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At least 361 records · Page 20

Human Factors and Information Operation for a Nuclear Power Space Vehicle

This paper describes human-interactive systems needed for a crewed nuclear-enabled space mission. A synthesis of aircraft engine and nuclear power plant displays, biofeedback of sensory input, virtual control, brain mapping for control process and manipulation, and so forth are becoming viable solutions. These aspects must maintain the crew's situation awareness and performance, which entails a delicate function allocation between crew and automation.

Trujillo, Anna C.↗

Identifying Human Errors and Error Mechanisms From Accident Reports Using Large Language Models

Emerging operational concepts for aviation hinge on novel paradigms for human machine interaction. Critical to their safe operation is early consideration of human error into the design process. Existing methods for consideration of human error require significant expert input, which is challenging both in early design and in novel systems for which there is little existing safety expertise. In this research, we propose a methodology for identifying human error, error producing factors, and mechanisms in early design from historical incident reports. Additionally, we hypothesize that cross-domain sharing of lessons learned can aid with early design human considerations in circumstances where data is not relevant or incomplete. This is addressed by identifying causes of human error in aviation and railway domains through applying state-of-the art natural language processing techniques to historical incident reports. Using this method, it is possible to extract extensive reports on human error from past incidents. Using the proposed approach, we identify nine human errors from railway reports and fourteen from aviation reports, with three errors common to both domains. There is at least one error producing conditions for each human error while a majority of the errors have more than one error mechanism. We also found that a majority of the human errors, error producing factors, and error mechanisms (even if they are not common between the domains) can be used to inform safe operations across domains as long as the errors are not domain specific and are interpreted and contextualized using engineering judgement.

Human Errors↗

Motion sickness and proprioceptive aftereffects following virtual environment exposure

To study the potential aftereffects of virtual environments (VE), tests of visually guided behavior and felt limb position (pointing with eyes open and closed) along with self-reports of motion sickness-like discomfort were administered before and after 30 min exposure of 34 subjects. When post- discomfort was compared to a pre-baseline, the participants reported more sickness afterward (p < 0.03). The change in felt limb position resulted in subjects pointing higher (p < 0.038) and slightly to the left, although the latter difference was not statistically significant (p = 0.08). When findings from a second study using a different VE system were compared, they essentially replicated the results of the first study with higher sickness afterward (p < 0.001) and post- pointing errors were also up (p < 0.001) and to the left (p < 0.001). While alternative explanations (e.g. learning, fatigue, boredom, habituation, etc.) of these outcomes cannot be ruled out, the consistency of the post- effects on felt limb position changes in the two VE implies that these recalibrations may linger once interaction with the VE has concluded, rendering users potentially physiologically maladapted for the real world when they return. This suggests there may be safety concerns following VE exposures until pre-exposure functioning has been regained. The results of this study emphasize the need for developing and using objective measures of post-VE exposure aftereffects in order to systematically determine under what conditions these effects may occur.

NASA Discipline Neuroscience↗

Certification of tactics and strategies in aviation

The paper suggests that the 'tactics and strategies' notion is a highly suitable paradigm to describe the cognitive involvement of human operators in advanced aviation systems (far more suitable than classical functional analysis), and that the workload and situational awareness of operators are intimately associated with the planning and execution of their tactics and strategies. If system designers have muddled views about the collective tactics and strategies to be used during operation, they will produce sub-optimum designs. If operators use unproven and/or inappropriate tactics and strategies, the system may fail. The author wants to make a point that, beyond certification of people or system designs, there may be a need to go into more detail and examine (certify?) the set of tactics and strategies (i.e., the Operational Concept) which makes the people and systems perform as expected. The collective tactics and strategies determine the information flows and situational awareness which exists in organizations and composite human-machine systems. The available infrastructure and equipment (automation) enable these information flows and situational awareness, but are at the same time the constraining factor. Frequently, the tactics and strategies are driven by technology, whereas we would rather like to see a system designed to support an optimized Operational Concept, i.e., to support a sufficiently coherent, cooperative and modular set of anticipation and planning mechanisms. Again, in line with the view of MacLeod and Taylor (1993), this technology driven situation may be caused by the system designer's and operator job designer's over-emphasis on functional analysis (a mechanistic engineering concept), at the expense of a subject which does not seem to be well understood today: the role of the (human cognitive and/or automated) tactics and strategies which are embedded in composite human-machine systems. Research would be needed to arrive at a generally accepted 'planning theory' which can elevate the analysis, description and design of tactics and strategies from today's cottage industry methods to an engineering discipline. The available infrastructure and equipment (automation) enable these information flows and situational awareness, but are at the same time the constraining factor. Frequently, the tactics and strategies are driven by technology, whereas we would rather like to see a system designed to support an optimized Operational Concept, i.e., to support a sufficiently coherent, cooperative and modular set of anticipation and planning mechanisms. Again, in line with the view of MacLeod and Taylor (1993), this technology driven situation may be caused by the system designer's and operator job designer's over-emphasis on functional analysis (a mechanistic engineering concept), at the expense of a subject which does not seem to be well understood today: the role of the (human cognitive and/or automated) tactics and strategies which are embedded in composite human-machine systems. Research would be needed to arrive at a generally accepted 'planning theory' which can evaluate the analysis, description and design of tactics and strategies from today's cottage industry methods to an engineering discipline.

