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The objective of this document is to present the outcomes of Task 4.3, titled “Development and testing of real-time damage detection tools for physical components”, developed within Work Package WP4 of TURNkey project. The main aim of Task 4.3 is the development of real-time algorithms for automated damage detection, through the use of signal analysis techniques to compute variations in the dynamic properties of buildings due to damage. It is worth mentioning that in this report “real-time” refers to a timeframe in the immediate aftermath of an earthquake. Indeed, by the terminology real-time, damage detection within minutes after the event is adopted, which remains in line with the concept of rapid response to earthquakes. Therefore, the more appropriate expression is “near real-time”, adopted hereinafter. In this Deliverable, we develop and test the algorithms that will be ready for an implementation in a near-real time context.

The paper presents the seismic monitoring network of the TURNKey Project (Towards more Earthquake-resilient Urban Societies through a Multi-sensor-based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response Actions) in Bucharest. TURNkey aims to contribute to the mitigation of earthquake risks through European and global scientific collaborations. To reach its objectives the project brings together a strong multidisciplinary team of experts (geophysicists/seismologists, geologists, engineers, disaster risk managers and sociologists) from 21 partner institutions covering 10 European countries. “Testbed 1” (Bucharest) is described in the paper, with its five monitored locations and the deployed seismic sensors and GNSS. The choice of monitored buildings is based upon the characteristics of the design code used in their construction. The paper considers the possible influence of local conditions at the sites of the monitored buildings.

Deliverable from WP3 of TURNkey project

This report details the procedures that have been applied, developed or improved in Task 3.4 for the rapid generation of ground shaking maps (i.e., shake-maps). The report revolves around several actions and technical results, which are organized as follows:  Section 3 summarizes the state-of-the-art of current shake-map algorithms and systems, based on a review by Guérin-Marthe et al. (2021). The USGS ShakeMap v4 approach is compared to a method based on Bayesian updating, which is put forward as one of the technical solutions to be implemented in the TURNkey platform.  Section 4 is based on previous work carried out in Task 3.3.2: in each TB, various GMMs (Ground-Motion Models) are evaluated and ranked, via different scoring metrics. The selected GMMs may then be used for the generation of shake-maps in each TB.  Section 5 details novel research efforts, where the GMM coefficients are updated in order to match the observations. This approach is useful to rapidly update a GMM in a given area for a given earthquake, so that the updated GMM may be reused for subsequent events (e.g., in a seismic sequence) in order to improve the accuracy of ground-shaking estimates. Two parallel and complementary methods are presented, namely a direct calibration of the coefficients (EUC) and a Bayesian updating of the uncertain coefficients in the shake-map (BRGM).  Section 6 discusses site amplification models that are available in each TB: besides local models, Vs30 maps generated at the European level (in the European project SERA) are extracted for each TB. Recommendations are given for each TB on which model should be applied, and whether the SERA model represents a satisfying approximation.  Section 7 explores additional sources of observations that may be used to characterise shake-maps: collection and aggregation of felt reports by EMSC; and extraction of Twitter data and integration as soft evidence in the shake-maps by BRGM. The Bayesian approach for the derivation of shake-maps has been implemented in a Python code, which is briefly described in the companion deliverable report D3.9.

The TURNkey concept model is being developed over three cycles of participatory action research (PAR). This report describes the process and findings of the 2nd PAR cycle in the TURNkey project. In light of these findings, the report reviews the end-user use cases that were developed for TURNkey during the 1st PAR cycle (which have been reported in D2.6) and revises them in light of the discussions with end-users and TURNkey scientists, engineers and software developers that occurred during the 2nd PAR cycle. The report lays the foundation for the 3rd and final round of PAR that will be conducted for TURNkey. It will also inform TURNkey deliverable D7.7, which will provide end-users with an (exemplar) model Business Continuity and Resilience Plan (BCRP) and Disaster Management Plan (DMP) framework for integrating the TURNkey FWCR platform into their disaster management planning process. This report provides the following: Review of the key lessons from the 1st PAR Cycle Online workshops with potential end-users using a virtual demonstrator (process and findings) SWOT analysis with TURNkey scientists and engineers (process and findings) TURNkey application workshop around a hypothetical hospital scenario (process and findings) Consortium-wide reflection on findings from the 2nd PAR Cycle (process and findings) Revised end-user use cases Revised table of TURNkey features, what end-users want vs what is possible and in scope A revised version of the FWCR concept model A conclusion and next steps, This report is intended as an internal working report for use by members of the TURNkey project in the development of the TURNkey FWCR platform. The report should be considered as a work in progress which will be amended and modified throughout the TURNkey project to reflect emerging issues identified through the 3rd PAR cycle.

Exposure means people, property, systems, or other elements present in hazard zones that are thereby subject to potential losses. Present research analyses the human exposure at one of the most dangerous earthquake zones in Bulgaria-Blagoevgrad region as one of the main parameters of the seismic risk. Seismic hazard is modelled using GIS and overlaid with one square kilometre grid of population distribution in order to determine the population exposure. We define a parameter called “population exposure index” (PEI) which has five classes: Minor, Low, Moderate, High and Major. As was expected, the seismic hazard levels of Blagoevgrad region are in the upper part of the classification scale. The Krupnik- Kresna area is fully covered with the highest 5th level and the remaining part falls within the interval limits of level 4. The total population in the Blagoevgrad region (NUTS II) is around 138 000 people. Results show that more than 45 000 people are exposed to the highest level of seismic hazard. More than 50 settlements (towns and villages) are classified with Major (5) PEI., Proceeding of 1st International Conference on Environmental Protection and Disaster RISKs, 2020, p. 353-360

The Near Real-Time System for Estimating the Seismic Damage in Romania, implemented in 2012 at the National Institute for Earth Physics, is one of the automated systems that can directly contribute to saving many lives right after a major earthquake, by translating earthquake parameters into damage probabilities for different areas within Romanian counties and showing emergency intervention necessities, and can also lead to mitigation actions before an earthquake, through raising awareness and highlighting vulnerable aspects of the building stock and economic and social impacts. This paper aims to present the scientific background of this constantly upgrading system, and to show different results for relevant scenarios, for intermediate-depth Vrancea earthquakes and other crustal earthquakes. Several important questions are tried to be answered, like: “How credible are the estimated losses?”, “What are the most vulnerable aspects?” or “How can the damage maps be useful for authorities?”. Currently, the system uses for building loss estimation the analytical methods (as the Improved-Displacement Capacity Method - I-DCM) implemented within the open-source software SELENA (SEismic Loss EstimatioN using a logic tree Approach), together with HAZUS methods for estimating the human casualties. The building stock is defined through 48 different capacity and fragility curves, depending on construction material, height and age. As hazard data, PGA and SA values obtained through the ShakeMap System and based on real recordings and attenuation relations are used. The area currently analyzed by the system consists of 19 Romanian Counties, capital Bucharest and 9 regions in northern Bulgaria; resolution of the data is at administrative unit (commune or city) level. We aim to provide an insight of each part of this system, justify the choices made and also discuss the improvement possibilities.