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Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.

The present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.

The results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.

The objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.

This paper aims to develop an efficient algorithm combining straightforward response surface functions with Monte Carlo simulation to conduct seismic reliability analysis in a systematical way.

The representative slip surfaces are identified and based on to calibrate multiple response surface functions with acceptable accuracy. The calibrated response surfaces are used to determine the yield acceleration in Newmark sliding displacement analysis. Then, the displacement-based limit state function is adopted to conduct seismic reliability analysis.

The calibrated response surface functions have fairly good accuracy in predicting the yield acceleration in Newmark sliding displacement analysis. The seismic reliability is influenced by such factors as PGA, spatial variability and threshold value. The proposed methodology serves as an effective tool for geotechnical practitioners.

The multiple sources of a seismic slope response can be effectively determined using the multiple response surface functions, which are easily implemented within geotechnical engineering.

The ways communities have regarded disasters and natural hazards in the cultural sphere can provide a lens to inform the understanding of their ability to withstand shocks and the factors that led to such conditions. Only by tracing the complexities of creating, transmitting and preserving a culture of preparedness among disaster-vulnerable communities can researchers and practitioners claim to be working toward policy that is informed by the communities’ own experience and design policy or programming on their behalf.

In efforts to prevent, respond to and recover from disasters, what alternatives are available to top-down strategies for imposing expert knowledge on lay publics? How is the context of communities’ socioecological context understood in the development of programs and policy on their behalf? What can be learned from community narratives and cultural practices to inform disaster risk reduction?

I collected examples of how different communities perceive, prevent and respond to disaster through art, music and literature and analyzed how these were embedded into local narratives and how historical context influenced such approaches. My findings show that communities use cultural practices to contextualize experiences of hazards into their collective narrative; that is, storytelling and commemoration make disasters comprehensible. By incorporating such findings into existing policies and programs, institutions may be able to more effectively apply them to affected communities or build new ones around their actual needs and experiences.

By framing disasters as an anthropological inquiry, practitioners can better recognize the influence of a place’s nuance in the disaster management canon–guided by these details, not despite them.

The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.

In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.

The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.

The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

This study aims to improve the rules and regulations system of high-speed rail emergency disposal.

Based on the analysis of the demands, rules and regulations of China concerning on-site high-speed rail emergency disposal, basic principles for revising the regulations on railway technical management (RRTM) are proposed and suggestions and evaluation methods according to the main clauses are put forward.

Basic principles for revising the RRTM are proposed, namely “to meet the actual needs of on-site high-speed railway emergency disposal, standardize the emergency disposal process, improve the efficiency of emergency disposal and keep the consistency between provisions of emergency disposal”. Existing provisions related to emergency disposal efficiency, scenarios, safety and service quality are made up for the deficiencies. To make up for the deficiencies of the existing provisions related to emergency disposal efficiency, improvement of emergency disposal scenarios and guarantee of emergency disposal safety and quality, this paper puts forward suggestions on revising 15 emergency disposal provisions of the RRTM with regard to earthquake monitoring and warning, in-station foreign body invasion warning, air conditioning failure of EMU trains and forced parking of trains in sections. A fuzzy comprehensive evaluation model based on the analytic hierarchy process (AHP) is constructed to evaluate the proposed revision scheme and suggestions, which has been highly recognized by experts.

This study implements the goal of high-quality railway development.

This paper examines what facilitates the swift reconfiguration of freight movements across transport modes in the wake of a major disaster.

A qualitative research approach focussing on the New Zealand (NZ) domestic freight transport operations in the wake of the 2016 Kaikōura earthquake is used with data collected through 19 interviews with 27 informants. The interviews are thematically analysed by using the framework method.

The paper provides rich and detailed descriptions of the ability of a freight transport system to recover from a disaster through rapid modal shifts. This paper identifies nine factors enabling modular transport operations and highlights the critical role of physical, digital, operational and inter-organisational interconnectivity in the aftermath of a disaster.

Although the management of freight disruptions has become a prevalent topic not only in industry and policy-making circles, but also in the academic literature, qualitative research focussing on the ability of commercial freight systems to adapt and recover from a disaster through rapid modal shifts is limited. This qualitative study sheds light on the mechanisms underlying the continuity of freight operations in the wake of a disaster and provides a comprehensive understanding of modular transport operations and the ability of freight systems to keep goods moving.

In the event of a disaster, educational institutions like schools serve as lifeline buildings. Hence, it is crucial to safeguard these buildings for the communities that may depend on the school as a disaster shelter and aid center. Thus, this paper aims to conduct a multihazard risk assessment survey at 50 schools (with 246 building blocks) in Dehradun.

The past few decades have witnessed the impact of multihazard frequency in Uttarakhand, India, due to the geographical features of the Himalayas and its neo-tectonic mountain-building process. Dehradun is the capital of Uttarakhand state and comes under seismic zone IV, which is highly prone to earthquakes.

The hazard assessment is divided into two types of surveys: first, building-level surveys that include rapid visual screening, nonstructural risk assessment and fire safety audit, and second, campus-level surveys that include vulnerability analysis for earthquake, flood, industrial hazard, landslide and wind.

This paper will list several gaps and unrecognized practices in the region that increase the schools’ multihazard risk. The study’s outcome will help prioritize the planning of disaster awareness, retrofitting execution, future construction practices and decision-making to minimize the risk and prepare the school for the upcoming disasters.

Physical data were collected by the author to determine the multihazard risk analysis in 50 schools in the Dehradun District of Uttarakhand, India. The building- and campus-level surveys have been used to generate a database for the retrofit and renovation process for each individual school to use their budget fruitfully and in a planned way. The survey conducted is more effort and a more detailed risk evaluation which necessitates effectively mitigating and ensuring the potential safety of the region’s schools.

Purpose: The study aims to analyse and discuss the effect of COVID-19 on businesses. The chapter discusses the various machine learning (ML) tools and techniques, which can help in better decision making by businesses in the present world.

Need for the Study: COVID-19 has increased the role of VUCA elements in the business environment, and there is a need to address the challenges faced by businesses in such environment. ML and artificial learning can help businesses in facing such challenges.

Methodology: The focus and approach of the chapter are in the context of using artificial intelligence (AI) and ML techniques for decision making during the COVID-19 pandemic in a VUCA business environment.

Findings: The key findings and their implications emphasise the importance of understanding and implementing AI and ML techniques in business strategies during times of crisis.

Practical Implications: The chapter’s content is in the context of using AI and ML techniques during the COVID-19 pandemic and in a VUCA business environment.