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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Modular System to Enable Extravehicular Activity

The ability to perform extravehicular activity (EVA), both human and robotic, has been identified as a key component to space missions to support such operations as assembly and maintenance of space system (e.g. construction and maintenance of the International Space Station), and unscheduled activities to repair an element of the transportation and habitation systems that can only be accessed externally and via unpressurized areas. In order to make human transportation beyond lower earth orbit (BLEO) practical, efficiencies must be incorporated into the integrated transportation systems to reduce system mass and operational complexity. Affordability is also a key aspect to be considered in space system development; this could be achieved through commonality, modularity and component reuse. Another key aspect identified for the EVA system was the ability to produce flight worthy hardware quickly to support early missions and near Earth technology demonstrations. This paper details a conceptual architecture for a modular extravehicular activity system (MEVAS) that would meet these stated needs for EVA capability that is affordable, and that could be produced relatively quickly. Operational concepts were developed to elaborate on the defined needs and define the key capabilities, operational and design constraints, and general timelines. The operational concept lead to a high level design concept for a module that interfaces with various space transportation elements and contains the hardware and systems required to support human and telerobotic EVA; the module would not be self-propelled and would rely on an interfacing element for consumable resources. The conceptual architecture was then compared to EVA Systems used in the Shuttle Orbiter, on the International Space Station to develop high level design concepts that incorporate opportunities for cost savings through hardware reuse, and quick production through the use of existing technologies and hardware designs. An upgrade option was included to make use of the developing suitport technologies.

Sargusingh, Miriam J.↗
NASA NTRS2012

Modular System to Enable Extravehicular Activity

The ability to perform extravehicular activity (EVA), both human and robotic, has been identified as a key component to space missions to support such operations as assembly and maintenance of space systems (e.g. construction and maintenance of the International Space Station), and unscheduled activities to repair an element of the transportation and habitation systems that can only be accessed externally and via unpressurized areas. In order to make human transportation beyond lower Earth orbit (LEO) practical, efficiencies must be incorporated into the integrated transportation systems to reduce system mass and operational complexity. Affordability is also a key aspect to be considered in space system development; this could be achieved through commonality, modularity and component reuse. Another key aspect identified for the EVA system was the ability to produce flight worthy hardware quickly to support early missions and near Earth technology demonstrations. This paper details a conceptual architecture for a modular EVA system that would meet these stated needs for EVA capability that is affordable, and that could be produced relatively quickly. Operational concepts were developed to elaborate on the defined needs, and to define the key capabilities, operational and design constraints, and general timelines. The operational concept lead to a high level design concept for a module that interfaces with various space transportation elements and contains the hardware and systems required to support human and telerobotic EVA; the module would not be self-propelled and would rely on an interfacing element for consumable resources. The conceptual architecture was then compared to EVA Systems used in the Space Shuttle Orbiter, on the International Space Station to develop high level design concepts that incorporate opportunities for cost savings through hardware reuse, and quick production through the use of existing technologies and hardware designs. An upgrade option was included to make use of the developing suit port technologies.

Sargusingh, Miriam J.↗
NASA NTRS1984

Pilot workload, performance and aircraft control automation

Conceptual and practical issues associated with the design, operation, and performance of advanced systems and the impact of such systems on the human operators are reviewed. The development of highly automated systems is driven by the availability of new technology and the requirement that operators safely and economically perform more and more activities in increasingly difficult and hostile environments. It is noted that the operators workload may become a major area of concern in future design considerations. Little research was done to determine how automation and workload relate to each other, although it is assumed that the abstract, supervisory, or management roles that are performed by operators of highly automated systems will impose increased mental workload. The relationship between performance and workload is discussed in relation to highly complex and automated environments.

Hart, S. G.↗
DOE OSTI2023

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

A recovery action is defined as the action that prevents deviant conditions from producing unwanted effects. It generally indicates a kind of countermeasure performed in response to a failure of human action. The recovery actions especially play an important role in complex systems like nuclear power plants (NPPs), which consist of highly sophisticated controllers to ensure that desired performance and safety must be achieved and maintained. This is because a combination of human error and its recovery failure may be able to cause a catastrophic effect on a system. Analyzing recovery actions has been a critical part of HRA, which is a technique to evaluate human errors and provide human error probabilities (HEPs) for application in probabilistic safety assessment (PSA). If recovery actions are not adequately analyzed and applied to PSA models, the PSA results may be under-estimated or be not able to reasonably account for the failure of human actions in the context of PSA. For this reason, some regulatory documents such as ASME/ANS RA-Sb-2013 by the American Society for Mechanical Engineers and the American Nuclear Society and NUREG-1792 by U.S. Nuclear Regulatory Commission have emphasized the importance of recovery analysis within the HRA. A couple of existing HRA methods, such as the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT), and the Korean Standard HRA (K-HRA), have respectively suggested their own approaches to the HRA recovery analysis. However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. The biggest limitation is that the existing recovery analysis does not explicitly consider a variety of recovery action types and recovery sequences as they occur in actual NPPs. To handle the limitations of existing recovery analysis, this study proposes a simulation-based recovery analysis method using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. The EMRALD software is a dynamic simulation tool for PSA. It supports realistic and dynamic modeling of human actions as they would be performed at NPPs. It is also favorable to simultaneously model the specific moment at which an action is performed, the time it takes to perform the action, and the failure probability of that action. In this paper, a detailed methodology for modeling recovery actions in the simulation platform is proposed with a couple of examples. Then, outputs from the simulation are discussed as reviewing if this novel approach can complement the challenges of existing recovery analyses.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1984

Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques

This Working Paper Series entry presents a detailed survey of knowledge based systems. After being in a relatively dormant state for many years, only recently is Artificial Intelligence (AI) - that branch of computer science that attempts to have machines emulate intelligent behavior - accomplishing practical results. Most of these results can be attributed to the design and use of Knowledge-Based Systems, KBSs (or ecpert systems) - problem solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. These systems can act as a consultant for various requirements like medical diagnosis, military threat analysis, project risk assessment, etc. These systems possess knowledge to enable them to make intelligent desisions. They are, however, not meant to replace the human specialists in any particular domain. A critical survey of recent work in interactive KBSs is reported. A case study (MYCIN) of a KBS, a list of existing KBSs, and an introduction to the Japanese Fifth Generation Computer Project are provided as appendices. Finally, an extensive set of KBS-related references is provided at the end of the report.

Dominick, Wayne D.↗
NASA NTRSDate not supplied

Human System Risk Changes in 2021

The Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. Risks are re-evaluated in a Continuous Risk Management (CRM) process. This session will summarize the risk posture changes that have occurred in the last year and what high level research, performance, and epidemiologic data have informed those changes. Human System Risks updated in 2021 include: Dynamic Loads, Sensorimotor, EVA, Crew Egress, Behavioral Medicine, Electrical Shock, Human System Integration Architecture (HSIA), Toxic Exposure, Bone Fracture, Cardiovascular, Medical Conditions, Renal Stone, CO2 Exposure, and Pharmacology.

Mary Van Baalen↗
NASA NTRS2012

NASA Human Health and Performance Strategy

In May 2007, what was then the Space Life Sciences Directorate, issued the 2007 Space Life Sciences Strategy for Human Space Exploration. In January 2012, leadership and key directorate personnel were once again brought together to assess the current and expected future environment against its 2007 Strategy and the Agency and Johnson Space Center goals and strategies. The result was a refined vision and mission, and revised goals, objectives, and strategies. One of the first changes implemented was to rename the directorate from Space Life Sciences to Human Health and Performance to better reflect our vision and mission. The most significant change in the directorate from 2007 to the present is the integration of the Human Research Program and Crew Health and Safety activities. Subsequently, the Human Health and Performance Directorate underwent a reorganization to achieve enhanced integration of research and development with operations to better support human spaceflight and International Space Station utilization. These changes also enable a more effective and efficient approach to human system risk mitigation. Since 2007, we have also made significant advances in external collaboration and implementation of new business models within the directorate and the Agency, and through two newly established virtual centers, the NASA Human Health and Performance Center and the Center of Excellence for Collaborative Innovation. Our 2012 Strategy builds upon these successes to address the Agency s increased emphasis on societal relevance and being a leader in research and development and innovative business and communications practices. The 2012 Human Health and Performance Vision is to lead the world in human health and performance innovations for life in space and on Earth. Our mission is to enable optimization of human health and performance throughout all phases of spaceflight. All HHPD functions are ultimately aimed at achieving this mission. Our activities enable mission success, optimizing human health and productivity in space before, during, and after the actual spaceflight experience of our crews, and include support for ground-based functions. Many of our spaceflight innovations also provide solutions for terrestrial challenges, thereby enhancing life on Earth. Our strategic goals are aimed at leading human exploration and ISS utilization, leading human health and performance internationally, excelling in management and advancement of innovations in health and human system integration, and expanding relevance to life on Earth and creating enduring support and enthusiasm for space exploration.

