Use of simulated ground motions for the evaluation of energy response of simple structural systems

Karimzadeh, Shaghayegh; Ozsarac, Volkan; Erberik, Murat Altuğ

doi:10.1016/j.soildyn.2019.05.024

Cited by 22 publications

(12 citation statements)

References 59 publications

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“…Moreover, Amiranlou et al (2016) predicted the strong ground motion of Tabriz's north fault utilizing the stochastic finite fault model based on a dynamic corner frequency simulation. Eventually, Karimzadeh et al (2019) simulated a vast range of ground motion, followed by simulating a large collection of simulated earth movements. They then studied the effects of various parameters on the seismic behavior of a single degree of freedom systems in terms of energy, applying a nonlinear time history analysis.…”

Section: Stochastic Finite Faultmentioning

confidence: 99%

Seismic zoning of Tabriz area by stochastic finite fault model considering site-specific soil effects

Alamdari¹,

Dabiri²,

Jani³

et al. 2021

S&R

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Tabriz, as one of the most earthquake-prone cities in the Iran plateau, has experienced enormous earthquakes that have even destroyed the city altogether. Considering this seismological background and the vicinity of Tabriz's northwestern fault, reducing the possible earthquake losses can be highly useful by scrutinizing the strong ground motion resulting from the fault activation. To this end, a stochastic finite-fault ground motion simulation (EXSIM) method was applied as an important means for predicting the ground motion near the epicenter of the earthquake. EXSIM is an open-source stochastic finite-fault simulation algorithm that generates the time-series of the earthquake's ground motion. Based on the findings, the peak horizontal acceleration reached 0.83 g in the northern parts by creating artificial accelerograms and Tabriz's seismic zonation. In comparison, it reduced by 0.48 g by departing from the fault in the city's southern parts. Additionally, providing a seismic zonation map in Tabriz revealed that stopping the construction in the north parts while extending the settlement construction to the south part of the city are considered vital and unavoidable. Also, by applying the magnification and effects of the soil layers above the bedrock, it was further found that the existence of the loose layer with low strength and compaction intensify the application of seismic acceleration on the near-surface structures in the central, west, and southwest parts of the target area.

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Section: Stochastic Finite Faultmentioning

confidence: 99%

Seismic zoning of Tabriz area by stochastic finite fault model considering site-specific soil effects

Alamdari¹,

Dabiri²,

Jani³

et al. 2021

S&R

View full text Add to dashboard Cite

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“…The simulation algorithm requires reliable input‐model parameters to generate final shaking, which matches specific features of the region‐specific real records. Finite‐fault stochastic simulations are tested and verified for different parts of the world by previous studies in the literature from both seismological and engineering points of view 31–36 . Before ground motion simulations can be applied confidently in engineering domains, they must undergo thorough and rigorous analysis and validation.…”

Section: Introductionmentioning

confidence: 99%

“…Finite-fault stochastic simulations are tested and verified for different parts of the world by previous studies in the literature from both seismological and engineering points of view. [31][32][33][34][35][36] Before ground motion simulations can be applied confidently in engineering domains, they must undergo thorough and rigorous analysis and validation. A literature review reveals that stochastic ground motion simulations are considered and evaluated to estimate seismic demand for single-degree-of-freedom models 23,36 or multi-degree-of-freedom reinforced concrete and steel structures.…”

Section: Introductionmentioning

confidence: 99%

“…[31][32][33][34][35][36] Before ground motion simulations can be applied confidently in engineering domains, they must undergo thorough and rigorous analysis and validation. A literature review reveals that stochastic ground motion simulations are considered and evaluated to estimate seismic demand for single-degree-of-freedom models 23,36 or multi-degree-of-freedom reinforced concrete and steel structures. [37][38][39][40][41][42][43] In a recent study, the authors used stochastically simulated ground motion records to evaluate the seismic damage to the historic masonry building of Arge-Tabriz (Iran).…”

