检索结果-内蒙古大学图书馆

rapid visual screening methodology for multi-hazard vulnerability assessment of reinforced concrete buildings in hilly region

引用

BULLETIN OF EARTHQUAKE ENGINEERING 2024年 1-44页

作者： Kulariya, Mahipal Aggarwal, Yati Kashyap, Harsha Saha, Sandip Kumar Indian Inst Technol Mandi IIT Mandi Sch Civil & Environm Engn Kamand 175075 Himachal Prades India Manav Rachna Int Inst Res & Studies Dept Civil Engn Faridabad 121004 Haryana India Jawaharlal Nehru Govt Engn Coll JNGEC Sundernagar Dept Civil Engn Sundernagar 175018 Himachal Prades India Indian Inst Technol Mandi IIT Mandi Sch Civil & Environm Engn Kamand 175075 Himachal Prades India

The present study proposes a rapid visual screening methodology for multi-hazard vulnerability assessment (termed as MH-RVS) of reinforced concrete (RC) buildings in the Indian Himalayan region considering earthquakes, debris flow, debris flood, and soil subsidence. An extensive field survey of 1200 buildings was conducted in three hill towns situated in the Northwestern Indian Himalayan region to identify prevalent multi-hazard vulnerability attributes. The presented MH-RVS methodology is statistically developed based on the information obtained from the current field survey and existing post-hazard reconnaissance studies. The proposed methodology effectively addresses the concern of underpredicting the expected damage states of RC buildings situated in hilly regions subjected to multi-hazard scenarios when they are assessed using RVS methodologies of seismic vulnerability assessment. Further, a simplified MH-RVS form is developed to collect field data and conveniently segregate the RC buildings based on their expected damage state under multi-hazard scenarios involving earthquakes, debris flow, debris flood, and soil subsidence. Stakeholders and decision-makers can use the proposed MH-RVS methodology to assess the perceived vulnerability of RC buildings in the Indian Himalayan region and devise timely strategies for structural strengthening and risk mitigation.

关键词： Indian Himalayan region MH-RVS Multi-hazard rapid visual screening Reinforced concrete buildings Vulnerability assessment

来源：评论

学校读者我要写书评

暂无评论

Enhancing seismic assessment and risk management of buildings: A neural network-based rapid visual screening method development

引用

ENGINEERING STRUCTURES 2024年 304卷

作者： Bektas, Nurullah Kegyes-Brassai, Orsolya Szechenyi Istvan Univ Dept Struct Engn & Geotech H-9026 Gyor Hungary

Some of the existing buildings are designed based on lower design standards or even without considering seismic design standards. Recent earthquakes have further highlighted the vulnerability of these buildings when subjected to severe seismic activity. Consequently, it has become imperative to conduct seismic vulnerability assessments of the existing building stock. Therefore, the assessment of the existing building stock is required through the utilization of rapid visual screening (RVS) methods. However, the existing conventional RVS methods used in seismic building assessments have shown limited accuracy. Furthermore, because these methods were developed based on expert opinions and/or due to access limitations to detailed assessment-based generated data used for their development, further enhancing them is challenging. To address these limitations, a new RVS method, which leverages Neural Networks (NN) and building-specific parameters, for reinforced concrete, adobe mud, bamboo, brick, stone, and timber buildings has been proposed in this study. Unlike conventional methods that rely on site seismicity class, the developed data-driven approach incorporates building-specific parameters such as the fundamental structural period and building spectral acceleration. The developed RVS method is specifically tailored to analyze diverse types of buildings in regions with varying seismicity risks, all in preparation for an impending earthquake. In this study, the developed RVS method demonstrated a promising 68% test accuracy, effectively representing the building performance against earthquakes. These findings illustrate the potential of the developed NN based RVS method in assessing existing buildings, thereby mitigating potential loss of life and property during imminent earthquake and alleviating the associated economic burden. Furthermore, this study introduces a new RVS method that can pave the way for future advancements in the field of seismic vulnerability asses

关键词： Earthquake Building vulnerability rapid visual screening Existing buildings Neural networks

来源：评论

学校读者我要写书评

暂无评论

EZRVS: An AI-Based Web Application to Significantly Enhance Seismic rapid visual screening of Buildings

引用

JOURNAL OF EARTHQUAKE ENGINEERING 2024年第3期28卷 689-706页

作者： Saadati, Davood Moghadam, A. S. Int Inst Earthquake Engn & Sesismol IIEES Tehran Iran Int Inst Earthquake Engn & Seismol IIEES Struct Engn Res Ctr Tehran Iran

