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At least 1,801 records · Page 100

Multi-Center Implementation of NPR 7123.1A: A Collaborative Effort

Collaboration efforts between MSFC and GRC Engineering Directorates to implement the NASA Systems Engineering (SE) Engine have expanded over the past year to include other NASA Centers. Sharing information on designing, developing, and deploying SE processes has sparked further interest based on the realization that there is relative consistency in implementing SE processes at the institutional level. This presentation will provide a status on the ongoing multi-center collaboration and provide insight into how these NPR 7123.1A SE-aligned directives are being implemented and managed to better support the needs of NASA programs and projects. NPR 7123.1A, NASA Systems Engineering Processes and Requirements, was released on March 26, 2007 to clearly articulate and establish the requirements on the implementing organization for performing, supporting, and evaluating SE activities. In early 2009, MSFC and GRC Engineering Directorates undertook a collaborative opportunity to share their research and work associated with developing, updating and revising their SE process policy to comply and align with NPR 7123.1A. The goal is to develop instructions, checklists, templates, and procedures for each of the 17 SE process requirements so that systems engineers will be a position to define work that is process-driven. Greater efficiency and more effective technical management will be achieved due to consistency and repeatability of SE process implementation across and throughout each of the NASA centers. An added benefit will be to encourage NASA centers to pursue and collaborate on joint projects as a result of using common or similar processes, methods, tools, and techniques.

Hall, Phillip B.↗

Extracting Space Weather Information from Research Models: Opportunities and Challenges

In addition to supporting space research in the international community, the Community Coordinated Modeling Center (CCMC) has as its second objective to apply the power of modern research models toward space weather specification and forecasting. Motivated by the objectives to test models and to ease the transition of research models to space weather forecasting organizations, the CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products for space weather forecasting support. Over time, these activities have produced tailored products for partners, as well as tools, which address the space weather needs of NASA's robotic mission community. All tools are accessible via a configurable, flexible interface. During this process, CCMC has accumulated substantial experience in understanding model performance, as well as in the design and execution of realtime systems. This presentation will focus on lessons learned and it will suggest low hanging fruit for transition to operations at partner agencies.

Hesse, Michael↗

Using a Multicore Processor for Rover Autonomous Science

Multicore processing promises to be a critical component of future spacecraft. It provides immense increases in onboard processing power and provides an environment for directly supporting fault-tolerant computing. This paper discusses using a state-of-the-art multicore processor to efficiently perform image analysis onboard a Mars rover in support of autonomous science activities.

Mars↗

Advanced Prototype Fan Operating Experience, Post Test Evaluation, and Refurbishment for PLSS 2.0 Test Use

NASA s plans for Extravehicular Activity (EVA) portable life support systems for future exploration missions result in different design requirements than those which led to the combined fan / pump / separator in the current ISS Extravehicular Mobility Unit (EMU). To meet these new requirements, NASA contracted with Hamilton Sundstrand to provide two new prototype fans designed to meet anticipated future system requirements. Based on design trade studies, a high speed fan with mechanical bearing support of the rotating elements and a novel non-metallic barrier canned motor design was developed and implemented in the deliverable prototypes. The prototypes, which used two different bearing lubricants, have been extensively tested in both stand-alone and integrated system tests in NASA laboratories and proven to meet the anticipated performance requirements. Subsequently, they have been subjected to post test inspection and analysis in Hamilton Sundstrand laboratories to assess the effects of integrated operation and resultant exposure to vent loop contaminants. Results have confirmed expectations that one of the lubricants would be superior in this application and the prototype fans have been reassembled with new bearings with the superior lubricant. They have now been returned to the Johnson Space Center for further testing and maturation as part of NASA s PLSS 2.0 integrated test effort. This paper will discuss the test history of these units, resulting test data, the results of post test evaluation, and plans for further testing in the near future.

