Journal of Infrastructure Intelligence and Resilience最新文献_第2页

Few-shot learning with large foundation models for automated segmentation and accessibility analysis in architectural floor plans 在建筑平面图中进行自动分割和可访问性分析的大型基础模型的少量学习

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-12-17 DOI: 10.1016/j.iintel.2024.100137

Haolan Zhang, Ruichuan Zhang

{"title":"Few-shot learning with large foundation models for automated segmentation and accessibility analysis in architectural floor plans","authors":"Haolan Zhang, Ruichuan Zhang","doi":"10.1016/j.iintel.2024.100137","DOIUrl":"10.1016/j.iintel.2024.100137","url":null,"abstract":"<div><div>This paper presents a novel approach for extracting accessibility features from 2D raster floor plans by integrating few-shot learning techniques with the Segment Anything Model (SAM) and GPT-4. The proposed method addresses the limitations of existing deep learning-based floor plan analysis, which often require extensive annotated datasets and struggle with the variability of raster floor plans. Furthermore, there is a lack of research on extracting accessibility features from 2D raster floor plans, which remain one of the most common formats for storing architectural plans post-design and construction. Our approach, GPT-integrated Multi-object Few-shot SAM (GMFS), leverages similarity maps and cluster-based point sampling to generate accurate visual prompts for SAM, enabling the segmentation of rooms and doors using only five reference samples. The segmented masks are then classified using GPT-4, enhancing the semantic richness of the floor plan analysis. We validated GMFS using the CubiCasa and Rent3D datasets, demonstrating impressive performance in segmentation and classification. A detailed case study further showcased the practical application of our approach in calculating accessible means of egress and wheelchair clear space, which are critical features for accessibility compliance. The results highlight the effectiveness and adaptability of our approach in real-world scenarios, underscoring its potential to improve building accessibility and safety analysis in the architecture, engineering, and construction (AEC) industry.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 2","pages":"Article 100137"},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent control of structural vibrations based on deep reinforcement learning 基于深度强化学习的结构振动智能控制

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-12-15 DOI: 10.1016/j.iintel.2024.100136

Xuekai Guo, Pengfei Lin, Qiulei Wang, Gang Hu

{"title":"Intelligent control of structural vibrations based on deep reinforcement learning","authors":"Xuekai Guo, Pengfei Lin, Qiulei Wang, Gang Hu","doi":"10.1016/j.iintel.2024.100136","DOIUrl":"10.1016/j.iintel.2024.100136","url":null,"abstract":"<div><div>This paper explores the application of Deep Reinforcement Learning (DRL) in structural vibration control, aiming to achieve effective control of the dynamic response of building structures during natural disasters such as earthquakes. A DRL-based control strategy is proposed, and dynamic interaction between the OpenSees environment and the deep reinforcement learning environment is realized. By adjusting the parameters in the reward function, the control preference of the DRL algorithm for different metrics can be effectively modified. Additionally, an intelligent structural vibration control platform based on DRL has been developed to simplify the design process of DRL algorithms. Case studies conducted on the platform demonstrate that DRL can effectively suppress structural responses in both single-layer and multi-layer complex structures. Meanwhile, comparisons with PID and LQR algorithms that are based on linear analysis design, reveal the stability advantages of DRL in handling structural dynamic responses characterized by high nonlinearity, time delay, and large actuator output intervals.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 2","pages":"Article 100136"},"PeriodicalIF":0.0,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fractal-based numerical simulation of multivariate typhoon wind speeds utilizing weierstrass mandelbrot function 基于weierstrass mandelbrot函数的多变量台风风速分形数值模拟

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-11-22 DOI: 10.1016/j.iintel.2024.100135

