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NASA NTRS1999

Combustion and Flammability Characteristics of Solids at Microgravity in very Small Velocity Flows

Fires still remain as one of the most important safety risks in manned spacecraft. This problem will become even more important in long endurance non orbital flights in which maintenance will be non existing or very difficult. The basic process of a fire is the combustion of a solid at microgravity conditions in O2/N2 mixtures. Although a large number of research programs have been carried out on this problem, especially on flame spreading, several aspects of these processes are not yet well understood. It may be mentioned, for example, the temperature and characteristic of low emissivity flames in the visual range that take place in some conditions at microgravity; and there exists a lack of knowledge on the influence of key parameters, such as convective flow velocities of the order of magnitude of typical oxygen diffusion velocities. The "Departamento de Motopropulsion y Termofluidodinamica" of the "Universidad Politecnica de Madrid, Escuela Tecnica Superior de Ingenieros Aeronauticos" is conducting a research program on the combustion of solids at reduced gravity conditions within O2/N2 mixtures. The material utilized has been polymethylmethacrylate (PMMA) in the form of rectangular slabs and hollow cylinders. The main parameters of the process have been small convective flow velocities (including velocity angle with the direction of the spreading flame) and oxygen concentration. Some results have also been obtained on the influence of material thickness and gas pressure.

Sanchez-Tarifa, C.↗

NASA NTRS2024

Assessing the Number of Crew for Mars Against Trade Space Parameters

Missions to Mars will differ from all previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner given the long communication delays on Mars missions. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk in that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, the crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise in the Mission Control Central (MCC) team on which NASA has come to rely. We present a framework for trade space analysis along with results from human-performance models developed in IMPRINT. We discuss the implications of model results on the trade space for number of crew for missions to Mars. This work was funded by the NASA Engineering and Safety Center (NESC) with support from NASA’s Human Research Program (HRP).

Donna Dempsey↗

NASA NTRS2008

Testing HyDE on ADAPT

The IVHM Project in the Aviation Safety Program has funded research in electrical power system (EPS) health management. This problem domain contains both discrete and continuous behavior, and thus is directly relevant for the hybrid diagnostic tool HyDE. In FY2007 work was performed to expand the HyDE diagnosis model of the ADAPT system. The work completed resulted in a HyDE model with the capability to diagnose five times the number of ADAPT components previously tested. The expanded diagnosis model passed a corresponding set of new ADAPT fault injection scenario tests with no incorrect faults reported. The time required for the HyDE diagnostic system to isolate the fault varied widely between tests; this variance was reduced by tuning HyDE input parameters. These results and other diagnostic design trade-offs are discussed. Finally, possible future improvements for both the HyDE diagnostic model and HyDE itself are presented.

Sweet, Adam↗

NASA NTRSDate not supplied

Predicting Adverse Events and their Precursors in Aviation Using Multi-Class Multiple-Instance Learning

In recent years, there has been a rapid growth in the application of machine learning techniques that leverage aviation data collected from commercial airline operations to improve safety. Anomaly detection and predictive maintenance have been the main targets for machine learning applications. However, this paper focuses on the identification of precursors, which is a relatively newer application. Precursors are events correlated with adverse events that happen prior to the adverse event itself. Therefore, precursor mining provides many benefits including understanding the reasons behind a safety incident and the ability to identify signatures, which can be tracked throughout a flight to alert the operators of an potential upcoming adverse event. This work proposes using the multiple-instance learning (MIL) framework, a weakly supervised learning task, combined with a carefully designed Multi-Head Convolutional Neural Networks-Recurrent Neural Networks (MHCNN-RNN) architecture to predict different type of adverse events for any given flights and identify their precursors with little to no post-processing.Results obtained show that the MHCNN-RNN is able to accurately forecast high speed and high path angle events during the approach, and that it is also capable of determining the aircraft’s parameters that are correlated to these events. These parameters can be considered precursors to the events.

