Robotics Demo Peer Group Review
This animated color video shows the Shuttle robot arm performing construction on the Spacelab.
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This animated color video shows the Shuttle robot arm performing construction on the Spacelab.
We introduce a real-time design methodology for large scale, distributed, parallel architecture, real-time systems (LDPARTS), as an alternative to those methods using rate or dead-line monotonic analysis. In our method the fundamental units of prioritization, work items, are domain specific objects with timing requirements (deadlines) found in user's specification. A work item consists of a collection of tasks of equal priority. Current scheduling theories are applied with artifact deadlines introduced by the designer whereas our method schedules work items to meet user's specification deadlines (sometimes called end-to-end deadlines). Our method supports these scheduling properties. Work item scheduling is based on domain specific importance instead of task level urgency and still meets as many user specification deadlines as can be met by scheduling tasks with respect to urgency. Second, the minimum (closest) on-line deadline that can be guaranteed for a work item of highest importance, scheduled at run time, is approximately the inverse of the throughput, measured in work items per second. Third, throughput is not degraded during overload and instead of resorting to task shedding during overload, the designer can specify which work items to shed. We prove these properties in a mathematical model.
The last of NASA's Great Observations, the Space Infrared Telescope Facility (SIRTF), is undergoing checkout 15,000 mi. from Earth this week following launch of the $1.2-billion mission here on board a Boeing Delta II Heavy booster Aug. 25. The SIRTF mission has been 25 years in the making. By using innovative technology and a unique "Earth-trailing" orbit, the Jet Propulsion Laboratory and Lockheed-Martin were able to reduce mission cost by about $800 million with no loss in expected science or mission life-time.
Since the loss of Columbia on February 1, 2003, the Space Shuttle Program (SSP) has significantly improved the understanding of launch and ascent debris, implemented hardware modifications to reduce debris, and conducted tests and analyses to understand the risks associated with expected debris. The STS-114 flight rationale for expected debris relies on a combination of all three of these factors. A number of design improvements have been implemented to reduce debris at the source. The External Tank (ET) thermal protection system (TPS) foam has been redesigned and/or process improvements have been implemented in the following locations: the bipod closeout, the first ten feet of the liquid hydrogen (LH2) tank protuberance air load (PAL) ramp, and the LH2 tank-to-intertank flange closeout. In addition, the forward bipod ramp has been eliminated and heaters have been installed on the bipod fittings and the liquid oxygen (LO2) feedline forward bellows to prevent ice formation. The Solid Rocket Booster (SRB) bolt catcher has been redesigned. The Orbiter reaction control system (RCS) thruster cover "butcher paper" has been replaced with a material that sheds at a low velocity. Finally, the pad area has been cleaned to reduce debris during lift-off.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to successfully land large payloads at Mars for both robotic and human-scale missions. Year 1 of the study focused on technologies required for Exploration-class missions to land payloads of 10 to 50 mt. Inflatable decelerators, rigid aeroshell and supersonic retro-propulsion emerged as the top candidate technologies. In Year 2 of the study, low TRL technologies identified in Year 1, inflatables aeroshells and supersonic retropropulsion, were combined to create a demonstration precursor robotic mission. This part of the EDL-SA Year 2 effort, called Exploration Feed Forward (EFF), took much of the systems analysis simulation and component model development from Year 1 to the next level of detail.
The ancient Martian orthopyroxenite ALH84001experienced a complex history of impact and aqueous alteration events. Here we summarize Sm-147-Nd-143 and Sm-146-Nd-142 analyses performed at JSC. Further, using REE data, we model the REE abundance pattern of the basaltic magma parental to ALH84001 cumulus orthopyroxene. We find the Sm-146-Nd-142 isotopic data to be consistent with isotopic evolution in material having the modeled Sm/Nd ratio from a time very close to the planet's formation to igneous crystallization of ALH84001 as inferred from the Sm-Nd studies.
Mr. Christopher Miller with the Kennedy Space Center (KSC) NASA Safety & Mission Assurance (S&MA) office requested the NASA Engineering and Safety Center's (NESC) technical support on March 15, 2012, to review and make recommendations on the structural analysis being performed for the Orbiter Atlantis static display at the KSC Visitor Center. The principal focus of the assessment was to review the engineering firm's structural analysis for lifting and aligning the orbiter and its static display configuration
This report details a sub-task (regarding Uncertainty Propagation for Model Validation) from a NASA Engineering and Safety Center assessment that is a multi-year activity spanning the complete development of the Space Launch System integrated vehicle structural dynamic models, and the development of the certification of flight readiness for the Artemis 1 and Artemis 2 vehicles and their variants.
A system noise assessment is performed for a Boeing-designed Transonic Truss-Braced Wing, resized using NASA tools in order to estimate the performance of the configuration relative to NASA noise goals. For comparison, a conventional configuration with comparable mission requirements, technology assumptions, and design assumptions is also assessed. Following the baseline noise assessments, a noise reduction technology roadmap is developed from technologies expected to mature to an appropriate technology readiness level by the targeted entry into service date. Noise prediction of both baseline configurations shows a 4.7 EPNdB cumulative certification advantage for the Transonic Truss-Braced Wing. Both configurations fall short of the mid term NASA noise goal, even with application of the noise reduction technologies in the roadmap. The roadmap provides 7.3 EPNdB of noise reduction for the conventional configuration and 7.8 EPNdB for the Transonic Truss-Braced Wing.
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NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.
The final stages of this work saw changes to the original framework, as well as the completion and integration of several data processing services. Initially, it was thought that a peer-to-peer architecture was necessary to make this work possible. The peer-to-peer architecture provided many benefits including the dynamic discovery of new services that would be continually added. A prototype example was built and while it showed promise, a major disadvantage was seen in that it was not easily integrated into the existing data environment. While the peer-to-peer system worked well for finding and accessing distributed data processing services, it was found that its use was limited by the difficulty in calling it from existing tools and services. After collaborations with members of the data community, it was determined that our data processing system was of high value and that a new interface should be pursued in order for the community to take full advantage of it. As such; the framework was modified from a peer-to-peer architecture to a more traditional web service approach. Following this change multiple data processing services were added. These services include such things as coordinate transformations and sub setting of data. Observatory (VHO), assisted with integrating the new architecture into the VHO. This allows anyone using the VHO to search for data, to then pass that data through our processing services prior to downloading it. As a second attempt at demonstrating the new system, a collaboration was established with the Collaborative Sun Earth Connector (CoSEC) group at Lockheed Martin. This group is working on a graphical user interface to the Virtual Observatories and data processing software. The intent is to provide a high-level easy-to-use graphical interface that will allow access to the existing Virtual Observatories and data processing services from one convenient application. Working with the CoSEC group we provided access to our data processing tools from within their software. This now allows the CoSEC community to take advantage of our services and also demonstrates another means of accessing our system.