Article
Engineering, Marine
Tao Li, Dapeng Jiang, Bing Liu, Yongjie Zhao, Peng Xie
Summary: This study analyzes the plastic deformation and fracture cross section of drill pipe using the plastic deformation theory and different ram structure configurations. The results show that the final fracture cross section of CT90 tube is a rhombus circle and the structure parameters have limited effect on pipe stress.
Article
Engineering, Marine
Tao Li, Dapeng Jiang, Peng Xie
Summary: The mechanical behavior of slip rams in anchoring and suspending pipe strings for subsea blowout preventers is explored. The wedge stress theory and thick-walled cylinder theory are applied to analyze the anchoring and suspending mechanical behavior of slip rams. The numerical results validate the applicability of the theories. Visible damage and plastic deformation occur in slip rams or CT90 tubes after anchoring and suspending operations.
Article
Engineering, Petroleum
Jose Luis Parraga Quispe, Lei Zhu, Segen F. Estefen, Marcelo Igor Lourenco de Souza
Summary: This paper studies two aspects of BOP shearing capability in deepwater drilling activities: the required shear force to cut the pipe inside BOP successfully and the time it takes to shear the pipe and close the well. A finite element model and an analytical hydraulic model are used to calculate the maximum shear force of a typical drillpipe and the BOP closing time. A case study is presented to estimate the emergency disconnect sequence time in a deepwater offshore scenario.
SPE DRILLING & COMPLETION
(2022)
Article
Engineering, Industrial
Shengnan Wu, Qiao Zhang, Bin Li, Laibin Zhang, Wenpei Zheng, Zhong Li, Zhandong Li, Yiliu Liu
Summary: This paper presents a Markov-Monte Carlo-DBN-based approach to predict the reliability of subsea wellhead systems and diagnose root causes during its service life. The model considers multi-factor impacts on system performance and proposes a multistate transition model of wellhead components to analyze system degradation. By embedding multi-factor effects and multistate transition into DBN, the system state can be effectively updated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Mechanical
P. L. Green, L. J. Devlin, R. E. Moore, R. J. Jackson, J. Li, S. Maskell
Summary: This paper discusses the optimization of the 'L-kernel' in Sequential Monte Carlo samplers to improve performance, resulting in reduced variance of estimates and fewer resampling requirements.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Interdisciplinary Applications
DanHua ShangGuan
Summary: The Monte Carlo method is a powerful tool in many research fields, but the increasing complexity of physical models and mathematical models requires efficient algorithms to overcome the computational cost.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Engineering, Mechanical
Adolphus Lye, Alice Cicirello, Edoardo Patelli
Summary: This tutorial paper reviews the use of advanced Monte Carlo sampling methods in Bayesian model updating for engineering applications, introducing different methods and comparing their performance. Three case studies demonstrate the advantages and limitations of these sampling techniques in parameter identification, posterior distribution sampling, and stochastic identification of model parameters.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Burak C. Civek, Emre Ertin
Summary: In this study, an alternative MCMC method is proposed for sparse blind deconvolution problems by utilizing the Normal-Inverse-Gamma prior. The computational bottlenecks caused by the discrete nature of the Bernoulli-Gaussian model are effectively eliminated, and time and frequency domain constraints are incorporated.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Statistics & Probability
Hai-Dang Dau, Nicolas Chopin
Summary: The paper proposes a new waste-free sequential Monte Carlo (SMC) algorithm that utilizes the outputs of all intermediate Markov chain Monte Carlo (MCMC) steps as particles. The consistency and asymptotic normality of its output are established, and insights on estimating the asymptotic variance of any particle estimate are developed. Empirical results show that waste-free SMC tends to outperform standard SMC samplers, particularly in scenarios where the mixing of the considered MCMC kernels decreases across iterations.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2022)
Article
Mathematics, Applied
Tengchao Yu, Hongqiao Wang, Jinglai Li
Summary: The paper introduces a design criterion based on KSE for optimizing algorithm parameters of HMC sampler, especially when the mass matrix is adapted. Analytically derivations of optimal algorithm parameters for near-Gaussian distributions are provided, as well as theoretical justification for adapting mass matrix in HMC sampler. An adaptive HMC algorithm is proposed and its performance demonstrated with numerical examples.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Automation & Control Systems
Johan Alenlov, Arnaud Doucet, Fredrik Lindsten
Summary: The pseudo-marginal HMC algorithm proposed in this paper combines the advantages of both HMC and pseudo-marginal schemes by controlling the precision parameter N to approximate the likelihood and efficiently sample the marginal posterior of parameters in high-dimensional scenarios. Results from experiments show that the PM-HMC algorithm can significantly outperform standard HMC and pseudo-marginal MH schemes.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Physics, Multidisciplinary
Hanqing Zhao, Marija Vucelja
Summary: We introduce an efficient nonreversible Markov chain Monte Carlo algorithm for generating self-avoiding walks with a variable endpoint, and compare its performance with existing algorithms in two and three dimensions.