multiple instance learning↗

NASA NTRS1989

Distributed neural control of a hexapod walking vehicle

There has been a long standing interest in the design of controllers for multilegged vehicles. The approach is to apply distributed control to this problem, rather than using parallel computing of a centralized algorithm. Researchers describe a distributed neural network controller for hexapod locomotion which is based on the neural control of locomotion in insects. The model considers the simplified kinematics with two degrees of freedom per leg, but the model includes the static stability constraint. Through simulation, it is demonstrated that this controller can generate a continuous range of statically stable gaits at different speeds by varying a single control parameter. In addition, the controller is extremely robust, and can continue the function even after several of its elements have been disabled. Researchers are building a small hexapod robot whose locomotion will be controlled by this network. Researchers intend to extend their model to the dynamic control of legs with more than two degrees of freedom by using data on the control of multisegmented insect legs. Another immediate application of this neural control approach is also exhibited in biology: the escape reflex. Advanced robots are being equipped with tactile sensing and machine vision so that the sensory inputs to the robot controller are vast and complex. Neural networks are ideal for a lower level safety reflex controller because of their extremely fast response time. The combination of robotics, computer modeling, and neurobiology has been remarkably fruitful, and is likely to lead to deeper insights into the problems of real time sensorimotor control.

Beer, R. D.↗

NASA NTRS1989

Automatic control of cryogenic wind tunnels

Inadequate Reynolds number similarity in testing of scaled models affects the quality of aerodynamic data from wind tunnels. This is due to scale effects of boundary-layer shock wave interaction which is likely to be severe at transonic speeds. The idea of operation of wind tunnels using test gas cooled to cryogenic temperatures has yielded a quantrum jump in the ability to realize full scale Reynolds number flow similarity in small transonic tunnels. In such tunnels, the basic flow control problem consists of obtaining and maintaining the desired test section flow parameters. Mach number, Reynolds number, and dynamic pressure are the three flow parameters that are usually required to be kept constant during the period of model aerodynamic data acquisition. The series of activity involved in modeling, control law development, mechanization of the control laws on a microcomputer, and the performance of a globally stable automatic control system for the 0.3-m Transonic Cryogenic Tunnel (TCT) are discussed. A lumped multi-variable nonlinear dynamic model of the cryogenic tunnel, generation of a set of linear control laws for small perturbation, and nonlinear control strategy for large set point changes including tunnel trajectory control are described. The details of mechanization of the control laws on a 16 bit microcomputer system, the software features, operator interface, the display and safety are discussed. The controller is shown to provide globally stable and reliable temperature control to + or - 0.2 K, pressure to + or - 0.07 psi and Mach number to + or - 0.002 of the set point value. This performance is obtained both during large set point commands as for a tunnel cooldown, and during aerodynamic data acquisition with intrusive activity like geometrical changes in the test section such as angle of attack changes, drag rake movements, wall adaptation and sidewall boundary-layer removal. Feasibility of the use of an automatic Reynolds number control mode with fixed Mach number control is demonstrated.

Balakrishna, S.↗

NASA NTRS2013

Large Scale Flame Spread Environmental Characterization Testing

Under the Advanced Exploration Systems (AES) Spacecraft Fire Safety Demonstration Project (SFSDP), as a risk mitigation activity in support of the development of a large-scale fire demonstration experiment in microgravity, flame-spread tests were conducted in normal gravity on thin, cellulose-based fuels in a sealed chamber. The primary objective of the tests was to measure pressure rise in a chamber as sample material, burning direction (upward/downward), total heat release, heat release rate, and heat loss mechanisms were varied between tests. A Design of Experiments (DOE) method was imposed to produce an array of tests from a fixed set of constraints and a coupled response model was developed. Supplementary tests were run without experimental design to additionally vary select parameters such as initial chamber pressure. The starting chamber pressure for each test was set below atmospheric to prevent chamber overpressure. Bottom ignition, or upward propagating burns, produced rapid acceleratory turbulent flame spread. Pressure rise in the chamber increases as the amount of fuel burned increases mainly because of the larger amount of heat generation and, to a much smaller extent, due to the increase in gaseous number of moles. Top ignition, or downward propagating burns, produced a steady flame spread with a very small flat flame across the burning edge. Steady-state pressure is achieved during downward flame spread as the pressure rises and plateaus. This indicates that the heat generation by the flame matches the heat loss to surroundings during the longer, slower downward burns. One heat loss mechanism included mounting a heat exchanger directly above the burning sample in the path of the plume to act as a heat sink and more efficiently dissipate the heat due to the combustion event. This proved an effective means for chamber overpressure mitigation for those tests producing the most total heat release and thusly was determined to be a feasible mitigation strategy to incorporate into the microgravity experiment.

