Article
Engineering, Industrial
Adel Mottahedi, Farhang Sereshki, Mohammad Ataei, Ali Nouri Qarahasanlou, Abbas Barabadi
Summary: Resilience is a growing concept in managing engineering systems, but estimating system resilience is challenged by lack of historical data and limited information. Current studies use various indices to quantify resilience, but lack detailed examination of influencing factors. This paper aims to develop a practical methodology using expert judgment and fuzzy set theory to effectively model factors influencing resilience, demonstrated with an underground coal mine fan system.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Geosciences, Multidisciplinary
Gonzalo L. Pita
Summary: This paper examines the survey-dependent variability of expert-opinion depth-damage functions and finds that the number of calibration questions contributes more to the variability than the number of experts. The survey-dependent damage variability ranges from +/- 10% to almost 50%.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Engineering, Industrial
Salvatore F. Greco, Luca Podofillini, Vinh N. Dang
Summary: This study presents a two-stage Bayesian model to integrate expert-elicited probability estimates and empirical evidence from simulator data for quantifying Human Error Probability (HEP) values. The model aims to provide a systematic and reproducible data aggregation framework, contributing to strengthening the empirical basis of future HRA methods.
Article
Engineering, Industrial
G. Rongen, O. Morales-Napoles, M. Kok
Summary: This study aims to assess the failure probabilities of Dutch dikes and compare them to model results through expert estimation. The research demonstrates that structured expert judgments can be successfully used for estimating the reliability of Dutch flood defenses, despite the presence of uncertainties and overestimated failure probabilities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Geochemistry & Geophysics
Matteo Taroni
Summary: The uncertainties in earthquake magnitudes have a minimal impact on the estimation of the Gutenberg-Richter b-value if these uncertainties are uniformly distributed. However, a non-uniform distribution of errors can significantly affect the estimation of the b-value, leading to a peak in the magnitude-frequency distribution. Through simulations, it is possible to determine the magnitude of the estimation bias and prevent its impact.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2022)
Article
Ecology
Edith Arndt, Libby Rumpff, Stephen Lane, Sana Bau, Martin Mebalds, Tom Kompas
Summary: This study investigated the methods that agronomists use for visual crop surveillance and assessed their confidence in detecting exotic pests and diseases. The results showed that agronomists were confident in detecting leaf pests and diseases, but lacked confidence in detecting non-leaf pests and diseases. Expert judgments aligned with agronomists' self-assessments, but highlighted uncertainty regarding the detection of non-leaf pests and diseases.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2022)
Article
Engineering, Industrial
C. M. La Fata, L. Adelfio, R. Micale, G. La Scalia
Summary: Since the 1970s, Human Reliability Analysis (HRA) methods have been applied to quantifying the Human Error Probability (HEP) in Nuclear Power Plants (NPPs). The second-generation HRA methods consider Performance Shaping Factors (PSFs) that may influence workers' performance. However, few studies focus on the manufacturing sector, and most contributions assume independence among PSFs, leading to potential estimation issues. This paper proposes a Fuzzy DEMATEL (FDEMATEL) based method to analyze PSF interrelationships and importance in the manufacturing sector, and demonstrates its application in an Italian textile company.
Article
Engineering, Civil
Xiukai Yuan, Shaolong Liu, M. A. Valdebenito, Jian Gu, Michael Beer
Summary: A novel procedure is proposed to estimate the failure probability function of design variables without distribution fitting, by transforming it into an expression that includes the posterior distribution and allowing it to be estimated by means of sampling. The proposed method shows efficient estimation of FPF within different simulation strategies and numerical examples demonstrate its performance.
Article
Multidisciplinary Sciences
Aleksandra Litvinova, Ralf H. J. M. Kurvers, Ralph Hertwig, Stefan M. Herzog
Summary: Researchers have found that experts tend to make inconsistent judgments when judging the same case twice, regardless of the level of expert consensus. Individual experts are less confident in their initial decision when there is less consensus among experts, and they are more likely to make a different judgment when faced with the same case again months later.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Software Engineering
Patricia Gomes Fernandes Matsubara, Bruno Freitas Gadelha, Igor Steinmacher, Tayana Uchoa Conte
Summary: This study aimed to identify the factors that affect estimates in software projects using expert judgment, resulting in the SEXTAMT map of influencing factors. Researchers investigated a wide range of different factors using diverse research strategies, providing compelling evidence for assessing and improving estimation in the software industry.
