Implementation of a condition monitoring strategy for the Monastery of Salzedas, Portugal: challenges and optimisation

The implementation of condition monitoring for damage identification and the generation of a reliable digital twin are essential elements of preventive conservation. The application of this promising approach to Cultural Heritage (CH) sites is deemed truly beneficial, constituting a minimally invasive mitigation strategy and a cost-effective decision-making tool. In this light, the present work focuses on establishing an informative virtual model as a platform for the conservation of the monastery of Santa Maria de Salzedas, a CH building located in the north of Portugal. The platform is the first step towards the generation of the digital twin and is populated with existing documentation as well as new information collected within the scope of an inspection and diagnosis programme. At this stage, the virtual model encompasses the main cloister, whose structural condition and safety raised concerns in the past and required the implementation of urgent remedial measures. In the definition of a vibration-based condition monitoring strategy for the south wing of the cloister, five modes were identified by carrying out an extensive dynamic identification. Nonetheless, significant challenges emerged due to the low amplitude of the ambient-induced vibrations and the intrusiveness of the activities. To this end, a data-driven Optimal Sensor Placement (OSP) approach was followed, testing and comparing five heuristic methods to define a good trade-off between the number of sensors and the quality of the collected information. The results showed that these algorithms for OSP allow the selection of sensor locations with good signal strength.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE, under reference LA/P/0112/2020

Performance of rammed earth subjected to in-plane cyclic displacement

Rammed earth structures are worldwide spread, both as architectural heritage and new constructions. Yet, rammed earth buildings present, in general, high seismic vulnerability. Despite the several studies conducted on the mechanical characterisation of rammed earth and on the numerical modelling of structural elements built with this material, further in-plane cyclic tests on rammed earth sub-assemblies are required to characterise their hysteretic behaviour. In this framework, an experimental program was conducted where cyclic in-plane tests were performed on a large-scale rammed earth wall. The geometry of the wall was defined to represent a sub-assembly commonly found in rammed earth dwellings from Alentejo (Southern Portugal). The wall was subjected to cyclic shear displacements with increasing amplitude, imposed in both positive and negative directions. To detect the dynamic properties of the wall and to assess the development of the structural damage, dynamic identification tests were conducted along the experimental programme. The results are analysed in terms of crack pattern, dynamic properties, displacement capacity, base shear performance and stiffness degradation. Further discussion is led on the dissipated energy, while a bi-linear and linear equivalent systems are proposed as simplified modelling approach. In conclusion, degradation of structural capacity was observed due to cyclic loads, while adequate energy dissipation and base shear coefficient were obtained.This work was partly financed by FEDER funds through the Operational Programme Competitiveness Factors (COMPETE 2020) and by national funds through the Foundation for Science and Technology (FCT) within the scope of project SafEarth-PTDC/ECM-EST/2777/2014 (POCI-01-0145-FEDER-016737). The support from grants SFRH/BD/131006/2017 and SFRH/BPD/97082/2013 is also acknowledged. Acknowledgments are addressed to the Laboratory of Structures (LEST) of the University of Minho, Joao Bernardino, Lda, and TERRACRUA-Construcoes Ecologicas Unipessoal, Lda for building the rammed earth model

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

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

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

A Bio-inspired Framework for Highly Efficient Structural Health Monitoring and Vibration Analysis

Civil engineering structures are continuously exposed to the risk of damage whether due to ageing effects, excessive live loads or extreme events, such as earthquakes, blasts and cyclones. If not readily identified, damage will inevitably compromise the structural integrity, leading the system to stop operating and undergo in-depth interventions. The economic and social impacts associated with such an adverse condition can be significant, therefore effective methods able to early identify structural vulnerabilities are needed for these systems to keep meeting the required life-safety standards and avoid the impairment of their normal function. In this context, vibration-based analysis approaches play a leading role as they allow to detect structural faults which lie beneath the surface of the structure by identifying and quantifying anomalous changes in the system’s inherent vibration characteristics. However, although the considerable degree of maturity attained within the fields of experimental vibration analysis (EVA) and structural health monitoring (SHM), several technical issues still need to be addressed in order to ensure the successful implementation of these powerful tools for damage identification purposes. The scope of this paper is to present a bio-inspired framework for optimal structural health monitoring and vibration analysis. After a critical overview on current methods and tools, three main sources of bio-inspiration are described along with the relative algorithms derived for SHM applications. It is shown how uncovering the general principles behind the functioning of selected biological systems can foster the development of efficient solutions to the technical conflicts of actual SHM architectures and lead to new sensing paradigms for optimal network topology and sensors location. A compatibility-matrix is proposed to help compare biological and SHM systems and discriminate desired from unwanted features. Such a framework will ultimately assist in seeking for the most suitable nature-inspired solutions for more accurate condition screening and robust vibration analysis.FEDER funds through the Competitiveness 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-007633info:eu-repo/semantics/publishedVersio