Kang Cai , Mingfeng Huang , Qiang Li , Qing Wang , Yi-Qing Ni

{"title":"Fractal-based numerical simulation of multivariate typhoon wind speeds utilizing weierstrass mandelbrot function","authors":"Kang Cai , Mingfeng Huang , Qiang Li , Qing Wang , Yi-Qing Ni","doi":"10.1016/j.iintel.2024.100135","DOIUrl":"10.1016/j.iintel.2024.100135","url":null,"abstract":"<div><div>This paper proposes a fractal-based technique for simulating multivariate nonstationary wind fields by the stochastic Weierstrass Mandelbrot function. Upon conducting a systematic fractal analysis, it was found that the structure function method is more suitable and reliable than the box counting method, variation method, and R/S analysis method for estimating the fractal dimension of the stochastic wind speed series. Wind field measurement at the meteorological gradient tower with a height of 356 m in Shenzhen was conducted during Typhoon Mandelbrot (1983). Significant non-stationary properties and fractal dimensions of typhoon wind speed data at various heights were analyzed and used to demonstrate the effectiveness of the proposed multivariate typhoon wind speed simulation method. The multivariate wind speed components simulated by the proposed fractal-based method are in good agreement with the measured records in terms of the fractal dimension, standard deviation, probability density function, wind spectrum and cross-correlation coefficient.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 2","pages":"Article 100135"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new method for predicting PM2.5 concentrations in subway stations based on a multiscale adaptive noise reduction transformer -BiGRU model and an error correction method 基于多尺度自适应降噪变压器-BiGRU模型和误差修正方法的地铁站点PM2.5浓度预测新方法

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-11-17 DOI: 10.1016/j.iintel.2024.100128

Dingyu Chen, Hui Liu

{"title":"A new method for predicting PM2.5 concentrations in subway stations based on a multiscale adaptive noise reduction transformer -BiGRU model and an error correction method","authors":"Dingyu Chen, Hui Liu","doi":"10.1016/j.iintel.2024.100128","DOIUrl":"10.1016/j.iintel.2024.100128","url":null,"abstract":"<div><div>PM2.5 is a significant contributor to air pollution, with a notable impact on human health. Subway stations, with their high pedestrian traffic, present a particular challenge in this regard. By monitoring PM2.5 levels, subway managers can take prompt action, such as optimizing the operation of air purification equipment in stations, to enhance air quality within stations and thereby enhance the passenger experience. This paper proposes an enhanced Transformer-BiGRU prediction model, which incorporates a MSHAM(Multiscale Hybrid Attention Mechanism)comprising a multi-scale convolutional attention mechanism and a VMD decomposition self-attention mechanism. Additionally, a ANR(Adaptive Noise Reduction) module has been integrated into the model to facilitate noise reduction. Finally, the prediction is performed by BiGRU. The resulting error sequence is predicted by BiGRU and the predicted sequence is corrected. In this paper, a dataset of pollutants from Seoul subway stations in South Korea is used to compare with the base model. The model presented in this paper achieves the highest accuracy.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review on optimization strategies of probabilistic diagnostic imaging methods 概率成像诊断方法的优化策略综述

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-10-22 DOI: 10.1016/j.iintel.2024.100127

Ning Li , Anningjing Li , Jiangfeng Sun

{"title":"Review on optimization strategies of probabilistic diagnostic imaging methods","authors":"Ning Li , Anningjing Li , Jiangfeng Sun","doi":"10.1016/j.iintel.2024.100127","DOIUrl":"10.1016/j.iintel.2024.100127","url":null,"abstract":"<div><div>With the continuous development of intelligent infrastructure, structural health monitoring (SHM) and non-destructive testing (NDT) have become major research focuses. Ultrasonic-guided wave imaging technology not only integrates the global impact of damage on structures but also provides intuitive localization and severity characterization of the damage. Probabilistic diagnostic imaging (PDI) methods, which do not require direct interpretation of guided wave signals and can achieve high-quality imaging with sparse arrays, have garnered increasing attention. This paper introduces the principles, general processes, and technical advantages of PDI methods. Based on the process of the PDI, existing optimization strategies are categorized into two types: internal process optimizations, which include sensor layout, damage indices optimization, construction of the distribution weight function, and data fusion; and external process optimizations, which include spurious image suppression, on-site environment detection, and integration of methodologies, each analyzed in detail. With the affirmation of the value of these strategies, this paper also highlights the current issues within these methods and explores potential future developments by integrating emerging technologies such as intelligent sensing, big data, and artificial intelligence. These insights provide valuable reference suggestions for the continued optimization of these methods.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An integrated management system (IMS) approach to sustainable construction development and management 可持续建筑开发和管理的综合管理系统（IMS）方法