JOURNAL OF SYSTEMS AND SOFTWARE
(2022)
Article
Geochemistry & Geophysics
Jannes Muenchmeyer, Dino Bindi, Ulf Leser, Frederik Tilmann
Summary: Precise real-time estimates of earthquake magnitude and location are crucial for early warning and rapid response. A new model based on attention-boosted transformer networks has been introduced, showing superior performance in both magnitude and location estimation compared to traditional algorithms, particularly for a wide range of seismic events.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2021)
Article
Multidisciplinary Sciences
Omar El Beggar
Summary: Many agile projects use expert judgment-based methods for estimating effort. However, conflicts among estimators can make achieving consensus difficult, and uncertainty can threaten the reliability and accuracy of assessments. To address these issues, a proposed intuitionistic fuzzy expert judgment method allows for fuzzified assessments and integrates estimators' priorities based on human factors. An initial empirical study on an agile project showed that the method is particularly useful for inexperienced estimators or in the early stages of a project with significant disagreement. As group agreement increases during the estimating process, the method maintains a neutral bias towards overestimating or underestimating user stories.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Chunyan Ling, Zhenzhou Lu
Summary: The proposed method introduces a novel two-stage meta-model importance sampling based on support vector machine (SVM) to efficiently estimate structural failure probability. It provides an algorithm to efficiently deal with multiple failure regions and rare events, with the SVM model accurately recognizing the states of samples. Several examples are performed to show the feasibility of the proposed method.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Multidisciplinary Sciences
Chalachew Kassaw, Alem Eskeziya, Tamrat Anbesaw
Summary: This study aimed to estimate patient satisfaction and associated determinants at the psychiatry unit of Dilla University Referral Hospital in 2020. By using appropriate tools and methods, significant factors associated with patient satisfaction were identified, and recommendations were provided.
Article
Transportation Science & Technology
Benedikt Badanik, Martin Janossy, Arthur Dijkstra
Summary: Improving safety has always been a top priority in the aviation industry, with safety and risk analyses becoming more thorough and sophisticated, serving as industry standards for safety investigations. Airlines are working to meet stricter safety standards, utilizing expert judgment for evaluation of Flight Data Monitoring (FDM) events to ensure accurate and useful outcomes. The paper details the method for selecting experts and implementing a classical model for calculations and visualization of probability distributions for different aircraft types, IATA accident types, and FDM events.
PROMET-TRAFFIC & TRANSPORTATION
(2021)
Article
Public, Environmental & Occupational Health
Peng Liu, Yong Du
Summary: The study found that people tend to attribute more blame to automation systems in semi-autonomous vehicle accidents, a bias known as blame attribution asymmetry, partially due to the higher negative affect triggered by the automation-caused crash. This bias has implications for policies as it may lead to negative consequences.
Article
Computer Science, Cybernetics
Peng Liu, Jinting Liu
Summary: The study found that participants were more inclined to accept AVs programmed with selfish algorithms, predicting greater intention to use and willingness to pay a premium for them. While there were no significant differences in deontological evaluation and perceived risk between the AV types, perceived benefit and perceived risk were predictive of behavioral intention.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2021)
Article
Computer Science, Cybernetics
Tingting Li, Lin Wang, Jinting Liu, Jiangshu Yuan, Peng Liu
Summary: The study found that perceiving automated vehicles as lacking agency may lead to greater anger towards their aberrant behaviors. Attributing high agency to AVs eliminated the difference between humans and AVs. Perceiving AVs as having high capability to feel and sense might induce more negative reactions.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2022)
Article
Computer Science, Cybernetics
Tingting Li, Peng Liu
Summary: The COVID-19 pandemic may have a positive impact on the adoption of automated vehicles, as individuals show a greater willingness to use driverless Robotaxis during similar situations. Participants exhibited a more positive attitude towards Robotaxis and were more willing to ride in them during the pandemic, indicating a potential shift in attitudes towards AVs in times of crises.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2022)
Article
Engineering, Industrial
Xi Lyu, Zhizhong Li, Quan Ma, Manrong She
Summary: This study investigates the influence of information amount on diagnosis by conducting an experiment using a simulated nuclear power plant accident. The findings suggest that increasing accessible information leads to a decrease in diagnostic accuracies, highlighting the need for system designers to limit information overload and users to make more efficient use of information.
