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The Magellan Mission consists of a single spacecraft to be placed in an elliptical orbit around Venus. The main objective of the mission is to perform radar imaging, altimetry, and reflectivity of 90 percent of the planet for one Venusian year (243 days). A flight profile is given, and information is presented in tabular form on the following topics: Deep Space Network support, frequency assignments, telemetry, command, and tracking support responsibilities.
The STS-64 Space Shuttle Program Mission Report summarizes the Payload activities as well as the Orbiter, External Tank (ET), Solid Rocket Booster (SRB), Redesigned Solid Rocket Motor (RSRM), and the Space Shuttle main engine (SSME) systems performance during the sixty-fourth flight of the Space Shuttle Program and the nineteenth flight of the Orbiter vehicle Discovery (OV-103). In addition to the Orbiter, the flight vehicle consisted of an ET that was designated ET-66; three SSMEs that were designated as serial numbers 2031, 2109, and 2029 in positions 1, 2, and 3, respectively; and two SRB's that were designated Bl-068. The RSRM's that were installed in each SRB were designated as 360L041 A for the left SRB, and 360L041 B for the right SRB. The primary objective of this flight was to successfully perform the planned operations of the Lidar In-Space Technology Experiment (LITE), and to deploy the Shuttle Pointed Autonomous Research Tool for Astronomy (SPARTAN) -201 payload. The secondary objectives were to perform the planned activities of the Robot Operated Materials Processing System (ROMPS), the Shuttle Amateur Radio Experiment - 2 (SAREX-2), the Solid Surface Combustion Experiment (SSCE), the Biological Research in Canisters (BRIC) experiment, the Radiation Monitoring Equipment-3 (RME-3) payload, the Military Application of Ship Tracks (MAST) experiment, and the Air Force Maui Optical Site Calibration Test (AMOS) payload.
This final report summarizes the research work conducted under NASA's Physical Oceanography Program, entitled, GFO-1 Geophysical Data Record And Orbit Verifications For Global Change Studies, for the investigation time period from December 1, 1997 through November 30, 2000. The primary objectives of the investigation include providing verification and improvement for the precise orbit, media, geophysical, and instrument corrections to accurately reduce U.S. Navy's Geosat-Followon-1 (GFO-1) mission radar altimeter data to sea level measurements. The status of the GFO satellite (instrument and spacecraft operations, orbital tracking and altimeter) is summarized. GFO spacecraft has been accepted by the Navy from Ball Aerospace and has been declared operational since November, 2000. We have participated in four official GFO calibration/validation periods (Cal/Val I-IV), spanning from June 1999 through October 2000. Results of verification of the GFO orbit and geophysical data record measurements both from NOAA (IGDR) and from the Navy (NGDR) are reported. Our preliminary results indicate that: (1) the precise orbit (GSFC and OSU) can be determined to approx. 5 - 6 cm rms radially using SLR and altimeter crossovers; (2) estimated GFO MOE (GSFC or NRL) radial orbit accuracy is approx. 7 - 30 cm and Operational Doppler orbit accuracy is approx. 60 - 350 cm. After bias and tilt adjustment (1000 km arc), estimated Doppler orbit accuracy is approx. 1.2 - 6.5 cm rms and the MOE accuracy is approx. 1.0 - 2.3 cm; (3) the geophysical and media corrections have been validated versus in situ measurements and measurements from other operating altimeters (T/P and ERS-2). Altimeter time bias is insignificant with 0-2 ms. Sea state bias is about approx. 3 - 4.5% of SWH. Wet troposphere correction has approx. 1 cm bias and approx. 3 cm rms when compared with ERS-2 data. Use of GIM and IRI95 provide ionosphere correction accurate to 2-3 cm rms during medium to high solar activities; (4) the noise of the GFO altimeter data (uncorrected SSH) is about 15 mm, compared to 19 min for ERS-2, and 12 min for TOPEX. It is anticipated that the operational GFO-1 altimeter data will contribute to a number of researches in physical oceanography. A list of relevant presentations and publications is attached.
In response to severe weather conditions, traffic management coordinators (TMCs) reroute air traffic around regions of airspace affected by the severe weather. Presently, acceptable reroutes are specified by issuing reroute advisories. Advisories, based on reroutes published in the National Severe Weather Playbook, consist of several routes describing routing options. These reroutes are selected by TMCs based on their understanding of weather conditions and their previous experience dealing with similar weather conditions. Providing recommendations and analysis of available reroute options could assist the TMCs in making rerouting decisions. While reroute advisories have historically been based on Playbook plays, plays are frequently modified or combined to generate an advisory. Thus, it is natural to present rerouting suggestions to TMCs as modified Playbook plays. The challenge here is to compare advisory subroutes and play subroutes in a meaningful way in order to map advisories back to the Playbook plays upon which they may have been based. In this work, several subroute comparison metrics are presented and discussed. One of these metrics is then used to match advisories to Playbook plays. With the development and implementation of NextGen technologies, there is currently a trend of moving away from the pre-defined Playbook plays (and related advisories) in favor of a more precise specification of trajectories using GPS based navigation tools, such as area navigation (RNAV). Moving towards ubiquitous use of RNAV routes, the objective of rerouting flights will be met with more precisely specified and accurately flown RNAV routes. In the final version of this paper, significant RNAV routes will be identified by finding RNAV routes that are flown frequently. This will require a trajectory comparison technique to compare actually flown flight tracks to specified RNAV routes. The metrics developed here will be used or modified for this task.
