Seismic analysis of slender monumental structures: current strategies and challenges

The preservation and seismic risk mitigation of built cultural heritage is considered today as a major priority in the international political agenda. Among the great variety of heritage structures spread worldwide, masonry towers belong to one of the most vulnerable categories against earthquake actions due to their morphological and material singularity. The proper understanding of the structural behavior of these artefacts at the micro, meso and macro scales, combined with a thorough knowledge of the best analysis practices deriving from the shared experience of the scientific community working in this field, is a fundamental prerequisite to appropriately address their seismic assessment. In this context, the present work offers an extensive discussion on the major challenges that slender monumental towers pose in terms of characterization of their actual behavior under seismic actions. A critical appraisal of the principal analysis methods applicable to the study of these structures is also presented along with a brief review of the existing modelling strategies for their numerical representation. Relevant examples are discussed in support of each argument. In spite of being a relatively young discipline, earthquake engineering has made remarkable progress in the last years and appropriate modi operandi have been consolidating to tackle the seismic assessment of unconventional systems, such as slender heritage structures. The work is conceived in a format of interest for both practitioners and researchers approaching the seismic assessment of this type of structures, and for those in need of an overall practical review of the topic.This work was carried out within the framework of the National Operational Programme on Research and Innovation (Attraction and International Mobility) PON-AIM 2014-2020 Line 2, co-financed by the European Social Fund and by the National Rotation Fund

The importance of structural monitoring as a diagnosis and control tool in the restoration process of heritage structures: A case study in Portugal

The paper discusses the monitoring-based approach unfolded to evaluate the health condition of a heritage structure in Portugal. An extensive experimental campaign, including geometric survey, visual inspections, damage diagnosis, monitoring and control, is carried out to support and evaluate the actions undertaken to re-establish the structural strength. The paper focuses on the analysis of case-specific static and dynamic parameters deemed representative of the structural behaviour and highlights the benefits associated with the implementation of a monitoring-weighed methodology in terms of diagnostics of the system's vulnerabilities as well as control of the effectiveness of the adopted consolidation measures. The results demonstrate the feasibility and suitability of this systematic experimental approach for the non-invasive assessment of the structural fitness of built cultural heritage.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.info:eu-repo/semantics/publishedVersio

Extraction of damage-sensitive eigen-parameters for supervised SHM

Revista ciêntífica: Procedia Engineering, Volume 199, 2017, Pages 2178-2183These last decades have seen an exponential increase in the amount of research related to structural health monitoring (SHM) due to its potential for significant life-safety and economic benefits. However, the success of this powerful tool strongly depends on the implemented damage identification strategy. Reliable and efficient damage identification algorithms enable to detect faults that lie beneath the surface of the structure and to spot system’s vulnerabilities at a very early-stage. This allows to adopt appropriate remedial measures in a timely fashion thereby minimizing the risk of unexpected collapses. The present paper describes a spectrum-driven damage identification method that investigates three levels of damage, i.e. detection, localisation and assessment. Peculiarity of the method is the use of spectral frequency-dependent Eigen-parameters estimated from the response Power Spectral Density (PSD) matrix, which is demonstrated to be very sensitive to damage-induced changes. The approach is detailed, including initial assumptions, scientific formulation of the problem and derivation of the algorithm. Finally, the effectiveness of the method is validated through a numerical simulation and verified on a case-study structure.FEDER funds through the Competitiveness Factors Operational Programme - COMPETE a n d by national funds through FCT – Foundation for Science and Technology within the scope of the project POCI-01 -0145-FEDER-007633.info:eu-repo/semantics/publishedVersio

Damage identification and seismic vulnerability assessment of a historic masonry chimney