FRONTIERS IN PHYSICS
(2022)
Article
Economics
Nianling Wang, Zhusheng Lou
Summary: The stochastic volatility (SV) model is widely used to study time-varying volatility. However, the linearity assumption for transition equation in basic SV model is restrictive. To allow for nonlinearity, we proposed a semiparametric SV model that specifies a nonparametric transition equation for log-volatility using natural cubic splines. The empirical applications to Bitcoin and convertible bond return data indicate that the transition equations of their log-volatility are highly nonlinear. Taking nonlinearity into account, the semi-parametric SV model can improve the likelihood of the basic SV model both in-sample and out-of-sample.
ECONOMIC MODELLING
(2023)
Article
Engineering, Industrial
Himanshu Srivastav, Mary Ann Lundteigen, Anne Barros
Summary: The all-electric systems are an upgrade of electro-hydraulic control systems that promise more reliable equipment and a safer environment. They perform safety functions by isolating reservoirs and activating safety valves with electric springs. These safety valves may experience performance deterioration due to interruptions in power supply.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Physics, Multidisciplinary
Alexei D. Chepelianskii, Satya N. Majumdar, Hendrik Schawe, Emmanuel Trizac
Summary: The study investigates Monte Carlo dynamics at zero temperature where a random walker seeks to minimize potential energy. The resulting dynamics is universal and not dependent on the underlying potential energy landscape. The long-time regime is determined by the behavior of small jumps, showing excellent agreement between analytical predictions and Monte Carlo simulations.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Automation & Control Systems
Aibo Zhang, Songhua Hao, Min Xie, Yiliu Liu, Haoshui Yu
Summary: Redundant structure is widely used to improve system reliability. This study addresses the stochastic dependency among units by introducing a novel activation sequence and proposes an adaptive system-level inspection policy. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is employed to find the optimal solutions in system unavailability and cost.
Article
Engineering, Marine
Yuandong Wang, Baoping Cai, Yanping Zhang, Jing Liu, Javed Akbar Khan, Yiliu Liu, Rongkang Li, Zhengde Chu, Zengkai Liu, Yonghong Liu
Summary: This paper proposes a condition-based maintenance (CBM) method based on remaining useful life (RUL) prediction, which dynamically sets inspection time and optimizes maintenance cost by considering maintenance preparation time and RUL prediction results.
Review
Engineering, Environmental
Chao Chen, Jie Li, Yixin Zhao, Floris Goerlandt, Genserik Reniers, Liu Yiliu
Summary: Resilience assessment and management of technical systems are increasingly important in complex process industries. While several review papers on resilience management methods have been published, this study focuses on the bibliometric analysis of relevant research works, specifically in the process industries. It examines the sources of publications, collaborations between institutions and authors, and development trends. Additionally, it investigates the development of resilience engineering and management in process safety and environmental protection journals. This review provides valuable insights into knowledge structure, evolution, influential publications, and future research directions.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Engineering, Industrial
Lin Xie, Federico Ustolin, Mary Ann Lundteigen, Tian Li, Yiliu Liu
Summary: This paper focuses on the analysis of thermal barriers in lithium-ion battery packs to prevent cascading failures. A method is proposed to evaluate the capabilities of thermal barriers against thermal failures and is validated through a practical case study. The study finds that barriers between parallel cells are more effective in mitigating failure propagation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Multidisciplinary
Yujie Zhang, Yukun Wang, Xiaopeng Li, Yiliu Liu, Weizheng Gao
Summary: Performance-based contracting (PBC) is a novel approach that uses defined performance goals and incentives to improve system availability and reduce costs. This paper proposes two new CBM optimization models within the PBC framework, considering the impact of destructive inspections on system degradation behavior. The models estimate the average maintenance cost rate and system availability within the contract period, and aim to maximize the expected profit rate to the supplier and/or the resulting system average availability using a solution procedure based on NSGA-II and WSM.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Computer Science, Artificial Intelligence
Xuelin Liu, Baoping Cai, Xiaobing Yuan, Xiaoyan Shao, Yiliu Liu, Javed Akbar Khan, Hongyan Fan, Yonghong Liu, Zengkai Liu, Guijie Liu
Summary: In this study, a hybrid multi-stage methodology for remaining useful life (RUL) prediction of control systems is proposed. The variant of unscented Kalman filter (UKF) and dynamic Bayesian networks (DBNs) are used for uncertainty analysis, and the real degradation process of control systems is simulated by optimizing the degradation process, leading to improved accuracy and robustness of RUL prediction.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Industrial
Yixin Zhao, Baoping Cai, Henry Hooi-Siang Kang, Yiliu Liu
