The main developments of Seismology and Earthquake Engineering since the early 1700s and the new challenges for a sustainable society

Oliveira, Carlos Sousa

doi:10.1007/s10518-022-01440-w

Cited by 7 publications

(6 citation statements)

References 129 publications

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“…As a final point, we stress the importance of knowing the position of the observer in order to correctly assign macroseismic intensity, since ground motion frequencies and building resonance can influence any diagnostic effect (Oliveira, 2022), including earthquake perception. To give an application example, we recall that EMS (Gru¨nthal, 1998) recommends neglecting observer reports above the fifth floor (interpreted as fifth above the ground floor by Bru¨stle et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…This is because it includes a heterogeneous set of effects, ranging from people’s perceptions to the consequences of shaking on objects and buildings. These diagnostics have different characteristics (Brüstle et al, 2020; Lesueur et al, 2013; Oliveira, 2022; Sbarra et al, 2020), causing macroseismic intensity to be an average measure with little sensitivity to different aspects of ground motion. Instead, studying the distribution and intensity of a single effect provides more detailed information.…”

Section: Introductionmentioning

confidence: 99%

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Earthquake perception data highlight natural frequency details of Italian buildings

2023

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As the distance from an earthquake increases, the percentage of people who do not feel it also increases. The average transition distance between “felt” and “not felt” reports is mainly determined by the magnitude and depth of the earthquake, but it also depends on the observation floor and building height. Buildings act as resonators and can amplify the shaking at specific frequencies. We analyzed over 286,000 crowdsourced reports to study the effect of floor and building height on earthquake perception. We found that, compared to average values, there is an increase in the percentage of “felt” reports on the highest floors and a decrease in the lowest floors of buildings of all heights. We determined the range within which an observer is likely to feel an earthquake (perception boundary) and examined how it varies with magnitude. We found that as the building height increases, people on higher floors perceive medium to high magnitude earthquakes progressively better than lower magnitude ones. We compared the perception boundary with a model of seismic response spectra to estimate the vibration frequency perceived by observers on each floor/building height combination. Our results show that the value of the fundamental period increases with building height for the top floor, and that higher vibration modes become more evident for buildings with more than 6 stories. In addition, we observed that the height of the building also affects the vibration of the basement, with the frequency tending to decrease as the building height increases. Concerning macroseismic intensity estimation, we show that in tall buildings, observations made on both the upper and lower floors must be considered outside the normal range, and that earthquake perception also changes as a function of magnitude and distance, pointing out the importance of collecting an adequate number of observations to sample different locations of observers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Earthquake perception data highlight natural frequency details of Italian buildings

2023

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“…Fortifying and renovating rural Chinese brick homes lowers earthquake risk (Oliveira, 2022). Bracing, foundation reinforcement, and seismically resistant materials reduce structure sensitivity (Furtado, 2020).…”

Section: Seismic Risk Mitigation In Rural Chinamentioning

confidence: 99%

Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry

Kong,

Petchsasithon

2024

J INFORM SYSTEMS ENG

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Using a novel methodology that integrates incremental dynamic analysis (IDA) and unmanned aerial vehicle positioning (POS) analysis, this study aims to assess the seismic risk of brick structures in rural China. This method can collect a lot of data and accurately anticipate seismic damage by combining UAV oblique photography with IDA analysis. Because rural China has many masonry structures, the project will design unique seismic risk mitigation strategies. High-resolution cameras on Unmanned Aerial Vehicles capture realistic photographs of rural brick buildings. The collected data is carefully examined to reveal architectural and structural elements. The project uses dynamic post-processing software from the CHC Geomatics Office to improve UAV-reference station position accuracy. This program analyzes UAV POS data disparities. The findings allow rural Chinese brick buildings to be assessed for seismic sensitivity during unexpected ground shaking occurrences. UAV tilt-photography reduces manpower and expenditures, improving inquiry efficiency. This combination improves seismic risk response. The IDA and UAV POS analysis are essential for earthquake preparedness and risk mitigation. This data-driven method informs lawmakers, urban planners, and disaster management authorities worldwide, improving earthquake engineering and catastrophe resilience programs. This work improves seismic threat assessment and masonry structure fortification, making earthquake-prone buildings safer. Thus, rural communities benefit from it.

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“…Particularly in the era since the commencement of the 21st century, the advancement of the second generation of performance-based seismic engineering has notably elevated the seismic resistance of architectural structures on an international scale [1]. However, in comparison to other fields, despite the industrialized nature of structural seismic design and post-earthquake assessment engineering, the level of mechanization, automation, intellectualization, and incorporation of information technology within infrastructure has remained relatively underdeveloped [2,3].…”

Section: Introductionmentioning

confidence: 99%

Applying Machine Learning to Earthquake Engineering: A Scientometric Analysis of World Research

Hu,

Wang,

et al. 2024

Buildings

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Machine Learning (ML) has developed rapidly in recent years, achieving exciting advancements in applications such as data mining, computer vision, natural language processing, data feature extraction, and prediction. ML methods are increasingly being utilized in various aspects of seismic engineering, such as predicting the performance of various construction materials, monitoring the health of building structures or components, forecasting their seismic resistance, predicting potential earthquakes or aftershocks, and evaluating the residual performance of post-earthquake damaged buildings. This study conducts a scientometric-based review on the application of machine learning in seismic engineering. The Scopus database was selected for the data search and retrieval. During the data analysis, the sources of publications relevant to machine learning applications in seismic engineering, relevant keywords, influential authors based on publication count, and significant articles based on citation count were identified. The sources, keywords, and publications in the literature were analyzed and scientifically visualized using the VOSviewer software tool. The analysis results will help researchers understand the trending and latest research topics in the related field, facilitate collaboration among researchers, and promote the exchange of innovative ideas and methods.

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The main developments of Seismology and Earthquake Engineering since the early 1700s and the new challenges for a sustainable society

Cited by 7 publications

References 129 publications

Earthquake perception data highlight natural frequency details of Italian buildings

Earthquake perception data highlight natural frequency details of Italian buildings

Information Acquisition and Seismic Damage Prediction of Masonry Structures in Rural Areas Based on UAV Inclined Photogrammetry

Applying Machine Learning to Earthquake Engineering: A Scientometric Analysis of World Research

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