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This paper presents a cooperative effort where the Software Engineering Institute and the Space Shuttle Onboard Software Project could experiment applying Statistical Process Control (SPC) analysis to inspection activities. The topics include: 1) SPC Collaboration Overview; 2) SPC Collaboration Approach and Results; and 3) Lessons Learned.
I think the biggest single issue in addressing any of the problems that I have mentioned is we do not have a way to marshal the adequate academic and intellectual resources in this country to solve these problems. So I would suggest that the country take a look at some of the national educational institutes that we have in the military. There are eight or nine of them The National War College, Industrial College of the Armed Services, and so forth. We need to have a National Space Institute that has some kind of Federal Charter. Its purpose would be to make available the intellectual resources necessary for the human exploration of space. It would have this as a single purpose. It would be a place where the appropriate knowledge, the experience, and the intellectual energy could be focused on this single goal. It would have the status of other national colleges. It would also be a virtual college or a university, and it would be collaborative with colleges and universities and other learning institutions all across the country and perhaps the world. Experts on space from almost any corridor could participate and contribute to what this institute would do. It also would have very strong business participation. We would have folks from industry come to this environment, learn, go back and work, and then come back and teach. It would be a means for individuals to become more proficient in the technical engineering operations, as well as the business and political aspects of space exploration. Such a national space institute also would need to establish and maintain close contact with ongoing development and operations in human space programs.
This abstract describes a research effort to apply technological advances in virtual reality simulation and computer-based games to create behavioral modification programs for individuals with Autism Spectrum Disorder (ASD). The research investigates virtual social skills training within a 3D game environment to diminish the impact of ASD social impairments and to increase learning capacity for optimal intellectual capability. Individuals with autism will encounter prototypical social contexts via computer interface and will interact with 3D avatars with predefined roles within a game-like environment. Incremental learning objectives will combine to form a collaborative social environment. A secondary goal of the effort is to begin the research and development of virtual reality exercises aimed at triggering the release of neurotransmitters to promote critical aspects of synaptic maturation at an early age to change the course of the disease.
Since the 1990's, when the Class I Ozone Depleting Substance (ODS) chlorofluorocarbon‐113 (CFC‐113) was banned, NASA's propulsion test facilities at Marshall Space Flight Center (MSFC) and Stennis Space Center (SSC) have relied upon hydrochlorofluorocarbon‐225 (HCFC‐225) to safely clean and verify the cleanliness of large scale propulsion oxygen systems. Effective January 1, 2015, the production, import, export, and new use of HCFC‐225, a Class II ODS, was prohibited by the Clean Air Act. In 2012 through 2014, leveraging resources from both NASA and the Defense Logistics Agency ‐ Aviation Hazardous Minimization and Green Products Branch, test labs at MSFC, SSC, and Johnson Space Center's White Sands Test Facility (WSTF) collaborated to seek out, test, and qualify a replacement for HCFC‐225 that is both an effective cleaner and safe for use with oxygen systems. This presentation summarizes the tests performed, results, and lessons learned. It also demonstrates the benefits of cross‐agency collaboration in a time of limited resources.
Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.
In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.
In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.
The goal of climate informatics, an emerging discipline, is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the field's remaining challenges. Given the impact of climate change, understanding the climate system is an international priority. The goal of climate informatics is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the remaining challenges.
The drive for the journey to Mars is in a higher gear than ever before. We are developing new spacecraft and life support systems to take humans to the Red Planet. The journey that development hardware takes before its final incarnation in a fully integrated spacecraft can take years, as is the case for the Orion environmental control and life support system (ECLSS). Through the Pressure Integrated Suit Test (PIST) series, NASA personnel at Johnson Space Center have been characterizing the behavior of a closed loop ECLSS in the event of cabin depressurization. This kind of testing - one of the most hazardous activities performed at JSC - requires an iterative approach, increasing in complexity and hazards). The PIST series, conducted in the Crew and Thermal Systems Division (CTSD) 11-ft Chamber, started with unmanned test precursors before moving to a human-in-the-loop phase, and continues to evolve with the eventual goal of a qualification test for the final system that will be installed on Orion. Meanwhile, the Human Exploration Spacecraft Testbed for Integration and Advancement (HESTIA) program is an effort to research and develop technologies that will work in concert to support habitation on Mars. September 2015 marked the first unmanned HESTIA test, with the goal of characterizing how ECLSS technologies work together in a closed environment. HESTIA will culminate in crewed testing, but it can benefit from the lessons learned from another test that is farther ahead in its development and life cycle. Discussing PIST and HESTIA, this paper illustrates how we approach testing, the kind of information that facility teams need to ensure efficient collaborations and successful testing, and how we can apply what we learn to execute future tests.
A three-day symposium sponsored by NASA was held in July 2022 in Suffolk, Virginia on the subject of Turbulence Modeling: Roadblocks, and the Potential for Machine Learning. This meeting brought together over 80 experts from academia, government, and industry to discuss critical issues for Reynolds-averaged Navier-Stokes turbulence and transition models, as well as to evaluate the results from a collaborative testing challenge based on data-driven methods and machine learning technology. This report puts this symposium in context with an earlier similar meeting and summarizes many of the questions, discussions, and conclusions that arose from it. Next steps are suggested.
