Ground Motion Intensity Parameters Research Articles

Machine learning-based collapse prediction for post-earthquake damaged RC columns under subsequent earthquakes

The rapid assessment for numerous post-earthquake damaged reinforced concrete (RC) structures is critical for making informed post-earthquake decisions. However, this often requires significant resources in terms of manpower and calculation costs. This study proposes a machine learning (ML)-based method for predicting the collapse state of post-earthquake damaged RC columns under subsequent earthquakes, which are a critical earthquake-resistant component in RC structures. First, the damage strain field theory is introduced to establish the numerical analysis models for 10000 post-earthquake damaged RC columns. A dataset is constructed using time history analysis results obtained from these numerical analysis models under the action of 1000 ground motion records. The Random Forest (RF) algorithm is then utilized to train an ML model that can predict the collapse state of post-earthquake damaged RC columns under subsequent earthquakes. To evaluate the accuracy of the ML prediction model, a testing dataset consisting of 47 full-size RC columns from the Pacific Earthquake Engineering Research Center (PEER) database is constructed. Results demonstrate that the prediction model has good accuracy, with an Area Under Curve (AUC) value and an F1 measure of 0.87 and 0.76, respectively. The SHapley Additive exPlanation (SHAP) algorithm is then utilized to interpret the ML prediction model, and the influences of design parameters, ground motion intensity parameters, and damage index on the prediction results are discussed. Finally, an interactive and user-friendly graphical user interface (GUI) tool is developed to provide a rapid collapse prediction of post-earthquake damaged RC columns. This study represents a pioneering step towards the application of ML in post-earthquake assessment for damaged RC columns.

Ranking method of the severest input ground motion for underground structures based on composite ground motion intensity measures

Underground structure seismic response analyses and structural safety seismic designs are based on the scientific and reasonable selection of ground motion records. Different input ground motions lead to varies seismic response due to the strong randomness of ground motion. The severest input ground motion for the seismic analysis of underground structures cannot be obtained via a single intensity measure (IM). For this purpose, a ranking method is proposed based on composite IM for the severest input ground motion for underground structures. Four composite ground motion IMs constructed using the partial least squares regression (PLSR) method are proposed as representative ground motion IMs of the seismic failure potential of underground structures. These composite ground motion IMs correspond to the evaluation of four engineering demand parameters (EDPs), including the moment, shear force, axial force, and relative displacement of the central column of a subway station. Elastic-plastic time-history analyses of a two-story three-span subway station are performed given 64 ground motion records to provide the necessary data samples. After the construction, a bilinear logarithmic regression analysis is carried out. The results show that the proposed composite ground motion IMs have a higher correlation with the seismic dynamic responses than single IMs with respect to effectiveness, practicability, and proficiency. Finally, a ranking method for the severest input ground motion based on these composite ground motion intensity parameters is proposed. This method can be used to obtain the severest design ground motion of underground structures for seismic design.

Propagation of 2-D SH waves in random media: Insights from ab initio numerical simulations and transport theory

Increasing the frequency range of physics-based predictions of earthquake ground motions requires to account for small-scale heterogeneities, which can only be described in a stochastic way. Although many studies have addressed the impact of random heterogeneities on ground motion intensity parameters obtained by numerical simulation, very few have verified the accuracy of their numerical solutions or controlled the scattering regime they were simulating. Here we present a comprehensive analysis ofSHwave propagation in 2D random media which covers a broad range of propagation regimes from ballistic to diffusive. The coherent and incoherent parts of the wavefield are examined independently. The random media consist in correlated density and velocity fluctuations described by a von Kármán autocorrelation function with a Hurst coefficient of 0.25 and a correlation lengtha= 500 m. The Birch correlation coefficient which relates density to velocity fluctuations takes 4 possible values between 0.5 and 1, and the standard deviation of the perturbations is either 5% or 10%. Spectral element simulations of SH wave propagation excited by a plane wave are performed for normalized wavenumbers (ka) up to 5. Analysis of the decay of the coherent wave amplitude, obtained through different averaging procedures, allows for a direct measure of the scattering attenuation, which we successfully compare with the predictions of the Dyson mean field theory. We also present the comparison between the energy envelopes measured from the synthetics and their theoretical counterpart provided by the radiative transfer theory and the diffusion approximation. Excellent agreement is found between numerical simulations and theoretical predictions of radiative transfer theory for the mean intensity. The numerical study highlights the difference of attenuation length between the mean field and the mean intensity. In the forward scattering regime, the peak intensity appears to decay exponentially over a length scale known as the transport mean free path. Furthermore, the fluctuations of intensity in the ballistic peak exhibit a transition from Log-normal to Exponential statistics. This transition occurs for a propagation distance of the order of the mean free path, which offers an alternative method of estimating this parameter.

