安全科学与韧性(英文)最新文献_第5页

Development of a framework for safety and resilience in overhead power cables: Use of a fuzzy inference system for risk and reliability analysis 开发架空电力电缆的安全性和弹性框架：使用模糊推理系统进行风险和可靠性分析

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-05-16 DOI: 10.1016/j.jnlssr.2025.03.005

A.M. Sakura R.H. Attanayake, R.M. Chandima Ratnayake, T. Markeset

Ensuring the safety, resilience, and reliability of overhead low-voltage (LV) and medium-voltage (MV) power cables in aging infrastructure is vital for maintaining essential services and mitigating risks in electrical power distribution systems. This study introduces a novel framework that integrates fault tree analysis (FTA)/failure mode and effect analysis (FMEA) and a fuzzy inference system (FIS) to systematically address performance variability and enhance the operational life of these critical assets while ensuring safety and resilience. This structured framework employs risk-informed decision-making as well as reliability-based safety and resilience assurance, incorporating international standards and best practices. Under this methodology, the FIS models uncertainties in asset performance, using expert-defined rules and membership functions to categorize risk levels and assess failure severity. A case study is performed on overhead MV power cables, specifically the "Racoon" all-aluminum alloy conductor (AAAC), demonstrating its practical implementation. The results reveal that for typical environmental conditions and design parameters, the yearly reliability of the conductor is nearly 1, indicating compliance with IEC standards. Furthermore, a risk matrix is developed using current carrying capacity (CCC), a failure mode obtained from the FTA as the probability of occurrence, and power shutdown duration (PSD) as the severity indicator. The risk matrix estimates the potential risk (PR) level based on CCC and PSD inputs. For example, for CCC = 260 A and PSD = 50 min, the resulting PR is 12.9, indicating a moderate risk exists. These risk levels guide appropriate resilience actions, ensuring proactive power cable management by identifying critical risks, prioritizing mitigation measures, and ensuring adaptability and compliance. This approach not only addresses the challenges of aging infrastructure but also contributes to long-term system integrity and operational reliability.

在老化的基础设施中，确保架空低压（LV）和中压（MV）电力电缆的安全性、弹性和可靠性对于维持配电系统的基本服务和降低风险至关重要。本研究引入了一个新的框架，该框架集成了故障树分析(FTA)/故障模式和影响分析（FMEA）以及模糊推理系统（FIS），以系统地解决性能变化问题，并在确保安全性和弹性的同时提高这些关键资产的使用寿命。该结构框架采用了风险知情决策以及基于可靠性的安全性和弹性保证，并结合了国际标准和最佳实践。在这种方法下，FIS对资产绩效中的不确定性进行建模，使用专家定义的规则和成员函数对风险级别进行分类并评估失败严重程度。以架空中压电力电缆为例，具体介绍了“浣熊”全铝合金导体（AAAC）的实际应用情况。结果表明，在典型环境条件和设计参数下，导线的年可靠度接近1，符合IEC标准。以载流容量（CCC）、故障模式（FTA）为发生概率，以断电时间（PSD）为严重程度指标，建立了风险矩阵。风险矩阵根据CCC和PSD输入估计潜在风险（PR）水平。例如，当CCC = 260 A, PSD = 50 min时，结果PR为12.9，表明存在中等风险。这些风险级别指导适当的弹性行动，通过识别关键风险、优先考虑缓解措施以及确保适应性和合规性，确保主动的电力电缆管理。这种方法不仅解决了基础设施老化的挑战，而且有助于长期的系统完整性和运行可靠性。

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引用次数: 0

Urban community exposure risk assessment for industrial asbestos cement roofing: Coupled GIS and computer vision-based approach 城市社区工业石棉水泥屋面暴露风险评估：基于GIS和计算机视觉的耦合方法

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-05-01 DOI: 10.1016/j.jnlssr.2025.03.002

