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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Development of a prototype interactive learning system using multi-media technology for mission independent training program

The Spacelab Mission Independent Training Program provides an overview of payload operations. Most of the training material is currently presented in workbook form with some lecture sessions to supplement selected topics. The goal of this project was to develop a prototype interactive learning system for one of the Mission Independent Training topics to demonstrate how the learning process can be improved by incorporating multi-media technology into an interactive system. This report documents the development process and some of the problems encountered during the analysis, design, and production phases of this system.

Matson, Jack E.↗
NASA NTRS2001

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Decker, Arthur J.↗
NASA NTRS2006

Fault Management Techniques in Human Spaceflight Operations

This paper discusses human spaceflight fault management operations. Fault detection and response capabilities available in current US human spaceflight programs Space Shuttle and International Space Station are described while emphasizing system design impacts on operational techniques and constraints. Preflight and inflight processes along with products used to anticipate, mitigate and respond to failures are introduced. Examples of operational products used to support failure responses are presented. Possible improvements in the state of the art, as well as prioritization and success criteria for their implementation are proposed. This paper describes how the architecture of a command and control system impacts operations in areas such as the required fault response times, automated vs. manual fault responses, use of workarounds, etc. The architecture includes the use of redundancy at the system and software function level, software capabilities, use of intelligent or autonomous systems, number and severity of software defects, etc. This in turn drives which Caution and Warning (C&W) events should be annunciated, C&W event classification, operator display designs, crew training, flight control team training, and procedure development. Other factors impacting operations are the complexity of a system, skills needed to understand and operate a system, and the use of commonality vs. optimized solutions for software and responses. Fault detection, annunciation, safing responses, and recovery capabilities are explored using real examples to uncover underlying philosophies and constraints. These factors directly impact operations in that the crew and flight control team need to understand what happened, why it happened, what the system is doing, and what, if any, corrective actions they need to perform. If a fault results in multiple C&W events, or if several faults occur simultaneously, the root cause(s) of the fault(s), as well as their vehicle-wide impacts, must be determined in order to maintain situational awareness. This allows both automated and manual recovery operations to focus on the real cause of the fault(s). An appropriate balance must be struck between correcting the root cause failure and addressing the impacts of that fault on other vehicle components. Lastly, this paper presents a strategy for using lessons learned to improve the software, displays, and procedures in addition to determining what is a candidate for automation. Enabling technologies and techniques are identified to promote system evolution from one that requires manual fault responses to one that uses automation and autonomy where they are most effective. These considerations include the value in correcting software defects in a timely manner, automation of repetitive tasks, making time critical responses autonomous, etc. The paper recommends the appropriate use of intelligent systems to determine the root causes of faults and correctly identify separate unrelated faults.

O'Hagan, Brian↗
NASA NTRS2018

Establishing and Monitoring an Aseptic Workspace

When are aseptic operations necessary? In order to meet certain bioburden requirements, some components must undergo dry heat microbial reduction (DHMR) or other sterilizing procedures. If sensitive surfaces must be re-exposed after DHMR, this could compromise the bioburden levels. Recontaminating sterilized surfaces could be costly both in time by requiring repeated DHMR and risk to the hardware, which may not be compatible with repeated high temperature bakes. In order to prevent recontamination of the sensitive surfaces, an aseptic environment and sterile technique must be employed. Aseptic environments mean working in a space with almost no detectable bioburden in the air or on surfaces. Ideally, DHMR happens as late as possible to avoid requiring aseptic operations, as it can be considered a high-risk operations. Preparing the cleanroom for aseptic operations Establishing an ISO (International Organization for Standardization) class 5 space to minimize airborne particles. Maintain low bioburden in the cleanroom by using biocidal cleaners. Using multiple biocidal techniques decreases the likelihood of selecting for resistant microorganisms. 70% Isopropyl Alcohol (IPA) denatures the proteins in a microorganism (note: 70% IPA is better at killing microorganisms than 100% IPA) 7% hydrogen peroxide: damages DNA and proteins through oxygen radical damage. Ultraviolet-C (UV-C) lamps: causes crosslinking in DNA which prevents replication. Monitor cleanroom regularly for bioburden trending: Standard bioassay: Swab or wipe samples of cleanroom surfaces processed for colony forming unity (viable or spore selected); Rapid bioassay: Adenosine triphosphate (ATP) or Limulus amebocyte lysate (LAL) for a bioburden snapshot. High levels can signal an immediate re-cleaning before standard bioassay samples are taken. Airborne monitoring: Active (pulling air through a filter) or passive (particle fallout) for bioburden. Verify bioburden levels just before aseptic operation. Test hardware and cleanroom surfaces and air 3 days before the planned aseptic operation. Rapid bioburden just before aseptic operation to ensure room was not re-contaminated. Preparing personnel and tools: Personnel training. Everyone in the cleanroom: Standard cleanroom certification Everyone on the team: 1 day Planetary Protection overview. Aseptic operators only: Half-day aseptic operations training. Covers sterile garmenting/gloves, Sterile handling with a focus on contact transfer risk, tool/GSE preparation, and two-operator system for opening sterilized tools/components. Tool sterilization: All tools to be used during an aseptic operation need to be identified. Compatible tools are sterilized by DHMR or Autoclave. Double wrapped so that the exterior bag can be handled by a non-sterile operator, and the sterile. Tools that are not compatible with high heat do not come in contact with sensitive surfaces: either substitutes are found, or tools are isolated by wrapping in sterile foil. During an aseptic operation. Pre-task to make sure everyone understands the operations, who is handling what, and when the most critical surfaces will be exposed. Monitoring during the operation. Bioburden: active and passive airborne bioburden sampling, glove-tip dabs onto a plate after completion of operation (3 days for results). Particles: real time particle counter constantly running, with alarm for exceeding ISO 5 conditions.