Summary: In this study, a model for analyzing the propagation process of failures in loading dependent systems is developed. Numerical analyses are conducted to evaluate the factors influencing the probability distributions of failed-and overloading components, as well as the occurrence frequencies of different stop scenarios. It is expected that this model can optimize the design and maintenance of loading dependent systems.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Tiantian Zhu, Stein Haugen, Yiliu Liu, Xue Yang
Summary: This paper proposes a novel value of (imperfect) prediction (VoP) model to estimate the optimal response time to potential threats that may lead to accidents. The model considers prediction accuracy, action failure probability, and parameters such as accident cost, response action cost, accident probability, prediction performance, and response strategy. A case study on iceberg management demonstrates the effectiveness of the proposed approach, and a sensitivity study evaluates how optimal response time changes with different parameters. The study shows that responding as early as possible is reasonable for serious threats, while response can be postponed for moderate consequences. The VoP model can also calculate accuracy requirements, risk tolerance thresholds, precautionary measures, and maximum investment in accident prevention.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Mihaela Mitici, Ingeborg de Pater, Anne Barros, Zhiguo Zeng
Summary: The development of data-driven Remaining Useful Life (RUL) prognostics has been incentivized by the increasing availability of condition-monitoring data for components/systems. However, most studies focus on point RUL prognostics without considering the uncertainty associated with these estimates, limiting their applicability to maintenance planning. In this paper, probabilistic RUL prognostics are developed using Convolutional Neural Networks and integrated into maintenance planning for aircraft turbofan engines. The results indicate that the proposed approach reduces costs and leads to a limited number of failures compared to traditional strategies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Green & Sustainable Science & Technology
Aibo Zhang, Zhaoyuan Yin, Zhiying Wu, Min Xie, Yiliu Liu, Haoshui Yu
Summary: Under the context of carbon neutrality, renewable energy has gained increasing attention. However, the strong reliance on natural processes for wind and solar energy leads to an imbalance between energy production and demand. Compressed Air Energy Storage (CAES) is a promising solution to increase renewable energy penetration, but it is a complex system with high-temperature and high-pressure working conditions. This paper applies System-Theoretic Process Analysis (STPA) to identify safety hazards in the CAES system, aiming to provide guidelines for practitioners to improve its safety and reliability.
Article
Engineering, Industrial
Shengnan Wu, Qiao Zhang, Bin Li, Laibin Zhang, Wenpei Zheng, Zhong Li, Zhandong Li, Yiliu Liu
Summary: This paper presents a Markov-Monte Carlo-DBN-based approach to predict the reliability of subsea wellhead systems and diagnose root causes during its service life. The model considers multi-factor impacts on system performance and proposes a multistate transition model of wellhead components to analyze system degradation. By embedding multi-factor effects and multistate transition into DBN, the system state can be effectively updated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Yixin Zhao, Valerio Cozzani, Tianqi Sun, Jorn Vatn, Yiliu Liu
Summary: Many industrial facilities are susceptible to failure interactions and degradation interactions between components. These interactions are characterized by failure dependences that can accelerate component degradation. Due to system layout and functional interactions, not all components have the same failure dependence. This study developed a framework and a maintenance optimization model to evaluate and address heterogeneous failure dependences in multi-component systems.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Mechanical
Chao Yang, Baoping Cai, Rui Zhang, Zhexian Zou, Xiangdi Kong, Xiaoyan Shao, Yiliu Liu, Haidong Shao, Javed Akbar Khan
Summary: A subsea production system is crucial for the production of oil and gas underwater. Real-time monitoring of the subsea production control system is essential for ensuring safety. This article proposes a methodology that combines digital twin technology and fault diagnosis to improve the accuracy of diagnosing minor faults in the subsea production control system.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Xiang Li, Yuchen Jiang, Yiliu Liu, Jiusi Zhang, Shen Yin, Hao Luo
Summary: In this article, an automatic bone age assessment method based on CNN and GCN is proposed. The method mimics the physician's clinical process by using CNN for feature extraction and GCN for bone key regions inference. The proposed method shows competitive and superior performance compared to other state-of-the-art methods.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Health Care Sciences & Services
Yiliu Liu
Summary: This study discusses the risks and management methods in smart healthcare systems. It proposes a systematic approach to identify risks and categorizes risk reduction strategies into design, operation, organization, and legislation.
JOURNAL OF PATIENT SAFETY AND RISK MANAGEMENT
(2022)
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)