Mia V. Hikuwai , Nicholas Patorniti , Rodney A. Stewart

Legacy asbestos in built-up urban areas poses a risk of exposure to the surrounding community through environmental exposure pathways. Better understanding the exposure risk of in-situ asbestos containing materials (ACM) presents to surrounding communities through these pathways can better inform its management and reduce asbestos-related diseases. Remote sensing imagery and computer vision techniques facilitate the automated detection of ACM roofs across urban areas. Identifying ACM roofs coupled with GIS-based approaches to evaluate urban community characteristics provides an assessment of community exposure risk to asbestos in a scenario where ACM roofs are disturbed or degraded. This study develops a novel Asbestos-Community Exposure Risk Assessment (A-CERA) framework and associated method and then applies it to a case study urban area located in Australia. A-CERA was developed and applied using a three-phase study method. Phase 1 develops a framework of asbestos exposure risk from literature and subject matter expert focus groups. Phase two formulates the techniques and methods underpinning A-CERA, including autonomous computer vision ACM roof detection, GIS-based land-use feature extraction, and community exposure risk quantification and assessment. Phase 3 applies the developed A-CERA framework to an urban area covering 320 square kilometres with 2,512 detected industrial ACM roofs. Each ACM roof was ranked from the highest assessed level of community exposure risk to the lowest. A-CERA advances the way ACM materials are managed within the urban footprint to reduce asbestos-related diseases.

城市建成区遗留的石棉通过环境暴露途径对周围社区构成暴露风险。通过这些途径更好地了解就地含石棉材料（ACM）对周围社区的暴露风险，可以更好地为其管理提供信息，并减少石棉相关疾病。遥感图像和计算机视觉技术促进了对城市地区ACM屋顶的自动检测。确定ACM屋顶并结合基于gis的方法来评估城市社区特征，可在ACM屋顶受到干扰或退化的情况下评估社区接触石棉的风险。本研究开发了一种新的石棉-社区暴露风险评估（a - cera）框架和相关方法，并将其应用于澳大利亚城市地区的案例研究。a - cera的开发和应用采用了三相研究方法。第一阶段根据文献和主题专家焦点小组制定石棉暴露风险框架。第二阶段制定支持A-CERA的技术和方法，包括自主计算机视觉ACM屋顶检测，基于gis的土地利用特征提取，以及社区暴露风险量化和评估。第三阶段将开发的A-CERA框架应用于覆盖320平方公里的城区，其中检测到2,512个工业ACM屋顶。每个ACM屋顶从社区暴露风险评估的最高水平到最低水平进行排名。A-CERA推进了在城市足迹范围内管理石棉材料的方式，以减少与石棉有关的疾病。

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引用次数: 0

DLW-CI: A Dynamic Likelihood-Weighted Cooperative Infotaxis approach for multi-drone cooperative multi-source search DLW-CI：一种多无人机协同多源搜索的动态似然加权协同信息趋向性方法

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-04-22 DOI: 10.1016/j.jnlssr.2025.04.001

Bin Chen , Xiaoran Zhang , Yatai Ji , Yong Zhao , Zhengqiu Zhu

Drones have gradually been employed to search for unknown sources during leakage accidents. However, current studies have mainly focused on the single-source search problem, while in practical situations, the location and quantity of the sources are commonly unknown. Existing multi-source search methods fail to accurately estimate the source term, primarily due to the inefficient utilization of concentration information. This limitation results in sub-optimal drone movement strategies. To address these issues, we propose a Dynamic Likelihood-Weighted Cooperative Infotaxis (DLW-CI) approach. The approach integrates the Infotaxis cognitive search strategy with multi-drone cooperation by optimizing both source term estimation and the cooperative mechanism. Specifically, we devise a novel source term estimation method that leverages multiple parallel particle filters, with each filter estimating the parameters of a potentially unknown source in scenarios. Subsequently, we introduce a cooperative mechanism based on dynamic likelihood weight to prevent multiple drones from concurrently estimating and searching for the same source. The results show that the success rate for the localization of 2–4 diffusion sources reaches 90%, 78%, and 42% respectively when employing the DLW-CI approach, achieving a 37% average improvement over baseline methods. Our findings indicate that the proposed DLW-CI approach significantly improves estimation accuracy and search efficiency for multi-drone cooperative multi-source search, making a valuable contribution to environmental safety monitoring applications.

