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At least 613 records · Page 34

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE)

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Mission

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗

Software Supports Distributed Operations via the Internet

Multi-mission Encrypted Communication System (MECS) is a computer program that enables authorized, geographically dispersed users to gain secure access to a common set of data files via the Internet. MECS is compatible with legacy application programs and a variety of operating systems. The MECS architecture is centered around maintaining consistent replicas of data files cached on remote computers. MECS monitors these files and, whenever one is changed, the changed file is committed to a master database as soon as network connectivity makes it possible to do so. MECS provides subscriptions for remote users to automatically receive new data as they are generated. Remote users can be producers as well as consumers of data. Whereas a prior program that provides some of the same services treats disconnection of a user from the network of users as an error from which recovery must be effected, MECS treats disconnection as a nominal state of the network: This leads to a different design that is more efficient for serving many users, each of whom typically connects and disconnects frequently and wants only a small fraction of the data at any given time.

Norris, Jeffrey↗

United States Nuclear Rocket Company (USNRC)

Historically, the development of advanced space technology has been accomplished by the federal government providing funding to commercial companies through the standard contracting process. Although recently, commercial space ventures, such as Space X, have begun to develop enhanced commercial space launch capabilities, and many companies provide space related services - including satellite development and operations, advanced technology development still requires (and should require) participation by the federal agency assigned this role - the National Aeronautics and Space Administration (NASA). However, this standard funding model may not be the most efficient and stable means of developing the advanced technology systems. And while the federal government does not need to be involved in areas where private industry can reasonably operate, it should remain the leader in supporting the development of new and advanced space technologies to further increase our national capability. And as these technologies mature, then private industry can begin the commercialization process, freeing up resources and funds for NASA to develop the next generations of advanced space technology. In fact, simply examining the last decades of space technology development shows that there is room for improvement. Part of the problem is that there are realistically two space frontiers. There is the commercialization frontier (the realm of Space X and others) and the exploratory frontier (the realm of NASA.). Often technologies that can support the exploratory frontier can also immediately support the commercialization frontier. Yet, these technologies are still developed under the standard model of federal funding and contracting. Is that really the best way to proceed? In this paper, the argument is put forward that a new process is required, a new paradigm. A consortium of federal agencies as well as commercial companies is needed - in a collaborative rather than a contractual relationship.

Hardin, L. A.↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Pathfinder for Artemis Gateway

The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission was developed by NASA in collaboration with Advanced Space, LLC of Westminster, Colorado. This technology demonstration mission serves as a pathfinder for near rectilinear halo orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) is the intended orbit for NASA’s Artemis Gateway, a small, human-tended space station planned for lunar orbit. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for Gateway’s Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The CAPSTONE mission consists of a 12-unit (U) CubeSat developed, integrated, and tested by the Terran Orbital Corporation that carries a payload communications system capable of cross-link ranging with NASA’s Lunar Reconnaissance Orbiter (LRO). CAPSTONE contains a chip scale atomic clock (CSAC) for a one-way ranging experiment with NASA’s Deep Space Network, a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA’s Launch Services Program, was provided by Rocket Lab on its Electron launch vehicle utilizing their Photon upper stage to deploy the CAPSTONE spacecraft into lunar orbit. The mission launched June 28, 2022. The CAPSTONE spacecraft deployed from Rocket Lab’s Photon stage and traversed an approximately 4 month highly efficient transfer phase entering the NRHO Novermber 13, 2022 for a six-month primary mission phase. The mission is currently in a twelve-month technology enhancement operations phase. The CAPSTONE technology demonstration mission is lead by Advanced Space, LLC. Spacecraft development and mission operations is conducted by Terran Orbital Corporation of Irvine, California. Noted accomplishments for the CAPSTONE mission include demonstration of the accessibility of NHROs, validation of key operational concepts in the NHRO environment, laying the foundation for commercial support of future lunar operations, and accelerating the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology (SST) program, which is one of several programs within NASA’s Space Technology Mission Directorate. The program is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The CAPSTONE mission launch was provided by NASA’s Exploration Systems Development Missions Directorate’s Advanced Exploration Systems Division. Coordination and acquisition of the launch was managed by NASA’s Launch Services Program. The CAPSTONE mission and project status will be presented.

