Reliability Engineering & System Safety最新文献_第6页

Uncertainty-aware remaining useful life prediction and PPO based optimal maintenance scheduling in industrial IoT 工业物联网中不确定性感知剩余使用寿命预测和基于PPO的最优维护调度

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ress.2026.112356

Guneet Kaur Walia, Mohit Kumar

{"title":"Uncertainty-aware remaining useful life prediction and PPO based optimal maintenance scheduling in industrial IoT","authors":"Guneet Kaur Walia, Mohit Kumar","doi":"10.1016/j.ress.2026.112356","DOIUrl":"10.1016/j.ress.2026.112356","url":null,"abstract":"<div><div>The rapid emergence of digitized factories and advanced automotive manufacturing has paved the way for the integration of Internet of Things (IoT) sensors and Artificial intelligence (AI) techniques to maximize equipment uptime, that enhances manufacturing operations and support reliability. Predictive maintenance (PdM) is a key approach that leverages equipment sensor data to monitor performance abnormalities. Further, the estimation of Remaining Useful Life (RUL) aids in predicting potential or impeding failover before its actual breakdown. However, only few studies extend the work of RUL prognostics prediction to scheduling equipment maintenance, but suffer from few challenges such as overestimation of Q-values, instability during training, and inefficient performance. In addition to this, existing investigations often consider single-point RUL predictions, however in real-world scenario, many factors such as noise, distinct operating conditions of the equipment and nevertheless complex nature of equipment agening, introduces the concept of uncertainity. Hence, it becomes paramount to quantify the uncertainity of RUL, for which the authors propose non-parametric probabilistic prediction method, known as Quantile Regression (QR) integrated with Gated Recurrent Unit (GRU) and Convolutional Neural Network (CNN) for predicting RUL values of the equipment. Further, the RUL values are utilized to design better adaptive maintenance scheduling plans using the Proximal Policy Optimization (PPO) approach. The work has been tested on a prominent NASA turbofan engine dataset, which illustrates the promising performance of the proposed framework. The experimental results validate that the proposed work improves RUL prediction up to 19.08 % and minimizes maintenance schedule time up to 24.18 % in comparison to state-of-the-art approaches.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112356"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175022","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

System-of-systems safety for low-altitude aviation transportation 低空航空运输的系统安全

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-23 DOI: 10.1016/j.ress.2026.112276

Anzhuo Yao , Shanghan Li , Kaifeng Feng , Tengfei Zhang , Xueying Song , Lizhi Wang , Ruixin Wang , Peng He , Hang Zhou , Hang Li , Shuiting Ding , Daqing Li

{"title":"System-of-systems safety for low-altitude aviation transportation","authors":"Anzhuo Yao , Shanghan Li , Kaifeng Feng , Tengfei Zhang , Xueying Song , Lizhi Wang , Ruixin Wang , Peng He , Hang Zhou , Hang Li , Shuiting Ding , Daqing Li","doi":"10.1016/j.ress.2026.112276","DOIUrl":"10.1016/j.ress.2026.112276","url":null,"abstract":"<div><div>Low-altitude (LA) transportation is rapidly evolving as a new sector of traditional aviation industry. Specifically, existing aviation safety studies were largely developed under traditional aviation System-of-systems (SoS) architectures, and primarily address system-level risks (human, vehicle, communication-navigation-surveillance, or operational management) with clear system boundaries. As a new SoS, LA SoS may have new emergent risk types and cross-domain cascading risk propagation via new architecture. This paper considers the LA transportation SoS from architecture viewpoint, and analyzes its new characteristics and risk patterns. Therefore, we propose LA SoS safety engineering framework to handle these possible new challenges through architecture design, testing & evaluation, and safety management. Accordingly, our SoS safety engineering framework mainly includes: architecture design (human-automation safety control and digital flight rules), testing & evaluation (traceable design-to-verification and equipment safety requirement), and safety management (monitor-assess-mitigate for in-time risk prediction and mitigation). Our safety engineering framework aims to provide possible solution for this new complex system of LA aviation transportation.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112276"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174756","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

Predicting operators reliability for control room alarm management using knowledge-based Bayesian networks 基于知识贝叶斯网络的控制室报警管理操作员可靠性预测

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-23 DOI: 10.1016/j.ress.2026.112261