在泄漏事故中，无人机逐渐被用于寻找未知来源。然而，目前的研究主要集中在单一来源的搜索问题上，而在实际情况下，来源的位置和数量通常是未知的。现有的多源搜索方法无法准确估计源项，主要原因是对浓度信息的利用效率不高。这种限制导致了次优的无人机移动策略。为了解决这些问题，我们提出了一种动态似然加权合作信息趋向性（DLW-CI）方法。该方法通过优化源项估计和合作机制，将信息趋向性认知搜索策略与多无人机合作相结合。具体来说，我们设计了一种新的源项估计方法，该方法利用多个并行粒子滤波器，每个滤波器估计场景中潜在未知源的参数。随后，我们引入了一种基于动态似然权的协同机制，防止多架无人机同时估计和搜索同一来源。结果表明，采用DLW-CI方法定位2-4个扩散源的成功率分别达到90%、78%和42%，比基线方法平均提高37%。研究结果表明，DLW-CI方法显著提高了多无人机协同多源搜索的估计精度和搜索效率，为环境安全监测应用做出了重要贡献。

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引用次数: 0

Urban road collapse risk assessment based on the extended xLSTM Network 基于扩展xLSTM网络的城市道路塌陷风险评估

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-04-11 DOI: 10.1016/j.jnlssr.2024.10.005

Jiahao Zhou , Juncai Jiang , Yizhao Wang , Wenfeng Bai , Fei Wang , Long Chen , Qinglun He

Rapid urbanization has substantially increased the complexity of urban underground spaces. This complexity leads to frequent road collapse incidents that pose significant threats to the safety and property of urban residents. Therefore, accurate methods of performing early road collapse risk assessments are crucial for preventing these incidents and emergency preparedness. In this study, road collapse incident data for 2016–2021 were collected for Foshan, Guangdong Province, a city in southern China. Utilizing InSAR time-series data from Sentinel-1 satellites, ground subsidence maps were generated, and the publicly accessible Ground Subsidence Trend-Based Urban Road Collapse Risk Dataset (GSTURCRD) was constructed. A novel risk assessment method for urban road collapse based on an extended long short-term memory (xLSTM) network was proposed. This method introduces two new LSTM variants, the scalar LSTM (sLSTM) and the matrix LSTM (mLSTM), incorporating exponential gating and an innovative matrix memory structure. These variants are integrated using residual connections to form a comprehensive network architecture that enables effective learning and representation of the temporal features. The experimental results from the dataset demonstrate that the proposed method significantly outperforms the original LSTM network and traditional machine learning methods regarding assessment capability (its accuracy was 0.886, and its recall was 0.857). Furthermore, the method's effectiveness was validated by an analysis of actual incidents that occurred in Foshan; thus, its ability to generate accurate and timely detections and provide early warnings for high-risk road sections in urban areas was confirmed.

快速城市化大大增加了城市地下空间的复杂性。这种复杂性导致道路坍塌事件频繁发生，对城市居民的安全和财产构成重大威胁。因此，早期进行道路塌陷风险评估的准确方法对于预防这些事件和应急准备至关重要。在本研究中，收集了中国南方城市广东省佛山市2016-2021年的道路塌陷事件数据。利用Sentinel-1卫星的InSAR时间序列数据，生成地面沉降图，并构建可公开访问的基于地面沉降趋势的城市道路塌陷风险数据集（GSTURCRD）。提出了一种基于扩展长短期记忆（xLSTM）网络的城市道路塌陷风险评估方法。该方法引入了两种新的LSTM变体，标量LSTM （sLSTM）和矩阵LSTM (mLSTM)，结合了指数门控和创新的矩阵存储结构。这些变体使用剩余连接进行集成，形成一个全面的网络架构，能够有效地学习和表示时间特征。数据集的实验结果表明，该方法在评估能力方面明显优于原始LSTM网络和传统机器学习方法（准确率为0.886，召回率为0.857）。最后，通过对佛山实际事故的分析，验证了该方法的有效性；因此，它能够对城市地区的高风险路段进行准确和及时的探测并提供早期预警。

