Article
Computer Science, Interdisciplinary Applications
Taoran Song, Hao Pu, Paul Schonfeld, Hong Zhang, Wei Li, Jianping Hu, Jie Wang, Jianxi Wang
Summary: This paper presents a quantitative seismic risk assessment model for railway alignment optimization, which combines probabilistic seismic fragility analysis and loss analysis. The aim is to provide safer and more economical solutions for railway alignment optimization.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Environmental Sciences
Tao Deng, Abubakar Sharafat, Young Min Wie, Ki Gang Lee, Euiong Lee, Kang Hoon Lee
Summary: This study proposes a geospatial analysis-based method to determine the most favorable landforms shaped by marine glaciers for railway network route selection. The method involves analyzing the availability of four major favorable landforms, understanding the regional glaciers, determining feasible locations for the railway, and optimizing the route using glacial landforms. The feasibility of the method was verified in the Palong Zangbo watershed, showing that it can provide comprehensive guidance for railway route selection in marine glacial areas.
Article
Engineering, Civil
Hui Zhang, Yao Li, Qingpeng Zhang, Dingjun Chen
Summary: Multimodal transport is advantageous in delivering goods to their destination through a reasonable combination of transport modes while ensuring safety and punctuality. It can reduce logistics costs, improve efficiency, and reduce environmental pollution. Research also indicates that, under the consideration of transportation reliability and safety, railway transportation is less affected by external interference compared to other modes of transportation.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Multidisciplinary Sciences
Xiaohua Zeng, Jieping Cai, Changzhou Liang, Chiping Yuan
Summary: This article presents an improved many-objective optimization algorithm that integrates random forest with a three-stage feature engineering process to decrease computational complexity and improve the accuracy of the prediction system. Experimental results show that the proposed algorithm outperforms other feature selection algorithms and the deep learning model in terms of average accuracy, optimal solution set, and running time.
Article
Computer Science, Interdisciplinary Applications
Yan-Ping Liang, De-Cheng Feng, Xiaodan Ren, Jie Li
Summary: This study proposes a three-stage method for simulating non-Gaussian fields over manifolds. The original manifold is first dimensionally reduced to a Euclidean domain, and then the underlying Gaussian field is simulated over the Euclidean domain using conventional representations. Finally, an enhanced translation procedure is used to convert the Gaussian field to the target non-Gaussian field over the manifold. The method's applicability and accuracy are demonstrated through simulations and error analysis.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Engineering, Geological
Chengcai Zong, Kun Ji, Ruizhi Wen, Xirong Bi, Yefei Ren, Xiaorui Zhang
Summary: The proposed three-stage optimization strategy based on computer simulation enhances the resilience of urban gas distribution networks. The FPDC-GA algorithm improves system robustness and resourcefulness, ML-KNN algorithm optimizes pressure test order, and greedy algorithm enhances the efficiency of pipeline repair.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2022)
Article
Construction & Building Technology
Jianling Huang, Xiaoye Zeng, Jing Fu, Yang Han, Huihua Chen
Summary: This study aims to develop a safety risk assessment model to help project managers evaluate safety risks in high cutting slope construction. By comprehensively analyzing risk technical specifications, literature, and case studies, a list of risk-influencing factors was formed. Based on historical data, a high side slope risk evaluation model was established and applied to an actual case for risk assessment.
Article
Engineering, Marine
Gerry Liston Putra, Mitsuru Kitamura
Summary: The rising prices of materials for ship construction is a primary issue faced by global shipbuilding industries. To address this, a three-stage optimization method has been proposed in this study to optimize the plate material and stiffener types, plate thickness, and plate layout in order to minimize material cost.
Article
Health Care Sciences & Services
Xinzheng Xu, Huihui Xu, Zhongnian Li
Summary: This paper proposes an automatic bone age assessment method using a hierarchical convolutional neural network to detect regions of interest and classify bone grades. Experimental results show that the proposed method is competitive in bone age assessment and outperforms existing fine-grained image classification methods.