We have previously shown that humans can pursue the motion of objects whose trajectories can be recovered only by spatio-temporal integration of local motion signals. We now explore the integration rule used to derive the target-motion signal driving pursuit. We measured the pursuit response of 4 observers (2 naive) to the motion of a line-figure diamond viewed through two vertical bar apertures (0.2 cd/square m). The comers were always occluded so that only four line segments (93 cd/square m) were visible behind the occluding foreground (38 cd/square m). The diamond was flattened (40 & 140 degree vertex angles) such that vector averaging of the local normal motions and vertical integration (e.g. IOC) yield very I or different predictions, analogous to using a Type II plaid. The diamond moved along Lissajous-figure trajectories (Ax = Ay = 2 degrees; TFx = 0.8 Hz; TFy = 0.4 Hz). We presented only 1.25 cycles and used 6 different randomly interleaved initial relative phases to minimize the role of predictive strategies. Observers were instructed to track the diamond and reported that its motion was always coherent (unlike type II plaids). Saccade-free portions of the horizontal and vertical eye-position traces sampled at 240 Hz were fit by separate sinusoids. Pursuit gain with respect to the diamond averaged 0.7 across subjects and directions. The ratio of the mean vertical to horizontal amplitude of the pursuit response was 1.7 +/- 0.7 averaged across subjects (1SD). This is close to the prediction of 1.0 from vertical motion-integration rules, but far from 7.7 predicted by vector averaging and infinity predicted by segment- or terminator-tracking strategies. Because there is no retinal motion which directly corresponds to the diamond's motion, steady-state pursuit of our "virtual" diamond is not closed-loop in the traditional sense. Thus, accurate pursuit is unlikely to result simply from local retinal negative feedback. We conclude that the signal driving steady-state pursuit is not the vector average of local motion signals, but rather a more vertical estimate of object motion, derived in extrastriate cortical areas beyond V1, perhaps NIT or MST.
Scientists are turning their focus to the Arctic, site of one of the strongest climate change signals. A new generation of technologies is required to function within that harsh environment, chart evolution of its trace gases and provide new kinds of information for models of the atmosphere. Our response to the solicitation tracks how global atmospheric monitoring was launched more than a half century ago; namely, acquisition of discrete samples of air by flask and subsequent analysis in the laboratory. AOS is proposing to develop a new generation of flask sampling technology. It will enable the new Arctic programs to begin with objective high density sampling of the atmosphere by UAS. The Phase I program will build the prototype flask technology and show that it can acquire and store mol fractions of CH4 and CO2 and value of δ13C with good fidelity. A CAD model will be produced for the entire platform including a package with 100 flasks and the airframe with auto-pilot, electronic propulsion and ground-to-air communications. A mobile flask analysis station will be prototyped in Phase I and designed to final form in Phase II. It expends very small sample per analysis and will interface directly to the flask package integrated permanently into the UAS fuselage. Commercial Applications and Other Benefits: • The New Generation Flask Sampling Technology able to provide a hundred or more samples of air per UAS mission. • A mobile analysis station expending far less sample than the existing ones and small enough to be stationed at the remote sites of Arctic operations. • A new form of validation for continuous trace gas observations from all platforms including the small UAS. • Further demonstration to potential customers of the AOS capabilities to invent, build, deploy and exploit entire platforms for observations of Earth’s atmosphere and ocean. Key Words: Flask Sampler, Mobile Analysis Station, Trace Gas, CO2, CH4, δC13, UAS, Baseline Airborne Observatory, Arctic, Climate Change. Summary for Members of Congress: The air, land and sea of the Arctic combine to produce a large climate change signal. AOS is proposing to develop unmanned airborne technologies able to begin prompt, objective observations of the signal’s atmospheric component.
Over the past two years, with the support of the Department of Energy, Powerhouse developed and launched Access Innovation, a partnership program to better connect clean energy startups with industry and investors for partnership. The program has successfully exceeded the objectives of the grant to pilot and validate successful methods of facilitating partnerships between early stage clean energy companies and industry and investors, secure follow on partnerships for early stage clean energy startups in the form of investment, pilot projects, new advisors, customer agreements, and joint development agreements and to track metrics, analyze, draft findings and distribute lessons on what models are most effective in forming partnerships to inform other organizational best practices.