Houda Briwa , Anders L. Madsen , Maria Chiara Leva

{"title":"Predicting operators reliability for control room alarm management using knowledge-based Bayesian networks","authors":"Houda Briwa , Anders L. Madsen , Maria Chiara Leva","doi":"10.1016/j.ress.2026.112261","DOIUrl":"10.1016/j.ress.2026.112261","url":null,"abstract":"<div><div>Despite comprehensive standards for industrial alarm management and existing human reliability studies on operator behavior, quantitative operator-centered reliability assessment within alarm management activities remains limited. This paper presents a Bayesian network framework that integrates alarm response task decomposition, cognitive modeling, and contextual factors to assess alarm management reliability across perception, planning, and execution phases, capturing both task effectiveness and temporal constraints. The model combines Performance Shaping Factors with phase-specific cognitive mechanisms using an object-oriented Bayesian network implementation in HUGIN Software. The model was built within the context of a simulated experiment to enable future data validation. Model parameters were defined through literature and, when unavailable, through expert assumptions. Value of information and sensitivity analyses reveal that performance is primarily driven by operator experience and task complexity, factors parameterized through established literature. In contrast, support system effects show minimal impact, possibly reflecting the experiment’s limited scope. Failure patterns differ across experience levels: novices most likely fail through timeout, while experienced operators typically fail through incorrect actions. Sensitivity analysis highlighted that the perception phase is most sensitive to parameter changes. This framework demonstrates how established HRA principles can be extended to alarm management contexts, establishing a structured approach for evaluating operator-alarm interaction pending empirical validation.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112261"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174839","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

A joint probability model for multi-hazard intensity in earthquake-induced rockfall scenarios 地震岩崩多灾害强度的联合概率模型

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-01 DOI: 10.1016/j.ress.2026.112342

Enjia Zhao , Jianian Wen , Xiaoyu Bai , Qiang Han , Xiuli Du

{"title":"A joint probability model for multi-hazard intensity in earthquake-induced rockfall scenarios","authors":"Enjia Zhao , Jianian Wen , Xiaoyu Bai , Qiang Han , Xiuli Du","doi":"10.1016/j.ress.2026.112342","DOIUrl":"10.1016/j.ress.2026.112342","url":null,"abstract":"<div><div>The earthquake-induced rockfall hazard is one of the multi-hazard scenarios that threaten the safety of structures in mountainous areas. However, the lack of quantitative load models for earthquake-induced rockfall multi-hazard significantly limits the ability to evaluate the reliability of structures under such conditions. To address this gap, a methodology was proposed to establish a joint probability model for multi-hazard intensity in earthquake-induced rockfall scenarios. First, an intensity database for earthquake-induced rockfall was established using a validated numerical simulation. Then, marginal distribution models were developed for earthquake and rockfall intensities, and joint probability models based on Copula theory were established and validated with simulated data. A case study of the methodology for establishing the joint probability model was conducted based on normalized terrains. The analysis results indicate a positive correlation between the cumulative absolute displacement of ground motions and the rockfall energy, with the Spearman coefficient exceeding 0.327. The randomly simulated data from the joint probability models effectively reproduce the fundamental patterns and the extreme characteristics of earthquake-induced rockfall scenarios. This demonstrated the proposed joint probability models accurately capture the energy characteristics of earthquake-induced rockfall, providing a valuable reference for risk assessment of structures located in mountainous areas.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112342"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174994","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

Dynamic evolutionary pathway analysis of urban rail transit flood risks and intelligent decision support based on knowledge graphs 基于知识图的城市轨道交通洪涝风险动态演化路径分析及智能决策支持

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-01 DOI: 10.1016/j.ress.2026.112345

Hao Wang , Shenglin Liu , Lei Li , Jian Zuo , Xianhai Meng , Michael Goodsite , Liudan Jiao , Liu Wu