Article
Economics
Song Pu, Shuguang Zhan
Summary: This paper presents a two-stage robust optimization model that can help minimize both operation and travel costs for railway enterprises under uncertain passenger demands.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Engineering, Industrial
Nikola Besinovic, Raphael Ferrari Nassar, Christopher Szymula
Summary: This paper proposes a passenger-centred resilience assessment method for railway disruption scenarios, which combines train traffic operations, passenger flows, and network restoration. An optimization-based approach has been developed to evaluate resilience and provide solutions for infrastructure restoration and traffic recovery. The approach is applicable to different types of disruptions and accurately quantifies the inconveniences caused to passengers.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Dingjun Chen, Xufeng Fang, Yao Li, Shaoquan Ni, Qingpeng Zhang, Chin Kwai Sang
Summary: This study proposes a model using ant colony optimization to optimize resource dispatch in global emergencies. The model considers route reliability and its relationship with delay. Numerical experiments using the 2008 Wenchuan earthquake as an example show that the proposed model has lower costs compared to other transportation networks. Dispatch plans with different route reliability are also compared.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Computer Science, Artificial Intelligence
Fayadh Alenezi, Ammar Armghan, Kemal Polat
Summary: This paper presents a novel hybrid model for diagnosing melanoma from dermoscopy images. The model includes a practical pre-processing approach, a deep residual neural network for feature extraction, and a support vector machine classifier for classification. The proposed model achieves approximately 99% accuracy in classifying melanoma or benign skin lesions, demonstrating its potential in automated melanoma identification based on dermatological imaging.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Tingwen Zheng, Yanping Jiang
Summary: The rise of carpooling has made it more convenient for intercity commuters to travel between work and home. In this paper, we propose a driver-rider matching and route optimization method to solve the carpooling problem of delivering intercity commuters to the high-speed railway station. We formulate the problem as a multi-objective mixed-integer nonlinear programming model and propose an improved NSGA-II algorithm to obtain optimal carpooling schemes. The results of numerical experiments validate the effectiveness of the proposed method.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Changjiang Liu, Qiuping Wang, Zhen Cao
Summary: This study proposes a comprehensive weight and intelligent selection algorithm to analyze and evaluate traffic schemes for optimization, addressing the limitations of common analysis methods. By establishing an evaluation index system considering technology, environment, and economy, and using a comprehensive weight vector and TOPSIS model, the study allows for more accurate and comprehensive selection of transportation schemes.
Review
Thermodynamics
Zhengguang Liu, Zhiling Guo, Qi Chen, Chenchen Song, Wenlong Shang, Meng Yuan, Haoran Zhang
Summary: This paper summarizes the sociological and engineering challenges of smart building-integrated photovoltaic (SBIPV) systems and proposes a data-driven solution. Data Sensing, Data Analysis, Data-driven Prediction, and Data-driven Optimization are the key steps to achieve a data-driven SBIPV system. Additionally, the technologies and models for data-driven SBIPV systems are explored to enable automated operational decisions.
Article
Green & Sustainable Science & Technology
Keyong Zhang, Sulun Li, Peng Qin, Bohong Wang
Summary: In the context of digital economy and low carbon economy, digital technology plays a crucial role in achieving carbon peaking and carbon neutrality. A study based on the panel data of 30 Chinese provinces from 2011 to 2019 found that digital technology development has a positive impact on reducing carbon emissions in the region in both the short term and long term. However, the spatial spillover effect of digital technology on carbon emissions in neighboring regions is not significant. Policy makers should consider spatial effects when promoting the application of digital technologies in environmental governance.
Article
Engineering, Chemical
Jianqin Zheng, Jian Du, Yongtu Liang, Bohong Wang, Miao Li, Qi Liao, Ning Xu
Summary: To improve the transport of different oil products and minimize contamination, a hybrid intelligent framework is proposed to track the real-time batch interface of multi-product pipelines. The framework includes a batch injection judgment module and a volume calculation model to accurately determine the location of each batch interface. A self-learning modified model is also introduced to compensate for tracking errors. The proposed model is verified using a real-world multi-product pipeline network in China and shows better performance compared to other methods.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Review
Energy & Fuels
Xianlei Chen, Manqi Wang, Bin Wang, Huadong Hao, Haolei Shi, Zenan Wu, Junxue Chen, Limei Gai, Hengcong Tao, Baikang Zhu, Bohong Wang
Summary: The oil & gas transport and storage engineering is exploring ways to reduce energy consumption and carbon footprints by connecting each part through supply chains. This study provides an overview of current methods, technological improvements, and the latest trends in OGTS to achieve sustainable development goals. The critical analyses focus on increasing flexibility, energy saving, emission reduction, and changing energy structure. The study emphasizes the need for further improvement in energy efficiency, reducing energy/water/material consumption and emissions, and maintaining safety in the extensive oil & gas network.
