Reliability Engineering & System Safety最新文献_第8页

Importance analysis of non-coherent Multi-State System 非相干多态系统的重要性分析

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-10 DOI: 10.1016/j.ress.2025.111618

Elena Zaitseva, Peter Sedlacek, Vitaly Levashenko

{"title":"Importance analysis of non-coherent Multi-State System","authors":"Elena Zaitseva, Peter Sedlacek, Vitaly Levashenko","doi":"10.1016/j.ress.2025.111618","DOIUrl":"10.1016/j.ress.2025.111618","url":null,"abstract":"<div><div>Non-coherent Multi-State System (MSS) is a special case in the point of view of reliability analysis and needs special methods for its reliability quantification. The specificity of this system behavior is a possibility of its performance degradation depending on the improvement of the functioning of its component, or its performance improving depending on the component work degradation/failure. Non-coherent system, mostly investigated for Binary-State System (BSS) where the system and its components have only two performance levels as functioning and failure. The case of MSS where the system and its components can have more than only two performance levels is studied fragmentarily. In this paper, a new method for importance analysis of non-coherent MSS is proposed. This method is based on the use of Logical Differential Calculus for the definition and calculation of Importance Measures (IM). In particular, the Structural Importance and Birnbaum’s Importance measures are defined and considered for a non-coherent MSS. These measures allow us to investigate the influence each of the system components has on its behavior, taking into consideration the specifics of a non-coherent MSS.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111618"},"PeriodicalIF":11.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerated life testing and reliability estimation for internet of things-based smart water networks 基于物联网的智能水网加速寿命试验与可靠性评估

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-10 DOI: 10.1016/j.ress.2025.111705

Ming-Hung Shu , I-Sheng Sun , Chung-Ming Yang , To-Cheng Wang

{"title":"Accelerated life testing and reliability estimation for internet of things-based smart water networks","authors":"Ming-Hung Shu , I-Sheng Sun , Chung-Ming Yang , To-Cheng Wang","doi":"10.1016/j.ress.2025.111705","DOIUrl":"10.1016/j.ress.2025.111705","url":null,"abstract":"<div><div>With the growing demand for sustainable urban water management, the reliability and longevity of smart water network components play a crucial role in reducing resource waste and enhancing environmental resilience. This study evaluates the reliability of a household-scale IoT-based smart water network, focusing on accelerated life testing (ALT) of key components, including electronic water meters and communication modules. A three-phase verification approach, i.e., engineering, design, and production verification tests, was implemented to identify and mitigate potential design weaknesses before mass deployment. By subjecting components to temperature, humidity, and thermal cycling stress, failure data were collected and analyzed using exponential and Weibull distribution models within a series-system reliability framework. Results indicate that, after iterative reinforcement, critical components achieved a reliability of 0.98 at a 90 % confidence level over an eight-year service period, significantly exceeding the target reliability level of 0.9. Deploying high-reliability smart water meters enhances real-time water resource monitoring, preventing excessive water loss and optimizing consumption efficiency, which is crucial for achieving urban sustainability goals. This study demonstrates that integrating ALT with a systematic three-phase validation process can significantly improve the durability and sustainability of smart water networks.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111705"},"PeriodicalIF":11.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving the reliability of aero-engine control system via virtual sensor-assisted fault-tolerant control 利用虚拟传感器辅助容错控制提高航空发动机控制系统的可靠性

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-10 DOI: 10.1016/j.ress.2025.111703

Zexi Jin , Jinxin Liu , Maojun Xu , Kang Wang , Hang Zhao , Zhiping Song

{"title":"Improving the reliability of aero-engine control system via virtual sensor-assisted fault-tolerant control","authors":"Zexi Jin , Jinxin Liu , Maojun Xu , Kang Wang , Hang Zhao , Zhiping Song","doi":"10.1016/j.ress.2025.111703","DOIUrl":"10.1016/j.ress.2025.111703","url":null,"abstract":"<div><div>Gas path sensors serve as critical information sources for the aero-engine control system, and the reliability of their measurements directly impacts engine safety. Constraints including installation space and maintenance cost limit further fault tolerance improvement through increasing hardware redundancy. To address this issue, this paper proposes a virtual sensor-assisted fault-tolerant control (VSFTC) method. Specifically, gas path virtual sensors are constructed using random vector functional link networks with correlation-based input selection and online sequential training, forming a triple-redundancy sensing architecture. A sensor fusion algorithm is developed to assess the confidence levels of physical sensors and generate high-confidence data for engine controller computations. Bias and drift faults are injected into the gas path sensors, and comparative simulations are performed to validate the proposed method. Verification results indicate that the VSFTC method exhibits robust fault tolerance against physical sensor failures, effectively mitigating high-pressure compressor surge risks and ensuring engine operational safety. Reliability analysis incorporating sensor diagnostic coverage demonstrates that the virtual sensor-assisted control system achieves a longer mean time between failures compared to the conventional dual hardware redundancy system.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111703"},"PeriodicalIF":11.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive mission risk control under incomplete health information and resource limitation: A constrained multi-state predictive maintenance model 不完全健康信息和资源限制下的自适应任务风险控制：一种约束多状态预测维护模型