Hodgson, Edward↗

Potential Applications for Radioisotope Power Systems in Support of Human Exploration Missions

Radioisotope power systems (RPS) for space applications have powered over 27 U.S. space systems, starting with Transit 4A and 4B in 1961, and more recently with the successful landing of the Mars Science Laboratory rover Curiosity in August 2012. RPS enable missions with destinations far from the Sun with faint solar flux, on planetary surfaces with dense or dusty atmospheres, and at places with long eclipse periods where solar array sizes and energy storage mass become impractical. RPS could also provide an enabling capability in support of human exploration activities. It is envisioned that with the higher power needs of most human mission concepts, a high efficiency thermal-to-electric technology would be required such as the Advanced Stirling Radioisotope generator (ASRG). The ASRG should be capable of a four-fold improvement in efficiency over traditional thermoelectric RPS. While it may be impractical to use RPS as a main power source, many other applications could be considered, such as crewed pressurized rovers, in-situ resource production of propellants, back-up habitat power, drilling, any mobile or remote activity from the main base habitat, etc. This paper will identify potential applications and provide concepts that could be a practical extension of the current ASRG design in providing for robust and flexible use of RPS on human exploration missions.

Cataldo, Robert L.↗

Metrics for Operator Situation Awareness, Workload, and Performance in Automated Separation Assurance Systems

A research consortium of scientists and engineers from California State University Long Beach (CSULB), San Jose State University Foundation (SJSUF), California State University Northridge (CSUN), Purdue University, and The Boeing Company was assembled to evaluate the impact of changes in roles and responsibilities and new automated technologies, being introduced in the Next Generation Air Transportation System (NextGen), on operator situation awareness (SA) and workload. To meet these goals, consortium members performed systems analyses of NextGen concepts and airspace scenarios, and concurrently evaluated SA, workload, and performance measures to assess their appropriateness for evaluations of NextGen concepts and tools. The following activities and accomplishments were supported by the NRA: a distributed simulation, metric development, systems analysis, part-task simulations, and large-scale simulations. As a result of this NRA, we have gained a greater understanding of situation awareness and its measurement, and have shared our knowledge with the scientific community. This network provides a mechanism for consortium members, colleagues, and students to pursue research on other topics in air traffic management and aviation, thus enabling them to make greater contributions to the field

Strybel, Thomas Z.↗

NASA Tech Briefs, January 2014

Topics include: Multi-Source Autonomous Response for Targeting and Monitoring of Volcanic Activity; Software Suite to Support In-Flight Characterization of Remote Sensing Systems; Visual Image Sensor Organ Replacement; Ultra-Wideband, Dual-Polarized, Beam-Steering P-Band Array Antenna; Centering a DDR Strobe in the Middle of a Data Packet; Using a Commercial Ethernet PHY Device in a Radiation Environment; Submerged AUV Charging Station; Habitat Demonstration Unit (HDU) Vertical Cylinder Habitat; Origami-Inspired Folding of Thick, Rigid Panels; A Novel Protocol for Decoating and Permeabilizing Bacterial Spores for Epifluorescent Microscopy; Method and Apparatus for Automated Isolation of Nucleic Acids from Small Cell Samples; Enabling Microliquid Chromatography by Microbead Packing of Microchannels; On-Command Force and Torque Impeding Devices (OC-FTID) Using ERF; Deployable Fresnel Rings; Transition-Edge Hot-Electron Microbolometers for Millimeter and Submillimeter Astrophysics; Spacecraft Trajectory Analysis and Mission Planning Simulation (STAMPS) Software; Cross Support Transfer Service (CSTS) Framework Library; Arbitrary Shape Deformation in CFD Design; Range Safety Flight Elevation Limit Calculation Software; Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors; Calculation of Operations Efficiency Factors for Mars Surface Missions; GPU Lossless Hyperspectral Data Compression System; Robust, Optimal Subsonic Airfoil Shapes; Protograph-Based Raptor-Like Codes; Fuzzy Neuron: Method and Hardware Realization; Kalman Filter Input Processor for Boresight Calibration; Organizing Compression of Hyperspectral Imagery to Allow Efficient Parallel Decompression; and Temperature Dependences of Mechanisms Responsible for the Water-Vapor Continuum Absorption.