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-10-18 DOI: 10.1016/j.iintel.2024.100126

Ahsan Waqar , Saad Nisar , Muhammad Muddassir , Omrane Benjeddou

{"title":"An integrated management system (IMS) approach to sustainable construction development and management","authors":"Ahsan Waqar , Saad Nisar , Muhammad Muddassir , Omrane Benjeddou","doi":"10.1016/j.iintel.2024.100126","DOIUrl":"10.1016/j.iintel.2024.100126","url":null,"abstract":"<div><div>Construction is significantly contributing to the severe environmental crisis it is facing. The sector consumes over 3 billion tons of raw materials annually, and its activities account for 40% of global CO<sub>2</sub> emissions. Traditional integrated strategies toward fragmented sustainability cannot offer total optimization. In this respect, the present research presents an integrated management system (IMS) containing a composite of metrics for sustainable construction management (SCM). This research was specifically geared to test the relationship between the elements of IMS and SCM from the perspective of the construction industry. A quantitative survey tested through 119 professionals was used for data collection. It is established through structural equation modeling (SEM) that the internal consistency of Cronbach’s Alpha 0.72–0.95 and construct validity was strong. The Fornell-Larcker criterion was realized to affirm good discriminant validity. Crucial results identified the presence of significant impacts for quality management (QM) (β = 0.643, <em>p</em> < 0.001), risk management (RM) (β = 0.53, <em>p</em> < 0.001), and safety management (SM) (β = 0.439, <em>p</em> < 0.001). Therefore, this study further enhances the scalability of IMS so that it is practically applied to improve project quality and safety, along with risk management. Future research could also focus on studying the context of the integration of IMS with SCM and continue to work using objective performance measures to validate these findings.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reliability-based safety format for structural fire engineering – Derivation based on the most likely failure point 结构消防工程的基于可靠性的安全格式。基于最可能失效点的推导

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-10-18 DOI: 10.1016/j.iintel.2024.100125

Ruben Van Coile, Balša Jovanović, Florian Put

{"title":"Reliability-based safety format for structural fire engineering – Derivation based on the most likely failure point","authors":"Ruben Van Coile, Balša Jovanović, Florian Put","doi":"10.1016/j.iintel.2024.100125","DOIUrl":"10.1016/j.iintel.2024.100125","url":null,"abstract":"<div><div>Designing structures for burnout resistance ensures stability during evacuation and search and rescue operations, limits collateral damage, and enhances post-fire repairability. This represents a significant shift from traditional prescriptive designs that do not evaluate performance under realistic fire conditions. However, given the variability in fire exposure and structural response, it is unclear which input values should be used to ensure a high level of reliability for burnout calculations. This paper introduces a safety format for burnout resistance compatible with the Eurocode and its reliability principles. The format allows users to specify desired reliability levels and prescribes equations for determining design values for load effects and fire load density using predetermined sensitivity weights. A method for calculating default sensitivity weights is outlined, proposing tentative values: 0.65 for resistance effect, −0.40 for load effect, and −0.80 for fire load density, with a default coefficient of variation of 0.30 for resistance effect when case-specific information is lacking. The safety format's performance is verified through case studies of a concrete slab and a numerical evaluation of a steel column, showing satisfactory and conservatively assessed results. Inherent conservatism in the design format may, however, occasionally lead to the undue rejection of designs. Further investigations are necessary to confirm the safety format's conceptualization, default sensitivity weights, and the influence of the adopted compartment fire model.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"4 1","pages":"Article 100125"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantitative risk analysis of road transportation of hazardous materials in coastal areas 沿海地区危险品公路运输的定量风险分析