Determining the Optimal Scalar Intensity Measure of Floor Communication Towers

Various structural types and ground motion characteristics lead to distinct intensity measures of structural seismic performance. For the lattice high-rise steel structure of communication towers, determining the intensity measures to adjust ground motion is critical. Additionally, a crucial problem is whether the ground motion intensity parameters of pulse-like ground motion and ordinary ground motion are consistent. In this study, a standard floor four-leg angle steeled communication tower was considered the study object, and 50 pulse-like ground motions and 50 ordinary ground motions were identified to form a pulse-like ground motion set and ordinary ground motion set, respectively. For comparative analyses, 15 ground motion parameters, including amplitude, spectrum, duration, and energy parameters, were selected. The results revealed that for the lattice towers, such as communication tower, under the action of pulse-like ground motion or ordinary ground motion, efficiency, practicability, and sufficiency should be considered. Furthermore, the most suitable intensity measure was the spectral acceleration corresponding to the natural period of the tower. This study provides a basis for selecting the ground motion for dynamic time history analysis of the lattice steel tower.

Incremental Dynamic Analysis of Guangyue Tower Timber Structure

This paper takes the wooden structure of Guangyue Tower as an example, selects ANSYS finite element software, establishes the upper wooden structure and the finite element model considering the whole structure of the high platform respectively, uses the incremental dynamic analysis method, and uses different ground motion intensity parameters to carry on the dynamic time history analysis to it. The results show that the existence of the high platform magnifies the displacement response of the wooden structure, which is not conducive to the seismic resistance of the wooden structure; IDA curve expressed by ground motion intensity parameter PGA can better reflect the overall change of the structure, which is helpful to improve the effectiveness of seismic performance evaluation of Guangyue Tower.

Vulnerability Analysis Based on Ground Motion Intensity Parameters

Based on the ground motion intensity parameters PGA and Sa, this paper conducts a comparative analysis of the vulnerability of the Guangyue building’s wooden structure. The results show that under the same earthquake intensity, the existence of a high platform will increase the probability of damage to the Guangyue building’s wooden structure; PGA is used as an earthquake When evaluating dynamic strength parameters, the probability of evaluating the structure to reach each limit state is large, that is, the possibility of the structure exceeding various limit states is large, and the result is conservative, which is more conducive to ensuring the safety of the structure.

Rapid seismic damage evaluation of bridge portfolios using machine learning techniques

The damage state of a bridge has significant implications on the post-earthquake emergency traffic and recovery operations and is critical to identify the post-earthquake damage states without much delay. Currently, the damage states are identified either based on visual inspection or pre-determined fragility curves. Although these methodologies can provide useful information, the timely application of these methodologies for large scale regional damage assessments is often limited due to the manual or computational efforts. This paper proposes a methodology for the rapid damage state assessment (green, yellow, or red) of bridges utilizing the capabilities of machine learning techniques. Contrary to the existing methods, the proposed methodology accounts for bridge-specific attributes in the damage state assessment. The proposed methodology is demonstrated using two-span box-girder bridges in California. The prediction model is established using the training set, and the performance of the model is evaluated using the test set. It is noted that the machine learning algorithm called Random Forest provides better performance for the selected bridges, and its tagging accuracy ranges from 73% to 82% depending on the bridge configuration under consideration. The proposed methodology revealed that input parameters such as span length and reinforcement ratio in addition to the ground motion intensity parameter have a significant influence on the expected damage state.

Filtered incremental velocity: A novel approach in intensity measures for seismic collapse estimation

SummaryThis study evaluates the performance of a new intensity measure, referred to as filtered incremental velocity FIV3, which is computed using time‐domain features extracted from an acceleration time series and is aimed at the evaluation of structural collapse. This novel approach focuses on the area under a small number of acceleration pulses in the ground motion instead of focusing on the peak response of linear elastic oscillators as in many recently proposed measures of ground motion intensity. FIV3 is developed based on previous research that has highlighted the close relation between the incremental velocity of a ground motion and its potential to induce large inelastic incursions on structures. However, unlike the original definition of incremental velocity which provides a single level of intensity for a ground motion, this new intensity measure is period‐dependent and computed as the sum of the three largest incremental velocities obtained from a low‐pass filtered ground acceleration time series. Efficiency and sufficiency with respect to several ground motion parameters such as magnitude, source‐to‐site‐distance, spectral shape, scale factor, and duration are carefully evaluated and compared against those computed with some traditional and recently proposed intensity measures using collapse results from a four‐story reinforced concrete frame. Results indicate that FIV3 leads to lower variability of collapse estimates and therefore higher efficiency as well as high sufficiency compared with those of other ground motion intensity parameters indicating that this new intensity measure is a promising parameter for structural collapse risk assessment.