The present paper deals with the dynamic characterisation of a historical masonry chimney aimed at identifying the structural damage and assessing its seismic performance. The structure was severely damaged by a lightning accident and in-depth repair works were executed to re-instate its sound configuration. The case study is fully detailed, including the aspects of survey, inspection, diagnosis, and evolution of the dynamic properties of the system throughout the structural intervention. Considering the explicit dependence of the power spectral densities of measured nodal processes on their frequency content, a spectrum-driven algorithm is used to detect and locate the damage. The paper shows that the eigenparameters obtained from the decomposition of the response power spectrum matrix are sensitive to system's changes caused by evolutionary damage scenarios, thereby resulting excellent indicators for assessing both the presence and position of structural vulnerabilities. The results are compared with the ones from other modal-based damage identification methods and the strengths/limitations of the tools currently available in literature are extensively discussed. Finally, based on the crack pattern surveyed before the repair works, the weakest links of the chimney are identified and the most meaningful collapse mechanisms are analysed to verify the seismic capacity of the structure. According to the results of the kinematic analysis, the chimney does withstand the maximum site peak ground acceleration.info:eu-repo/semantics/publishedVersio

HeritageCare: “Prevenir mejor que curar”

El patrimonio histórico construido representa una expresión irremplazable del desarrollo social y de la variedad cultural de la humanidad. Esté protegido o no, sea público o privado, este patrimonio es un recurso fundamental en la formación y consolidación de la identidad cultural, rico en valores intangibles y provisto de una significación atribuida por la propia sociedad que lo usa. Los edificios patrimoniales representan una parte muy significativa del entorno construido, por tanto asegurar su conservación sostenible resulta esencial para el traspaso de este patrimonio a las generaciones futuras

Earthquake-induced damage localization through non-linear dynamic analysis

The development of vibration-based long-term SHM methods for damage detection and preventive conservation of historic masonry buildings is receiving a growing trend of scientific interest. At the state of the art, well-acknowledged techniques for damage detection have been developed and validated, especially when dealing with earthquake-induced damages. The next scientific challenge to deal with in SHM is therefore damage localization, thus, not just detecting the occurrence of a damage, but also inferring, with a certain level of confidence, its location. This paper presents a methodology aimed at addressing the damage localization task in heritage masonry structures, based on Incremental Dynamic Analysis (IDA) carried out from a numerical model together with data recorded during the earthquake. IDA curves are built with reference to different portions of the structure, relating some local damage parameters (DMs) to some seismic or response intensity measures (IMs) and earthquake's intensity is used for locally identifying the damage in such portions. The choice of IM represents an important aspect of the IDA curves effectiveness and an appropriate study is carried out. The proposed methodology is validated through application to the numerical model of a reduced-scale masonry structure, called Brick House, which represents a well-known international benchmark case study tested on the LNEC-3D shaking table. The obtained results demonstrate that the proposed methodology is capable of achieving earthquake-induced damage detection and localization with a good level of aproximation.(undefined

Application of a bio-inspired anomaly detection algorithm for unsupervised SHM of a historic masonry church

Variations in dynamic properties are commonly used in Structural Health Monitoring to assess the conditions of a structural system, being these parameters sensitive to damage-induced changes. Yet, such variations can also be due to changes in environmental parameters, like fluctuations in temperature, humidity, etc. By performing a continuous monitoring, the correlation between those factors appears and their variations, if no damage exists, result in a cyclic phenomenon. Negative selection, a bio-inspired classification algorithm, can be exploited to distinguish anomalous from normal changes, thus eliminating the influence of environmental effects on the assessment of the structural condition. This algorithm can be trained to relate specific extracted features (e.g. modal frequencies) and other monitored parameters (e.g. environmental conditions), allowing to identify damage when the registered value oversteps the confidence interval defined around the predicted value. Negative selection draws inspiration from the mammalian immune system, whose physiology demonstrates the efficiency of this process in discriminating non-self elements, despite the restricted number of receptors available to face a vast amount of aggressors. In this paper, a negative-selection algorithm based on a non-random strategy for detector generation is optimized and tested on the monitoring data of a prominent monument of the Portuguese architecture.- (undefined