The Multi-Anode Microchannel Arrays (MAMAs) are a family of photoelectric, photoncounting array detectors that have been developed and qualified specifically for use in space. MAMA detectors with formats as large as 256 x 1024 pixels are now in use or under construction for a variety of imaging and tracking applications. These photo-emissive detectors can be operated in a windowless configuration at extreme ultraviolet and soft X-ray wavelengths or in a sealed configuration at ultraviolet and visible wavelengths. The construction and modes-of-operation of the MAMA detectors are briefly described and the scientific objectives of a number of sounding rocket and Space Shuttle instruments utilizing these detectors are outlined. Performance characteristics of the MAMA detectors that are of fundamental importance for operation in the Space Shuttle environment are described and compared with those of the photo-conductive array detectors such as the CCDs and CIDs.
Virtual Reality (VR) is a way for humans to use computers in visualizing, manipulating and interacting with large geometric data bases. This paper describes a VR infrastructure and its application to marketing, modeling, architectural walk through, and training problems. VR integration techniques used in these applications are based on a uniform approach which promotes portability and reusability of developed modules. For each problem, a 3D object data base is created using data captured by hand or electronically. The object's realism is enhanced through either procedural or photo textures. The virtual environment is created and populated with the data base using software tools which also support interactions with and immersivity in the environment. These capabilities are augmented by other sensory channels such as voice recognition, 3D sound, and tracking. Four applications are presented: a virtual furniture showroom, virtual reality models of the North Carolina Global TransPark, a walk through the Dresden Fraunenkirche, and the maintenance training simulator for the National Guard.
An overview of the NASA Wiring for Space Applications Program and its relationship to NASA's space technology enterprise is given in viewgraph format. The mission of the space technology enterprise is to pioneer, with industry, the development and use of space technology to secure national economic competitiveness, promote industrial growth, and to support space missions. The objectives of the NASA Wiring for Space Applications Program is to improve the safety, performance, and reliability of wiring systems for space applications and to develop improved wiring technologies for NASA flight programs and commercial applications. Wiring system failures in space and commercial applications have shown the need for arc track resistant wiring constructions. A matrix of tests performed versus wiring constructions is presented. Preliminary data indicate the performance of the Tensolite and Filotex hybrid constructions are the best of the various candidates.
In this research program, we obtained and analyzed an X-ray observation of the young nearby intermediate mass pre-main sequence star HD 104237 using the XMM-Newton space-based observatory. The observation was obtained on 17 Feb. 2002. This observation yielded high-quality X-ray images, spectra, and timing data which provided valuable information on the physical processes responsible for the X-ray emission. This star is a member of the group of so-called Herbig Ae/Be stars, which are young intermediate mass (approx. 2 - 4 solar masses) pre-main sequence (PMS) stars a few million years old that have not yet begun core hydrogen burning. The objective of the XMM-Newton observation was to obtain higher quality data than previously available in order to constrain possible X-ray emission mechanisms. The origin of the X-ray emission from Herbig Ae/Be stars is not yet known. These intermediate mass PMS stars lie on radiative tracks and are not expected to emit X-rays via solar-like magnetic processes, nor are their winds powerful enough to produce X-rays by radiative wind shocks as in more massive O-type stars. The emission could originate in unseen low-mass companions, or it may be intrinsic to the Herbig stars themselves if they still have primordial magnetic fields or can sustain magnetic activity via a nonsolar dynamo.
The scientific objective of this research program was to utilize drifter, Jason-1 altimeter data and a variety of wind data for the determination of time mean and time variable wind driven surface currents of the global ocean. To accomplish this task has required the interpolation of 6-hourly winds on drifter tracks and the computation of the wind coherent motions of the drifters. These calculations showed that the Ekman current model proposed by Ralph and Niiler for the tropical Pacific was valid for all the oceans south of 40N latitude. Improvements to RN99 model were computed and poster presentations of the results were given in several ocean science venues, including the November 2004 GODAY meeting in St. Petersburg, FL.
Predictions are given for occultations of catalog stars by asteroids, planets, Titan, and Triton in 1990 and 1991. The predictions are based on a computerized comparison of the occulting bodies' ephemerides and nine major star catalogs. The search is complete for all numbered asteroids whose angular diameters exceed 0.08 arcsec during the search years. Preliminary ground tracks are shown for the more favorable occultations.
