as active structure - and new tools - such as combined structure and control optimization algorithm - and their verification in ground and possibly flight test. A focus mission spacecraft was designed based upon a space interferometer and is the basis for design of the ground test article. The ground test bed objectives include verification of the spacecraft design concepts, the active structure elements and certain design tools such as the new combined structures and controls optimization tool. In anticipation of CSI technology flight experiments, the test bed control electronics must emulate the computation capacity and control architectures of space qualifiable systems as well as the command and control networks that will be used to connect investigators with the flight experiment hardware. The Test Bed facility electronics were functionally partitioned into three units: a laboratory data acquisition system for structural parameter identification and performance verification; an experiment supervisory computer to oversee the experiment, monitor the environmental parameters and perform data logging; and a multilevel real-time control computing system. The design of the Test Bed electronics is presented along with hardware and software component descriptions. The system should break new ground in experimental control electronics and is of interest to anyone working in the verification of control concepts for large structures.
A technology development plan designed to reduce the data load and data-management problems associated with global study and monitoring missions is described with a heavy emphasis placed on developing mission capabilities to eliminate the collection of unnecessary data. Improved data selectivity can be achieved through sensor automation correlated with the real-time needs of data users. The first phase of the plan includes the Feature Identification and Location Experiment (FILE) which is scheduled for the 1980 Shuttle flight. The FILE experiment is described with attention given to technology needs, development plan, feature recognition and classification, and cloud-snow detection/discrimination. Pointing, tracking and navigation received particular consideration, and it is concluded that this technology plan is viewed as an alternative to approaches to real-time acquisition that are based on extensive onboard format and inventory processing and reliance upon global-satellite-system navigation data.