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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Built Environ. | doi: 10.3389/fbuil.2019.00095

Use of the knowledge-based system LOG-IDEAH to assess failure modes of masonry buildings, damaged by L’Aquila earthquake in 2009.

  • 1Faculty of Engineering, University of Bristol, United Kingdom
  • 2University College London, United Kingdom

This article, first, discusses the decision-making process, typically used by trained engineers to assess failure modes of masonry buildings, and then, presents the rule-based model, required to build a knowledge-based system for post-earthquake damage assessment. The acquisition of the engineering knowledge and implementation of the rule-based model lead to the developments of the knowledge-based system LOG-IDEAH (Logic trees for Identification of Damage due to Earthquakes for Architectural Heritage), a web-based tool, which assesses failure modes of masonry buildings by interpreting both crack pattern and damage severity, recorded on site by visual inspection. Assuming that failure modes detected by trained engineers for a sample of buildings are the correct ones, these are used to validate the predictions made by LOG-IDEAH. Prediction robustness of the proposed system is carried out by computing Precision and Recall measures for failure modes, predicted for a set of buildings selected in the city centre of L’Aquila (Italy), damaged by an earthquake in 2009. To provide an independent meaning of verification for LOG-IDEAH, random generations of outputs are created to obtain baselines of failure modes for the same case study. For the baseline output to be compatible and consistent with the observations on site, failure modes are randomly generated with the same probability of occurrence as observed for the building samples inspected in the city centre of L’Aquila. The comparison between Precision and Recall measures, calculated on the output, provided by LOG-IDEAH and predicted by random generations, underlines that the proposed knowledge-based system has a high ability to predict failure modes of masonry buildings, and has the potential to support surveyors in post-earthquake assessments.

Keywords: Knowledge-based system (KBS), Masonry buildings, seismic damage, Failure modes, Post-earthquake assessment

Received: 05 Apr 2019; Accepted: 02 Jul 2019.

Edited by:

Andrea Belleri, University of Bergamo, Italy

Reviewed by:

Antonio Formisano, University of Naples Federico II, Italy
Francesco Fabbrocino, Pegaso University, Italy
Maria Rosa Valluzzi, University of Padova, Italy  

Copyright: © 2019 Novelli and D'Ayala. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Viviana I. Novelli, Faculty of Engineering, University of Bristol, Bristol, BS8 1TR, England, United Kingdom, viviana.novelli@bristol.ac.uk