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-09 DOI: 10.1016/j.ress.2025.111697

Fanping Wei , Xiaobing Ma , Qingan Qiu , Yuhan Ma , Jingjing Wang , Li Yang

{"title":"Adaptive mission risk control under incomplete health information and resource limitation: A constrained multi-state predictive maintenance model","authors":"Fanping Wei , Xiaobing Ma , Qingan Qiu , Yuhan Ma , Jingjing Wang , Li Yang","doi":"10.1016/j.ress.2025.111697","DOIUrl":"10.1016/j.ress.2025.111697","url":null,"abstract":"<div><div>Information-empowered online predictive maintenance (PdM) is essential to mitigating unplanned failure risks of safety-critical industrial equipment during mission executions, whose effectiveness, however, is increasingly challenged by data inadequacy and resource limitation. This study investigates an innovative predictive maintenance model for multi-state mission-oriented systems under limited maintenance resources, where the system's health evolution is only partially revealed through collected monitoring data. As opposed to previous studies, we synthesize incomplete system health information and resource reservation conditions to inform sequential replacement actions under resource constraints, so as to maximizing system mission reliability. In particular, we establish an adaptive belief-state-based maintenance decision model based on belief states, and delve into a series of structural properties with respect to the model. The optimization problem of interest is shown to constitute a dynamic control limit structure that substantially improves decision robustness; by exploiting this structure, we present an efficient heuristic algorithm to alleviate computational burden in acquiring optimal maintenance solutions. Numerical experiments conducted on radar driver demonstrate the theoretical feasibility and practical implications of our approach.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111697"},"PeriodicalIF":11.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling the dynamical process of behavioral contagion in human crowds during evacuation 疏散过程中人群行为传染的动态过程建模

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-09 DOI: 10.1016/j.ress.2025.111649

Wenhan Wu , Wenfeng Yi

{"title":"Modeling the dynamical process of behavioral contagion in human crowds during evacuation","authors":"Wenhan Wu , Wenfeng Yi","doi":"10.1016/j.ress.2025.111649","DOIUrl":"10.1016/j.ress.2025.111649","url":null,"abstract":"<div><div>Behavioral contagion, the process by which individuals adopt behaviors from neighbors, plays a critical role in crowd evacuations by shaping collective decision-making and movement patterns. Despite its observable and tractable nature compared to emotional contagion, however, behavioral contagion remains underexplored in crowd models, with its propagation mechanisms and effects on evacuation dynamics yet to be systematically explored. To address these gaps, we propose a behavioral contagion-based social force model (BC-SFM) that explicitly couples contagion mechanisms with movement behaviors. Numerical simulations show that BC-SFM outperforms the classical SFM by enabling faster and more synchronized changes in escape behaviors, highlighting the performance superiority of our model in characterizing behavioral contagion dynamics. The intensity and heterogeneity of interaction radius and response threshold jointly determine the spatial–temporal dynamics of behavioral contagion, with their effects also varying across different crowd densities. Moreover, four typical contagion mechanisms, shaped by distinct combinations of perceptual capacity and individual responsiveness, significantly affect evacuation dynamics, particularly in terms of efficiency and congestion. These findings demonstrate the pivotal impact of behavioral contagion on emergent evacuation outcomes, offering theoretical foundations for advancing predictive models and adaptive management strategies.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111649"},"PeriodicalIF":11.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-contact automated identification of earthquake-induced micro damage in substation equipment system based on local damping parameter screening with a surrogate model 基于替代模型局部阻尼参数筛选的变电站设备系统地震微损伤非接触自动识别

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-09 DOI: 10.1016/j.ress.2025.111704