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-09-08 DOI: 10.1016/j.iintel.2024.100124

Daijie Chen , Xiyong Bai

{"title":"Quantitative risk analysis of road transportation of hazardous materials in coastal areas","authors":"Daijie Chen , Xiyong Bai","doi":"10.1016/j.iintel.2024.100124","DOIUrl":"10.1016/j.iintel.2024.100124","url":null,"abstract":"<div><p>Given the complex climate conditions in coastal areas and their role as key transportation hubs for hazardous chemicals, this study proposes a method to quantitatively and comprehensively evaluate transportation risks. Initially, accident data were analyzed to identify risk factors from five aspects: human, vehicle, materials, environment, and management, based on system safety theory. Subsequently, a risk analysis model was developed using Decision-making Trial and Evaluation Laboratory, interpretive structural model theory, and Bayesian theory to quantitatively assess accident risk levels. The model was applied to a case involving a hazardous chemical accident on a cross-sea bridge, where Bayesian backward reasoning was used to analyze the sensitivity and importance of risk factors. This approach facilitated the key risk factors affecting the safety of hazardous chemical transportation systems. Notably, the study incorporated scenarios involving hazardous material transport vehicles crossing sea bridges into the risk assessment framework, offering valuable insights for management authorities. It also considered the impact of strong side winds-a factor often overlooked-in hazardous material transport. The validation process demonstrated that the method accurately quantifies the risk of hazardous chemical transportation and identifies the key factors influencing accident occurrence. The research highlights that strong gusts of wind significantly impact safety, and human factors are crucial in the overall risk system.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991524000434/pdfft?md5=964f153c00429cfef1e5889999414f17&pid=1-s2.0-S2772991524000434-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multimodal vortex-induced vibration mitigation and design approach of bistable nonlinear energy sink inerter on bridge structure 多模式涡流诱导振动缓解与桥梁结构双稳态非线性能量吸收器的设计方法

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-09-07 DOI: 10.1016/j.iintel.2024.100123

Ruihong Xie , Kun Xu , Houjun Kang , Lin Zhao

{"title":"Multimodal vortex-induced vibration mitigation and design approach of bistable nonlinear energy sink inerter on bridge structure","authors":"Ruihong Xie , Kun Xu , Houjun Kang , Lin Zhao","doi":"10.1016/j.iintel.2024.100123","DOIUrl":"10.1016/j.iintel.2024.100123","url":null,"abstract":"<div><div>Large-scale structures, e.g., long-span bridge structures, are prone to induce multi-modal vibrations due to their densely spaced low modal frequencies. Due to the limited frequency bandwidth of linear dynamic absorbers, they are incapable of effectively mitigating vibrations across multiple modes. To this end, the bistable nonlinear energy sink inerter (BNESI) is used to mitigate the multimodal vortex-induced vibration (VIV) of the beam structure. The highly nonlinear equilibrium differential equations of the beam-BNESI system are numerically solved, and the simulated annealing (SA) algorithm is employed to determine the optimal VIV reduction ratio and BNESI parameters. In comparison to the cubic-type nonlinear energy sink inerter (CNESI), BNESI is found to possess more stable equilibrium positions, smaller stiffness coefficients, and higher VIV mitigation efficiency. The selection of design modes has been found to influence the efficiency of multimodal VIV mitigation, with the use of the intermediate modal order as the design mode resulting in the highest efficiency for multimodal VIV mitigation. The performance-based multimodal VIV mitigation design can be realized with three parameters, i.e., inertance ratio, damping coefficient, and stiffness coefficient. Moreover, the performance-based multimodal VIV mitigation approach and models proposed in this study demonstrate a high level of precision.</div></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 4","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review of artificial intelligence in dam engineering 人工智能在大坝工程中的研究进展

Journal of Infrastructure Intelligence and Resilience Pub Date : 2024-09-02 DOI: 10.1016/j.iintel.2024.100122

Wenxuan Cao , Xinbin Wu , Junjie Li , Fei Kang

引用次数: 0