Clayman, Lauren K.↗

NASA NTRS2012

Design of Low Complexity Model Reference Adaptive Controllers

Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

Hanson, Curt↗

NASA NTRS2003

A Dynamic Risk Model for Evaluation of Space Shuttle Abort Scenarios

The Space Shuttle is an advanced manned launch system with a respectable history of service and a demonstrated level of safety. Recent studies have shown that the Space Shuttle has a relatively low probability of having a failure that is instantaneously catastrophic during nominal flight as compared with many US and international launch systems. However, since the Space Shuttle is a manned. system, a number of mission abort contingencies exist to primarily ensure the safety of the crew during off-nominal situations and to attempt to maintain the integrity of the Orbiter. As the Space Shuttle ascends to orbit it transverses various intact abort regions evaluated and planned before the flight to ensure that the Space Shuttle Orbiter, along with its crew, may be returned intact either to the original launch site, a transoceanic landing site, or returned from a substandard orbit. An intact abort may be initiated due to a number of system failures but the highest likelihood and most challenging abort scenarios are initiated by a premature shutdown of a Space Shuttle Main Engine (SSME). The potential consequences of such a shutdown vary as a function of a number of mission parameters but all of them may be related to mission time for a specific mission profile. This paper focuses on the Dynamic Abort Risk Evaluation (DARE) model process, applications, and its capability to evaluate the risk of Loss Of Vehicle (LOV) due to the complex systems interactions that occur during Space Shuttle intact abort scenarios. In addition, the paper will examine which of the Space Shuttle subsystems are critical to ensuring a successful return of the Space Shuttle Orbiter and crew from such a situation.

Henderson, Edward M.↗

NASA NTRS2008

Redesigned Human Metabolic Simulator

A design has been formulated for a proposed improved version of an apparatus that simulates atmospheric effects of human respiration by introducing controlled amounts of carbon dioxide, water vapor, and heat into the air. Denoted a human metabolic simulator (HMS), the apparatus is used for testing life-support equipment when human test subjects are not available. The prior version of the HMS, to be replaced, was designed to simulate the respiratory effects of as many as four persons. It exploits the catalytic combustion of methyl acetate, for which the respiratory quotient (the molar ratio of carbon dioxide produced to oxygen consumed) is very close to the human respiratory quotient of about 0.86. The design of the improved HMS provides for simulation of the respiratory effects of as many as eight persons at various levels of activity. The design would also increase safety by eliminating the use of combustion. The improved HMS (see figure) would include a computer that would exert overall control. The computer would calculate the required amounts of oxygen removal, carbon dioxide addition, water addition, and heat addition by use of empirical equations for metabolic profiles of respiration and heat. A blower would circulate air between the HMS and a chamber containing a life-support system to be tested. With the help of feedback from a mass flowmeter, the blower speed would be adjusted to regulate the rate of flow according to the number of persons to be simulated and to a temperature-regulation requirement (the air temperature would indirectly depend on the rate of flow, among other parameters). Oxygen would be removed from the circulating air by means of a commercially available molecular sieve configured as an oxygen concentrator. Oxygen, argon, and trace amounts of nitrogen would pass through a bed in the molecular sieve while carbon dioxide, the majority of nitrogen, and other trace gases would be trapped by the bed and subsequently returned to the chamber. If, as recommended, the oxygen concentrator were of a rotating twelve-bed design, then variations in the product stream could be made very small. Carbon dioxide would be added directly to the circulating air by simple injection from a supply tank. The rate of injection would be maintained at the required rate by use of a mass flowmeter/controller. In the same way, nitrogen would be added to make up for the small amount of nitrogen lost through the oxygen concentrator. Water vapor would be added to the circulating air by heating the corresponding required flow of water to steam in a heat exchanger. More heat, required to complete the simulation of the thermal effect of respiration, would be added through another heat exchanger. Heat would be supplied to both heat exchangers via a hot-oil loop.

