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NASA NTRSDate not supplied

Strategies for Quantifying Human Space Flight Performance in the Crew Health and Performance System

The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center is planning a customized approach to quantify human spaceflight performance changes with respect to changes to the CHP system functions and capabilities. Using the Directed Acyclic Graphs (DAG) initiated by NASA’s Human Systems Risk Board (HSRB) [1], the team is surveying potential candidate models and novel strategies that generate metrics suitable for supporting decision making related to how the CHP system may influence human system performance risk. One such investigation includes classic Human Reliability Analysis (HRA) models. Traditionally, HRA methods estimate the occurrence of human errors and their impact on the success of an activity when designing and operating a system. While humans perceive, interpret, decide on, and carry out a course of action, the factors affecting performance and error likelihood are commonly referred to as performance shaping factors (PSFs). Originally developed to alleviate safety concerns related to nuclear power plant operations, HRA methods such as THERP [2] and CREAM [3] dismantle an activity into tasks, requiring elemental steps to be executed, and assess their failure due to predefined PSFs. In this study, we compare generic HRA methods and those that incorporate some human spaceflight aspects, such as sleep conditions (SCREAM [4]), with respect to how they may be adopted to capture performance with an intention to mitigate detrimental outcomes elucidated by the HSRB DAGs. We suggest strategies to quantify astronaut performance specific to spaceflight activities and illustrate how such concepts may help in optimizing the CHP system capabilities with respect to Artemis missions.

dag↗
NASA NTRS1974

An analysis of pilot error-related aircraft accidents

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Kowalsky, N. B.↗
NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗
NASA NTRS2011

The Psychology of Safety

Many studies of mishaps show that human error is a factor in a significant majority of accidents. Trying to decide how to change human behavior to be safer is generally the biggest challenge of any safety program. However, understanding the human psyche is the first step to changing behavior. Many studies focus on the before and after of an accident, but what about the thoughts of a person in the commission of an unsafe act? This is a less understood area. Examining it reveals why it is not well comprehended. This paper attempts to examine a part of the thought process, with an eye to helping influence people to less hurtful actions.

Anderson, Brenda Lindley↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗
NASA NTRS2002

Skills, rules and knowledge in aircraft maintenance: errors in context

Automatic or skill-based behaviour is generally considered to be less prone to error than behaviour directed by conscious control. However, researchers who have applied Rasmussen's skill-rule-knowledge human error framework to accidents and incidents have sometimes found that skill-based errors appear in significant numbers. It is proposed that this is largely a reflection of the opportunities for error which workplaces present and does not indicate that skill-based behaviour is intrinsically unreliable. In the current study, 99 errors reported by 72 aircraft mechanics were examined in the light of a task analysis based on observations of the work of 25 aircraft mechanics. The task analysis identified the opportunities for error presented at various stages of maintenance work packages and by the job as a whole. Once the frequency of each error type was normalized in terms of the opportunities for error, it became apparent that skill-based performance is more reliable than rule-based performance, which is in turn more reliable than knowledge-based performance. The results reinforce the belief that industrial safety interventions designed to reduce errors would best be directed at those aspects of jobs that involve rule- and knowledge-based performance.

Aircraft↗
NASA NTRS1988

Human operator response to error-likely situations in complex engineering systems

The causes of human error in complex systems are examined. First, a conceptual framework is provided in which two broad categories of error are discussed: errors of action, or slips, and errors of intention, or mistakes. Conditions in which slips and mistakes might be expected to occur are identified, based on existing theories of human error. Regarding the role of workload, it is hypothesized that workload may act as a catalyst for error. Two experiments are presented in which humans' response to error-likely situations were examined. Subjects controlled PLANT under a variety of conditions and periodically provided subjective ratings of mental effort. A complex pattern of results was obtained, which was not consistent with predictions. Generally, the results of this research indicate that: (1) humans respond to conditions in which errors might be expected by attempting to reduce the possibility of error, and (2) adaptation to conditions is a potent influence on human behavior in discretionary situations. Subjects' explanations for changes in effort ratings are also explored.