The buildings' damages due to the recent worldwide earthquakes have highlighted the vulnerability of the existing constructions and the significance of seismic retrofitting. Many of the currently operational buildings need further evaluation to minimize seismic damage and improve performance. Precise and comprehensive building evaluation would not be feasible due to the great expenditure it requires, which is why rapid visual screening (RVS) techniques are to be used to predict the level of seismic damage to the buildings that should have otherwise been evaluated using accurate assessments. Pre-earthquake building screening is thus carried out to identify the buildings with high seismic vulnerability and prioritize those that require more accurate analysis. The present study takes advantage of FEMA-154 and an artificial neural network model with a noticeable accuracy of 83% to predict the level of damage to reinforced concrete buildings and is the first to consider the two parameters of potential earthquake magnitude and the distance of the building from the earthquake epicenter. A web-based, responsive, and platform-independent application called EZRVS (available at http://***/) has been developed that implemented the proposed methodology.

关键词： EZRVS rapid visual screening reinforced concrete structures artificial neural network FEMA-154 earthquake safety assessment

来源：评论

学校读者我要写书评

暂无评论

RiskSchools: a prioritization-based system for the risk assessment of school buildings combining rapid visual screening smartphone app and detailed vulnerability analysis

引用

BULLETIN OF EARTHQUAKE ENGINEERING 2024年第6期22卷 2951-2980页

作者： Karafagka, Stella Riga, Evi Oikonomou, George Karatzetzou, Anna Fotopoulou, Stavroula Pitilakis, Dimitris Pitilakis, Kyriazis Aristotle Univ Thessaloniki Dept Civil Engn POB 424 Thessaloniki 54124 Greece

A multi-purpose and multi-scale tool for the seismic vulnerability and risk classification of critical buildings, such as schools, is proposed for pre- and post-event decision-making to mitigate the risk and reduce losses. The herein proposed "RiskSchools" system, is capable of performing the seismic risk assessment and grading of school buildings at various scales (district, municipality, region etc.), using (a) a pre-seismic rapid visual screening and grading of the school buildings in different vulnerability-risk classes and (b) a seismic risk assessment of the school buildings population, applying probabilistic or scenario-based methods for the seismic hazard and analytical methods for the vulnerability and risk assessment, also leading to a grading of the buildings' risk. The results of the two approaches are compared and combined through a flexible and adaptable expert elicitation scheme to provide a final classification of the seismic risk of the school buildings in the scale of interest and a prioritization scheme with respect to the need for seismic upgrade and retrofitting. The RiskSchools system consists of a powerful, state-of-the-art, user-friendly, and easy-to-use smartphone application for the compilation of the inventory and the rapid visual screening, and a project-dedicated multi-purpose webGIS platform for the seismic vulnerability and risk classification of school buildings at any scale. Although it is initially developed and applied to the school building stock of the Region of Central Macedonia in Greece, it has been specifically designed to be easily applied to other regions of Greece and worldwide and adapted to other critical buildings, like health care and hospital buildings. The ultimate scope of the RiskSchools System is to allow for the optimal design of decision-making procedures in support of disaster management to enhance critical buildings resilience.

关键词： rapid visual screening Smartphone app WebGIS platform Seismic vulnerability Hazard maps Risk classification School buildings

来源：评论

学校读者我要写书评

暂无评论

Developing a machine learning-based rapid visual screening method for seismic assessment of existing buildings on a case study data from the 2015 Gorkha, Nepal earthquake

引用

BULLETIN OF EARTHQUAKE ENGINEERING 2024年 1-39页

作者： Bektas, Nurullah Kegyes-Brassai, Orsolya Szechenyi Istvan Univ Dept Struct Engn & Geotech H-9026 Gyor Hungary