aseptic processing↗
NASA NTRS1967

Safety in flight operations.

Manned space flight safety, discussing system design, operations planning, staffing, training and simulation

OPERATIONS RESEARCH↗
NASA NTRS1986

Interaction between workload and training - Converging evidence from psychophysiology and performance measurement

Traditionally, the domains of mental workload and training have been studied in isolation even though they share many common characteristics. The present paper integrates findings from psychophysiological and performance-based studies which address both of these issues. By augmenting traditional indices of skill acquisition such as RMS error scores, reaction times, and accuracy measures with psychophysiological measures such as the event-related brain potential, it is shown that workload effects can be assessed throughout the training process. More specifically, it is argued that the development of skill and the effects of workload on the human operator can be modeled within the framework of resource theories of attentional allocation. Also described is how converging evidence from psychophysiological and behavioral studies can be used to examine subtle changes in operator strategies during training.

Kramer, Arthur F.↗
NASA NTRSDate not supplied

Artemis Geology Training Introduction to A3GT

Artemis Internal Science Training Team partners closely with the xEVA Trainers and Crew Training Office in FOD; together, all parties acknowledge the importance of integrated science and operations skill-building within training for surface operations.

Geology↗
NASA NTRSDate not supplied

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models–specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

resilience↗
NASA NTRSDate not supplied

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models--specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

Daniel Hulse↗
NASA NTRS1993

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Decker, Arthur J.↗
NASA NTRS1999

[X-33 Launch and Landing Facilities]

Sverdrup is responsible for the design, construction and activation of the X-33 Flight Operations Center at Edwards Air Force Base and for providing assistance in activating the X-33 Landing Sites. The past year has seen the completion of the construction of the X-33 Flight Operations Center. Construction was completed in December of 1998, with systems checkout and testing continuing into early 1999. Integration of the site with LMCMS and other partner-supplied systems began in December and will continue through rollout of the X-33 vehicle. The construction of the X-33 Launch Complex has been performed within the Edwards AFB and Air Force Research Laboratory (AFRL) systems with no substantial interference to either parties. A high level of cooperation exists between Sverdrup, Edwards AFB, and the Air Force Research Laboratory in the areas of access, training, security, and operations. There have been no conflicts between programs that have not been accommodated. Development of the landing sites is progressing with many of the modifications necessary underway. GSE commitments are in place. The personnel training program developed by Sverdrup for persons entering the launch site construction areas, was modified by Lockheed for use in training and access control to the Center during flight operations to maximize safety and minimize intrusion upon the environment. Close cooperation between Sverdrup, the construction workers, and the environmental biologist permitted construction to proceed in a timely fashion without harm to the wildlife, in particular, the Desert Tortoise. Although the entire X-33 site encompasses approximately 50 acres including a new access road, only the areas directly impacted by the construction were cleared to minimize the impact on the environment. A total of about 30 acres was actually disturbed.

Source record↗
NASA NTRS1971

Modular space station phase B extension integrated ground operations

Requirements for development test, manufacturing, facilities, GSE, training, logistics support, and launch operations are described. The prime integrating requirement is the early establishment of a common data base and its use throughout the design, development, and operational life of the station. The common data base is defined, and the concept of its use is presented. Development requirements for the station modules and subsystems are outlined along with a master development phasing chart.