Elwood Agasid↗

Satellite communications experiment for the Ontario air ambulance service

A satellite communications experiment was conducted to develop a reliable voice communications system between paramedics and doctors at certain larger medical centers. The experiment used INMARSAT's Atlantic Ocean Region satellite which provides coverage to the western border of Ontario. Forward downlink power from the satellite is in great demand, so two highly power-efficient modulation schemes were chosen for evaluation during the experiment. These were amplitude-companded single-sideband (ACSSB) and linear predictive coding in conjunction with DMSK modulation. Good performance with a signal to noise ratio of about 10 dB was demonstrated from many parts of the province with the evevation angle to the satellite ranging from five to twenty degrees and with the aircraft both in-flight and on the runway.

Butterworth, John S.↗

Leveraging the Cloud for Robust and Efficient Lunar Image Processing

The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use encounters with remote resources. As part of this discussion this paper will outline some of the technologies employed, the reasons for their selection, the resulting performance metrics and the direction the project is headed based upon the demonstrated capabilities thus far.

Cloud Computing↗

Example of input-output analysis

The thirty sectors included in the ECASTAR energy input-output model were listed. Five of these belong to energy producing sectors, fifteen to manufacturing industries, two to residential and commercial sectors, and eight to service industries. The model is capable of tracing impacts of an action in three dimensions: dollars, BTU's of energy, and labor. Four conservation actions considered were listed and then discussed separately, dealing with the following areas: increase in fuel efficiency, reduction in fuel used by the transportation and warehousing group, manufacturing of smaller automobiles, and a communications/transportation trade-off.

Source record↗

Primary Disaster Field Office (DFO), Lufkin, Texas

On February 1, 2003, the Space Shuttle Columbia broke apart during atmospheric re-entry on mission STS-107; the complexity of such an event cannot be underestimated. The Lufkin Disaster Field Office (DFO) served as the primary DFO for all operations, including staging assets and deploying field teams for search, recovery and security. There were many organizations that had operational experience with disaster recovery. Offers to help came from many groups including the White House Liaison Office, the Department of Defense (DOD), branches of local, state and federal government, the Federal Bureau of Investigation (FBI), the Federal Emergency Management Agency (FEMA), the Environmental Protection Agency (EPA), state police, fire departments, the Texas Forestry Service, the Texas Army National Guard, medical groups, various rescue forces, contractor companies, the Salvation Army, local businesses, and citizens of our country and especially East Texas. The challenge was to know how much help to accept and how to efficiently incorporate their valuable assistance into a comprehensive and cohesive operational plan. There were more than 2,000 people involved with search and recovery.

Wetherbee, James D.↗

Teleoperator system man-machine interface requirements for satellite retrieval and satellite servicing. Volume 1: Requirements

Requirements were determined analytically for the man machine interface for a teleoperator system performing on-orbit satellite retrieval and servicing. Requirements are basically of two types; mission/system requirements, and design requirements or design criteria. Two types of teleoperator systems were considered: a free flying vehicle, and a shuttle attached manipulator. No attempt was made to evaluate the relative effectiveness or efficiency of the two system concepts. The methodology used entailed an application of the Essex Man-Systems analysis technique as well as a complete familiarization with relevant work being performed at government agencies and by private industry.

Malone, T. B.↗

On-board processing concepts for future satellite communications systems

The initial definition of on-board processing for an advanced satellite communications system to service domestic markets in the 1990's is discussed. An exemplar system with both RF on-board switching and demodulation/remodulation baseband processing is used to identify important issues related to system implementation, cost, and technology development. Analyses of spectrum-efficient modulation, coding, and system control techniques are summarized. Implementations for an RF switch and baseband processor are described. Among the major conclusions listed is the need for high gain satellites capable of handling tens of simultaneous beams for the efficient reuse of the 2.5 GHz 30/20 frequency band. Several scanning beams are recommended in addition to the fixed beams. Low power solid state 20 GHz GaAs FET power amplifiers in the 5W range and a general purpose digital baseband processor with gigahertz logic speeds and megabits of memory are also recommended.