Abstract Tricolored bats (Perimyotis subflavus) that roost in subterranean hibernacula have experienced precipitous declines from white-nose syndrome (WNS); however, understudied populations also use during winter non-subterranean roosts such as tree cavities, bridges, and foliage. Our objectives were to determine winter roost use by tricolored bats in an area devoid of subterranean roosts, determine roost microclimates to relate them to growth requirements of the fungal causal agent of WNS, and determine habitat factors influencing winter tree selection. From November to March 2017–2019, we used radiotelemetry to track 15 bats to their day roosts in the upper Coastal Plain of South Carolina and recorded microclimates in accessible tree cavities and bridges. We also characterized habitat and tree characteristics of 24 used trees and 153 random, available trees and used discrete choice models to determine selection. Roost structures included I-beam bridges, cavities in live trees, and foliage. Bridges were warmer and less humid than cavities. Roost temperatures often were amenable to fungal growth (< 19.5°C) but fluctuated widely depending on ambient temperatures. Bats used bridges on colder days (8.7°C ± 5.0 SD) and trees on warmer days (11.3°C ± 5.4). Bats selected low-decay trees closer to streams in areas with high canopy closure and cavity abundance. Bats also appeared to favor hardwood forests and avoid pine forests. Our results suggest that access to multiple roost microclimates might be important for tricolored bats during winter, and forest management practices that retain live trees near streams and foster cavity formation in hardwood forests likely will benefit this species. Our results also suggest tricolored bats using bridge and tree roosts might be less susceptible to WNS than bats using subterranean hibernaculum roosts. Thus, forests in areas without subterranean hibernacula in the southeastern United States that support bats during winter might represent important refugia from WNS for multiple species.
Sensalert is a wearable health tracking application that enables monitoring of a target population’s health status in real-time. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and topography, and calculates the corresponding physiological strain index for each point in time. The objective of this application is to provide early warning, support decision making, and increase situational awareness by displaying comprehensive information and providing alerts at the right time and place. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agencies Bio Surveillance Ecosystem (BSVE). We present the user requirements and design principles for developing this type of application. We hope this work helps and inspires future research in the area of wearable technologies for surveillance.
Here, a statistical passive microwave intensity estimation (PMW-IE) algorithm for estimating the intensity of tropical cyclones (TCs) in the North Atlantic and northeastern and central Pacific basins is developed and tested. The algorithm is derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) 85-GHz brightness temperatures and near-surface rain-rate retrievals to provide objective estimates of current maximum sustained surface winds (Vmax) and 6-h future Vmax of TCs. The full record of TRMM data (1998–2013) including 2326 TMI overpasses of 503 TCs is separated into dependent samples (1998–2010) for model development and independent samples (2011–13) for model verification. The best track intensities are used as dependent variables in a stepwise multiple-regression approach. Separately for each basin, three regression models are derived using selected 1) 85-GHz-only variables, 2) rain-rate-only variables, and 3) combined 85-GHz and rain variables. The algorithms are assessed using independent samples and those with contemporaneous aircraft-reconnaissance measurements. Rain-only and combined models perform better than the 85-GHz-only model. Lower errors are found for estimating the 6-h future Vmax than estimating the current Vmax using all three models. This implies that it is optimal to use passive-microwave-retrieved rain variables observed a few hours earlier to estimate TC intensity. The MAE (RMSE) of 6-h future Vmax is 9 (12) kt (1 kt ≈ 0.51 m s -1 ) when testing the combined models with ATL and EPA independent samples. Aircraft-reconnaissance-based independent samples yields a MAE of 9.6 kt and RMSE of 12.6 kt for estimating 6-h future Vmax.
Modular construction methods have recently gained interest due to the advantages offered in terms of safety, quality, and productivity for projects. In this method, a significant portion of the construction is performed off-site in factories where modular components are built in different workstations, assembled on the production line, and shipped to the site for installation. Due to the labor-intensive nature of tasks, cycle times in modular construction factories are highly variable, which commonly leads to major bottlenecks and delays in construction projects. To remedy this effect, recent methods rely on sensors such as RFID to monitor the production process, which is reportedly expensive, and intrusive to the work process. Recently, computer vision-based methods have been proposed to track the production process in modular construction factories. However, these methods overlook monitoring the assembly process on the production line. Therefore, this paper presents a method to monitor the assembly process by integrating computer vision-based methods with Building Information Modeling (BIM). The proposed method detects the modular units using object segmentation; superimposes the installation area with the corresponding 2D region using BIM, and identifies the installation of the components using image processing techniques. The proposed method has been validated using surveillance videos captured from a modular construction factory in the US. Successful implementation of the proposed method can lead to timely identification of delays during the assembly process and reduce delays in modular integrated construction projects.
The spectral reflectance characteristics of vegetation have been studied with the objective to learn how to extract useful information about the state of surface vegetation from space-borne observing systems, with emphasis on agricultural applications. Results of simulation studies based on high-resolution airborne spectrometer data indicate that changes in biomass, plant pigment, and leaf water content can be independently tracked by monitoring the reflective properties of vegetation with an appropriate selection of bands.