Methodology for estimating human perception to tremors in high-rise buildings

Human perception to tremors during earthquakes in high-rise buildings is usually associated with psychological discomfort such as fear and anxiety. This paper presents a methodology for estimating the level of perception to tremors for occupants living in high-rise buildings subjected to ground motion excitations. Unlike other approaches based on empirical or historical data, the proposed methodology performs a regression analysis using the analytical results of two generic models of 15 and 30 stories. The recorded ground motions in Singapore are collected and modified for structural response analyses. Simple predictive models are then developed to estimate the perception level to tremors based on a proposed ground motion intensity parameter—the average response spectrum intensity in the period range between 0.1 and 2.0 s. These models can be used to predict the percentage of occupants in high-rise buildings who may perceive the tremors at a given ground motion intensity. Furthermore, the models are validated with two recent tremor events reportedly felt in Singapore. It is found that the estimated results match reasonably well with the reports in the local newspapers and from the authorities. The proposed methodology is applicable to urban regions where people living in high-rise buildings might feel tremors during earthquakes.

Simulation of large earthquakes and its implications on earthquake insurance rates: a case study in Bursa region (Turkey)

Ground motion intensity parameters of past and potential earthquakes are required for a range of purposes including earthquake insurance practice. In regions with no or sparse earthquake recordings, most of the available methods generate only peak ground motion parameters. For cases where full ground motion time histories are required, simulations that consider fault rupture processes become necessary. In this study, a major novel use of simulated ground motions is presented in insurance premium calculations which also require ground motion intensity measures that are not always available through observations. For this purpose, potential earthquakes in Bursa are simulated using stochastic finite-fault simulation method with dynamic corner frequency model. To ensure simulations with reliable synthetic ground motions, input parameters are derived from regional data. Regional model parameters are verified by comparisons against the observations as well as ground motion prediction equations. Next, a potential large magnitude event in Bursa is simulated. Distribution of peak ground motion parameters and time histories at selected locations are obtained. From these parameters, the corresponding Modified Mercalli Intensities (MMI) are estimated. Later, these MMIs are used as the main ground motion parameter in damage probability matrices (DPM). Return period of the scenario earthquake is obtained from the previous regional seismic hazard studies. Finally, insurance rates for Bursa region are determined with implementation of two new approaches in the literature. The probability of the scenario event and the expected mean damage ratios (MDR) from the corresponding DPMs are used, and the results are compared to Turkish Catastrophe Insurance Pool (TCIP) rates. Results show that insurance premiums can be effectively computed using simulated ground motions in the absence of real data.

Probabilistic assessment of structures with SPSW systems and LYP steel infill plates using fragility function method

Steel plate shear walls (SPSWs) have been used as primary lateral force-resisting systems in seismic design of new and retrofit of existing buildings. Employment of low yield point (LYP) steel infill plates with considerably low yield strength and high ductility, on the other hand, has been shown in a number of studies to improve the structural performance of SPSW systems. By considering the various sources of randomness and uncertainties involved in the design and retrofit process, adoption of a probabilistic methodology can result in a robust seismic performance assessment of such structural systems. This paper presents the results of a study on the seismic performance and vulnerability of retrofitted structures employing SPSW systems and LYP steel material through probabilistic seismic demand analysis (PSDA). Three 9-story code-designed and retrofitted structural models including a moment-resisting and two SPSW frames are considered. Appropriate seismic response and ground motion intensity parameters, and damage as well as repair states are selected. Structural and nonstructural drift and acceleration fragility functions are subsequently developed based on nonlinear time-history analysis results. The effectiveness of SPSW systems in improving the seismic performance and reducing the vulnerability of buildings is demonstrated through seismic response assessment and fragility analysis. Also, it is shown that employment of relatively thicker LYP steel infill plates in seismic design and retrofit of SPSWs results in smaller damage potential and better seismic performance of such systems.