Each existing building is required to be assessed before an impending severe earthquake utilizing rapid visual screening (RVS) methods for its seismic safety since many buildings were constructed before seismic standards, without taking into account current regulations, and because they have a limited lifetime and safety based on how they were designed and maintained. Building damage brought on by earthquakes puts lives in danger and causes significant financial losses. Therefore, the fragility of each building needs to be determined and appropriate precautions need to be taken. RVS methods are used when assessing a large building stock since further in-depth vulnerability assessment methods are computationally expensive and costly to examine even one structure in a large building stock. RVS methods could be implemented in existing buildings in order to determine the damage potential that may occur during an impending earthquake and take necessary measures for decreasing the potential hazard. However, the reliability of conventional RVS methods is limited for accurately assessing large building stock. In this study, building inspection data acquired after the 2015 Gorkha, Nepal earthquake is used to train nine different machine learning algorithms (Decision Tree Classifier, Logistic Regression, Light Gradient Boosting Machine Classifier, eXtreme Gradient Boosting Classifier, Gradient Boosting Classifier, Random Forest Classifier, Support Vector Machines, K-Neighbors Classifier, and Cat Boost Classifier), which ultimately led to the development of a reliable RVS method. The post-earthquake building screening data was used to train, validate, and ultimately test the developed model. By incorporating advanced feature engineering techniques, highly sophisticated parameters were introduced into the developed RVS method. These parameters, including the distance to the earthquake source, fundamental structural period, and spectral acceleration, were integrated to enhance t

关键词： Earthquake Existing buildings Vulnerability assessment rapid visual screening Machine learning Damage state

来源：评论

学校读者我要写书评

暂无评论

An improved rapid visual screening method for seismic vulnerability assessment of reinforced concrete buildings in Indian Himalayan region

引用

BULLETIN OF EARTHQUAKE ENGINEERING 2023年第1期21卷 319-347页

作者： Aggarwal, Yati Saha, Sandip Kumar Indian Inst Technol Mandi IIT Mandi Sch Civil & Environm Engn Kamand 175075 Himachal Prades India

This study proposes an improved method for rapid visual screening (RVS) to assess the seismic vulnerability of reinforced concrete (RC) buildings in the hilly region, especially in the northern part of the Indian Himalayan region. Several small towns in the Indian Himalayan region are rapidly expanding their building infrastructure to meet the demand of ever-increasing population and tourists. An extensive survey of the existing buildings in Mandi, which is one of the populous towns of the Himachal Pradesh state in northern India, is carried out to assess the seismic vulnerability of buildings. A total of 573 RC buildings were assessed using existing pre-earthquake RVS guidelines, and critical attributes that are known to be associated with the performance of the buildings under earthquake shaking were noted. It was noticed that there is an inconsistency in counting the number of stories in the hilly buildings when different RVS methods are employed. Therefore, a numerical study is also performed to establish guidelines for counting the number of stories in hilly buildings for their RVS. Further, based on the vulnerable attributes in the buildings of hilly region, an improved RVS method is proposed. It is shown that the proposed method is convenient to use for segregating the RC buildings in the hilly region according to the damage that they are expected to experience.

关键词： Earthquake Hilly buildings rapid visual screening Seismic vulnerability Vulnerability score

来源：评论

学校读者我要写书评

暂无评论

Android application of rapid visual screening for buildings in Indian context

引用

STRUCTURES 2022年 46卷 1823-1836页

作者： Nanda, Radhikesh P. Damarla, Rithwez Nayak, Kumbla Anupa NIT Durgapur Dept Civil Engn Durgapur 713209 India

Computers lessen all the laborious work, specifically by introducing software applications following mobile applications and IoT (Internet of Things) in numerous civil engineering disciplines. Prevention of forfeiture of life and property is becoming the prime agenda, and seismic vulnerability assessment of existing buildings is one of the quickest methods for an earthquake disaster mitigation plan. In this study, an attempt is made to modify the commonly used FEMA rapid visual screening score sheet concerning Indian building typology and the age of the building. Also, to make RVS further rapid an RVS tool named RVS_IND App is developed using the android App, particularly for the seismic performance evaluation of buildings at the visual inspection level. The application reduced the time taken for RVS from 15 to 20 mins per building to <2-3 mins per building and all the building score sheets can be stored during a walk down, apprising the speed of assessment of huge building stock.

关键词： Seismic assessment Android application JAVA rapid visual screening Vulnerability assessment

来源：评论

学校读者我要写书评

暂无评论

A rapid visual screening Procedure to Evaluate Seismic Risk of Non-structural Elements in Critical Facilities 17th

A Rapid Visual Screening Procedure to Evaluate Seismic Risk ...