{"title":"Dynamic evolutionary pathway analysis of urban rail transit flood risks and intelligent decision support based on knowledge graphs","authors":"Hao Wang , Shenglin Liu , Lei Li , Jian Zuo , Xianhai Meng , Michael Goodsite , Liudan Jiao , Liu Wu","doi":"10.1016/j.ress.2026.112345","DOIUrl":"10.1016/j.ress.2026.112345","url":null,"abstract":"<div><div>With the intensification of global climate change, rainstorm disasters have become increasingly frequent and catastrophic. Urban rail transit (URT) systems, which are primarily constructed underground, possess structural features that make them particularly vulnerable to severe impacts during heavy rainfall events. Such disasters can result in significant casualties and substantial losses. Meanwhile, extensive domain-specific knowledge has been accumulated from historical disaster events. Effectively extracting and utilizing such knowledge is essential for improving disaster risk identification and enhancing emergency management practice. To address these challenges, this study proposes a method for analyzing risk evolution mechanisms by integrating Knowledge Graph and Natural Language Processing (NLP) technologies. The knowledge graph enables structured knowledge representation and facilitates effective knowledge reuse. Building on this, a knowledge-driven decision support model is established by combining the language understanding capability of NLP with the inferential capacity of knowledge graphs. Case studies of representative examples are conducted to validate the effectiveness of the proposed method in this study. The findings show that structuring knowledge in the form of a graph network offers significant advantages for the intelligent analysis of disaster risk evolution. On one hand, a large amount of multi-source, heterogeneous knowledge related to URT flood risks is systematically structured and represented, thereby enhancing the efficiency of knowledge utilization by decision-makers. On the other hand, integrating NLP with knowledge graph–based risk network analysis enables the accurate identification of potential risk paths, providing valuable insights and a foundation for disaster prevention and mitigation decision-making.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112345"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174996","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

Nested adaptive Kriging-based reliability analysis and computational resource allocation for complex systems 基于嵌套自适应kriging的复杂系统可靠性分析与计算资源分配

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ress.2026.112367

Kewei Ye , Xiaobing Ma , Han Wang

{"title":"Nested adaptive Kriging-based reliability analysis and computational resource allocation for complex systems","authors":"Kewei Ye , Xiaobing Ma , Han Wang","doi":"10.1016/j.ress.2026.112367","DOIUrl":"10.1016/j.ress.2026.112367","url":null,"abstract":"<div><div>Efficient reliability analysis of complex engineering systems faces significant challenges due to the integration of multiple subproblems, multidisciplinary coupling, high-dimensional characteristics, and resource incompatibility. These systems are often decomposed into multiple cascading subsystems, which enables concurrent analysis to manage this complexity. Surrogate-based techniques are widely utilized to alleviate the computational burden associated with time-consuming simulations. This study proposes a nested adaptive Kriging-based method for the reliability analysis of complex systems by integrating system decomposition with adaptive surrogate-based methods. The proposed method operates within a multilayer framework and proceeds in two stages, namely, a sequential updating stage and a resource allocation stage. In the first stage, an efficient nested reliability-oriented acquisition function is developed to guide model updating, and its closed-form expression is derived. In the second stage, a cost-effectiveness strategy that accounts for both simulation costs and modeling costs is introduced to determine which model combinations should be updated at each iteration. Finally, the proposed method is validated to be superior to the benchmark method and strategy through two mathematical examples and two practical applications.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112367"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174955","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

Optimal Bayesian maintenance policy for gear shafts under variable operating conditions with partially observable information 具有部分可观测信息的变工况下齿轮轴的最优贝叶斯维修策略

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-09 DOI: 10.1016/j.ress.2026.112388

Xin Li , Jing Cai , Weixi Shi , Zhenzhen Liu , Zhendong Zhao , Yan Liu , Hang Fei , Hongfu Zuo

{"title":"Optimal Bayesian maintenance policy for gear shafts under variable operating conditions with partially observable information","authors":"Xin Li , Jing Cai , Weixi Shi , Zhenzhen Liu , Zhendong Zhao , Yan Liu , Hang Fei , Hongfu Zuo","doi":"10.1016/j.ress.2026.112388","DOIUrl":"10.1016/j.ress.2026.112388","url":null,"abstract":"<div><div>In mechanical transmission systems, gear shafts serve as essential conduits for torque transfer and alignment processes, and their failure can lead to substantial increases in maintenance and supportability costs. Sensor-based condition monitoring yields only partially observable information about the actual health of gear shafts, which complicates maintenance decisions. To overcome this challenge, a novel optimal Bayesian maintenance policy under partially observable information is presented. A hidden semi-Markov model (HSMM) consisting of three states—unobservable healthy and unhealthy states, as well as an observable failure state—is employed to model the performance degradation process of the target system. Considering the nondecreasing characteristics of the system hazard rate in normal operations and wear-out stages in practical scenarios, the Erlang and hyper-Erlang distributions are employed to depict the sojourn times in the healthy and unhealthy states, respectively. An explicit conditional reliability function is updated in real time on the basis of Bayes’ theorem and integrated into a cost-minimizing semi-Markov decision process (SMDP). A control limit algorithm identifies the reliability threshold for optimal downtime scheduling. A validation of the gear shaft life test conducted under variable operating conditions reveals the earlier detection of incipient failures and lower expected average costs than those of other fault detection models. The proposed approach offers both theoretical insights and practical value for enhancing the safety and reliability of high-end mechanical equipment.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112388"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174922","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

