SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The 1993 Shuttle Small Payloads Symposium is a combined symposia of the Get Away Special (GAS), Hitchhiker, and Complex Autonomous Payloads (CAP) programs, and is proposed to continue as an annual conference. The focus of this conference is to educate potential Space Shuttle Payload Bay users as to the types of carrier systems provided and for current users to share experiment concepts.
Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.
This paper presents case-studies of 9 shuttle crewmembers (prime and alternates) and one U.S. Navy F-18 pilot, as they participated in all preflight training and testing activities in support of a life sciences flight experiment aboard Spacelab-J, and Spacelab-3. The primary objective of the flight experiment was to determine if Autogenic-feedback training (AFT), a physiological self-regulation training technique would be an effective treatment for motion sickness and space motion sickness in these crewmembers. Additional objectives of this study involved the examining human Physiological- responses to motion sickness on Earth and in space, as well as developing predictive criteria for susceptibility to space motion sickness based on ground-based data. Comparisons of these crewmembers are made to a larger set of subjects from previous experiments (treatment and test-only controls subjects). This paper describes all preflight methods, results and proposed changes for future tests.
The Feature Identification and Location Experiment (FILE), which was flown on the second Space Shuttle flight to test a technique for real-time, autonomous classification of water, vegetation and bare land as well as clouds, snow and ice, senses earth radiation in spectral bands centered at 0.65 and 0.85 microns. The radiance ratio classification algorithm has successfully made automatic data selection decisions. A classification image obtained on the mission is providing data needed to evaluate the FILE algorithm and overall system performance.
The Flight Telerobotic Servicer (FTS) will provide a telerobotic capability to the Space Station in the early assembly phases of the program and will be used for assembly, maintenance, and inspection throughout the lifetime of the Station. Here, the FTS design approach to the development of autonomous capabilities is discussed. The FTS telerobotic workstations for the Shuttle and Space Station, and facility for on-orbit storage are examined. The rationale of the FTS with regard to ease of operation, operational versatility, maintainability, safety, and control is discussed.
A new refrigerator which uses resonant high amplitude sound in inert gases to pump heat is described and demonstrated. The phasing of the thermoacoustic cycle is provided by thermal conduction. This 'natural' phasing allows the entire refrigerator to operate with only one moving part (the loudspeaker diaphragm). The thermoacoustic refrigerator has no sliding seals, requires no lubrication, uses only low-tolerance machine parts, and contains no expensive components. Because the compressor moving mass is typically small and the oscillation frequency is high, the small amount of vibration is very easily isolated. This low vibration and lack of sliding seals makes thermoacoustic refrigeration an excellent candidate for food refrigeration and commercial/residential air conditioning applications. The design, fabrication, and performance of the first practical, autonomous thermoacoustic refrigerator, which will be flown on the Space Shuttle (STS-42), are described, and designs for terrestrial applications are presented.
The problems involved in automated autonomous rendezvous are briefly reviewed, and the Rendezvous Expert (RENEX) expert system is discussed with reference to its goals, approach used, and knowledge structure and contents. RENEX has been developed to support streamlining operations for the Space Shuttle and Space Station program and to aid definition of mission requirements for the autonomous portions of rendezvous for the Mars Surface Sample Return and Comet Nucleus Sample return unmanned missions. The experience with REMEX to date and recommendations for further development are presented.
Increasing interest and investment in connected, automated, and electric vehicles as well as mobility-as-a-service (MaaS) concepts are paving the way for the next major transformation in transportation through automated and shared mobility. The initial excitement toward rapid deployment and adoption of automated vehicles (AVs) has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geofenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities in relation to benefits or disadvantages of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This paper presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles (SAVs) in geofenced regions. This paper describes the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina, U.S. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.
The flight crew of the STS-72 Space Shuttle Orbiter Endeavour Cmdr. Brian Duffy, Pilot Brent W. Jett, and Mission Specialists; Leroy Chiao, Daniel T. Barry, Winston E. Scott, and Koichi Wakata (NASDA) present an overview of their mission, whose primary objective is the retrieval of two research satellites. The major activities of the mission will include retrieval of the Japanese Space Flyer Unit (SFU), which was launched aboard a Japanese H-2 rocket to conduct a variety of microgravity experiments. In addition, the STS-72 crew will deploy the AST-Flyer, a satellite, that will fly free of the Shuttle for about 50 hours. Four experiments on the science platform will operate autonomously before the satellite is retrieved by Endeavour's robot arm. Three of Endeavour's astronauts will conduct a pair of spacewalks during the mission to test hardware and tools that will be used in the assembly of the Space Station. Video footage includes the following: prelaunch and launch activities; the crew eating breakfast; shuttle launch; retrieval of the Japanese Space Flyer Unit (SFU); suit-up and EVA-1; EVA-2; crew members performing various physical exercises; various earth views; and the night landing of the shuttle at KSC.
The use of fuzzy sets in modeling the human expert for certain Space Shuttle navigation problems is discussed with particular reference to onboard and ground console data monitoring tasks traditionally performed by astronauts and engineers. Specific problems include determining the quality of sensor data and of the filter state. The results obtained in this study indicate that fuzzy sets can be successfully used in modeling human reaction to rules in decision-making processes. They can also be used within software systems where guidelines have traditionally been used to set strict tolerances.