A three-day symposium sponsored by NASA was held in July 2022 in Suffolk, Virginia on the subject of Turbulence Modeling: Roadblocks, and the Potential for Machine Learning. This meeting brought together over 80 experts from academia, government, and industry to discuss critical issues for Reynolds-averaged Navier-Stokes (RANS) turbulence and transition models, as well as to evaluate the results from a collaborative testing challenge based on data-driven methods and machine learning (ML) technology. The symposium represents a continuation of an earlier symposium sponsored by the University of Michigan and NASA, held in Ann Arbor, MI in 2017. The 2022 symposium included a wide variety of talks on the subjects of RANS and ML, five invited talks, and three panel discussions. This talk summarizes the main outcomes of the symposium, and includes suggested recommendations and future directions.
A conference was held on March 18-20, 1997 to investigate the lessons learned by the Aeronautics Cooperative Agreement Projects with regard to the most effective strategies for developing instruction for the World Wide Web. The conference was a collaboration among the NASA Aeronautics and Space Transportation Technology Centers (Ames, Dryden, Langley, and Lewis), NASA Headquarters, the University of Idaho and The Pennsylvania State University. The conference consisted of presentations by the Aeronautics Cooperative Agreement Teams, the University of Idaho, and working sessions in which the participants addressed teacher training and support, technology, evaluation and pedagogy. The conference was also undertaken as part of the Dryden Learning Technologies Project which is a collaboration between the Dryden Education Office and The Pennsylvania State University. The DFRC Learning Technology Project goals relevant to the conference are as follows: conducting an analysis of current teacher needs, classroom infrastructure and exemplary instructional World Wide Web sites, and developing models for Web-enhanced learning environments that optimize teaching practices and student learning.
Faculty in the Department of Physical, Environmental and Computer Sciences strongly believe in the concept that undergraduate research and research-related activities must be integrated into the fabric of our undergraduate Science and Technology curricula. High level skills, such as problem solving, reasoning, collaboration and the ability to engage in research, are learned for advanced study in graduate school or for competing for well paying positions in the scientific community. One goal of our academic programs is to have a pipeline of research activities from high school to four year college, to graduate school, based on the GISS Institute on Climate and Planets model.
The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi-Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the life-cycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reachback support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-ofthe- art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.
The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi- Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the lifecycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reach-back support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-of-the-art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.
The NASA Ames Research Center (ARC) Office of the Chief Scientist (OCS) is part of the Center Management. The OCS adds value to the organization by encouraging and facilitating innovation and value to the Agency, Nation, and the scientific community through its well-developed, diverse, and strategically formed charter. The OCS provides the Center with the oversight and advice by facilitating and evaluating the Scientific Innovation Fund (SIF) and promoting science-based research partnerships. Additionally, the Office contributes to to the Agency by organizing annual Summer Series Colloquia, Workshops, and support to the Early Career Network, which allows for international and inter-agency collaborations. Working at the OCS allowed me to further learn about the working of the Office and how the Office engages and provides guidance with rest of the Center and the Agency. As part of my internship, I am working on developing the initial infrastructure required for the organization of the Standardized Distributed Workshop and further developing the layout for the Hibernation Workshop. The Standardized Distributed System workshop will investigate the scope of developing and using standardized distributed systems for a wide range of applications including satellite systems, aerospace-oriented systems, water-based systems, automobiles, and various other robotics applications. The goal of this workshop is to determine the feasibility of developing a standardized distributed system that can be customized for different technological applications, which will enable resource sharing, openness, robustness, and fault tolerance. This workshop will bring together experts from different fields, including satellite operations, unmanned aerial vehicles, aircraft operation and management, and artificial intelligence to provide a global evaluation of the aspects associated with the development and adoption of distributed systems. The workshop will also guide the participants through state of the art distributed systems, discuss some of the challenges in designing control systems with a distributed structure, and consider the future of distributed system based technologies for future applications. Additionally, I am also working on finalizing the details and documentation for the proposed Hibernation Workshop. This workshop will address the phenomenon of hibernation through three major aspects: hibernation on Earth, hibernation in space, and knowledge gaps in the approaches to future deep space exploration. The primary objective of the workshop is to explore the current state of science in the area of hibernation, and as a scientific community, explore the gaps and challenges preventing this scientific field from advancing to the next level. This workshop will consist of presentations, panel discussions, and breakout sessions focused on addressing this scientific field, and bringing experts from educational and commercial sectors together. As a part of my internship report, I will be document the process of planning these workshops and further provide a brief summary of my experience with the 2016 NASA Ames Summer Series and various professional visits.
NASA’s Earth Science Division (ESD) is committed to empower Environmental Justice (EJ) communities by expanding awareness, accessibility, and use of Earth science data to enable contributions to Earth science research and applications. To that end, the NASA Earth Science Data Systems (ESDS) Program developed an EJ Data Catalog, a simple guide to NASA datasets and socioeconomic datasets that may be useful in EJ research. The EJ Data Catalog is divided by topics—such as disasters, urban flooding, extreme heat, food availability, water availability, climate, and health and air quality—and possible use cases for each dataset. The new version of the EJ Data Catalog is now integrated into NASA’s Science Discovery Engine (SDE), an open-source science infrastructure to enable collaborative and interdisciplinary science. In this workshop you will learn about NASA’s Equity and Environmental Justice (EEJ) activities and opportunities as well as participate on an interactive live demo of the new Science Discovery Engine for Environmental Justice.
The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.