The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Youchao Sun - One of the best experts on this subject based on the ideXlab platform.
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Flight Safety assessment based on an integrated human reliability quantification approach.
PloS one, 2020Co-Authors: Yundong Guo, Youchao SunAbstract:Human error is an important risk factor for Flight Safety. Although the human error assessment and reduction technique (HEART) is an available tool for human reliability derivation, it has not been applied in Flight Safety assessment. The traditional HEART suffers from imprecise calculation of the assessed proportion of affect (APOA) because it heavily depends on a single expert's judgment. It also fails to provide remedial measures for Flight Safety problems. To overcome these defects of the HEART, this study proposes an integrated human error quantification approach that uses the improved analytic hierarchy process method to determine the APOA values. Then, these values are fused to the HEART method to derive the human error probability. A certain Flight task is completed to assess human reliability. The results demonstrate that the proposed method is a reasonable and feasible tool for quantifying human error probability and assessing Flight Safety in the aircraft manipulation process. In addition, the critical error-producing conditions influencing Flight Safety are identified, and improvement measures for high-error-rate operations are provided. The proposed method is useful for reducing the possibility of human error and enhancing Flight Safety levels in aircraft operation processes.
Ella M. Atkins - One of the best experts on this subject based on the ideXlab platform.
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markov decision process framework for Flight Safety assessment and management
Journal of Guidance Control and Dynamics, 2017Co-Authors: Sweewarman Balachandran, Ella M. AtkinsAbstract:Loss of control is the most common precursor to aircraft accidents. This paper presents a Flight Safety assessment and management system aimed at mitigating loss-of-control risks. Nominally, Flight Safety assessment and management serves as a passive watchdog system. When loss-of-control scenarios are encountered, Flight Safety assessment and management issues resilient control overrides to restore a safe operational state. This paper formulates Flight Safety assessment and management as a Markov decision process to account for uncertainties in state evolution and tradeoffs between passive monitoring and Safety-based override. To ensure unsafe states are unreachable, probabilistic constraints are incorporated into the Markov decision process formulation. The Markov decision process framework is applied to prevent loss-of-control events during takeoff. An abstract representation of the underlying state space is specified to minimize Markov decision process computational overhead and to facilitate understan...
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Verification Guided Refinement of Flight Safety Assessment and Management System for Takeoff
Journal of Aerospace Information Systems, 2016Co-Authors: Sweewarman Balachandran, Necmiye Ozay, Ella M. AtkinsAbstract:Systems that make Safety-critical decisions must undergo a rigorous verification and validation process to ensure automation decisions do not jeopardize the nominal safe state of operation. Flight Safety assessment and management is a high-level decision-making system to reduce loss of control risk. This paper demonstrates how tools from formal verification can be used to guide the design of a takeoff Flight Safety assessment and management system implemented as a deterministic Moore machine. Finite state abstractions of simplified takeoff dynamics under different control authorities (i.e., pilot vs Safety controller) are computed and composed with the Moore machine. By construction, the composition captures all behaviors of simplified takeoff dynamics. Then, a model checking tool analyzes whether this composition satisfies the takeoff Safety requirements specified by federal aviation regulations. The results of model checking together with the abstraction are used to refine the Moore machine to ensure sa...
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Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines
Journal of Aerospace Information Systems, 2015Co-Authors: Sweewarman Balachandran, Ella M. AtkinsAbstract:This paper presents a novel Flight Safety assessment and management augmentation to the Flight management system designed to assist a Flight crew in avoiding or recovering from impending loss-of-control situations. Nominally, this system serves as a passive monitor but, in high-risk situations, warnings and (ultimately) override actions are initiated to mitigate the high-risk situation. In this work, Flight Safety assessment and management is applied to the task of preserving Safety during takeoff, which is one of the highest-risk phases of Flight. Flight Safety assessment and management is specified as a deterministic Moore machine that can ultimately be certified using existing software certification processes. To facilitate understanding and to reduce state-space complexity, Flight Safety assessment and management’s state machines are split into longitudinal and lateral-directional submachines that identify and mitigate loss-of-control contributing factors associated with aircraft dynamics and control ...
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Flight Safety assessment and management during takeoff
AIAA Infotech@Aerospace (I@A) Conference, 2013Co-Authors: Sweewarman Balachandran, Ella M. AtkinsAbstract:The goal of a Safety management system is to monitor sensors, identify hazards and mitigate risk to the extent possible. In this paper, we present a novel approach called Flight Safety Assessment and Management (FSAM) to assess key quantitative and qualitative feedback parameters for loss of control (LOC) risk. Decision making logic is specified as a set of hierarchical timed automata models. Logic is customized to phase of Flight as well as the control authority and modes. States are classified as nominal, moderate risk and high risk, enabling FSAM to issue warnings and override actions as necessary. FSAM logic for the takeoff phase of Flight is presented in this paper.
Zhao Lu-feng - One of the best experts on this subject based on the ideXlab platform.
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Fatalness assessment of Flight Safety hidden danger based on support vector machine
Journal of Safety Science and Technology, 2010Co-Authors: Zhao Lu-fengAbstract:A method for fatalness assessment of Flight Safety hidden danger,based on support vector machine(SVM),was proposed.And the corresponding model,which took the basic assessment factors of Flight Safety hidden danger fatalness as input node and assessment results as output node,was built.Then the Safety situation of a regiment of China Air Force was assessed.The results showed that,for fatalness assessment of Flight Safety hidden danger,SVM has better performance on precision,rapidity and realization in comparison with the traditional neural network.
Cong Wei - One of the best experts on this subject based on the ideXlab platform.
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Notice of Retraction Fatalness evaluation of Flight Safety hidden danger based on support vector machine
2010 IEEE International Conference on Advanced Management Science(ICAMS 2010), 2010Co-Authors: Gan Xusheng, Duanmu Jingshun, Cong WeiAbstract:A method for fatalness evaluation of Flight Safety hidden danger, based on support vector machine (SVM), is proposed. And the corresponding model, which makes the basic evaluation factors of Flight Safety hidden danger fatalness as input node and evaluation results as output node, is established. Then the Safety situation of a regiment of China Air Force is evaluated. The application result shows that, for fatalness evaluation of Flight Safety hidden danger, SVM has better performance on precision, rapidity and realization in comparison with traditional neural network.
Chen Zhang - One of the best experts on this subject based on the ideXlab platform.
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Study on Flight Safety Risk Evaluation Model Based on Flight Exceedance Events
DEStech Transactions on Computer Science and Engineering, 2018Co-Authors: Xin Wang, Chen ZhangAbstract:The aim of this study is to establish the risk evaluation model for evaluating the Flight Safety level objectively and precisely based on Flight exceedace events. The traditional risk assessment is revised. The Flight quality monitoring projects which are the main factors affecting the Flight Safety are selected as the evaluation indices. The weights of the indices are determined by the analytic hierarchy process, the corresponding coefficients are set for different grades of exceedance events. The exceedance events rate is the frequency of occurrence. And the risk evaluation model is established. The Flight Safety risk is calculated with qualitative and quantitative methods. The risk level and the main risk factors affecting the Flight Safety risk are determined. Some specific measures are taken to improve the Flight Safety risk management level. The Flight quality monitoring events of a certain airline’s B737 fleets during the first half of 2017 verify the validity of the model. It is found that the risks in landing and take-off are the greatest. The risk in landing contributed greatly to overweight landing, high speed during landing, vertical g high during landing and high roll during landing. The risk in the taking off phase contributed greatly to high pitch rate at rotation, low speed at rotation, high speed at rotation and low pitch rate at rotation.