Davis, Jeffrey R.↗
NASA NTRS2012

NASA Human Health and Performance Strategy

In May 2007, what was then the Space Life Sciences Directorate, issued the 2007 Space Life Sciences Strategy for Human Space Exploration. In January 2012, leadership and key directorate personnel were once again brought together to assess the current and expected future environment against its 2007 Strategy and the Agency and Johnson Space Center goals and strategies. The result was a refined vision and mission, and revised goals, objectives, and strategies. One of the first changes implemented was to rename the directorate from Space Life Sciences to Human Health and Performance to better reflect our vision and mission. The most significant change in the directorate from 2007 to the present is the integration of the Human Research Program and Crew Health and Safety activities. Subsequently, the Human Health and Performance Directorate underwent a reorganization to achieve enhanced integration of research and development with operations to better support human spaceflight and International Space Station utilization. These changes also enable a more effective and efficient approach to human system risk mitigation. Since 2007, we have also made significant advances in external collaboration and implementation of new business models within the directorate and the Agency, and through two newly established virtual centers, the NASA Human Health and Performance Center and the Center of Excellence for Collaborative Innovation. Our 2012 Strategy builds upon these successes to address the Agency's increased emphasis on societal relevance and being a leader in research and development and innovative business and communications practices. The 2012 Human Health and Performance Vision is to lead the world in human health and performance innovations for life in space and on Earth. Our mission is to enable optimization of human health and performance throughout all phases of spaceflight. All HH&P functions are ultimately aimed at achieving this mission. Our activities enable mission success, optimizing human health and productivity in space before, during, and after the actual spaceflight experience of our crews, and include support for ground-­‐ based functions. Many of our spaceflight innovations also provide solutions for terrestrial challenges, thereby enhancing life on Earth. Our strategic goals are aimed at leading human exploration and ISS utilization, leading human health and performance internationally, excelling in management and advancement of innovations in health and human system integration, and expanding relevance to life on Earth and creating enduring support and enthusiasm for space exploration.

Davis, Jeffrey R.↗
NASA NTRS1995

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Kim, Jonnathan H.↗
NASA NTRS2015

Detection of Operator Performance Breakdown as an Automation Triggering Mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator "loses control of context" and "cannot maintain required task performance." Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method for objectively identifying the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best matches the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.

multi-task environment↗
NASA NTRS1990

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

Mitchell, Christine M.↗
NASA NTRS2016

Application of Human-Autonomy Teaming (HAT) Patterns to Reduce Crew Operations (RCO)

Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.

design patterns↗
DOE OSTI2024

DICER: Data Intensive Computing Environment and Runtime for Evaluating Unprecedented Scale of Geospatial-Temporal Human Mobility Data

With the significant increase in sources and volume of human mobility data through commercial data vendors as well as microsimulation of cities, the scale of geospatial-temporal data to analyze and assess for mobility characterization has grown to the level of Big Data. There are mobility related commercial organizations deploying scalable computing, but often the system architecture, workflow, and intermediate processing components are not fully disclosed in relevant scope. Current research literature has a notable lack of studies demonstrating architectures and workflows for human mobility analytics that are implemented on a TeraByte scale of geospatial-temporal data. In this context, this paper presents a hyperscale-level system solution named DICER (Data Intensive Computing Environment and Runtime) for processing and analytics of geospatial-temporal data at big data scale. Although the cluster computing architecture of DICER with Apache Spark job running on Kubernetes cluster is not new, there are innovations in the workflow, hierarchical processing logic, and a wide range of intermediate preprocessing and mobility metrics calculation. We have performed case studies to validate the effectiveness of DICER system solution by performing detailed analytics and assessment of human mobility microsimulation output at three different scopes and scale, including a usecase with 16.97 TeraByte and 259.2 Billion rows of data. In addition, we have presented another case study of utilizing DICER to perform the same mobility processing and comparative analytics on large-scale commercially available geospatial-temporal data. All these case studies validate the efficiency and usefulness of DICER in computing population mobility characteristics from geospatial-temporal trajectory data at an unprecedented scale (not only just data volume, but also combination of: number of user entities, temporal frequency, spatial resolution, data duration).

De, Debraj↗
NASA NTRS1978

Human problem solving performance in a fault diagnosis task

It is proposed that humans in automated systems will be asked to assume the role of troubleshooter or problem solver and that the problems which they will be asked to solve in such systems will not be amenable to rote solution. The design of visual displays for problem solving in such situations is considered, and the results of two experimental investigations of human problem solving performance in the diagnosis of faults in graphically displayed network problems are discussed. The effects of problem size, forced-pacing, computer aiding, and training are considered. Results indicate that human performance deviates from optimality as problem size increases. Forced-pacing appears to cause the human to adopt fairly brute force strategies, as compared to those adopted in self-paced situations. Computer aiding substantially lessens the number of mistaken diagnoses by performing the bookkeeping portions of the task.

Rouse, W. B.↗
NASA NTRS1981

Symposium on Aviation Psychology, 1st, Ohio State University, Columbus, OH, April 21, 22, 1981, Proceedings

The impact of modern technology on the role, responsibility, authority, and performance of human operators in modern aircraft and ATC systems was examined in terms of principles defined by Paul Fitts. Research into human factors in aircraft operations and the use of human factors engineering for aircraft safety improvements were discussed, and features of the man-machine interface in computerized cockpit warning systems are examined. The design and operational features of computerized avionics displays and HUDs are described, along with results of investigations into pilot decision-making behavior, aircrew procedural compliance, and aircrew judgment training programs. Experiments in vision and visual perception are detailed, as are behavioral studies of crew workload, coordination, and complement. The effectiveness of pilot selection, screening, and training techniques are assessed, as are methods for evaluating pilot performance.

