Measuring Instantaneous Resilience of a Highway Bridge Subjected to Earthquake Events

Bridges in a road network play a significant role in supporting the flows of people, goods, and freight during an earthquake event and are expected to maintain their functionality following the event. Thus, measuring the capability of a bridge immediately following an earthquake event is critical for understanding the post-earthquake functionalities of transportation networks and supply chain systems involving highway bridges. To this end, this paper proposes a new metric for measuring the resistant capacity of a highway immediately following an earthquake event, which is here called instantaneous resilience. The proposed metric first compares the reliability indices of a bridge before and following an earthquake event to measure the immediate earthquake impact. Although this comparison (i.e., robustness measure in this paper) indicates the remaining strength of the bridge subjected to a given earthquake event, it does not reflect collapse failure modes appropriately. Therefore, the proposed instantaneous-resilience metric combines the robustness measure with the structural redundancy measure to consider various scenarios of load path distribution. The proposed metric is computationally efficient because, in the process, it utilizes a generalized reliability-intensity (R-I) surface of a bridge which can be used to calculate the pre- and post-earthquake reliabilities of any bridge designed based on the American Association of State Highway and Transportation Officials (AASHTO) load and resistance factor design (LRFD). Without developing bridge-specific fragility curves and performing structural analysis of a bridge, the proposed measure enables engineers to make a preliminary assessment of the immediate impact of the earthquake on bridges on a quantitative basis. The step-by-step calculation process of the proposed instantaneous-resilience of a bridge is presented, and its potential use in highway network performance assessment is illustrated with a simple hypothetical network system.

Parametric and non-parametric estimation of extreme earthquake event: the joint tail inference for mainshocks and aftershocks

In an earthquake event, the combination of a strong mainshock and damaging aftershocks is often the cause of severe structural damages and/or high death tolls. The objective of this paper is to provide estimation for the probability of such extreme events where the mainshock and the largest aftershocks exceed certain thresholds. Two approaches are illustrated and compared – a parametric approach based on previously observed stochastic laws in earthquake data, and a non-parametric approach based on bivariate extreme value theory. We analyze the earthquake data from the North Anatolian Fault Zone (NAFZ) in Turkey during 1965–2018 and show that the two approaches provide unifying results.

On-Site Earthquake Early Warning Using Smartphones

In this study, the measured accelerations of a single smartphone were used to provide an earthquake early warning system. In the presented system, after the smartphone is triggered, the triggering event is then classified as an earthquake event or not. Once an earthquake event is detected, the peak ground acceleration is then predicted every second until 10 s after the trigger. These predictions are made by the neural network classifier and predictor embedded in the smartphone, and an alert can be issued if a large peak ground acceleration is predicted. The proposed system is unique among approaches that use crowdsourcing ideas for earthquake early warning because the proposed system provides on-site earthquake early warning. In general, the accuracy rates of the earthquake classifications and peak ground acceleration predictions of the system were quite high according to the results of large amounts of earthquake and non-earthquake data. More specifically, according to said earthquake data, 96.9% of the issued alerts would be correct and 61.9% of the earthquakes that exceeded the threshold would have resulted in an alert being issued before the arrival of the peak ground acceleration. Among the false negative cases, approximate 97.8% would occur because of negative lead time. Using the shake table tests of worldwide and Meinong earthquake datasets, the proposed approach is confirmed to be quite promising.

Emergency shelter selection in the context of seismic risk. Case study – Bucharest, Romania

<p>Big cities are prone to suffer important losses, both economic and human, in case of a risk occurrence. Bucharest is the most vulnerable European capital to earthquakes due to its exposure, being located about 130 km from the main seismic region of the country – Vrancea Region, and also due to its high physical and social vulnerability.</p><p>Based on the past experiences and on the present development of the city, there is an urge to find and to develop measures and policies for seismic risk mitigation. The first step in this direction, which is also the aim of the present work, is to assess the current situation regarding the vulnerability of the city and to understand the dimension of the losses throughout the city in case of a major earthquake event.</p><p>In this study we discuss the best locations to deploy shelters which can provide first-aid and temporary residence for those who lost their homes after an earthquake event. Our research is based on estimating the losses at a detailed scale and by knowing the limitations of the infrastructure (including emergency hospitals and roads) and of the public services (like the firefighters, ambulances, police, medical care etc.).</p><p>Social, economic and housing quality criteria were integrated in a multicriteria analysis in order to assess the most vulnerability hotspots at city level and to estimate losses. The results showed the presence of two extended areas, situated in the south-west and the western part of the city, with high vulnerability scores and high potential losses. These two areas were introduced into a new multicriteria analysis for finding suitable locations that can be used as indoor and outdoor shelters.</p><p>Our study is a step forward to increase the preparedness of the population, that will know where to go in case of need. It will also help the authorities that will better allocate their resources and overall mitigate the seismic risk.</p>