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引用次数: 0

Quantitative resilience assessment on critical infrastructures – A systematic literature review of the last decade (2014-2024) 关键基础设施的定量弹性评估——过去十年（2014-2024）的系统文献综述

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-04-07 DOI: 10.1016/j.jnlssr.2025.02.002

Andrea De Marco , Davide Berardi , Marta Galuppi , Mara Lombardi

The everyday functioning of infrastructures and the capacity of their owners to provide high-quality services are critical to the well-being of communities and societies. When disruptions endanger society's well-being, security, and economy, some of these infrastructures are relevant and, as a result, are designated as critical for an entire nation. Therefore, research has focused on a peculiar infrastructure ability, or capacity, that summarizes these concepts in one word: resilience; its quantification, however, is not straightforward. Many authors have attempted to assess resilience using different subjects, infrastructures, resilience phases, and models. Therefore, through a systematic literature review based on the PRISMA protocol, this work presents an overview of quantitative methods and techniques developed over the past decade to numerically assess the resilience of critical infrastructures (CIs). A total of 111 papers were included in the study, which focused on studies published between April 2014 and April 2024. This article focuses on a model-based classification, highlighting strengths and weaknesses in the proposed methodologies, and performs a SWOT analysis on the modeling approaches identified within the retrieved papers. Future works could be useful to extend this research to those papers that describe and quantify single domains, stages, and features of CIs resilience, exploring the possibility of searching protocols to identify and correctly address them.

基础设施的日常运作及其所有者提供高质量服务的能力对社区和社会的福祉至关重要。当破坏威胁到社会福祉、安全和经济时，其中一些基础设施是相关的，因此，被指定为对整个国家至关重要。因此，研究集中在一种特殊的基础设施能力或能力上，用一个词概括了这些概念：弹性；然而，它的量化并不简单。许多作者尝试使用不同的主题、基础结构、弹性阶段和模型来评估弹性。因此，通过基于PRISMA协议的系统文献综述，本工作概述了过去十年中开发的定量方法和技术，用于对关键基础设施（ci）的弹性进行数值评估。该研究共纳入了111篇论文，主要集中在2014年4月至2024年4月期间发表的研究。本文着重于基于模型的分类，突出了所提出方法的优点和缺点，并对检索到的论文中确定的建模方法进行SWOT分析。未来的工作可能有助于将这项研究扩展到那些描述和量化CIs弹性的单个领域，阶段和特征的论文，探索搜索协议以识别和正确解决它们的可能性。

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引用次数: 0

Spatio-temporal prediction of terrorist attacks based on GCN-LSTM 基于 GCN-LSTM 的恐怖袭击时空预测

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-04-07 DOI: 10.1016/j.jnlssr.2025.02.005

Yingjie Du , Ning Ding , Hongyu Lv

Terrorist attacks represent a significant threat to national order, social stability, and economic security. Accurate prediction of such attacks is a critical task for casualty reduction, enhanced decision-making, and optimal resource distribution in counter-terrorism efforts. This paper introduces an innovative spatio-temporal fusion framework that combines graph convolutional network (GCN) with long short-term memory (LSTM) models. By capturing and merging spatio-temporal features from relevant events, the proposed GCN-LSTM model achieves remarkable accuracy in predicting terrorist attacks. The experimental results demonstrate outstanding performance, with the model attaining minimal RMSE and MAE values of 0.037 and 0.031, respectively, surpassing all baseline models (LSTM, GCN, and CNN-LSTM-Transformer). Through its effective interpretation of complex spatio-temporal patterns underlying terrorist attacks, our model substantially enhances the predictive accuracy across diverse time horizons. These findings carry crucial implications for enhancing counter-terrorism strategies.

