Braga, Franco;Gigliotti, Rosario;Monti, Giorgio;Morelli, Francesco;Nuti, Camillo;Salvatore, Walter;Vanzi, Ivo
Earthquakes and Structures
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v.8
no.1
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pp.37-56
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2015
The Emilia, May-July 2012, earthquake has dramatically highlighted the only the hazards facing the people in insufficiently secured workplaces, but also the socio-economic consequences of interruption of production activities. After the event, in order to guarantee suitable safety levels, the Italian government asked for a generalized seismic retrofit of buildingsaffected by the earthquake under consideration. Considering that Emilia is one of the most industrialized Italian region, the number of the industrial buildings to be verified could however lead to not acceptable resumption of production time. So, with the aim to speed up the recovery, were leaved out from this request the buildings which had undergone a strong enoughshaking without any damage. In practice, the earthquakes were being used as a "test" to evaluate the seismic structural strength. Besides, the Italian government provision specifies also the zones, within which buildings that escaped evident damage are exempt from obligatory checks, and termed "exclusion zones", shall be individuated using the data provided by the Italian National Institute of Geophysics and Volcanology in the form of so-called "shakemaps". Obviously, the precision of such data greatly influences the determination of the exclusions zones and so all the economic issues related to them. Starting from these considerations, the present paper describes an evaluation of the reliability of the procedure of shakemap generation with specific regard to the seismic events that struck the Emilia region on May 20 and 29, 2012.
Wen Tang;Tarutal Ghosh Mondal;Rih-Teng Wu;Abhishek Subedi;Mohammad R. Jahanshahi
Smart Structures and Systems
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v.31
no.4
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pp.365-381
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2023
The existing vision-based techniques for inspection and condition assessment of civil infrastructure are mostly manual and consequently time-consuming, expensive, subjective, and risky. As a viable alternative, researchers in the past resorted to deep learning-based autonomous damage detection algorithms for expedited post-disaster reconnaissance of structures. Although a number of automatic damage detection algorithms have been proposed, the scarcity of labeled training data remains a major concern. To address this issue, this study proposed a semi-supervised learning (SSL) framework based on consistency regularization and cross-supervision. Image data from post-earthquake reconnaissance, that contains cracks, spalling, and exposed rebars are used to evaluate the proposed solution. Experiments are carried out under different data partition protocols, and it is shown that the proposed SSL method can make use of unlabeled images to enhance the segmentation performance when limited amount of ground truth labels are provided. This study also proposes DeepLab-AASPP and modified versions of U-Net++ based on channel-wise attention mechanism to better segment the components and damage areas from images of reinforced concrete buildings. The channel-wise attention mechanism can effectively improve the performance of the network by dynamically scaling the feature maps so that the networks can focus on more informative feature maps in the concatenation layer. The proposed DeepLab-AASPP achieves the best performance on component segmentation and damage state segmentation tasks with mIoU scores of 0.9850 and 0.7032, respectively. For crack, spalling, and rebar segmentation tasks, modified U-Net++ obtains the best performance with Igou scores (excluding the background pixels) of 0.5449, 0.9375, and 0.5018, respectively. The proposed architectures win the second place in IC-SHM2021 competition in all five tasks of Project 2.
After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.
After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.
Rojas-Mercedes, Norberto;Erazo, Kalil;Di Sarno, Luigi
Earthquakes and Structures
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v.22
no.5
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pp.503-515
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2022
This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.
Journal of the Earthquake Engineering Society of Korea
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v.7
no.4
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pp.81-87
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2003
In this paper, the feasibility of using Shannon's sampling theorem to reconstruct exact mode shapes of a structural system from a limited number of sensor points and localizing damage in that structure with reconstructed mode shapes is investigated. Shannon's sampling theorem for the time domain is reviewed. The theorem is then extended to the spatial domain. To verify the usefulness of extended theorem, mode shapes of a simple beam are reconstructed from a limited amount of data and the reconstructed mode shapes are compared to the exact mode shapes. On the basis of the results, a simple rule is proposed for the optimal placement of accelerometers in modal parameter extraction experiments. Practicality of the proposed rule and the extended Shannon's theorem is demonstrated by detecting damage in laboratory beam structure with two-span via applying to mode shapes of pre and post damage states.
Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration.
Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.
The inclusion of a ductile steel bracing as means of repairing an earthquake-damaged bridge bent is evaluated and experimentally assessed for the purposes of restoring the damaged bent's strength and stiffness and further improving the energy dissipation capacity. The study is focused on substandard reinforced concrete multi-column bridge bents constructed in the 1950 to mid-1970 in the United States. These types of bents have numerous deficiencies making them susceptible to seismic damage. Large-scale experiments were used on a two-column reinforced concrete bent to impose considerable damage of the bent through increasing amplitude cyclic deformations. The damaged bent was then repaired by installing a ductile fuse steel brace in the form of a buckling-restrained brace in a diagonal configuration between the columns and using post-tensioned rods to strengthen the cap beam. The brace was secured to the bent using steel gusset plate brackets and post-installed adhesive anchors. The repaired bent was then subjected to increasing amplitude cyclic deformations to reassess the bent performance. A subassemblage test of a nominally identical steel brace was also conducted in an effort to quantify and isolate the ductile fuse behavior. The experimental data from these large-scale experiments were analyzed in terms of the hysteretic response, observed damage, internal member loads, as well as the overall stiffness and energy dissipation characteristics. The results of this study demonstrated the effectiveness of utilizing ductile steel bracing for restoring the bent and preventing further damage to the columns and cap beams while also improving the stiffness and energy dissipation characteristics.
International conference on construction engineering and project management
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2015.10a
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pp.339-343
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2015
To rapidly recover ceased functionality of a facility after a catastrophic seismic event, critical decisions on facility repair works are made within a limited period of time. However, prolonged damage assessment of facilities, due to massive damage in the surrounding region and the complicated damage judgment procedures, may impede restoration planning. To assist reliable structural damage estimation without a deep knowledge and rapid interactive analysis among facility damage and restoration operations during the approximate restoration project planning phase, we developed a prototype of distributed facility restoration simulations through the use of high-level architecture (HLA) (IEEE 1516). The simulation prototype, in which three different simulations (including a seismic data retrieval technique, a structural response simulator, and a restoration simulation module) interact with each other, enables immediate damage estimation by promptly detecting earthquake intensity and the restoration operation analysis according to estimated damage. By conducting case simulations and experiments, research outcomes provide key insights into post-disaster restoration planning, including the extent to which facility damage varies according to disaster severity, facility location, and structures. Additional insights arise regarding the extent to which different facility damage patterns impact a project's performance, especially when facility damage is hard to estimate by observation. In particular, an understanding of required type and amount of repair activities (e.g., demolition works, structural reinforcement, frame installation, or finishing works) is expected to support project managers in approximate work scheduling or resource procurement plans.
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