Brandon, W. T.↗

Research and technology

As the NASA Center responsible for assembly, checkout, servicing, launch, recovery and operational support of Space Transportation System elements and payloads, Kennedy Space Center is placing emphasis on its research and technology program. In addition to strengthening those areas of engineering and operations technology that contribute to safer, more efficient, and more economical execution of our current mission, we are developing the technological tools needed to execute the Center's mission relative to future programs. The Engineering Development Directorate encompasses most of the laboratories and other Center resources that are key elements of research and technology program implementation, and is responsible for implementation of the majority of the projects in this Kennedy Space Center 1988 Annual Report.

Source record↗

An authoring system for creating a practice environment in the network service field

This paper describes an authoring system whose main purpose is to reduce the cost of developing and maintaining courseware which contains procedural knowledge used in the network service field. This aim can be achieved by considering the characteristics of this field. Material knowledge is divided into two parts, behavioral knowledge and procedural knowledge. We show that both of these parts are constructed by an easy authoring methods and efficient modification algorithms. This authoring system has been used to build several types of courseware, and the development costs have been reduced.

Kiyama, Minoru↗

ScyFlow: An Environment for the Visual Specification and Execution of Scientific Workflows

With the advent of grid technologies, scientists and engineers are building more and more complex applications to utilize distributed grid resources. The core grid services provide a path for accessing and utilizing these resources in a secure and seamless fashion. However what the scientists need is an environment that will allow them to specify their application runs at a high organizational level, and then support efficient execution across any given set or sets of resources. We have been designing and implementing ScyFlow, a dual-interface architecture (both GUT and APT) that addresses this problem. The scientist/user specifies the application tasks along with the necessary control and data flow, and monitors and manages the execution of the resulting workflow across the distributed resources. In this paper, we utilize two scenarios to provide the details of the two modules of the project, the visual editor and the runtime workflow engine.

McCann, Karen M.↗

The Path to NGATS

NGATS operational Improvements and benefits include: 1) Broad area and precision navigation to access and capacity; 2) Airspace access and management to capacity; 3) 4D trajectory based ATM to capacity and efficiency; 4) Reduced separation between aircraft to capacity; 5) Flight deck situational awareness and delegation to capacity and safety; 6) ATM decision support to capacity; 7) Improved weather data and dissemination to capacity and safety; 8) Reduced cost to deliver ATM services to cost; 9) Greatly expanded airport network and improved terminals to capacity.

Scardina, John↗

Embracing Safe Ground Test Facility Operations and Maintenance

Conducting integrated operations and maintenance in wind tunnel ground test facilities requires a balance of meeting due dates, efficient operation, responsiveness to the test customer, data quality, effective maintenance (relating to readiness and reliability), and personnel and facility safety. Safety is non-negotiable, so the balance must be an "and" with other requirements and needs. Pressure to deliver services faster at increasing levels of quality in under-maintained facilities is typical. A challenge for management is to balance the "need for speed" with safety and quality. It s especially important to communicate this balance across the organization - workers, with a desire to perform, can be tempted to cut corners on defined processes to increase speed. Having a lean staff can extend the time required for pre-test preparations, so providing a safe work environment for facility personnel and providing good stewardship for expensive National capabilities can be put at risk by one well-intending person using at-risk behavior. This paper documents a specific, though typical, operational environment and cites management and worker safety initiatives and tools used to provide a safe work environment. Results are presented and clearly show that the work environment is a relatively safe one, though still not good enough to keep from preventing injury. So, the journey to a zero injury work environment - both in measured reality and in the minds of each employee - continues. The intent of this paper is to provide a benchmark for others with operational environments and stimulate additional sharing and discussion on having and keeping a safe work environment.

Dunn, Steven C.↗

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

data management↗