Morris, Nancy M.↗
NASA NTRS2011

Man-Machine Integration Design and Analysis System (MIDAS) v5: Augmentations, Motivations, and Directions for Aeronautics Applications

As automation and advanced technologies are introduced into transport systems ranging from the Next Generation Air Transportation System termed NextGen, to the advanced surface transportation systems as exemplified by the Intelligent Transportations Systems, to future systems designed for space exploration, there is an increased need to validly predict how the future systems will be vulnerable to error given the demands imposed by the assistive technologies. One formalized approach to study the impact of assistive technologies on the human operator in a safe and non-obtrusive manner is through the use of human performance models (HPMs). HPMs play an integral role when complex human-system designs are proposed, developed, and tested. One HPM tool termed the Man-machine Integration Design and Analysis System (MIDAS) is a NASA Ames Research Center HPM software tool that has been applied to predict human-system performance in various domains since 1986. MIDAS is a dynamic, integrated HPM and simulation environment that facilitates the design, visualization, and computational evaluation of complex man-machine system concepts in simulated operational environments. The paper will discuss a range of aviation specific applications including an approach used to model human error for NASA s Aviation Safety Program, and what-if analyses to evaluate flight deck technologies for NextGen operations. This chapter will culminate by raising two challenges for the field of predictive HPMs for complex human-system designs that evaluate assistive technologies: that of (1) model transparency and (2) model validation.

Gore, Brian F.↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Multitasking

Multitasking is endemic in modern life and work: drivers talk on cell phones, office workers type while answering phone calls, students do homework while text messaging, nurses prepare injections while responding to doctor’s calls, and air traffic controllers direct aircraft in one sector while handling additional traffic in another. Whether in daily life or at work, we are constantly bombarded with multiple concurrent demands, and we have all somehow come to believe in the myth that we can, and in fact are expected to, easily address them all - without any repercussions. However, accumulating scientific evidence is now suggesting that multitasking increases the probability of human error. This talk presents a set of NASA studies that characterize concurrent demands in routine airline flight operations, in order to illustrate the ways operational task demands together with the proclivity to manage them all concurrently make human performance in this and in any domain vulnerable to potentially serious errors and to accidents.

multitasking↗
NASA NTRS1985

Investigation of technology needs for avoiding helicopter pilot error related accidents

Pilot error which is cited as a cause or related factor in most rotorcraft accidents was examined. Pilot error related accidents in helicopters to identify areas in which new technology could reduce or eliminate the underlying causes of these human errors were investigated. The aircraft accident data base at the U.S. Army Safety Center was studied as the source of data on helicopter accidents. A randomly selected sample of 110 aircraft records were analyzed on a case-by-case basis to assess the nature of problems which need to be resolved and applicable technology implications. Six technology areas in which there appears to be a need for new or increased emphasis are identified.

Chais, R. I.↗
NASA NTRS1988

Human factors: Aeronautics

The objectives of the Aeronautics Human Factors Research and Technology program are to provide the technology base and capability to design effective crew-cockpit systems and to advance solutions to human problems affecting air transport and rotorcraft effectiveness and safety. Advanced automation technologies, information display capabilities under computer control, and concern for the effects of human error in flight operations are elements which drive the directions of the program. Thus, the program has four thrusts: flight management, human engineering methods, rotorcraft, and subsonic transports.

Jenkins, James P.↗
NASA NTRS2012

Human Systems Engineering for Launch processing at Kennedy Space Center (KSC)

Launch processing at Kennedy Space Center (KSC) is primarily accomplished by human users of expensive and specialized equipment. In order to reduce the likelihood of human error, to reduce personal injuries, damage to hardware, and loss of mission the design process for the hardware needs to include the human's relationship with the hardware. Just as there is electrical, mechanical, and fluids, the human aspect is just as important. The focus of this presentation is to illustrate how KSC accomplishes the inclusion of the human aspect in the design using human centered hardware modeling and engineering. The presentations also explain the current and future plans for research and development for improving our human factors analysis tools and processes.

Henderson, Gena↗
NASA NTRS2018

The Story of Multitasking

Multitasking is endemic in modern life and work: drivers talk on cell phones, office workers type while answering phone calls, students do homework while text messaging...but, nurses also prepare injections while responding to doctor's calls, and air traffic controllers direct aircraft in one sector while handling aircraft additional traffic in another. Whether in daily life or at work, we are constantly bombarded with multiple, concurrent interruptions and demands and we have all somehow come to believe in the myth that we can, and in fact are expected to, easily address them all - without any repercussions. Accumulating However, accumulating scientific evidence is now suggesting that multitasking increases the probability of human error. This talk presents a set of NASA studies that characterize concurrent demands in one work domain, routine airline cockpit operations, in order to illustrate the ways operational task demands together with the natural proclivity to manage them all concurrently make human performance in this and in any work domain vulnerable to potentially serious errors and to accidents.