Selegue, D. F.↗
NASA NTRS1977

Real-time dynamic spacecraft simulation

This paper presents experience in designing and implementing a fully interactive real-time dynamic spacecraft simulation software system for the International Ultraviolet Explorer (IUE) satellite to be launched by NASA. The primary objective for this simulator, called SIMIUE, is to help train the IUE Operations Control Center personnel in the dynamic commanding and operations of the IUE spacecraft. It is felt that the approach taken in developing SIMIUE will prove to be largely valid for spacecraft training simulators to be developed for future satellites. For this reason discussion of those aspects of SIMIUE which relate specifically to the IUE satellite has been kept to a minimum.

Macker, A. J.↗
NASA NTRS2006

Moving from Bilateral to Multilateral Medical Operations

When the ISS Integrated Medical Group moved to a multilateral configuration for the ASTROLAB mission, several challenges were encountered and overcome that allowed for a streamlined operational experience. Dating back to the early 1990s, the European Space Agency (ESA) has sent flight surgeon and Biomedical Engineering (BME) personnel to NASA-JSC and Russia to train for space flight operational support. This training was tailored towards the needs of particular Shuttle/Soyuz missions, and more generally for eventual ISS support. With the announcement of the ASTROLAB mission, NASA and ESA personnel worked together to develop a detailed training template for ESA BMEs to ensure successful support of the mission from the European Astronaut Center (EAC). This training included the deployment of ESA BMEs to JSC, as well as the development of a rotation of ISS-certified NASA BMEs to the EAC. In addition to training, NASA, ESA, and the Russian Federal Space Agency (FSA) worked together preflight to develop multilateral flight control support concepts and implementation plans. This resulted in flight control support schedules, operational rules of engagement, and the delineation of responsibilities. NASA also assisted ESA with the development and deployment of workstation displays to allow the ESA medical flight control team to monitor ISS telemetry from the EAC. The goal of this presentation is to provide details of the preflight preparation and in-flight support of the ASTROLAB mission by the ESA, NASA, and FSA medical support teams. In addition, it will identify lessons learned that will be implemented for future multilateral endeavors.

Roden, S.↗
NASA NTRS1976

STS payloads mission control study phase A-1, volume 1, phases A and A-1

The Space Transportation System (STS) Payloads Mission Control Phase A-1 Study results are summarized. The composite resources required to accomplish Joint STS-Payload preflight preparation for joint flight operations, including flight planning, training, and simulations are presented. The Standard Payload Operations Control Center (POCC) concept was developed.

Source record↗
NASA NTRS2003

Concept of Operations for the NASA Weather Accident Prevention (WxAP) Project

The Weather Accident Prevention Concept of Operations (CONOPS) serves as a decision-making framework for research and technology development planning. It is intended for use by the WxAP members and other related programs in NASA and the FAA that support aircraft accident reduction initiatives. The concept outlines the project overview for program level 3 elements-such as AWIN, WINCOMM, and TPAWS (Turbulence)-that develop the technologies and operating capabilities to form the building blocks for WxAP. Those building blocks include both retrofit of equipment and systems and development of new aircraft, training technologies, and operating infrastructure systems and capabilities. This Concept of operations document provides the basis for the WxAP project to develop requirements based on the operational needs ofthe system users. It provides the scenarios that the flight crews, airline operations centers (AOCs), air traffic control (ATC), and flight service stations (FSS) utilize to reduce weather related accidents. The provision to the flight crew of timely weather information provides awareness of weather situations that allows replanning to avoid weather hazards. The ability of the flight crew to locate and avoid weather hazards, such as turbulence and hail, contributes to safer flight practices.

Green, Walter S.↗
NASA NTRSDate not supplied

Development of a Human Systems Integration Plan

NASA defines Human Systems Integration (HSI) as part of the overall systems engineering and acquisition strategy for space systems. The HSI Plan defines how HSI activities will be implemented across the lifecycle of the mission, as required by NPR 7123.1C, NASA Systems Engineering Processes and Requirements, and NPR 8705.2C Human-Rating Requirements for Space Systems. The goal of this presentation is to share with government and industry how an HSI Plan can be implemented. The presentation will cover HSI implementation for flight systems, vehicle processing, and interfaces. These are divided into six NASA HSI Domains: human factors engineering, operations resources, safety, training, maintainability and supportability, habitability and environment. HSI activities go across the mission’s lifecycle from pre-formulation and acquisition through design, development, operations, maintenance, and decommissioning. The HSI Plan includes a description of the HSI activities and products that are essential for human rating, operability, maintainability, supportability, and affordability of the mission systems. It also describes the role of the HSI Team required as part of the Human Rating process. The HSI Plan utilizes the operational expertise within NASA to ensure designs and testing are successful, leading to acceptable human spaceflight vehicles.

Jackelynne Silva-Martinez↗
NASA NTRS2006

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Decker, Arthur J.↗