恐怖袭击是对国家秩序、社会稳定和经济安全的重大威胁。准确预测此类袭击是反恐工作中减少伤亡、加强决策和优化资源分配的关键任务。本文介绍了一种将图卷积网络（GCN）与长短期记忆（LSTM）模型相结合的创新时空融合框架。通过捕获和融合相关事件的时空特征，所提出的GCN-LSTM模型在预测恐怖袭击方面取得了显著的准确性。实验结果表明，该模型的最小RMSE和MAE值分别为0.037和0.031，优于所有基线模型（LSTM、GCN和CNN-LSTM-Transformer）。通过对恐怖袭击背后复杂时空模式的有效解释，我们的模型大大提高了不同时间范围内的预测准确性。这些发现对加强反恐战略具有重要意义。

引用次数: 0

Evaluation of the underground space safety resilience of Chinese urban agglomerations based on the “Pressure-State-Response”: A case study of underground rail transit in 26 cities 基于“压力-状态-响应”的中国城市群地下空间安全弹性评价——以26个城市地下轨道交通为例

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-03-28 DOI: 10.1016/j.jnlssr.2025.02.001

Chong Li, Yibao Wang

Urban underground space disasters exhibit characteristics including complex causal mechanisms and high risk. They also present unpredictability and risk coupling amplification. Differences in underground space safety resilience (USSR) and key pathways of urban agglomerations are issues that remain under-discussed. This study is based on the perspective of resilience genesis, and it constructs a Pressure-State-Response (PSR) analysis framework. This study employs methods such as the composite index method, Dagum Gini coefficient, and fuzzy set Qualitative Comparative Analysis (fsQCA) to explore the differences in safety resilience levels and key pathways of underground spaces of urban agglomerations. The study offered several findings: (1) The safety resilience index rankings of the five major urban agglomerations, from highest to lowest, are as follows: Chengdu-Chongqing City Group, Pearl River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, Triangle of Central China and Yangtze River Delta urban agglomeration. In addition, the underground space safety resilience systems of cities were clustered and categorized into demonstration and leadership type, striving catch-up type, and stable development type. (2) Overall differences between urban agglomerations are reflected in the differences between individual urban agglomerations. The internal development imbalance is the primary reason for the more significant differences in and between the Pearl River Delta and Yangtze River Delta urban agglomerations. (3) High-level safety resilience of urban underground space is the result of a multi-factor combination in the PSR framework. In addition, there are four high-level safety resilience configuration paths, and these paths are categorized into three modes: "state-driven response", "pressure-triggered response", and "autonomous response". Policy implications and countermeasures for urban underground space development are proposed for each mode of urban underground space safety resilience. These proposals offer theoretical references for optimizing the safety resilience of underground spaces of urban agglomerations.

城市地下空间灾害具有因果机制复杂、危险性高的特点。它们还表现出不可预测性和风险耦合放大。城市群地下空间安全弹性差异及其关键路径是目前研究的热点问题。本研究基于弹性成因的视角，构建了压力-状态-反应（PSR）分析框架。本研究采用综合指数法、达格姆基尼系数法、模糊集定性比较分析法（fsQCA）等方法，探讨城市群地下空间安全弹性水平差异和关键通道差异。研究发现：(1)五大城市群安全弹性指数从高到低依次为成渝城市群、珠三角城市群、京津冀城市群、华中三角城市群和长三角城市群。并将城市地下空间安全弹性系统集群划分为示范引领型、奋发追赶型和稳定发展型。(2)城市群整体差异体现在单个城市群之间的差异上。内部发展不平衡是珠三角城市群与长三角城市群差异显著的主要原因。③城市地下空间的高安全弹性是PSR框架中多因素综合作用的结果。此外，还存在4种高水平安全弹性配置路径，这些路径可分为“状态驱动响应”、“压力触发响应”和“自主响应”三种模式。针对城市地下空间安全弹性的各种模式，提出了城市地下空间开发的政策启示和对策。这些建议为优化城市群地下空间安全弹性提供了理论参考。