Source record↗
NASA NTRSDate not supplied

Human Systems Integration Relationships Between Deep Space and Deepwater Exploration Challenges

NASA pursuit of human missions Beyond Earth Orbit (BEO) to the moon and eventually Mars will pose many new challenges. These missions are characterized by increased risks to human performance due to stress, fatigue, radiation exposure, and isolation. Fundamental changes in spaceflight operations will be required as well. A very critical part of future missions will be assisting the crew with problem-solving and contingency resolution using next-generation smart spacecraft systems. Human Systems Integration (HSI) must be included as part of the systems engineering process. Gateway1 will serve as part of the proving ground for maturing technology such as autonomous systems and space operations procedures to help meet moon mission goals and prepare humans for missions to Mars. For deep space missions, risk factors affecting humans such as mission duration, distance, and physiological/psychological effects, must be considered. A human is not a simple component but rather a system in a systems-of-systems application-a system influenced by cognitive and biological factors that are difficult to model/analyze. System complexity will demand an integrated approach that requires multiple viewpoints, including the understanding of the astronauts' capabilities and limitations to enhance safety, performance, and satisfaction on the interaction between all system users in a variety of environments to achieve acceptable mission goals and performance. HSI will play a vital role in the development of these future missions. This paper provides a discussion of HSI used at NASA and the critical role human factors engineering will play in the HSI process for future missions along with the challenges. Industries such as oil and gas (O&G) could benefit from the content of this paper to help improve the safety and operations of deepwater/oil and gas exploration activities. NASA engineering and human systems subject-matter expert personnel reviewed challenges reported in space-related environments for long space duration missions and identified similarities with the challenges encountered in deepwater exploration. The researchers noted the space industry's current solutions and proposed a system development view to solve future deepwater exploration challenges using HSI principles. This paper discusses the results of the review.

George Salazar↗
NASA NTRSDate not supplied

Reports of Resilient Performance: Investigating Operators' Descriptions of Safety-producing Behaviors in the Aviation Safety Reporting System

While many existing taxonomies and frameworks provide a common vocabulary for describing how human operators fail in the context of sociotechnical systems, at present, there is no common vocabulary to describe how humans succeed. Such a framework would facilitate systematically collecting and analyzing data on how human performance can produce safety, not just how it can reduce safety. One potentially rich source of currently available information for exploring desired performance is the reports submitted to NASA’s Aviation Safety Reporting System (ASRS). These de-identified, confidential, and voluntary narrative reports are submitted by pilots, controllers, ground operators, and others within aviation operations. While these reports are primarily submitted to describe safety risks, incidents, and problems, they also often describe how those risks were mitigated, and provide a window into aspects of everyday work in aviation. This paper describes an analysis of ASRS narratives to understand how operators talk about their own resilient behaviors during adverse safety conditions and events. Guided by Erik Hollnagel’s Resilience Assessment Grid framework (i.e., anticipate, monitor, respond, learn), we illustrate our approach and methodology with examples from reports. We also highlight some of the challenges and how further research is needed in developing a taxonomy of operators’ descriptions of resilient performance.

resilient behaviors↗
NASA NTRSDate not supplied

Reports of Resilient Performance: Investigating Operators' Descriptions of Safety-producing Behaviors in the Aviation Safety Reporting System

While many existing taxonomies and frameworks provide a common vocabulary for describing how human operators fail in the context of sociotechnical systems, at present, there is no common vocabulary to describe how humans succeed. Such a framework would facilitate systematically collecting and analyzing data on how human performance can produce safety, not just how it can reduce safety. One potentially rich source of currently available information for exploring desired performance is the reports submitted to NASA’s Aviation Safety Reporting System (ASRS). These de-identified, confidential, and voluntary narrative reports are submitted by pilots, controllers, ground operators, and others within aviation operations. While these reports are primarily submitted to describe safety risks, incidents, and problems, they also often describe how those risks were mitigated, and provide a window into aspects of everyday work in aviation. These reports can be searched in a variety of ways. This paper describes methods for systematically examining ASRS narratives to understand how operators talk about their own resilient behaviors during adverse safety conditions and events. Guided by Erik Hollnagel’s Resilience Assessment Grid framework (i.e., anticipate, monitor, respond, learn), various approaches and tools for such inquiries are described. The approach, process, challenges, and suggestions to building an operator-based description of resilient performance are discussed, and tools to facilitate data analysis to maximize learning from these reports are described.

ASRS narratives↗