Article
Thermodynamics
Qing Yuan, Yuyao Gao, Yiyang Luo, Yujie Chen, Bohong Wang, Jinjia Wei, Bo Yu
Summary: In this study, a general operation optimization model with the optimal goal of minimum energy cost is established for a heated oil pipeline system considering mixed discrete-continuous decision variables and complex constraint conditions. An intelligent optimization method combining the hybrid binary-real-coded genetic algorithm (BRCGA) and the penalty method coupled with the simulation of a heated oil pipeline system is proposed to solve the optimization model. The optimization model and solution method are applied to the operation optimization of a complex actual heated oil pipeline system, and an optimal operation scheme is intelligently determined, resulting in a significant saving of 18.7% in energy cost.
Article
Thermodynamics
Yifan Xu, Mengmeng Ji, Jiri Jaromir Klemes, Hengcong Tao, Baikang Zhu, Petar Sabev Varbanov, Meng Yuan, Bohong Wang
Summary: This paper investigates the economic viability of transforming renewable energy into exportable electricity or hydrogen. A comprehensive renewable energy system model is developed based on the P-graph to simulate an energy system that integrates electricity, heat, and hydrogen on a virtual island. Findings from the case study show that exporting extra renewable energy by electricity is cheaper than using hydrogen for the studied island, and the optimal dispatch structure can deliver 51 GWh of electricity annually for 292 M CNY (about 42 M EUR). A sensitivity analysis of export prices and renewable energy uncertainty verifies the economics of electricity export.
Article
Thermodynamics
Mengmeng Ji, Wan Zhang, Yifan Xu, Qi Liao, Jirf Jaromfr Klemes, Bohong Wang
Summary: Renewable energy systems are important in reducing environmental pollution. This paper proposes a multi-period energy model that uses hydrogen for energy storage to meet the fluctuating energy demand of an island. Economic and carbon footprint analyses show that renewable energy systems with hydrogen or battery storage are cheaper and have lower CO2 emissions compared to systems without energy storage. The study also explores the impact of biomass supply and hydrogen storage cost variations.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Energy & Fuels
Xiaojuan Hu, Yunqian Long, Gong Xuan, Yuyi Wang, Xiaohe Huang, Yupeng Xu, Jing Liu, Bohong Wang, Fuquan Song
Summary: In this study, a novel Pickering emulsion stabilized by magnetic nanoparticles Fe3O4@PDA@Si was designed and prepared. The emulsion showed excellent stability and inhibition of demulsification, making it a potential option for enhanced oil recovery.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Weitao Zhang, Dongxu Han, Bohong Wang, Yujie Chen, Kaituo Jiao, Liang Gong, Bo Yu
Summary: The thermo-hydro-mechanical-chemical (THMC) coupling process is crucial in Enhanced Geothermal System (EGS) for long-term heat extraction. However, most models for fractured reservoirs are computationally expensive, limiting their practical use. This study proposes and verifies a THMC-coupled model based on embedded discrete fracture model (EDFM) and extended finite element method (XFEM). The results show the potential of geothermal energy for energy supply and environmental benefits, while investigating the effects of critical parameters on EGS production performance.
JOURNAL OF CLEANER PRODUCTION
(2023)
Review
Green & Sustainable Science & Technology
Xinxiang Yang, Ergun Kuru, Xiuyuan Zhang, Shuyu Zhang, Rui Wang, Jihong Ye, Dingding Yang, Jiri Jaromir Klemes, Bohong Wang
Summary: This paper reviews recent direct measurement results and technological advances in the upstream oil and gas sector. The findings show that the increasing methane emissions deviate from the goals of the Paris Agreement. No consensus was found on the correlation between methane emissions and well data items. Aircraft surveys were the most frequently used technology. Developed countries lead in direct measurement, with only 12.5% of studies conducted in developing countries. Mitigating super-emitters and reported venting and flares could reduce methane emissions by 20% and 25% respectively. China, the world's largest methane emitter, emitted approximately 2135 kt methane from its upstream oil and gas sector, mainly through venting. Direct methane measurements and government management could assist China in prioritising carbon emission reduction.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Thermodynamics
Lianghui Guo, Yi Wang, Yuejiu Liang, Bohong Wang
Summary: The heat exchange network is an important energy recovery unit in chemical processes. This article proposes an optimization method, which includes a Temperature Zone Diagram (TZDM), and a mathematical programming model, to present the optimization results through solving the model. An energy representation method of the stream temperature-energy diagram (STED) is also established. The example shows that the optimized heat transfer recovery of this method is 1.12MJ, which is 10.42% higher than the traditional Pinch Analysis-based approach. This method has good adaptability and can solve the complex optimization problem of heat exchange networks in natural gas purification plants, etc.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2023)
Article
Thermodynamics
Yu-Jie Chen, Dongliang Sun, Bo Yu, Bohong Wang, Wei Lu, Wei Zhang