Article
Nuclear Science & Technology
Zijian Yin, Zhizhong Li, Zhaopeng Liu, Dongfang Yang, Jinghong Zhang, Lei Long, Yijing Zhang, Boyang Gong
Summary: Nominal human error probability (NHEP) data for nuclear power plant commissioning was collected through expert elicitation, providing a valuable indicator for assessing human reliability. The obtained NHEP values for detection, understanding, action execution, and inter-team coordination were consistent with those in the Integrated Human Event Analysis System (IDHEAS)-Event Cause Analysis (ECA), while the NHEP for decision-making was lower. Challenges related to the IDHEAS-based cognitive failure modes (CFMs) and expert elicitation process were identified. The applicability of the obtained NHEP values extends to other application domains due to the technology-neutral and human cognition-focused nature of the IDHEAS-based CFMs.
ANNALS OF NUCLEAR ENERGY
(2023)
Article
Engineering, Manufacturing
Junxiu Zhang, Dunxing Wang, Qin Gao, Zhizhong Li
Summary: This study examines the coordination-behavior patterns of control crews in digital nuclear power plants during emergencies. The findings show that high-performing crews demonstrate higher cohesion and more balanced behavioral patterns in team coordination compared to low-performing ones. Additionally, high-performing crews exhibit a higher level of team autonomy and self-management among junior operators, while low-performing crews tend to be centered around senior reactor operators.
HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES
(2023)
Article
Engineering, Industrial
Yueying Chu, Peng Liu
Summary: Given that automation complacency is already used to blame and punish human drivers, it is essential to review its status quo and determine whether current research can support its legitimate usage. This review work shows that current academic research in driving automation cannot support its legitimate usage.
Article
Computer Science, Cybernetics
Zhigang Xu, Guanqun Wang, Siming Zhai, Peng Liu
Summary: Automated agents need social recovery strategies to mitigate the negative impacts of their errors and maintain resilient human-automation relationships. This study tested the efficacy of verbal recovery design in a real automated vehicle after a failure. The results showed that human-voice-recovery can somewhat mitigate the negative impacts on user experience, while Siri-voice-recovery works on positive experience but cannot fully restore it to normal levels. More empirical efforts are needed to develop strategies specific to human-automation interaction in natural environments.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Computer Science, Cybernetics
Evangelos Paschalidis, Siming Zhai, Junhua Guo, Tangjian Wei, Peng Liu, Haibo Chen
Summary: The study investigated the impact of liability attribution on intention to buy automated vehicles. It found that improper liability attribution can negatively affect purchase intentions. Negative misattribution affects intention to buy through the mediating effects of trust, negative affect, and crash acceptability.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Review
Engineering, Industrial
Yu Zhang, Manrong She, Zhizhong Li
Summary: The purpose of this paper is to provide a clear and systematic model of team workload. The models and conceptual framework of team workload are summarized from the perspectives of resource requirement, system, and interaction. A nominal definition of team workload is proposed as the total effort spent for processes involved in the execution of team tasks. The components and indicators of teamwork are identified from various team processes, and the team workload is constructed in four dimensions: task-focused activities, task-induced team activities, situational response, and team maintenance and development. Finally, the proposed model is compared with existing models.
INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS
(2023)
Article
Economics
Siming Zhai, Shan Gao, Lin Wang, Peng Liu
Summary: The emergence of automated and algorithmic technology raises the question of responsibility when something goes wrong. This study examines human judgments of responsibility in automated vehicle crashes caused by both human and machine drivers. Participants assigned more responsibility to the test driver than the car manufacturer, but the car manufacturer was not completely exempt from responsibility. Manipulating passive and active errors did not significantly impact responsibility judgments. These findings provide insights for developing a socially-acceptable framework for assigning responsibility in automated vehicle crashes.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Computer Science, Cybernetics
Peng Liu
Summary: Automation poses potential risks for operators, such as automation complacency, which has been extensively studied in the field of human-automation interaction. It has been identified as a probable cause of recent traffic crashes and has implications for liability litigation.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Letter
Multidisciplinary Sciences
Yueying Chu, Peng Liu
Article
Public, Environmental & Occupational Health
Peng Liu
Summary: The research presents two mental models - one suggesting machine drivers are superior, the other suggesting human and machine drivers may lead to negative outcomes due to incompatibility. Recent empirical studies support the second model, indicating emerging traffic risks from human-AV social interactions.
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