Jiayi Wen , Longquan Wang , Xiaoxuan Li , Yantai Zhang , Yang Wei

{"title":"Non-contact automated identification of earthquake-induced micro damage in substation equipment system based on local damping parameter screening with a surrogate model","authors":"Jiayi Wen , Longquan Wang , Xiaoxuan Li , Yantai Zhang , Yang Wei","doi":"10.1016/j.ress.2025.111704","DOIUrl":"10.1016/j.ress.2025.111704","url":null,"abstract":"<div><div>Substation equipment systems may experience invisible micro-damage to local components after an earthquake, which can lead to electrical functionality failure. Such micro-damage typically has little effect on equipment stiffness or natural frequency, posing challenges to conventional damage monitoring techniques. As a result, post-earthquake inspections currently rely on manual diagnosing of each piece of equipment, making rapid recovery a challenging task. Given that micro-damage is likely to alter the damping of materials, this paper proposes a method to detect local damping variation of a system, aiding in the swift screening of potentially damaged components. The approach is based on a surrogate theoretical model developed from the motion equilibrium equations of separated components within a system and requires only measured ground motion and displacement at the top of the equipment. The method is solved in the frequency domain, effectively suppressing the influence of undamaged components and highlighting abnormalities caused by damaged parts. A key output, the indicator <em>EG</em>, is susceptible to local damping variation and allows for both the localization and quantification of damage. When applied to randomly generated damage scenarios, the method is shown to accurately identify different damage modes, including both single- and multiple-component damage modes. The damage localization accuracy is 100%, and the estimation error for quantifying damping variation is within ±5%. This method offers a new path for efficiently detecting minor post-earthquake damage in substation equipment systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111704"},"PeriodicalIF":11.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is there difference in landslide susceptibility model based on explainable artificial intelligence from the perspective of slope units with different scales? 基于可解释人工智能的滑坡易感性模型在不同尺度边坡单元的视角下是否存在差异？

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-09 DOI: 10.1016/j.ress.2025.111701

Junhao Huang , Haijia Wen , Xinzhi Zhou , Jiafeng Xiao

{"title":"Is there difference in landslide susceptibility model based on explainable artificial intelligence from the perspective of slope units with different scales?","authors":"Junhao Huang , Haijia Wen , Xinzhi Zhou , Jiafeng Xiao","doi":"10.1016/j.ress.2025.111701","DOIUrl":"10.1016/j.ress.2025.111701","url":null,"abstract":"<div><div>The scale of mapping units significantly affects the accuracy and reliability of landslide susceptibility assessment. However, existing landslide susceptibility studies lack a clear determination of the appropriate slope unit scale, and the impact of different slope unit configurations on the modeling process and model interpretability has not been thoroughly investigated. This study conducted an empirical analysis using extensive real-world landslide data from the core area of the Three Gorges Reservoir region, comprehensively investigating the effect of slope-unit scales on the landslide susceptibility assessment. Initially, a geospatial dataset comprising 3594 historical landslide events and 22 initial condition factors was compiled. Subsequently, 30 different slope unit schemes of varying scales were generated by the r.slopeunits tool. For each scheme, the dataset was randomly divided into training and testing subsets with a 7:3 ratio and modeled using random forest model. This study reveals the significant impact of slope unit scales on hyperparameter optimization, factor selection, and model interpretability. The results highlight that: (1) appropriate slope unit scale can improve the quality of input variables, thereby enhancing the generalization ability and interpretability of landslide susceptibility assessments, reducing the risk of overfitting. (2) Finer and more concentrated slope units do not always lead to better results; they may excessively rely on distance metrics, resulting in overly conservative high susceptibility classifications in landslide susceptibility models. This study provides valuable insights into selecting the appropriate slope unit scale for landslide susceptibility assessment.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111701"},"PeriodicalIF":11.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human-AI interactive framework for smart evacuation safety analysis in large infrastructures 大型基础设施智能疏散安全分析的人机交互框架

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-09 DOI: 10.1016/j.ress.2025.111695