Section: Introductionmentioning

confidence: 99%

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Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: Source‐based vs site‐based approaches

Karimzadeh,

Funari,

Szabó

et al. 2023

Earthq Engng Struct Dyn

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Earthquakes are among the most destructive natural disasters and have resulted in a massive number of fatalities and economic losses all over the world. Simulated ground motion records are valuable, particularly for regions lacking seismic stations or with a limited history of large‐magnitude earthquakes. Notably, a significant percentage of monumental masonry buildings are located in regions with limited access to real records; hence, simulated records play a paramount role in their seismic protection. However, few studies have investigated the structural response of heritage buildings via response history analyses to assess the performance of simulated earthquakes against real ones. To accomplish this, this study simulates the recorded time‐series of the 9th of July 1998 Faial earthquake in the Azores (Mw = 6.2) at four available stations, using two different simulation approaches, that is, a source‐based stochastic finite‐fault method and a site‐based broadband stochastic method. First, two masonry facades with sidewalls characterized by different slenderness levels are adopted to conduct this research. Moreover, the proposed approach is also applied to an existing monumental structure, that is, São Francisco Church, located at Horta, which was affected by damage during the Faial earthquake. Results demonstrate that both simulation approaches provide similar results in terms of structural response prediction. The proposed framework also demonstrates that a small mismatch in terms of predicted damage patterns can result in a significant relative error in terms of displacement predictions.

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“…If such data is unavailable, ground motion IMs can be estimated through the use of simulated databases generated by various empirical, numerical, and analytical methodologies 6 . The simulated dataset can better represent the regional seismicity of the study areas 7–12 . Douglas 5 lists 87 GMMs developed based on simulated records for the prediction of PGA and elastic response spectral ordinates.…”

Section: Introductionmentioning

confidence: 99%

Backbone ground motion model through simulated records and XGBoost machine learning algorithm: An application for the Azores plateau (Portugal)

Karimzadeh,

Mohammadi,

Salahuddin

et al. 2023

Earthq Engng Struct Dyn

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Azores Islands are seismically active due to the tectonic structure of the region. Since the 15th century, they have been periodically shaken by approximately 33 moderate to strong earthquakes, with the most recent one in 1998 (Mw = 6.2). Nonetheless, due to insufficient instrumental seismic data, the region lacks a uniform database of past real records. Ground motion simulation techniques provide alternative region‐specific time series of prospective events for locations with limited seismic networks or regions with a seismic gap of catastrophic earthquake events. This research establishes a local ground motion model (GMM) for the Azores plateau (Portugal) by simulating region‐specific records for constructing a homogeneous dataset. Simulations are accomplished in bedrock using the stochastic finite‐fault approach by employing validated input‐model parameters. The simulation results undergo validation against the 1998 Faial event and comparison with empirical models for volcanic and Pan‐European datasets. A probabilistic numerical technique, namely the Monte‐Carlo simulation, is employed to estimate the outcome of uncertainty associated with these parameters. The results of the simulations are post‐processed to predict the peak ground motion parameters in addition to spectral ordinates. This study uses XGBoost to circumvent the difficulties inherent to linear regression‐based models in establishing the form of equations and coefficients. The input parameters for prediction are moment magnitude (Mw), Joyner and Boore distance (RJB), and focal depth (FD). The quantification of GMM uncertainty is accomplished by analyzing the residuals, providing insight into inter‐ and intra‐event uncertainties. The outcomes demonstrate the effectiveness of the suggested model in simulating physical phenomena.

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Use of simulated ground motions for the evaluation of energy response of simple structural systems

Cited by 22 publications

References 59 publications

Seismic zoning of Tabriz area by stochastic finite fault model considering site-specific soil effects

Seismic zoning of Tabriz area by stochastic finite fault model considering site-specific soil effects

Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: Source‐based vs site‐based approaches

Backbone ground motion model through simulated records and XGBoost machine learning algorithm: An application for the Azores plateau (Portugal)

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