Koelman, Hartmut↗

Digital risk analysis in nuclear engineering projects: Designing for safety, performance, reliability, and security

Cyber-informed engineering and security-by-design frameworks are important in promoting the need to identify cybersecurity concerns early in the systems engineering lifecycle so risks from adversarial cyber-attacks can be eliminated or reduced through engineering design practices. In addition to adversarial risk, risk in operational technology systems also includes non-adversarial and unintentional risk from other factors such as human performance errors, environmental conditions, design flaws, and device degradation or failure. This paper introduces a new concept for characterizing digital risk, both adversarial and non-adversarial, and provides the basis for initial research into a novel digital risk analysis approach focused on incorporating attack difficulty into a multi-attribute analysis technique using robust decision-making. This digital risk characterization is also used to frame a discussion on the challenges of competing objectives and competing stakeholder requirements in an integrated energy system project that incorporates a small modular reactor and industrial facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Enhancing Interdisciplinary Human System Risk Research Through Modeling and Network Approaches

NASA's Human Research Program (HRP) supports research to reduce human health and performance risks inherent in future human space exploration missions. Understanding risk outcomes and contributing factors in an integrated manner allows HRP research to support development of efficient and effective mitigations from cross‐disciplinary perspectives, and to enable resilient human and engineered systems for spaceflight. The purpose of this work is to support scientific collaborations and research portfolio management by utilizing modeling for analysis and visualization of current and potential future interdisciplinary efforts.

Mindock, Jennifer↗

Research and Technology Challenges for Human Data Analysts in Future Safety Management Systems

Enabling new and novel concepts of operations for Advanced Air Mobility poses an important need to evolve current safety management systems (SMS) and is posited to be realized through advances in Machine Learning (ML) Data Sciences and Artificial Intelligence. The “In-time Aviation Safety Management System” (IASMS) concept of operations supports the need to evolve today’s SMS to become more tailorable, scalable, and interoperable in response to forecasted changes expected for the future airspace system. Key to IASMS is integration of proactive and predictive ML algorithms trained to provide “in time” detection and mitigation of hazards and emergent risks through new methods and novel data types. IASMS research and technology development includes human factors design considerations for these systems to include human-system teaming, innovations in human interfaces and management of complex digital data information, human-system interaction/model-based system engineering, and verification and validation for data assurance and trust.

Chad L Stephens↗

Integrated Systems Engineering, Safety, Reliability and Risk Management – Minimizing Black Swan Events

This paper examines key barriers that can possibly inhibit safe and reliable mission execution and, in the worst case, result in loss of human life due to many unknown contributory factors that can lead to Black Swan events. Some of the representative contributory factors include decision errors, overconfidence and a host of common causes including cultural and human factors. Decisions are always easy to criticize in hindsight when more information is available after a major accident. Depending on the type and complexity of the project and/or mission, the catastrophic risks of drifting into failure can be alleviated by implementing uniquely and strategically tailored Integrated-System-of-Systems, dynamic, risk-informed decision management processes. This paper presents some of the lessons learned from James Webb Space Telescope (JWST), NASA’s Human Space Flight program, and industry that provide motivation to organizations working on mega-complex missions to prudently accomplish targeted mission success. These lessons are important for future human Lunar, Mars and Beyond missions planned to be pursued by NASA through a public-private partnership using nimble but effective safety-conscious, proven sound engineering practices including implementation of integrated risk mitigation practices.