Summary: This paper proposes a horizontal refined piecewise linear interface reconstruction (HOPLIRE) method for the numerical research of two-phase problems in incompressible flow. The method reconstructs the two-phase interface within one grid cell using multiple horizontal refined pieces, making implementation straightforward and allowing easy computation of the volume fraction flux for solving the VOF function. The HOPLIRE method not only has a simple implementation but also achieves high accuracy in reconstructing the vapor-liquid interface. The performance of the VOSET-HOPLIRE method is verified through comparisons with other popular methods, demonstrating good accuracy and efficiency. Further improvements to extend the method to three-dimensional problems and unstructured meshes are expected in the future.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2023)
Article
Engineering, Civil
Xiaodan Shi, Haoran Zhang, Wei Yuan, Ryosuke Shibasaki
Summary: In order to achieve long-term trajectory prediction for pedestrians in crowds, we propose a general framework that allows prediction models to transfer well to unseen scenes and objects by quickly learning prior information of trajectories. This framework utilizes carefully designed sub-tasks and meta-tasks to learn trajectory information related to scenes and objects, resulting in accurate long-term future prediction.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jinyu Chen, Xiaodan Shi, Haoran Zhang, Wenjing Li, Peiran Li, Yuhao Yao, Satoshi Miyazawa, Xuan Song, Ryosuke Shibasaki
Summary: Monitoring the crowd in urban hotspots is a crucial research topic in urban management with significant social impact. This study proposes a confirmed case-driven time-series prediction model named MobCovid to forecast the crowd in urban hotspots, considering both the number of nighttime staying people and confirmed COVID-19 cases. The effectiveness of the proposed method is validated through multiple comparisons with other baselines.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Industrial
Hao Sun, Haiqing Wang, Ming Yang, Genserik Reniers
Summary: To maintain continuous production, chemical plant operators may choose to ignore or handle faults online rather than shutting down process systems. However, the interaction and interdependence between components in a digitalized process system are significant, and faults can propagate to downstream nodes, potentially leading to risk accumulation and major accidents. This study proposes a dynamic risk assessment method that integrates the system-theoretic accident model and process approach (STAMP) with the cascading failure propagation model (CFPM) to model the risk accumulation process. The proposed method is applied to a Chevron refinery crude unit and demonstrates its effectiveness in quantifying the process of risk accumulation and providing real-time dynamic risk profiles for decision-making.
Article
Engineering, Industrial
M. Rempel
Summary: This article examines a major maritime disaster scenario and explores the evacuation process in such a situation. The study finds that there are various factors that affect the number of lives saved, including the uncertainty of individuals' medical condition, the arrival time of maritime and air assets, and the decision policies used. The authors formulate the multi-domain operation as a sequential decision problem using a modeling framework and provide decision support through a hypothetical case study.
Review
Engineering, Industrial
D. Scorgie, Z. Feng, D. Paes, F. Parisi, T. W. Yiu, R. Lovreglio
Summary: This study investigates the application and effectiveness of VR safety training solutions in various industries such as construction, fire, aviation, and mining. The findings suggest a need for more studies that adopt theories and measure long-term retention. Two meta-analyses demonstrate that VR safety training outperforms traditional training in terms of knowledge acquisition and retention.
Article
Engineering, Industrial
Shital Thekdi, Terje Aven
Summary: This paper examines biases in risk studies and investigates how to identify and address them to ensure high-quality risk analysis. By considering biases related to systematic error, event inclusion, models, and cognitive factors, the paper explores their influence on risk characterization. The insights gained from this exploration can be valuable to risk analysts, policymakers, and other stakeholders involved in risk study applications.
Article
Engineering, Industrial
Maryam Lari
Summary: Occupational health and safety (OHS) are crucial for employee well-being and productivity. This study examines the impact of OHS practices on employee productivity in a UAE Fire and Security company, finding that OHS interventions can enhance workplace ambiance and significantly boost employee productivity.
Review
Engineering, Industrial
Elleke Ketelaars, Cyrille Gaudin, Simon Flandin, Germain Poizat
Summary: This systematic literature review examines the literature on resilience training (RT), specifically focusing on the effectiveness of RT interventions in preparing professionals to effectively respond to critical situations. The review identifies five types of RT and suggests the need for conceptual advancements, vocational education and training perspectives, and a cross-disciplinary approach in future research to enhance resilience in safety-related domains.