引用

17th World Conference on Base Seismic Isolation (WCSI)

作者： De Angelis, Alessandra Perrone, Daniele Maddaloni, Giuseppe Pecce, Maria Rosaria Aiello, Maria Antonietta Univ Sannio Benevento Italy Univ Salento Lecce Italy Univ Naples Federico II Naples Italy

ISBN: (纸本)9783031211898;9783031211874;9783031211867

Non-structural elements (NSEs) represent most of the total construction cost of typical buildings. A significant portion of the total losses in recent earthquakes worldwide has been attributed to damage to NSEs, demonstrating the need for the harmonization of the seismic performance of the NSEs and of the seismic force-resisting systems. Unfortunately, lack of research results on the seismic performance of NSEs available in the public domain has, and continues to hamper, the development of efficient performance-based seismic design methods for buildings. Even though recent research continues to develop new and improved seismic design methodologies for NSEs, significant efforts are still required, particularly for existing building for which seismic mitigation detailing for NSEs are generally not adopted. To deal with this issue, and to reduce non-structural related seismic losses in existing buildings, simplified tools, which allow to quantify the seismic risk at which NSEs are prone, should be developed. This paper presents a rapid visual screening procedure useful to perform a large-scale classification of the seismic vulnerability of NSEs installed in critical facilities. The methodology is based on questionnaire forms that are used to calculate a nonstructural index and to identify the most vulnerable NSE category. The methodology has been applied to some case study buildings focusing the attention on critical facilities.

关键词： rapid visual screening Non-structural elements Critical facilities Seismic risk

来源：评论

学校读者我要写书评

暂无评论

rapid visual screening of soft-story buildings from street view images using deep learning classification

引用

Earthquake Engineering and Engineering Vibration 2020年第4期19卷 827-838页

作者： Qian Yu Chaofeng Wang Frank McKenna Stella XYu Ertugrul Taciroglu Barbaros Cetiner Kincho HLaw International Computer Science Institute University of CaliforniaBerkeleyCAUSA Department of Civil and Environmental Engineering University of CaliforniaBerkeleyCAUSA Civil and Environmental Engineering University of CaliforniaLos AngelesCAUSA Civil and Environmental Engineering Stanford UniversityCAUSA

rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthquakes. Identifying and retrofitting buildings with such irregularities—generally termed as soft-story buildings—is, therefore, vital in earthquake preparedness and loss mitigation efforts. Soft-story building identification through conventional means is a labor-intensive and time-consuming process. In this study, an automated procedure was devised based on deep learning techniques for identifying soft-story buildings from street-view images at a regional scale. A database containing a large number of building images and a semi-automated image labeling approach that effectively annotates new database entries was developed for developing the deep learning model. Extensive computational experiments were carried out to examine the effectiveness of the proposed procedure, and to gain insights into automated soft-story building identification.

关键词： soft-story building deep learning CNN rapid visual screening street view image

来源：评论

学校读者我要写书评

暂无评论

rapid visual screening method for vertically irregular buildings based on Seismic Vulnerability Indicator

引用

INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2021年 54卷

作者： Ishack, Suhail Bhattacharya, Shankha Pratim Maity, Damodar Indian Inst Technol Dept Civil Engn Kharagpur 721302 W Bengal India Indian Inst Technol Dept Architecture & Reg Planning Kharagpur 721302 W Bengal India

Seismic vulnerability assessment of a large group of buildings can prove to be extremely difficult as it requires huge amount of time and resources. rapid visual screening (RVS) alleviates this problem by classifying buildings into different classes of vulnerability thereby limiting the need for detailed analysis only to a few selected vulnerability classes. RVS survey of five G+1 houses were conducted using Arya et al. method, Sinha et al. method, Jain et al. method, FEMA Level 1 and FEMA Level 2 method. The lack of details regarding irregularities resulted in the same RVS score for buildings with significantly different configurations. This renders the RVS procedure difficult to be used for comparison. This paper provides a qualitative comparison of seismic vulner-ability among vertically irregular buildings in terms of mass, geometric and stiffness irregularity through rapid visual screening. 3D Response spectrum analysis of reinforced concrete buildings have been done using STAAD Pro software and Seismic Vulnerability Indicator (SVI) values are calculated for comparison of seismic vulner-abilities with respect to vertical irregularities. Mass irregularity near the mid height of building or stiffness ir-regularity below the mid height of building is found to be more critical among the possible locations of irregularity. Elevation asymmetry above mid height is found to decrease the seismic vulnerability of a building. Presence of stiffness irregularity is found to be significantly more critical than mass or geometric irregularity.

关键词： Seismic vulnerability rapid visual screening Vertical irregularity Seismic vulnerability indicator

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：