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引用次数: 0

JMoE-FAP: A novel model for telecom network fraud victimization pattern analysis JMoE-FAP：电信网络诈骗受害模式分析的新模型

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-03-26 DOI: 10.1016/j.jnlssr.2025.01.006

Tuo Shi , Jing Hu , Danyang Li , Min Chen

A comprehensive examination of the victimization process, coupled with the development of effective preventive strategies, represents the most promising approach for mitigating telecom network fraud. However, the limited availability of telecom fraud case text data hinders the advancement of robust data extraction algorithms, thereby complicating the identification of victimization patterns. To address this gap, this study proposes a victimization process analysis model that leverages mixed expert event joint extraction, utilizing real telecom fraud case data. The model integrates LERT-MoE to extract trigger words and arguments related to the victimization process from law enforcement reports, followed by the application of a dot-product attention mechanism for argument role classification. To the best of our knowledge, this represents the first attempt to apply a mixture-of-experts model with a purpose-built dot-product attention mechanism for the in-depth analysis of telecom network fraud victimization patterns, overcoming the limitations of previous methods in managing the complexity and diversity of fraudulent behaviors. Additionally, the Apriori method is employed to uncover prevalent behavioral patterns in the victimization process. Experimental results demonstrate that the proposed model outperforms baseline models in precision, accuracy, and F1-score for event extraction tasks in telecom fraud instances. Furthermore, the model identifies more granular fraud patterns within the victimization process, offering a valuable knowledge base for the development of targeted preventive strategies. The identified patterns can be used to design focused awareness campaigns, enhance fraud detection algorithms, and improve law enforcement training, thereby significantly increasing the effectiveness of anti-fraud initiatives.

对受害过程进行全面审查，再加上制定有效的预防战略，是减轻电信网络欺诈的最有希望的方法。然而，电信诈骗案件文本数据的有限可用性阻碍了稳健数据提取算法的发展，从而使受害模式的识别复杂化。为了解决这一差距，本研究提出了一个受害过程分析模型，该模型利用混合专家事件联合提取，利用真实的电信欺诈案例数据。该模型集成了LERT-MoE，从执法报告中提取与受害过程相关的触发词和论点，然后应用点积注意机制进行论点角色分类。据我们所知，这是首次尝试将专家混合模型与专门构建的点积注意机制应用于电信网络欺诈受害模式的深入分析，克服了以前方法在管理欺诈行为的复杂性和多样性方面的局限性。此外，Apriori方法被用来揭示在受害过程中普遍存在的行为模式。实验结果表明，该模型在电信诈骗事件提取任务的精密度、准确度和f1分数上都优于基线模型。此外，该模型在受害过程中确定了更细粒度的欺诈模式，为制定有针对性的预防战略提供了宝贵的知识库。所确定的模式可用于设计重点突出的宣传活动、增强欺诈检测算法和改进执法培训，从而显著提高反欺诈举措的有效性。

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引用次数: 0

Evaluation of the cognitive performance of nuclear power plant operators using heart rate variability under hot-humid exposure 在湿热环境下使用心率变异性评价核电站操作员的认知能力

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-03-26 DOI: 10.1016/j.jnlssr.2025.01.004

Lingzhong Du , Ming Jia , Tao Chen , Yan Zhang , Yicheng Zhang , Zhihui Xu , Yanchao Su , Xiangbiao Xing , Tingdong Chen , Cheng Yang