Tong Lu, Yuxin Zhang, Weikang Xie, Xinyan Huang

{"title":"Human-AI interactive framework for smart evacuation safety analysis in large infrastructures","authors":"Tong Lu, Yuxin Zhang, Weikang Xie, Xinyan Huang","doi":"10.1016/j.ress.2025.111695","DOIUrl":"10.1016/j.ress.2025.111695","url":null,"abstract":"<div><div>The increasing scale and complexity of large urban infrastructures have led to greater pedestrian concentrations and high risks of crowd-related incidents in emergencies. This study develops an Intelligent Evacuation Prediction Tool (IEPTool) with a human-AI interactive framework for evacuation prediction and safety assessment in large infrastructures. The tool is equipped with a deep learning engine trained from a comprehensive evacuation-simulation database of 66 real-life architectural floor plans, including air terminals, exhibition centers, large stadiums, and various stations. By integrating long-short-term memory (LSTM) networks and generative adversarial networks (GANs), key metrics, including evacuation time, the pedestrian flow rate at each exit, and dynamic pedestrian density distribution, are predicted with a high accuracy of over 90 %. Subsequently, a large language model (LLM) is incorporated for interactive risk analysis, enabling intelligent evacuation safety assessments and providing optimization guidance. The integrated graphical user interface allows fast and accurate evaluation of evacuation safety for complex floorplans. This intelligent framework provides practical and reliable support to fire safety design analysis and urban resilience management.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111695"},"PeriodicalIF":11.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Determining the service life of a gondola car with an increased floor body safety factor 在增加底板安全系数的情况下确定吊篮车的使用寿命

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-08 DOI: 10.1016/j.ress.2025.111670

Denys Baranovskyi , Maryna Bulakh , Mariia Bulakh

{"title":"Determining the service life of a gondola car with an increased floor body safety factor","authors":"Denys Baranovskyi , Maryna Bulakh , Mariia Bulakh","doi":"10.1016/j.ress.2025.111670","DOIUrl":"10.1016/j.ress.2025.111670","url":null,"abstract":"<div><div>This study presents a newly optimized design for the gondola car body floor aimed at reducing mechanical wear and significantly extending service life without increasing structural weight or material costs. The scientific novelty of this study lies in the integration of structural optimization, probabilistic modeling, and finite element analysis to enhance the service life and reliability of the gondola car body floor while maintaining material and weight constraints. The study proposes a new mathematical model, which is built on the basis of reliability theory taking into account the physical and mechanical characteristics of the material and the load - it allows for accurate prediction of the service life of the gondola car based on the wear of the body floor structure. The study also introduces the concept of an operational safety factor, which accounts for variability in load and material strength, providing a more realistic measure of structural performance under real-world conditions. Using a combination of finite element analysis, statistical modeling, and a novel reliability-based mathematical approach, the mechanical behavior of the redesigned floor was evaluated under dynamic load conditions. The analysis demonstrated that the proposed floor geometry reduced equivalent stresses by up to 91.6 % and improved the safety factor by up to 12.9 times compared to traditional designs. Statistical models, including normal and Weibull distributions, confirmed the extended durability of the redesigned gondola car body, with service life improvements ranging from 1.22 to 2.07 times. Notably, the use of cost-effective plain carbon steel was maintained, ensuring practical applicability. These results validate the effectiveness of structural optimization in enhancing the performance, reliability, and economic viability of freight rail vehicles.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111670"},"PeriodicalIF":11.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Building condition assessment methodology to support public finance and disaster risk management 建筑状况评估方法，以支持公共财政和灾害风险管理

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2025-09-08 DOI: 10.1016/j.ress.2025.111641

Gonzalo Pita , Francisco Michati , Shaochong Xu

{"title":"Building condition assessment methodology to support public finance and disaster risk management","authors":"Gonzalo Pita , Francisco Michati , Shaochong Xu","doi":"10.1016/j.ress.2025.111641","DOIUrl":"10.1016/j.ress.2025.111641","url":null,"abstract":"<div><div>Natural disasters can severely damage a country’s public buildings and infrastructure, often resulting in substantial increases in public debt. To develop cost-effective mitigation strategies, governments need information of their public buildings’ current physical condition—yet such data is often unavailable, and surveying numerous buildings is impractical. While several analytical models exist to characterize structural condition, a more granular modeling approach would better support the design and evaluation of targeted fiscal interventions. This paper introduces a probabilistic systems-aggregated condition assessment methodology that reflects how overall building condition emerges from localized deterioration processes. The methodology disaggregates a building into the levels at which deterioration naturally occurs — components, systems, and critical load paths — and models it using techniques tailored to each. Condition estimates are then coherently aggregated to characterize the compound effect on the entire structure. This structured approach affords modelers significant flexibility to represent diverse structural configurations and materials. Case study results align with expected service lifespans from the literature and resemble Weibull-type deterioration functions. The model offers a valuable tool for public agencies’ work in public finance management, risk management, and preventive maintenance planning.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111641"},"PeriodicalIF":11.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0