Earthquake‐induced damage detection and localization in masonry structures using smart bricks and Kriging strain reconstruction: A numerical study

García‐Macías, Enrique; Ubertini, Filippo

doi:10.1002/eqe.3148

Cited by 39 publications

(25 citation statements)

References 35 publications

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“…Recently, García-Macías and Ubertini proposed a theoretical study concerning the effectiveness of the smart bricks to reconstruct strain field maps when embedded into either new constructions or preexisting structures. 27 As a logical continuation of previous work, this paper reports the first full-scale application of smart bricks considering an unreinforced masonry (URM) building subjected to shaking table tests. A seismic sequence, with increasing intensity, was considered to induce progressive damage to the structure.…”

Section: Introductionmentioning

confidence: 85%

“…Considering the damage index proposed by García‐Macías and Ubertini, indicative of the load‐path changes induced by damages and detected by embedded smart bricks, global and local damage indexes,

I_{\exp}^{s}

, were defined in order to estimate the severity of the damage occurred on the whole URM building specimen or on each façade at a generic step of the seismic sequence, as follows:

I_{\exp}^{s} = \frac{1}{n} \sum_{i} \frac{1}{λ_{i} ϵ_{vol, i}^{0}} \frac{false| R_{i}^{s} - R_{i}^{0} false|}{R_{i}^{0}},

where n is the number of smart bricks considered in the estimation of the index ( n = 8 for the global damage index, n = 2 for the local damage index),

R_{i}^{s}

is the value of the electrical resistance, referred to the step, s , of the seismic sequence,

R_{i}^{0}

is the value of the electrical resistance measured after performing the WN1 white noise, λ i is the gauge factor, and

ϵ_{vol, i}^{0}

is the value of the volumetric strain after performing WN1 white noise, for the i th smart brick. According to Equation ,

I_{\exp}^{s}

is an average change in volumetric strain of the smart bricks under dead loads with respect to undamaged conditions.…”

Section: Methodsmentioning

confidence: 99%

“…This section illustrates the novel sensing technology of smart bricks, including their manufacturing process and the methodology to conduct electrical measurements in the presented experiments. More details on fabrication and structural deployment can be found in García‐Macías and Ubertini …”

Section: Smart Brickmentioning

confidence: 99%

“…More details on fabrication and structural deployment can be found in García-Macías and Ubertini. 27…”

Section: Smart Brickmentioning

confidence: 99%

“…The obtained experimental results promoted the use of microstainless steel fibers, as a more suitable conductive filler for clay‐based materials, and the use of external copper plate electrodes for the acquisition of electrical measurements. Recently, García‐Macías and Ubertini proposed a theoretical study concerning the effectiveness of the smart bricks to reconstruct strain field maps when embedded into either new constructions or preexisting structures …”

Section: Introductionmentioning

confidence: 99%

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Shaking table tests on a masonry building monitored using smart bricks: Damage detection and localization

Meoni

D’Alessandro

Cavalagli

et al. 2019

Earthq Engng Struct Dyn

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Summary The seismic behavior of unreinforced masonry buildings is typically characterized by premature brittle collapse mechanisms that can cause serious consequences for the protection of human lives and for the preservation of historical and cultural heritage. Structural health monitoring can be a powerful tool enabling a quick post‐earthquake assessment of the structure's performance, but its applications are still scarce as a consequence of the severe limitations affecting off‐the‐shelf sensing technologies, in terms of local nature of the measurements, costs, as well as long‐term behavior, installation, and maintenance. To overcome some of these limitations, the authors have recently proposed a new sensing technology, called “smart brick,” that is a durable clay brick doped with stainless steel microfibers, working as a smart strain sensor for masonry buildings. This paper presents the first full‐scale application of smart bricks, used for detecting and localizing progressive earthquake‐induced damage in an unreinforced masonry building subjected to shaking table tests. Smart bricks are employed to detect changes in load paths on masonry walls, comparing strain measurements acquired after each step of the seismic sequence with those referring to the undamaged structure. Experimental results are interpreted using a 3D finite element model built to reproduce the shaking table tests. Overall, the results demonstrate that the smart bricks can effectively reveal local permanent changes in structural conditions following a progressive damage, therefore being apt for earthquake‐induced damage detection and localization.