When sudden disasters such as earthquakes and tsunamis culminate in the outage of control systems in nuclear power plants, the operators may be exposed to extremely hot-humid environmental conditions while still facing demanding cognitive tasks. To investigate how their cognitive performance is related to their heart rate variability (HRV), we exposed nuclear power plant operators to four high temperature and humidity environments and measured their HRV during seven different cognitive tasks for 30 min. Generalized linear mixed-effects models (GLMMs) are used to analyze the relationship between HRV and operators' cognitive performance. Studies have shown that all indicators of HRV have a significant impact on the cognitive ability of operators. In both the low frequency (LF) and high frequency (HF), especially in the very low frequency (VLF) domain, HRV significantly correlates with the operator's cognition. Although the cognitive performance aggravates slightly within 30 min, increasing the humidity under fixed high temperatures does not exhibit an overall effect on cognitive performance. Henceforth, this study provides a guidance for safety limits of the operator's working duration. Moreover, VLF, LF, and HF domains might be potential physiological indicators to monitor the cognitive ability of operators.

当地震和海啸等突发灾害最终导致核电站控制系统中断时，操作人员可能会暴露在极端湿热的环境条件下，同时仍然面临苛刻的认知任务。为了研究他们的认知表现与心率变异性（HRV）之间的关系，我们将核电站操作员暴露在4种高温高湿环境中，并在7种不同的认知任务中测量了他们的心率变异性（HRV），时间为30分钟。研究表明，HRV的各项指标对操作人员的认知能力有显著影响。在低频（LF）和高频（HF）领域，特别是在甚低频（VLF）领域，HRV与操作员的认知显著相关。虽然在30min内认知表现略有恶化，但在固定高温下增加湿度对认知表现没有整体影响。因此，本研究为操作人员工作时长安全限值的制定提供了指导。此外，VLF、LF和HF结构域可能是监测操作者认知能力的潜在生理指标。

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引用次数: 0

An improved multi-velocity cellular automaton model that considers psychological impatience 考虑心理不耐的改进多速度元胞自动机模型

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-03-22 DOI: 10.1016/j.jnlssr.2024.11.006

Hongpeng Qiu , Wenke Zhang , Meng Shi , Eric Wai Ming Lee

The cellular automaton (CA) model is an essential tool for studying pedestrian evacuation dynamics; moreover, improving simulations of actual evacuation environments and increasing the reliability of evacuation data are important problems for researchers. The complex psychological dynamics of pedestrians during evacuation and the evacuation velocities are essential components of such models. This study proposes and verifies a synchronously updated multi-velocity evacuation impatient CA model with a corresponding time correction formula. Our model that considers pedestrians’ psychological impatience can simulate complex scenarios in which different pedestrians simultaneously evacuate at different speeds. In addition, our model accurately simulates and reproduces the phenomena found in actual experiments: as the self-growth parameter of impatience increases, the evacuation efficiency first increases and then decreases, and as the contagion parameter of impatience increases, the evacuation efficiency decreases. The time correction method and formula are critical for obtaining reliable results from simulations in which pedestrians evacuate at various speeds, and they are expected to be indispensable parts of multi-velocity CA models for predicting complex evacuation scenes.

元胞自动机（CA）模型是研究行人疏散动力学的重要工具；此外，改进对实际疏散环境的模拟，提高疏散数据的可靠性是研究人员需要解决的重要问题。行人在疏散过程中复杂的心理动态和疏散速度是该模型的重要组成部分。本文提出并验证了一个同步更新的多速度疏散失稳CA模型，并给出了相应的时间校正公式。我们的模型考虑了行人的心理不耐烦，可以模拟不同行人同时以不同速度疏散的复杂场景。此外，我们的模型准确地模拟和再现了实际实验中发现的现象：随着不耐烦的自我生长参数的增加，疏散效率先增加后降低，随着不耐烦的传染参数的增加，疏散效率降低。时间校正的方法和公式对于在行人以不同速度疏散的模拟中获得可靠的结果至关重要，是多速度CA模型预测复杂疏散场景不可缺少的部分。

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