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

Monitorização e conservação preventiva de património histórico com BIM: o projeto HeritageCare

A gestão de ativos (facility management) é uma área interdisciplinar que tem como objetivo manter um sistema e os seus respetivos serviços operacionais. Nesse contexto, as metodologias Building Information Modeling (BIM) já demonstraram ter capacidade de agregar e gerir informação na coordenação de processos, espaços, pessoas e atividades. No entanto, a definição de boas práticas de modelação e de estratégias para obtenção de informação para o caso de construções existentes, particularmente no caso do património histórico, é ainda um assunto em aberto. No presente trabalho apresenta-se uma abordagem viável para modelação, em plataforma BIM, da gestão de construções existentes com especial atenção para o acompanhamento da evolução de danos detetados em inspeções. A metodologia proposta requer a definição do nível de necessidade de informação adequado para o modelo e cada um dos seus componentes, baseado num equilíbrio entre características geométricas e não geométricas (ex. o nível de precisão no detalhe e a quantidade de informação acoplada). Para este efeito desenvolveu-se um procedimento que permite aos técnicos obter informação proveniente do modelo BIM para atualizar os cenários de dano, sendo baseado na interoperabilidade entre: (a) software BIM proprietário e open source, através do formato IFC (Industry Foundation Classes); (b) modelo BIM e folhas de cálculo. A metodologia desenvolvida é aplicada ao Paço dos Duques de Bragança, situado em Guimarães.Este trabalho foi parcialmente financiado pelo projeto HeritageCare (programa InterregSudoe/FEDER, SOE1/P5/P0258), por fundos do FEDER (programa COMPETE) e por fundos nacionais através da Fundação para a Ciência e Tecnologia FCT no âmbito do projeto POCI01-0145-FEDER-007633

Dynamic characterization of progressively damaged segmental masonry arches with one settled support: experimental and numerical analyses

This paper aims to explore the dynamic behavior of a segmental masonry arch subjected to increasing horizontal displacements of one support. To this end, output-only dynamic identification techniques are first used to track the evolution of the dynamic features of the system under progressive damage scenarios and evaluate their sensitivity to settlement-induced cracks. Considerations on the structural response of the segmental arch up to failure are also included. Then, a numerical procedure coupling linear perturbation and modal analysis is applied to simulate the dynamic behavior of the arch over consecutive scenarios, taking into account the influence of the damage on the structure's dynamic properties in an automatic way. The combination of experimental and numerical analyses allows to fully investigate the dynamics of the cracked masonry arch and to shed light on relevant aspects about the effects of settlement-induced cracks on the modal blueprints of masonry arches

Análisis filogenético de aislados de aspergillus flavus no aflatoxigénicos, potenciales agentes de biocontrol en maíz, aislados en Santiago del Estero y región colindante de Tucumán y Córdoba

PosterAspergillus flavus es un hongo patógeno de maíz responsable de la contaminación con aflatoxinas. Por medio del análisis filogenético se establecieron relaciones entre aislados de A. flavus a través de la secuenciación de segmentos del gen de la calmodulina (CaM).Instituto de Patología VegetalFil: Barontini, Javier Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola; ArgentinaFil: Barontini, Javier Miguel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Trucco, Veronica Milagros. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Trucco, Veronica Milagros. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola; ArgentinaFil: Torrico Ramallo, Ada Karina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Torrico Ramallo, Ada Karina. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Druetta, Marcelo Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimilí; ArgentinaFil: Chulze, Sofía. Universidad Nacional de Río Cuarto (UNRC). Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación en Micología y Micotoxicología (IMICO); ArgentinaFil: Gimenez, Maria De La Paz. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Gimenez, Maria De La Paz. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola; Argentin