Source record↗

Coordinated Field Campaigns in Chesapeake Bay and Gulf of Mexico

NASA's GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission concept recommended by the U.S. National Research Council (2007) focuses on measurements of atmospheric trace gases and aerosols and aquatic coastal ecology and biogeochemistry from geostationary orbit (35,786 km altitude). Two GEO-CAPE-sponsored multi-investigator ship-based field campaigns were conducted to coincide with the NASA Earth Venture Suborbital project DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaigns: (1) Chesapeake Bay in July 2011 and (2) northwestern Gulf of Mexico in September 2013. Goal: to evaluate whether GEO-CAPE coastal mission measurement and instrument requirements are optimized to address science objectives while minimizing ocean color satellite sensor complexity, size and cost - critical mission risk reduction activities. NASA continues to support science studies related to the analysis of data collected as part of these coordinated field campaigns and smaller efforts.

GoMex↗

Airborne Mission Concept for Coastal Ocean Color and Ecosystems Research

NASA airborne missions in 2011 and 2013 over Monterey Bay, CA, demonstrated novel above- and in-water calibration and validation measurements supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The resultant airborne data characterize contemporaneous coastal atmospheric and aquatic properties plus sea-truth observations from state-of-the-art instrument systems spanning a next-generation spectral domain (320-875 nm). This airborne instrument suite for calibration, validation, and research flew at the lowest safe altitude (ca. 100 ft or 30 m) as well as higher altitudes (e.g., 6,000 ft or 1,800 m) above the sea surface covering a larger area in a single synoptic sortie than ship-based measurements at a few stations during the same sampling period. Data collection of coincident atmospheric and aquatic properties near the sea surface and at altitude allows the input of relevant variables into atmospheric correction schemes to improve the output of corrected imaging spectrometer data. Specific channels support legacy and next-generation satellite capabilities, and flights are planned to within 30 min of satellite overpass. This concept supports calibration and validation activities of ocean color phenomena (e.g., river plumes, algal blooms) and studies of water quality and coastal ecosystems. The 2011 COAST mission flew at 100 and 6,000 ft on a Twin Otter platform with flight plans accommodating the competing requirements of the sensor suite, which included the Coastal-Airborne In-situ Radiometers (C-AIR) for the first time. C-AIR (Biospherical Instruments Inc.) also flew in the 2013 OCEANIA mission at 100 and 1,000 ft on the Twin Otter below the California airborne simulation of the proposed NASA HyspIRI satellite system comprised of an imaging spectrometer and thermal infrared multispectral imager on the ER-2 at 65,000 ft (20,000 m). For both missions, the Compact-Optical Profiling System (Biospherical Instruments, Inc.), an in-water system with microradiometers matching C-AIR, was deployed to compare sea-truth measurements and low-altitude Twin Otter flights within Monterey Bay red tide events. This novel airborne and in-water sensor capability advances the science of coastal measurements and enables rapid response for coastal events.

Oceans↗

Autonomous RPOD Technology Challenges for the Coming Decade

Rendezvous Proximity Operations and Docking (RPOD) technologies are important to a wide range of future space endeavors. This paper will review some of the recent and ongoing activities related to autonomous RPOD capabilities and summarize the current state of the art. Gaps are identified where future investments are necessary to successfully execute some of the missions likely to be conducted within the next ten years. A proposed RPOD technology roadmap that meets the broad needs of NASA's future missions will be outlined, and ongoing activities at OSFC in support of a future satellite servicing mission are presented. The case presented shows that an evolutionary, stair-step technology development program. including a robust campaign of coordinated ground tests and space-based system-level technology demonstration missions, will ultimately yield a multi-use main-stream autonomous RPOD capability suite with cross-cutting benefits across a wide range of future applications.

Naasz, Bo J.↗

Development of a Ground Test and Analysis Protocol for NASA's NextSTEP Phase 2 Habitation Concepts

The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.

Gernhardt, Michael L.↗

NC Space Grant Report

During the summer of 2018 I supported the Safety & Mission Assurance Directorate (SMA) and Operations Support Division (QA-20) at Stennis Space Center. The mission of the SMA team is to prove safety, risk, reliability, independent assessments, configuration management and quality assurance guidance, and services for all NASA Stennis Space Center (SSC) programs, facilities, and supporting infrastructure. The office actively participates and contributes to the Agency-level Safety & Mission Assurance (S&MA) effort. Over the course of the Summer I participated in three projects. Two of them were focused around Fault Tree Analysis (FTA) and the third focused on relief valves for their E-1 engine test stand.