Duffield, Bruce↗

NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

NASA NTRS2018

Exploring Li-Air Batteries for High Specific Energy and High Power Applications: A Simulation Study

Commercialization of lithium-air batteries face many challenges, such as electrolyte decomposition, short cycle life, low energy efficiency, low power density, etc. However, commercialization of Li-air batteries for mass sensitive applications such as electric vehicles, portable power source, and drones is more challenging due to additional constraints of safety, electrolyte evaporation, high specific energy requirements, and reliable discharge times. In this presentation, we will present our finite element simulation results comparing Li-O2 and Li-air batteries using power density, energy density, specific power, and discharge times as metrics to evaluate different electrolytes and electrode geometry to reduce total mass and maximize discharge current. We use a finite element model and a discharge product model developed in which is based on porous electrode and concentrated electrolyte theories and the discharge product is modeled using quantum tunneling; for reaction kinetics and oxygen diffusion, an improved model was used. The electrolyte properties such as ion conductivity and ion diffusion were obtained from Molecular Dynamics (MD) simulations while the other parameters for the finite element model were calibrated to match experiments at high discharge current densities (>1.5 mA/cm2). The mass densities of different electrolytes were computed using MD simulations as well. For this presentation, we examine the practical electrochemical mass of a system at different current ratings, the sensitivity of mass to the use of ambient air as compared to pure oxygen as well as the electrolyte, which affects maximum current density and the total mass associated with the electrolyte (which includes the mass of additional components), and, the optimization of battery geometry for total discharge time, average discharge voltage, maximum discharge current, and minimum electrochemical mass.

Mehta, M.↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

Systems Health Managent↗

NASA NTRS2015

Dynamic Open-Rotor Composite Shield Impact Test Report

The Federal Aviation Administration (FAA) is working with the European Aviation Safety Agency to determine the certification base for proposed new engines that would not have a containment structure on large commercial aircraft. Equivalent safety to the current fleet is desired by the regulators, which means that loss of a single fan blade will not cause hazard to the aircraft. NASA Glenn and Naval Air Warfare Center (NAWC) China Lake collaborated with the FAA Aircraft Catastrophic Failure Prevention Program to design and test a shield that would protect the aircraft passengers and critical systems from a released blade that could impact the fuselage. This report documents the live-fire test from a full-scale rig at NAWC China Lake. NASA provided manpower and photogrammetry expertise to document the impact and damage to the shields. The test was successful: the blade was stopped from penetrating the shield, which validates the design analysis method and the parameters used in the analysis. Additional work is required to implement the shielding into the aircraft.

Shielding↗

NASA NTRSDate not supplied

NASA’s Space Sustainability Strategy: An Overview and a Conceptual Framework for Implementation

Space sustainability is crucial for the continuation of humanity's exploration and utilization of space. NASA recognizes the imperative of maintaining a sustainable space operating environment to safeguard the future of space activities. On April 9, 2024, NASA released its first part of an integrated Space Sustainability Strategy focused on the domain of earth orbit, with future volumes to address impacts of space operations on earth itself; cislunar space, including the Lagrange points and the lunar surface; and deep space, including other celestial bodies. This commitment extends to ensuring the safety of astronauts conducting operations in Low Earth Orbit (LEO), as well as enabling missions to the Moon and Mars. Moreover, sustainable space practices are essential for the uninterrupted operation of NASA's robotic science missions, which monitor Earth's changes and probe the mysteries of the universe. The strategy sets out a set of goals, the first of which is to establish a framework for assessing space sustainability at NASA, addressing the absence of a universally accepted framework with key metrics that promotes understanding of how metrics are interconnected. This framework will provide a basis for evaluating the sustainability of orbital activities, with metrics informed by input from the domestic and international space community. Objectives under this goal include defining key parameters affecting space sustainability, determining tolerable levels of risk, and annually publishing NASA's effect on space sustainability, including compliance with orbital debris mitigation standards. The subsequent goals build upon this foundation, identifying effective actions for enhancing space sustainability, incentivizing adoption of these actions through technology development and policy changes, and ensuring coordination with the global space community. An organizational change within NASA is also proposed to facilitate day-to-day coordination and accountability for space sustainability efforts. By pursuing these goals, NASA aims to strengthen the technical foundations of and continue to set an example for sustainable space operations. Regular evaluation of NASA mission performance in context with meeting sustainability objectives will ensure alignment with evolving challenges in the space operating environment.

Matt Forsbacka↗

NASA NTRS1998

Structural Similitude and Scaling Laws

Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.

Simitses, George J.↗

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↗