SLS↗

Humans to Mars, but How Many? Using Imprint Human Performance Models to Inform Crew Size

HUMANS TO MARS, BUT HOW MANY? USING IMPRINT HUMAN PERFORMANCE MODELS TO INFORM CREW SIZE Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The custom-built crew expertise model results will be presented in the training sub-tag. Here we present results of the three IMPRINT models. Two of these models were built using IMPRINT’s Operations Model capability, with detailed task networks for specific systems and scenarios allowing for a comprehensive mental workload analysis on certain crew positions. The third model was built using IMPRINT’s Force Model capability, allowing for a higher-level manpower analysis based on crew engagement in activities performed over a longer Mars transit scenario, and how those activities may be impacted by unplanned events and new tasking unique to the Mars mission. Differences between the models will be presented, as well as examples of model results and a discussion of how those results may inform future Mars mission manpower requirements, system design, and operating procedures.

Donna L Dempsey↗

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗

Engineering management of large scale systems

The organization of high technology and engineering problem solving, has given rise to an emerging concept. Reasoning principles for integrating traditional engineering problem solving with system theory, management sciences, behavioral decision theory, and planning and design approaches can be incorporated into a methodological approach to solving problems with a long range perspective. Long range planning has a great potential to improve productivity by using a systematic and organized approach. Thus, efficiency and cost effectiveness are the driving forces in promoting the organization of engineering problems. Aspects of systems engineering that provide an understanding of management of large scale systems are broadly covered here. Due to the focus and application of research, other significant factors (e.g., human behavior, decision making, etc.) are not emphasized but are considered.

Sanders, Serita↗

Enabling the Capture and Sharing of NASA Technical Expertise Through Communities of Practice

Historically, engineers at the National Aeronautics and Space Administration (NASA) had few opportunities or incentives to share their technical expertise across the Agency. Its center- and project- focused culture often meant that knowledge never left organizational and geographic boundaries. With increasingly complex missions, the closeout of the Shuttle Program, and a new generation entering the workforce, developing a knowledge sharing culture became critical. To address this need, the Office of the Chief Engineer established communities of practice on the NASA Engineering Network. These communities were strategically aligned with NASA's core competencies in such disciplines as avionics, flight mechanics, life support, propulsion, structures, loads and dynamics, human factors, and guidance, navigation, and control. This paper describes the process used to identify and develop communities, from establishing simple websites that compiled discipline-specific resources to fostering a knowledge-sharing environment through collaborative and interactive technologies. It includes qualitative evidence of improved availability and transfer of knowledge. It focuses on pivotal capabilities that increased knowledge exchange such as a custom-made Ask An Expert system, community contact lists, publication of key resources, and submission forms that allowed any user to propose content for the sites. It discusses the peer relationships that developed through the communities and the leadership and infrastructure that made them possible.

Topousis, Daria E.↗

Remotely Piloted Aircraft Systems

Remotely piloted aircraft range from quadcopter “drones” with endurance measured in minutes, to large, long endurance aircraft powered by jet turbine engines. The central message of this chapter is that the further development of unmanned aviation may be held back more by a lack of attention to human factors, than by technological hurdles. This chapter begins with a brief overview of remotely piloted aircraft, follows with a review of their accident record, and then focuses on human factors principles for Remote Pilot Stations (RPS).