Torres, David↗

Key Technologies, Systems, and Infrastructure Enabling the Commercialization and Human Settlement of the Moon and Cislunar Space

Over 50 years have passed since 2001: A Space Odyssey debuted in April 1968. In the film, Dr. Heywood Floydflies to a large artificial gravity space station orbiting Earth aboard a commercial space plane. He then embarks on acommuter flight to the Moon arriving there 25 hours later. Today, in this the 50th anniversary year of the Apollo 11lunar landing, the images portrayed in 2001 still remain well beyond our capabilities. This paper examines keytechnologies and systems (e.g., in-situ resource utilization, fission power, advanced chemical and nuclearpropulsion), and supporting orbital infrastructure (providing a propellant and cargo transfer function), that could bedeveloped by NASA and industry over the next 30 years allowing the operational capabilities presented in 2001 to beachieved, albeit on a more spartan scale. Lunar-derived propellants (LDPs) will be essential to developing a reusablelunar transportation system that can allow initial outposts to evolve into settlements supporting a variety ofcommercial activities. Deposits of icy regolith discovered at the lunar poles can supply the feedstock material neededto produce liquid oxygen (LO2) and hydrogen (LH2) propellants. On the lunar nearside, near the equator, iron oxiderichvolcanic glass beads from vast pyroclastic deposits, together with mare regolith, can provide the feedstockmaterials to produce lunar-derived LO2 plus other important solar wind implanted (SWI) volatiles, including H2and helium-3. Megawatt-class fission power systems will be essential for providing continuous "24/7" power toprocessing plants, human settlements and commercial enterprises that develop on the Moon and in orbit. Reusablelunar landing vehicles will provide cargo and passenger "orbit-to-surface" access and will also transport LDP toSpace Transportation Nodes (STNs) located in lunar polar (LPO) and equatorial orbits (LLO). Reusable space-based,lunar transfer vehicles (LTVs), operating between STNs in low Earth orbit, LLO, and LPO, and able to refuel withLDPs, offer unique mission capabilities including short transit time crewed cargo transports. Even commuter flightssimilar to that portrayed in 2001 appear possible, allowing 1-way trip times to and from the Moon as short as 24hours. The performance of LTVs using both RL10B-2 chemical rockets, and a variant of the nuclear thermal rocket(NTR), the LO2-Augmented NTR (LANTR), are examined and compared. If only 1% of the LDP obtained from icyregolith, volcanic glass, and SWI volatile deposits were available for use in lunar orbit, such a supply could supportroutine commuter flights to the Moon for many thousands of years. This paper provides a look ahead at what mightbe possible in the not too distant future, quantifies the operational characteristics of key in-space and surfacetechnologies and systems, and provides conceptual designs for the various architectural elements discussed.

Borowski, Stanley K.↗

NASA space cryocooler programs -- a 2003 overview

Mechanical cryocoolers represent a significant enabling technology for NASA's Earth and Space Science Missions. An overview is presented of ongoing cryocooler activities within NASA in support of current flight projects, near-term instruments, and long-term technology development.

cryocoolers↗

A Framework for Extending the Science Traceability Matrix: Application to the Planned Europa Mission

One of the most critical functions of the systems engineering requirements process for a large multi-instrument science-driven space mission is to successfully communicate customer expectations into a comprehensive and traceable science requirements flowdown. These requirements are essential to communicating the constraints on the scope of the science investigations and clarifying how multiple instruments contribute to a given science goal. They also provide insight into how the science goals of the whole mission are affected by design choices. There is little specific guidance available on best practices for developing this science-driven flowdown. A unified Science Traceability Matrix (USTM) contains a significant amount of information that can be leveraged for that purpose, but the USTM was not designed to directly produce a complete science requirements flowdown. Thus, starting with the principles codified in a USTM, the authors propose a framework that directly maps into the requirements flowdown and supports broader systems engineering processes while retaining its meaning to the science team. This Science Traceability and Alignment Framework, or STAF, defines a set of common definitions and valid relationships to structure communication across the project. In addition, STAF populates a network of information that can be useful to support complex mission analysis activities such as fault protection. This work discusses the highest-level implementation of the STAF, the project-domain or P-STAF, which describes an approach to decomposing customer requirements into science requirements. The planned Europa Mission is used as a case study for the implementation of this framework and its potential benefits to a project.

Susca, Sara↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

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