Particle Swarm Optimization for damage identification in beam-like structures

The main objectives of Structural Health Monitoring (SHM) are the characterization and the assessment of the health condition of structural systems. Combined with appropriate Damage Identification (DI) strategies, SHM aims to provide reliable information about the localization and quantification of the structural damage by using an inverse formulation approach, with the damage parameters being estimated from parametric changes in dynamic properties. Mathematically, an inverse problem consists of the optimization of a function which represents the "distance" between the experimental and the numerically-simulated features of the system. Such process requires the development of a mock-up numerical model fairly representative of the system and iteratively updated until a response, as close as possible to the experimental one, is provided. The minimization of the difference between measured and predicted features' values is the objective function, whose global minimum corresponds to the best adjustment of the model variables. Metaheuristics represent a large class of global methods for optimization purposes able to outperformtraditional methods in the following aspects: ease of implementation, time consumption, suitability for non-linear phenomena, black-box and high-dimensional problems. The present paper analyses, through a numerical experimentation approach, the suitability of one of the best-known metaheuristics, i.e. the Particle Swarm Optimization (PSO) algorithm, for DI of beam-like structures. Modal properties are used to define the objective function and various algorithm instances are tested across different problem instances to assess robustness and influence of the algorithm parameters.This work was supported by FCT (Portuguese Foundation for Science and Technology), within ISISE, scholarship SFRH/BD/115188/2016. This work was also financed by FEDER funds through the Competitivity Factors Operational Programme - COMPETE and by national funds through FCT - Foundation for Science and Technology within the scope of the project POCI-01-0145-FEDER-007633

Application of a classification algorithm to the early-stage damage detection of a masonry arch

The early-stage identification of structural damage still represents a relevant challenge in civil engineering. Localized damages if not readily detected can lead to disruption or even collapse, involving hazard to people and economical losses. Although the final goal of the identification is to localize and quantify the damage, a reliable discrimination between normal and abnormal states of the structure in the very early stage of the damage onset is not an easy task. In the field of Structural Health Monitoring (SHM) great attention has been paid to the development of damage detection methods based on continuous and automatic registration of the system response to unknown ambient inputs. The numerical algorithms exploited must be: (1) easy to implement and computationally inexpensive, eventually being embedded in the sensors; (2) as much independent on human decision as possible; (3) robust to the many sources of uncertainties affecting the monitoring; (4) able to detect small damage extents in order to provide an early warning; (5) suitable for the application in the case of few and sparse measurements collected only in the normal condition. The performance of a novel version of Negative Selection Algorithm, recently developed by the authors, is here analyzed with attention to these issues. The algorithm is tested against data collected on a segmental masonry arch built in the laboratory of the University of Minho and subject to progressive lateral displacement of one support.- (undefined

An overview on structural health monitoring: From the current state-of-the-art to new bio-inspired sensing paradigms

In the last decades, the field of structural health monitoring (SHM) has grown exponentially. Yet, several technical constraints persist, which are preventing full realization of its potential. To upgrade current state-of-the-art technologies, researchers have started to look at nature’s creations giving rise to a new field called ‘biomimetics’, which operates across the border between living and non-living systems. The highly optimised and time-tested performance of biological assemblies keeps on inspiring the development of bio-inspired artificial counterparts that can potentially outperform conventional systems. After a critical appraisal on the current status of SHM, this paper presents a review of selected works related to neural, cochlea and immune-inspired algorithms implemented in the field of SHM, including a brief survey of the advancements of bio-inspired sensor technology for the purpose of SHM. In parallel to this engineering progress, a more in-depth understanding of the most suitable biological patterns to be transferred into multimodal SHM systems is fundamental to foster new scientific breakthroughs. Hence, grounded in the dissection of three selected human biological systems, a framework for new bio-inspired sensing paradigms aimed at guiding the identification of tailored attributes to transplant from nature to SHM is outlined.info:eu-repo/semantics/acceptedVersio