A safety protection method based on trajectory prediction for the operation of virtual coupling trains 基于轨迹预测的虚拟联轴车运行安全保护方法

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-30 DOI: 10.1016/j.ress.2026.112328

Ying Zhao , Haijun Li , Xiaobing Liu , Yan Huang

{"title":"A safety protection method based on trajectory prediction for the operation of virtual coupling trains","authors":"Ying Zhao , Haijun Li , Xiaobing Liu , Yan Huang","doi":"10.1016/j.ress.2026.112328","DOIUrl":"10.1016/j.ress.2026.112328","url":null,"abstract":"<div><div>This study proposes a safety protection method based on trajectory prediction (SPTP) for the operation of virtual coupling trains. Specifically, a hybrid TLMA model that integrates Temporal Convolutional Networks (TCN), Long Short-Term Memory (LSTM), and Multi-head Self-attention (MATT) was developed to predict the trajectory of the leading train. Based on the prediction results, the SPTP method was introduced, grounded in principles such as space requirements for the following train’s operation, safety requirements when trains are stationary in the station platform, and operation safety requirements under different adverse conditions. Furthermore, a microscopic multi-state train-following model was constructed to validate the effectiveness of the SPTP method. The comparative results of the prediction model demonstrate that the TLMA model outperforms baseline models, achieving high accuracy and demonstrating excellent applicability for train trajectory prediction. Then, the SPTP method was compared with existing safety protection methods. Numerical simulation results showed that the SPTP method effectively reduced the distance interval between trains by 34.6 %, the speed difference between trains by 7.0 %, and the arrival time deviation by 65.0 %. These findings suggest that the SPTP method could effectively improve operation efficiency for urban rail trains and enhance passenger service quality.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112328"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174927","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

SCADA data-driven failure rate and reliability prediction for offshore wind turbines SCADA数据驱动的海上风力涡轮机故障率和可靠性预测

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-06 DOI: 10.1016/j.ress.2026.112378

Xiangyu Kong , Ruishu Huang , He Li , C. Guedes Soares

引用次数: 0

Seismic fragility of CAP1400 nuclear power plant consisting of steel-concrete shield building under mainshock-aftershock sequences 主余震序列下钢-混凝土盾构结构CAP1400核电站的地震易损性

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-24 DOI: 10.1016/j.ress.2026.112288

Xiao-Bin Wang , Ye-Yao Weng , Miao-Jun Qin , Yan-Gang Zhao

{"title":"Seismic fragility of CAP1400 nuclear power plant consisting of steel-concrete shield building under mainshock-aftershock sequences","authors":"Xiao-Bin Wang , Ye-Yao Weng , Miao-Jun Qin , Yan-Gang Zhao","doi":"10.1016/j.ress.2026.112288","DOIUrl":"10.1016/j.ress.2026.112288","url":null,"abstract":"<div><div>The seismic safety of the CAP1400 nuclear power plant (NPP) is critically important as its failure would result in significant loss of life and economic damage. Currently, seismic fragility analysis for the CAP1400 NPP has been conducted solely under single ground motions. Since strong ground motions often trigger multiple aftershocks, a comprehensive seismic fragility analysis of the CAP1400 NPP under mainshock-aftershock (MS-AS) sequences is conducted in this paper. Incremental dynamic analysis results and seismic fragility curves are derived using 20 MS-AS records, scaled with different intensity ratios of 1:0.6, 1:0.8, and 1:1. The results indicate that MS-AS sequences cause more severe damage to the CAP1400 NPP compared to mainshock records, and the damage intensifies as the aftershock ratio increases. Furthermore, as the CAP1400 NPP generally adopts steel-concrete (SC) shield building instead of conventional reinforcement concrete (RC) shield building, a comparative seismic fragility analysis of the CAP1400 NPP with SC and RC shield building is conducted under MS-AS sequences. It is found that the CAP1400 NPP consisting of SC shield building exhibits significantly lower fragility than RC shield building under MS-AS sequences, and as the aftershock ratio increases, the seismic superiority of SC shield building becomes more pronounced.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112288"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175036","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