GPS based programs at NASA-JSC are enumerated on page 1: Several Detailed Test Objectives (DTOs) flown on STS missions featuring GPS are the primary focus of the DTO: GANE on STS-77, RGPS RME on STS-80, ARPK on STS-84 & STS-86, SIGI DTOs on STS-88, STS-101 (SOAR and STS-108 (CRV); Shuttle program switching to GPS receivers for navigation sensor; International Space Station baselined with GPS based navigation and attitude determination. Operational since 2002; Crew return vehicle features GPS based navigation; Mini Autonomous Extravehicular Robotic Camera (AERCam) relies on precise real-time relative GPS for relative navigation. Shuttle GPS testing is narrated in page 2.
Discussion of the astronaut's role in the Space Shuttle and its associated payload operations. It is shown that there will be a shift in the astronaut's tasks as the Shuttle system matures. The Shuttle is designed for automatic guidance, navigation, and control, and the need for active piloting will accordingly decrease. With the shift to onboard autonomous operation, the system management role will expand. Direct tasks with delivery/recovery and laboratory/observatory payloads will continue to expand throughout the Shuttle program duration through the 1980s.
A review is presented of the secondary or piggyback flight opportunities that are presently available along with an overview of NASA's secondary payload plans, policies and requirements. When there is excess capacity on either the Space Shuttle or an expendable launch vehicle (ELV), a logical step is to carry a secondary payload to provide a relatively low-cost launch for small satellites. NASA has already flown more than a dozen piggyback payloads on the Delta rocket. The Small Expendable Deployment system experiment is currently planned as the first of small space experiments launched as a piggyback on an ELV. Some details are provided on various secondary payload flight opportunities aboard the Space Shuttle including the Get-Away Special Canister Program, the complex autonomous payload, the Hitchhiker Program, and the middeck lockers concept. Also described are several secondary payload possibilities utilizing ELVs.
As NASA plans to send human explorers beyond low Earth orbit, onward to Mars and other destinations in the solar system, there will be new challenges to address in terms of HSI. These exploration missions will be quite different from the current and past missions such as Apollo, Shuttle, and International Space Station. The exploration crew will be more autonomous from ground mission control with delayed, and at times, no communication. They will have limited to no resupply for much longer mission durations. Systems to deliver and support extended human habitation at these destinations are extremely complex and unique, presenting new opportunities to employ HSI practices. In order to have an effective and affordable HSI implementation, both research and programmatic efforts are required. Currently, the HSI-related research at NASA is primarily in the area of space human factors and habitability. The purpose is to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration beyond low Earth orbit, and update standards, requirements, and processes to verify and validate these requirements. In addition, HSI teams are actively engaged in technology development and demonstration efforts to influence the mission architecture and next-generation vehicle design. Finally, appropriate HSI references have been added to NASA' s systems engineering documentation, and an HSI Practitioner's Guide has been published to help design engineers consider HSI early and continuously in the acquisition process. These current and planned HSI-related activities at NASA will be discussed in this panel.
Increasing interest and investment in connected, automated, and electric vehicles (CAEVs), and mobility-as-a-service (MaaS) concepts are paving the way for the next major shift in transportation through automated and shared mobility. The initial excitement towards rapid deployment and adoption of automated vehicles has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geo-fenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities regarding benefits or dis-benefits of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This presentation provide the details of a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as Automated Mobility District (AMD) modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles in geofenced regions.The AMD modeling and simulation task is funded through DOE's SMART Mobility Consortium. This presentation outlines the progress of the AMD modeling and simulation task in FY19, including case studies conducted in Greenville, SC, and Austin, TX.
The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.
This paper introduces a spatial pattern recognition processing concept involving the use of spectral feature classification technology and coherent optical correlation. The concept defines a hybrid image processing system incorporating both digital and optical technology. The hybrid instrument provides simplified pseudopattern images as functions of pixel classification from information embedded within a real-scene image. These pseudoimages become simplified inputs to an optical correlator for use in a subsequent pattern identification decision useful in executing landmark pointing, tracking, or navigating functions. Real-time classification is proposed as a research tool for exploring ways to enhance input signal-to-noise ratio as an aid in improving optical correlation. The approach can be explored with developing technology, including a current NASA Langley Research Center technology plan that involves a series of related Shuttle-borne experiments. A first-planned experiment, Feature Identification and Location Experiment (FILE), is undergoing final ground testing, and is scheduled for flight on the NASA Shuttle (STS2/flight OSTA-1) in 1980. FILE will evaluate a technique for autonomously classifying earth features into the four categories: bare land; water; vegetation; and clouds, snow, or ice.
This paper describes the concept of a large gamma-ray imaging telescope system (GRITS) which will provide sufficient sensitivity for the identification of faint objects to be catalogued by the Gamma-Ray Observatory. The technique used in this telescope for the detection of gamma rays is based on the conversion of the incident gamma ray into an electron-positron pair which subsequently produces Cherenkov radiation. The gamma ray is identified by a unique signature based on a sequence of time-delayed coincidence events. The GRITS telescope will use the extended Shuttle external tank, ET, as the pressure vessel necessary for the gas-Cherenkov process. Astronauts from the Shuttle or the Space Station performing EVA will convert ET to an autonomous spacecraft and install the telescope inside the ET.