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Section: Introductionmentioning

confidence: 85%

I_{\exp}^{s}

, were defined in order to estimate the severity of the damage occurred on the whole URM building specimen or on each façade at a generic step of the seismic sequence, as follows:

I_{\exp}^{s} = \frac{1}{n} \sum_{i} \frac{1}{λ_{i} ϵ_{vol, i}^{0}} \frac{false| R_{i}^{s} - R_{i}^{0} false|}{R_{i}^{0}},

where n is the number of smart bricks considered in the estimation of the index ( n = 8 for the global damage index, n = 2 for the local damage index),

R_{i}^{s}

is the value of the electrical resistance, referred to the step, s , of the seismic sequence,

R_{i}^{0}

is the value of the electrical resistance measured after performing the WN1 white noise, λ i is the gauge factor, and

ϵ_{vol, i}^{0}

is the value of the volumetric strain after performing WN1 white noise, for the i th smart brick. According to Equation ,

I_{\exp}^{s}

is an average change in volumetric strain of the smart bricks under dead loads with respect to undamaged conditions.…”

Section: Methodsmentioning

confidence: 99%

Section: Smart Brickmentioning

confidence: 99%

“…More details on fabrication and structural deployment can be found in García-Macías and Ubertini. 27…”

Section: Smart Brickmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Shaking table tests on a masonry building monitored using smart bricks: Damage detection and localization

Meoni

D’Alessandro

Cavalagli

et al. 2019

Earthq Engng Struct Dyn

Self Cite

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Self‐Sensing Cementitious Composites with Hierarchical Carbon Fiber‐Carbon Nanotube Composite Fillers for Crack Development Monitoring of a Maglev Girder

Ding

Wang

Qiu

et al. 2022

Small

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In view of high‐performance, multifunctional, and low‐carbon development of infrastructures, there is a growing demand for smart engineering materials, making infrastructures intelligent. This paper reports a new‐generation self‐sensing cementitious composite (SSCC) incorporated with a hierarchically structured carbon fiber (CF)‐carbon nanotube (CNT) composite filler (CF‐CNT), which is in situ synthesized by directly growing CNT on CF. Various important factors including catalyst, temperature, and gas composition are considered to investigate their kinetic and thermodynamic influence on CF‐CNT synthesis. The reciprocal architecture of CF‐CNT not only alleviates the CNT aggregation, but also significantly improves the interfacial bonding between CF‐CNT and matrix. Due to the synergic and spatially morphological effects of CF‐CNT, that is, the formation of widely distributed multiscale reinforcement networks, SSCCs with CF‐CNTs exhibit high mechanical properties and electrical conductivity as well as excellent self‐sensing performances, particularly enhanced sensing repeatability. Moreover, the SSCCs with CF‐CNTs are integrated into a full‐scale maglev girder to devise a smart system for crack development monitoring. The system demonstrates high sensitivity and fidelity to capture the initiation of cracks/damage, as well as progressive and sudden damage events until the complete failure of the maglev girder, indicating its considerable potential for structural health monitoring of infrastructures.

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Recent advances in embedded technologies and self‐sensing concrete for structural health monitoring

Civera,

Naseem,

Chiaia

2024

Structural Concrete

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Fully embedded and spatially diffuse sensors are central to the advancement of civil and construction engineering. Indeed, they serve as an enabling technology necessary for addressing the current challenges associated with through‐life management and structural health monitoring of existing structures and infrastructures. The need to identify structural issues early on has driven the integration of such embedded sensing capabilities into construction materials, turning passive structures into proactive, self‐aware “entities,” commonly referred to as Smart Structures. The economic rationale behind this endeavor is underscored by the vital significance of continuous monitoring, which enables prompt anomaly assessment and thus mitigates the risks of potential structural failures. This is particularly relevant for road and rail infrastructures, as they represent a substantial and enduring investment for any nation. Given that a large majority of these large infrastructures are composed of concrete and reinforced concrete, both academics and construction companies are continuously researching micro‐ and nano‐engineered self‐sensing solutions specifically tailored for this building material. This comprehensive review paper reports the latest advances in the field of self‐sensing concrete as of 2024, with an emphasis on intrinsic self‐sensing concrete, that is, electrically conductive functional fillers. A critical analysis and a discussion of the findings are provided. Based on the perceived existing gaps and demands from the industry, the field's future perspectives are also briefly outlined.

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Earthquake‐induced damage detection and localization in masonry structures using smart bricks and Kriging strain reconstruction: A numerical study

Cited by 39 publications

References 35 publications

Shaking table tests on a masonry building monitored using smart bricks: Damage detection and localization

Shaking table tests on a masonry building monitored using smart bricks: Damage detection and localization

Self‐Sensing Cementitious Composites with Hierarchical Carbon Fiber‐Carbon Nanotube Composite Fillers for Crack Development Monitoring of a Maglev Girder

Recent advances in embedded technologies and self‐sensing concrete for structural health monitoring

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