remotely piloted aircraft↗

Fast Paced, Low Cost Projects at MSFC

What does an orbiting microsatellite, a robotic lander and a ruggedized camera and telescope have in common? They are all fast paced, low cost projects managed by Marshall Space Flight Center (MSFC) teamed with successful industry partners. MSFC has long been synonymous with human space flight large propulsion programs, engineering acumen and risk intolerance. However, there is a growing portfolio/product line within MSFC that focuses on these smaller, fast paced projects. While launching anything into space is expensive, using a managed risk posture, holding to schedule and keeping costs low by stopping at egood enough f were key elements to their success. Risk is defined as the possibility of loss or failure per Merriam Webster. The National Aeronautics and Space Administration (NASA) defines risk using procedural requirement 8705.4 and establishes eclasses f to discern the acceptable risk per a project. It states a Class D risk has a medium to significant risk of not achieving mission success. MSFC, along with industry partners, has created a niche in Class D efforts. How did the big, cautious MSFC succeed on these projects that embodied the antithesis of its heritage in human space flight? A key factor toward these successful projects was innovative industry partners such as Dynetics Corporation, University of Alabama in Huntsville (UAHuntsville), Johns Hopkins Applied Physics Laboratory (JHU APL), Teledyne Brown Engineering (TBE), Von Braun Center for Science and Innovation (VCSI), SAIC, and Jacobs. Fast Affordable Satellite Technology (FastSat HSV01) is a low earth orbit microsatellite that houses six instruments with the primary scientific objective of earth observation and technology demonstration. The team was comprised of Dynetics, UAHuntsvile, SAIC, Goddard Space Flight Center (GSFC) and VCSI with the United States Air Force Space Test Program as the customer. The team completed design, development, manufacturing, environmental test and integration in one year. FastSat HSV01 also deployed a Poly Picosatellite Orbital Deployer (PPOD) for a separate nano ]satellite class spacecraft (Cubesat: Nano Sail Demonstration) in partnership with Ames Research Center. The Robotic lunar lander is a MSFC JHU APL partnership that led to the development of a flexible architecture for landers to support robotic missions to a wide range of lunar and asteroid destinations. The team started with the goal of meeting NASA agency directives that led to the creation of a test bed focusing on GN&C and software to demonstrate the descent and landing on any airless body for the final 30 to 60 meters. The team created a complex technology demonstration as well as Guidance Control and Navigation (GN&C) algorithms providing autonomous control of the lander. The team uses a green propellant of 90% hydrogen peroxide and has completed 18 successful test flights. The International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) is a technology demonstration payload to assist the SERVIR project with environmental monitoring for disaster relief and humanitarian efforts. The ISERV project was a partnership with TBE. The ISERV payload consists of a commercial off the shelf camera, telescope, and MSFC developed power distribution box and interfaces on ISS with the Window Observational Research Facility in the US Lab. MSFC has identified three key areas that enabled the low cost mission success to include culture, partnering, and cost/schedule control. This paper will briefly discuss these three Class D efforts, FastSat HSV-01, the Robotic Lunar Lander and the ISERV camera system, the lessons learned, their successes and challenges.

Watson-Morgan, Lisa↗

Resilience Modeling in Complex Engineered Systems with Human-Machine Interactions

In recent times, there has been a growing interest in resilience-based design. Resilience-based design operates on the concept that failures and unexpected events will happen, and when they occur, complex engineered systems should be able to operate within acceptable bounds and recover reasonably. Humans can contribute to the resilience of a system by quickly detecting unforeseen events and taking corrective measures. To this effect, researchers have proposed guidelines and design approaches that can help promote human-system resilience. However, there is no early design stage tool to validate if a system is indeed resilient after applying these guidelines and design methods. In this research, we integrate the Human Error and Functional Failure Reasoning (HEFFR) framework into the fmdtools toolkit to enable designers to model the combined (machine, human, and joint) failures, including their propagation and dynamic effects, during early design stages. This integrated tool also allows designers to model the effects of performance shaping factors, team dynamics, and human-machine interactions in systems of systems. A demonstrative example of a remotely operated rover is explored to demonstrate how this approach can be applied to understand resilience in complex engineered systems with human interactions.

Lukman Irshad↗

Human Factors Checklist: Think Human Factors - Focus on the People

A quick-look Human Factors (HF) Checklist condenses industry and NASA Agency standards consisting of thousands of requirements into 14 main categories. With support from contractor HF and Safety Practitioners, NASA developed a means to share key HF messages with Design, Engineering, Safety, Project Management, and others. It is often difficult to complete timely assessments due to the large volume of HF information. The HF Checklist evolved over time into a simple way to consider the most important concepts. A wide audience can apply the checklist early in design or through planning phases, even before hardware or processes are finalized or implemented. The checklist is a good place to start to supplement formal HF evaluation. The HF Checklist was based on many Space Shuttle processing experiences and lessons learned. It is now being applied to ground processing of new space vehicles and adjusted for new facilities and systems.

Human Factors; Human Systems Integration↗

Human Factors Considerations in System Design

Human factors considerations in systems design was examined. Human factors in automated command and control, in the efficiency of the human computer interface and system effectiveness are outlined. The following topics are discussed: human factors aspects of control room design; design of interactive systems; human computer dialogue, interaction tasks and techniques; guidelines on ergonomic aspects of control rooms and highly automated environments; system engineering for control by humans; conceptual models of information processing; information display and interaction in real time environments.

Christine M Mitchell↗