Barshi, Immanuel↗
NASA NTRSDate not supplied

Design and Applications of Tethered Spacecraft Simulators

Small, tethered spacecraft, or space tugs, are a promising space capability. They can be deployed on tethers and used for a wide variety of in-space activities; a large portion of which fall under in-space servicing, assembly, manufacturing (ISAM) functions. This includes functions such as structural mating and assembly, servicing, proximity operations, capture, docking, mating, and relocation. However, there is a great deal of work to be done to raise the Technology Readiness Level (TRL) of the capabilities needed to fully realize these capabilities. The Flat Floor Robotics Lab (FFRL) at NASA’s Marshall Spaceflight Center (MSFC) has been working on space tug development for several years. The eponymous floor is 44 by 86 feet, made from a self-leveling epoxy. This creates an extremely smooth surface that air bearings can float on with very little friction, creating a simulation of zero gravity in a two-dimensional plane. The lab has several platforms of various sizes that act as vehicle simulators for testing sensors, control algorithms, mechanisms, etc. One of these platforms is a small spacecraft simulator, which can be tethered to simulate a space tug. In the last several months, the FFRL team has been working with MSFC’s welding group to conduct a laser beam welding demonstration on air bearing platforms. This demo is utilizing a space tug simulator to fly up to a floating weld platform, where two parts are clamped together and laser welded. The space tug simulator has an air bearing to provide float, as well as several actuated air thrusters to provide propulsion and make the simulator maneuverable. Currently, flights of this simulator are completed by a human operator. An RF hand controller sends signals to both actuate and fire three sets of thrusters on the simulator. This makes any maneuvers of the space tug highly subject to human error, and operators must have dedicated practice time before being able to perform maneuvers with any sufficient reliability. For the current laser welding demonstration, human operated performance is sufficient, but future implementations of in-space welding and other ISAM efforts will require higher precision, reliability, and autonomy. MSFC has funded a project that will allow a small team in the FFRL to develop the next generation of space tug simulator, which will be automated. Closed loop control will allow a user to command a position, or set of positions, that the simulator will be able to “fly” to on its own. This Maneuverable Automated Tethered Spacecraft (MATS) simulator will have configurable design, to allow a variety of payloads and mission configurations to be demonstrated on the air bearing floor. This will be an invaluable test bed for low and mid TRL advancement for space tether mission subsystems, such as more advanced demonstrations of in-space welding. Once one MATSS is constructed and demonstrated effectively, several more can be built, enabling more advanced tether missions; Electric Sail test beds, sensor arrays, and other science-enabling missions. This paper will detail the design and test of the FFRL’s MATS simulator, including efforts to establish closed loop control and autonomous capabilities. It will also detail use cases for this technology, and how it will further develop both develop science and exploration missions.

Space Tethers↗
NASA NTRS2011

Should Pruning be a Pre-Processor of any Linear System?

There are many real-world problems whose mathematical models turn out to be linear systems Ax = b , where A is an m by x n matrix. Each equation of the linear system is an information. An information, in a physical problem, such as 4 mangoes, 6 bananas, and 5 oranges cost $10, is mathematically modeled as 4x(sub 1) + 6x(sub 2) + 5x (sub 3) = 10, where x(sub 1), x(sub 2), x(sub 3) are each cost of one mango, that of one banana, and that of one orange, respectively. All the information put together in a specified context, constitutes the physical problem and need not be all distinct. Some of these could be redundant, which cannot be readily identified by inspection. The resulting mathematical model will thus have equations corresponding to this redundant information and hence are linearly dependent and thus superfluous. Consequently, these equations once identified should be better pruned in the process of solving the system. The benefits are (i) less computation and hence less error and consequently a better quality of solution and (ii) reduced storage requirements. In literature, the pruning concept is not in vogue so far although it is most desirable. In a numerical linear system, the system could be slightly inconsistent or inconsistent of varying degree. If the system is too inconsistent, then we should fall back on to the physical problem (PP), check the correctness of the PP derived from the material universe, modify it, if necessary, and then check the corresponding mathematical model (MM) and correct it. In nature/material universe, inconsistency is completely nonexistent. If the MM becomes inconsistent, it could be due to error introduced by the concerned measuring device and/or due to assumptions made on the PP to obtain an MM which is relatively easily solvable or simply due to human error. No measuring device can usually measure a quantity with an accuracy greater that 0.005% or, equivalently with a relative error less than 0.005%. Hence measurement error is unavoidable in a numerical linear system when the quantities are continuous (or even discrete with extremely large number). Assumptions, though not desirable, are usually made when we find the problem sufficiently difficult to be solved within the available means/tools/resources and hence distort the PP and the corresponding MM. The error thus introduced in the system could (not always necessarily though) make the system somewhat inconsistent. If the inconsistency (contradiction) is too much then one should definitely not proceed to solve the system in terms of getting a least-squares solution or a minimum norm solution or the minimum-norm least-squares solution. All these solutions will be invariably of no real-world use. If, on the other hand, inconsistency is reasonably low, i.e. the system is near-consistent or, equivalently, has near-linearly-dependent rows, then the foregoing solutions are useful. Pruning in such a near-consistent system should be performed based on the desired accuracy and on the definition of near-linear dependence. In this article, we discuss pruning over various kinds of linear systems and strongly suggest its use as a pre-processor or as a part of an algorithm. Ideally pruning should (i) be a part of the solution process (algorithm) of the system, (ii) reduce both computational error and complexity of the process, and (iii) take into account the numerical zero defined in the context. These are precisely what we achieve through our proposed O(mn2) algorithm presented in Matlab, that uses a subprogram of solving a single linear equation and that has embedded in it the pruning.