Article
Engineering, Industrial
Meng Shi, Zhichao Zhang, Wenke Zhang, Yi Ma, Hanbo Li, Eric Wai Ming Lee
Summary: This study investigates pedestrian behaviours and evacuation processes in both fire and non-fire conditions using Minecraft. The results demonstrate the potential of Minecraft for realistically simulating evacuation processes, as the behaviours and flow patterns of pedestrians in virtual experiments fit well with real-life experiments. The study also shows that pedestrians exhibit fire avoidance behaviours and orderly queuing during a fire emergency, resulting in faster evacuation.
Article
Engineering, Industrial
Andrea Bikfalvi, Esperanza Villar Hoz, Gerusa Gimenez Leal, Monica Gonzalez-Carrasco, Nuria Mancebo
Summary: This paper proposes a solution for integrating occupational safety and health (OSH) into education, combining theoretical foundations and empirical evidence. The findings include analysis of teachers as stakeholders, barriers and facilitators of OSH integration, and the development of an ICT tool for interaction and sharing in this field. The main contribution lies in envisioning, orchestrating, and validating a solution to integrate OSH into schools and ultimately contribute to sustainable development goals.
Article
Engineering, Industrial
David Rehak, Alena Splichalova, Martin Hromada, Neil Walker, Heidi Janeckova, Josef Ristvej
Summary: This article discusses the adoption of a new directive on the resilience of critical entities and emphasizes the importance of assessing their level of resilience in relation to current security threats. The authors have developed a tool, known as the CERFI Tool, which uses a probabilistic algorithm to predict the failure point of critical entity resilience based on the relationship between threat intensity and protection. The tool is important for increasing the safety of technically oriented infrastructures, particularly in the energy and transport sectors.
Review
Engineering, Industrial
Leonardo Leoni, Ahmad Bahootoroody, Mohammad Mahdi Abaei, Alessandra Cantini, Farshad Bahootoroody, Filippo De Carlo
Summary: This paper presents a systematic bibliometric analysis (SBA) on the research of machine learning and deep learning in the field of safety. The main research areas, application fields, relevant authors and studies, and temporal evolution are investigated. It is found that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields, and there is an increase in popularity of deep learning and new approaches such as deep reinforcement learning.
Article
Engineering, Industrial
Tom Becker, Peter Ayton
Summary: By analyzing global civil aviation data, we found that there is a significant increase in the number of accidents and safety critical incidents, as well as the fatalities, when the Pilot-in-Command acts as the Pilot Flying instead of the Pilot Monitoring. Most of these events occurred in technically airworthy aircraft without any emergencies, and the flight crew assessed them as preventable. These findings align with the crew assignment effect, suggesting that role-dependent status hierarchy and cognitive overload contribute to ineffective flight crew teamwork. The measures implemented to enhance flight crew teamwork, such as Crew Resource Management training, have not been successful in preventing these issues.
Article
Engineering, Industrial
Ben Hutchinson, Sidney Dekker, Andrew Rae
Summary: This study found that health and safety audits often fail to identify critical deficiencies, with corrective actions mainly focusing on superficial fixes rather than addressing significant operational risks.
Review
Engineering, Industrial
Sina Rasouli, Yaghoub Alipouri, Shahin Chamanzad
Summary: Construction projects are risky environments, but the development of Personal Protective Equipment (PPE) and comprehensive safety management can effectively control the number of accidents.
Article
Engineering, Industrial
Laura Mills, Verity Truelove
Summary: This study investigated the use of police location communities (PLCs) for obtaining information about roadside drug testing (RDT) among drivers, and found that drivers who used PLCs were more concerned about being caught for drug driving, had a better understanding of the related penalties and procedures, and knew others who also used PLCs to avoid detection for drug driving. Furthermore, the study found that the use of PLCs was associated with choosing back roads for driving, which may reduce the risk of detection for drug driving.
Review
Engineering, Industrial
Chao Wu, Xi Huang, Bing Wang
Summary: After decades of development, the safety discipline in China has made remarkable progress. The project led by the Safety & Security Theory Innovation and Promotion Center of Central South University has filled the gaps in safety science education by creating textbooks and courses for postgraduate students. These achievements have played an important role in the development of safety science and can serve as a reference for basic research and talent training in safety science globally.