Estimation of Seismic Economic Loss and Downtime of Precast Concrete Frames with “Dry” Connections

The seismic loss of buildings comes not only from the damaged structural components. Much more loss may be induced by non-structural components, the demolition loss and social impacts associated with excessive downtime. One of the main characteristics of a resilient city is that the buildings in the city should be able to recover to their pre-earthquake functionalities with minimized economic loss and downtime. For this purpose, a comparative study regarding seismic economic loss and downtime is conducted between the conventional cast-in-situ reinforced concrete frames (RCFs) and precast concrete frames (PCFs) with "dry" connections. The results show that the PCFs with prestressed tendons (PTs) can effectively reduce demolition loss given their extraordinary self-centering capacity provided by PTs. By adding web friction devices at the beam ends, the economic loss of structural components and drift-sensitive non-structural components can be effectively reduced. The downtime of PCFs is reduced at given hazard levels compared with RCF given their rapid repair speed and easy assemblage. In view of the rapid post-earthquake repair and lower earthquake loss, the PCFs are worth further investigation and application to develop resilient cities.

Toward a uniform earthquake loss model across Central America

This study presents a probabilistic earthquake loss model for Central America, which is used to evaluate the indicators of the Sendai Framework for Disaster Risk Reduction (SFDRR). The exposure, vulnerability, and hazard components of the model were established using a uniform methodology for all the countries. Earthquake risk is expressed according to three indicators: mortality (A-1), population affected (B-1), and economic losses (C-1). Exposure results indicate that over 9.1 million structures (with an economic value of US$635 billion) are exposed to seismic hazard in the region. The risk results indicate an average annual human loss of 0.7 fatalities per 100,000 inhabitants, an average number of 35 people affected per 100,000 inhabitants, and an average annual economic loss of US$990 million. This represents 0.43% and 0.16% of the regional gross domestic product (GDP) and total replacement value, respectively. Guatemala, Nicaragua, and El Salvador present the highest risk, contributing with 75% of the absolute economic losses and 84% of the average annual fatalities in the region.

Rapid earthquake loss assessment based on machine learning and representative sampling

This article proposes a new framework for rapid earthquake loss assessment based on a machine learning damage classification model and a representative sampling algorithm. A random forest classification model predicts a damage probability distribution that, combined with an expert-defined repair cost matrix, enables the calculation of the expected repair costs for each building and, in aggregate, of direct losses in the earthquake-affected area. The proposed building representation does not include explicit information about the earthquake and the soil type. Instead, such information is implicitly contained in the spatial distribution of damage. To capture this distribution, a sampling algorithm, based on K-means clustering, is used to select a minimal number of buildings that represent the area of interest in terms of its seismic risk, independently of future earthquakes. To observe damage states in the representative set after an earthquake, the proposed framework utilizes a local network of trained damage assessors. The model is updated after each damage observation cycle, thus increasing the accuracy of the current loss assessment. The proposed framework is exemplified using the 2010 Kraljevo, Serbia earthquake dataset.

Earthquake Damage Repair Loss Estimation in New Zealand: What Other Variables Are Essential Based on Experts’ Opinions?

Major earthquakes can cause extensive damage to buildings and alter both the natural and built environments. Accurately estimating the financial impact from these events is complex, and the damage is not always visible to the naked eye. PACT, SLAT, and HAZUS are some of the computer-based tools designed to predict probable damage before an earthquake. However, there are no identifiable models built for post-earthquake use. This paper focuses on verifying the significance and usage of variables that specifically need to be considered for the post-earthquake cost estimation of earthquake damage repair work (CEEDRW). The research was conducted using a questionnaire survey involving 92 participants who have experience in cost estimating earthquake damage repair work in New Zealand. The Weighted Average, Relative Importance Index (RII), and Exploratory Factor Analysis were used to analyse the data. The research verified that eleven major variables that are significant to the CEEDRW and should be incorporated to cost estimation models. Verified variables can be used to develop a post-earthquake repair cost estimation tool and can be used to improve the pre-earthquake loss prediction tools.

Comparing Short-Term Seismic and COVID-19 Fatality Risks in Italy

Risks assessment and risks comparison are basic concepts for emergency management. In the fields of earthquake engineering and engineering seismology, the operational earthquake loss forecasting (OELF) is the research frontier for the assessment of short-term seismic risk. It combines seismicity models, continuously updated based on ground-motion monitoring (i.e., operational earthquake forecasting), with large-scale vulnerability models for the built environment and exposure data. With the aim of contributing to the discussion about capabilities and limitations of OELF, the study presented aims at comparing the OELF results and the fatality risk (based on fatality data) related to coronavirus 2019 (COVID-19) that, at the time of writing, is perceived as very relevant and required unprecedented risk reduction measures in several countries, most notably Italy. Results show that, at a national scale in Italy, the COVID-19 risk has been higher than the seismic risk during the two pandemic waves even if, at the end of the so-called lockdown, the evolution of the pandemic suggested the possibility (not realized) of reaching a situation of comparable seismic and COVID-19 risks in a few weeks. Because the two risks vary at a local scale, risks comparison was also carried out on a regional basis, showing that, before the beginning of the second wave, in some cases, the seismic risk, as assessed by means of OELF, was larger than the pandemic one.