Article
Engineering, Civil
Mohsen Masoomzadeh, Mohammad Charkhtab Basim, Mohammad Reza Chenaghlou, Hesam Khajehsaeid
Summary: The hysteric behavior of shear links in Eccentric Braced Frames (EBFs) and the uncertainties in their behavioral parameters have been studied in this research. The study investigates the variations in structural responses due to these uncertainties and proposes a practical method using artificial neural networks (ANNs) to predict the responses with lower computational effort. The results show that the web thickness and yielding strength of shear links have significant effects on seismic structural responses.
Article
Nuclear Science & Technology
Seunghyun Eem, In Kil Choi, Sang Lyul Cha, Shinyoung Kwag
Summary: This study focused on the seismic response correlation coefficient for Korean NPPs to enhance the accuracy and reliability of safety assessments. By quantifying the correlation of seismic failure, correlation coefficient values applicable to auxiliary buildings were suggested.
ANNALS OF NUCLEAR ENERGY
(2021)
Article
Engineering, Civil
Luis C. M. da Silva, Gabriele Milani, Paulo B. Lourenco
Summary: This paper presents a probabilistic-based numerical strategy for assessing the seismic fragility of masonry structures using non-linear time-history analysis. The strategy couples a discrete macro-element model at a structural-scale with a homogenization model at a meso-scale to ensure a probabilistic nature. The approach is computationally efficient and effective in evaluating the seismic response of masonry structures.
Article
Acoustics
Taiming Huang, Weiping Li, Wanhao Yue, Nianzhou Ji, Changjie Ou, Xiaoshan Wang, Chenglin Guan
Summary: In this study, experimental and optimization studies were conducted to investigate the high-frequency aerodynamic noise of claw-pole alternator during high-speed operation. The results revealed the main noise orders and identified the main noise source. A hybrid simulation method was applied to solve the acoustics field problem, and the simulation and experimental results agreed satisfactorily. The pressure amplitude distribution on the rotor surface was analyzed, and claw-pole notching was parametrically modeled and optimized.
Article
Green & Sustainable Science & Technology
Jilin Cai, Lili Hao, Qingshan Xu, Keqi Zhang
Summary: A scalable Latin hypercube importance sampling (ELHIS) method is proposed in this paper, which combines importance sampling (IS) and Latin hypercube sampling (LHS) to reduce the computational costs of evaluating power system reliability, and shows good performance on test systems.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Chemistry, Physical
Yisheng Yin, Chengrui Zhang, Tieshuang Zhu
Summary: This study utilized Latin hypercube sampling method to design experimental parameters for different penetration depth welded joints, and proposed a neuroevolution-based method for predicting penetration depth, with validation results indicating its accuracy. The methodology and model can guide the preliminary selection of main process parameters and lay the foundation for further research on penetration morphology control of laser welding.
Article
Engineering, Electrical & Electronic
Unal Kurt, Okan Ozgonenel, Birsen Boylu Ayvaz
Summary: This study compares the Monte Carlo simulation with Latin Hypercube sampling method and Unscented transformation methods in power systems. The results show that the Unscented transformation method is faster and more reliable than the other two methods.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Energy & Fuels
Geon Gyu Choi, Woo Sik Jung, Seong Kyu Park
Summary: This study demonstrates that seismic core damage frequencies (CDFs) in both single-unit and multi-unit nuclear power plants (NPPs) are severely distorted when the assumption of full correlation among correlated seismic failures is employed. It highlights the importance of carefully calculating and interpreting seismic CDFs in NPP regulations.
Article
Engineering, Civil
Geetopriyo Roy, Subhrajit Dutta, Satyabrata Choudhury
Summary: This study develops a framework for quantifying the uncertainty in PSHA parameters, considering the uncertainty in source-to-site distance and the interdependency between hazard parameters. The results can be used for planning and constructing new projects, and evaluating the seismic risk of existing infrastructure in a city.
ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING
(2023)
Article
Engineering, Chemical
Wensi Cao, Shuo Wang, Mingming Xu
Summary: In the context of the Carbon peak and Carbon neutral target, the introduction of carbon trading and the connection of new energy generation such as wind power and photovoltaics to the power grid have become important means to achieve low carbon emissions. A virtual optimization model is established to consider both low-carbon and economic aspects, taking into account the uncertainty of wind power and photovoltaic power generation and introducing a carbon-trading mechanism and time-sharing tariff to maximize net benefit and minimize carbon emissions.
Article
Green & Sustainable Science & Technology
Zeyang Ma, Jianwei Gao, Wenqiang Hu, Venkata Dinavahi
Summary: This paper presents a risk-adjustable stochastic day-ahead scheduling model for balancing the risk requirements of PSPs and proposes an improved sampling approach. By combining SaLHS and D-vine copula, WF error scenarios can be generated to account for wind farm correlations. A Glue-VaR-based generation adequacy index is proposed to measure operational risk and adjust risk levels based on PSP requirements.
IET RENEWABLE POWER GENERATION
(2021)
Article
Nuclear Science & Technology
Junghyun Ryu, Moosung Jae
Summary: The study focuses on seismic probabilistic safety assessment and proposes a new Monte Carlo Simulation Allocation Method to derive exact CDF and MCSs in the event of a strong earthquake.
ANNALS OF NUCLEAR ENERGY
(2021)
Article
Chemistry, Multidisciplinary
Mohammadreza Mohammadi, Araliya Mosleh, Mehran S. Razzaghi, Pedro Alves Costa, Rui Calcada
Summary: The research aims to investigate the seismic performance of railway embankments using a probabilistic approach. Nonlinear response history analyses were conducted using PLAXIS software, with more than 2400 embankment-earthquake case studies. Sensitivity analyses were performed to identify the most important variables in the seismic performance of railway embankments. Fragility curves were generated based on the mechanical properties of embankments, and incremental dynamic analysis approach was employed to develop fragility functions.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Yong Pang, Liangliang Yang, Yitang Wang, Xiaonan Lai, Wei Sun, Xueguan Song
Summary: This research addresses the limitations of Latin hypercube design in constrained design space by developing Latin hypervolume designs with good space-filling and noncollapsing properties. Monte Carlo sampling is introduced to approximate the hypervolume in high-dimensional and irregular design spaces. The experiments demonstrate that the proposed method is considerably better compared to other methods in benchmark numerical examples and engineering modeling scenarios.
ENGINEERING WITH COMPUTERS
(2023)
Article
Soil Science
Adnan Khan, Matt Aitkenhead, Craig R. Stark, M. Ehsan Jorat
Summary: Soil properties are crucial for plant growth, ecosystems, and biota functioning. Digital Soil Mapping (DSM) uses Conditioned Latin Hypercube (CLH) sampling method to map soil properties. A study on Scotland's Finzean Estate determined the optimum sample size and suggested a range of 25-50 CLH samples.
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)