Sen, Syamal K.↗
NASA NTRS2011

Should Pruning be a Pre-Processor of any Linear System?

There are many real-world problems whose mathematical models turn out to be linear systems Ax = b, where A is an m x n matrix. Each equation of the linear system is an information. An information, in a physical problem, such as 4 mangoes, 6 bananas, and 5 oranges cost $10, is mathematically modeled as an equation 4x(sub 1) + 6x(sub 2) + 5x(sub 3) = 10 , where x(sub 1), x(sub 2), x(sub 3) are each cost of one mango, that of one banana, and that of one orange, respectively. All the information put together in a specified context, constitutes the physical problem and need not be all distinct. Some of these could be redundant, which cannot be readily identified by inspection. The resulting mathematical model will thus have equations corresponding to this redundant information and hence are linearly dependent and thus superfluous. Consequently, these equations once identified should be better pruned in the process of solving the system. The benefits are (i) less computation and hence less error and consequently a better quality of solution and (ii) reduced storage requirements. In literature, the pruning concept is not in vogue so far although it is most desirable. It is assumed that at least one information, i.e. one equation is known to be correct and which will be our first equation. In a numerical linear system, the system could be slightly inconsistent or inconsistent of varying degree. If the system is too inconsistent, then we should fall back on to the physical problem (PP), check the correctness of the PP derived from the material universe, modify it, if necessary, and then check the corresponding mathematical model (MM) and correct it. In nature/material universe, inconsistency is completely nonexistent. If the MM becomes inconsistent, it could be due to error introduced by the concerned measuring device and/or due to assumptions made on the PP to obtain an MM which is relatively easily solvable or simply due to human error. No measuring device can usually measure a quantity with an accuracy greater that 0.005% or, equivalently with a relative error less than 0.005%. Hence measurement error is unavoidable in a numerical linear system when the quantities are continuous (or even discrete with extremely large number). Assumptions, though not desirable, are usually made when we find the problem sufficiently difficult to be solved within the available means/tools/resources and hence distort the PP and the corresponding MM. The . error thus introduced in the system could (not always necessarily though) make the system somewhat inconsistent. If the inconsistency (contradiction) is too much then one should definitely not proceed to solve the system in terms of getting a least-squares solution or the minimum-norm least-squares solution. All these solutions will be invariably of no real-world use. If, on the other hand, inconsistency is reasonably low, i.e. the system is near-consistent or, equivalently, has near-linearly-dependent rows, then the foregoing solutions are useful. Pruning in such a near-consistent system should be performed based on the desired accuracy and on the definition of near-linear dependence. In this article, we discuss pruning over various kinds of linear systems and strongly suggest its use as a pre-processor or as a part of an algorithm. Ideally pruning should (i) be a part of the solution process (algorithm) of the system, (ii) reduce both computational error and complexity of the process, and (iii) take into account the numerical zero defined in the context. These are precisely what we achieve through our proposed O(mn2) algorithm presented in Matlab, that uses a subprogram of solving a single linear equation and that has embedded in it the pruning.

Sen, Syamal K.↗