Evaluating the Reliability of Phones as Seismic Monitoring Instruments

Emergency responders must “see” the effects of an earthquake clearly and rapidly for effective response. This paper presents a novel use of cell phone and information technology to measure ground motion intensity parameters. The phone sensor is an imperfect device and has a limited operational range. Thus, shake table tests were performed to evaluate their reliability as seismic monitoring instruments. Representative handheld devices, either rigidly connected to the table or free to move, measured shaking intensity parameters well. Bias in 5%-damped spectral accelerations measured by phones was less than 0.05 and 0.2 [log(g)] during one-dimensional (1-D) and three-dimensional (3-D) shaking in frequencies ranging from 1 Hz to 10 Hz. They did tend to overestimate the Arias Intensity, but this error declined for stronger motions with larger signal-to-noise ratios. With these ubiquitous measurement devices, a more accurate and rapid portrayal of the damage distribution during an earthquake can be provided.

Research of Earthquake Topographic Effect

In this paper, the influence of topography on ground-motion intensity parameter, response spectrum, peak ground acceleration (PGA) and the ratio of response spectrum were studied based on the measured data from large scale shaking table test and observation stations in XiShan park for Wenchuan earthquake. The results show that: in the EW direction, the height do not affect PGD, SMA, VSI and HI, while V_RMS decreases slightly at the middle of the slope, the other intensity parameters increase with the increase of height. In the EW direction, the height has no influence on PGD, V_RMS, SMA, SED, A_RMS, VSI and HI, while other parameters increase as the height increase. In the UD direction, the height has no influence on SMV, PGD, V_RMS, SMV, ASI, VSI and HI, while A_RMS decreases at the middle of the slope, and the other intensity parameters increase as the height increase. Ignoring the local topographic effect, the amplitude of response spectrum increases with the increase of height at the part of short period (T1s), the part of long period (T>1s) is not effected by height. The ground motion will be amplified by local canyon topography, and the influence of local topography is larger than height. The research carried out in paper will deepen the understanding of topographic effect. 0 Preface Earthquake often cause extensive rock slope failures and various types of mass movement in mountainous areas. Catastrophic seismically-induced landsides are among the Earths most powerful geomorphic events, causing sudden and dramatic changes to the landscape, creating high risks to both infrastructures and life, and reputedly causing large economic losses. Seismic waves interacting with topography lead to amplification and deamplification of resulting ground motion. In the western mountainous areas of China, the topography is extremely complex, many large hydropower stations were built in narrow valleys and many large bridge piers were built on valleys and hillsides, so the research about topographic effect is essential to the seismic design of large-scale projects. Topographic effect is always analyzed with following three approaches: motion observation, analytical analysis and numerical analysis. The motion observation is regarded as the most efficient and common approach [1]. Long time ago, the researchers found that the intensity of buildings built on local convex topography was abnormal, in order to reveal the reason of abnormal intensity, array stations were constructed specially to study the effect of local convex topography on ground motion, some observation data were obtained. Some L-7 type strong motion seismographs were installed at the crest and foot of Kagel and Josephine mountain, California, by Lawrence L. Davis and Lewis R. West, the 2 array stations had recorded several aftershocks record of SanFernando earthquake, which occurred on February 9, 1971[. Some L-7 type strong motion seismographs were also installed at the crest, hillside and foot of Butler mountain, Nevada, to record blasting vibration in test site. In 1984, in order to observe the topographic effect of rocky mountain, 8 observation stations were installed by B. E. Tucker, five stations were placed in two tunnels with different elevation, the other three were placed at the surface of outcropped rock [. After the 1989 Loma prieta earthquake, dense array stations of seven digital and triaxial seismographs were mounted on Robinwood Ridge, which is located at 7.3km northwest of epicenter, to analyze the reason of seriously damage on high-strength buildings and cracks of ground [4,. In China, a earthquake observation station was constructed in XiShan Park, ZiGong, SiChuan province in 2007, which recorded the main acceleration time history of WenChuan earthquake perfectly, the establishment of this station offers valuable data to researchers for exploring the local topographic effect on ground motion [6]. In 2010, a research was conducted by Wang Haiyun and Xie Lili with traditional spectral ratio method, some significant conclusions were drawn about the influence of topographic effect on ground motion [7]. In this paper, WenChuan seismic wave was analyzed in time and frequency domain to explore the influence of topography on ground-motion intensity parameters, response spectrum and spectrum characteristic.

Surrogate modeling and failure surface visualization for efficient seismic vulnerability assessment of highway bridges

Seismic response and vulnerability assessment of key infrastructure elements, such as highway bridges, often requires a large number of nonlinear dynamic analyses of complex finite element models to cover the predictor parameter space. The substantial computation time may be reduced by using statistical learning techniques to develop surrogate models, or metamodels, which efficiently approximate the complex and implicit relationship between predictor variables, such as bridge design and ground motion intensity parameters, and the predicted bridge component seismic responses (e.g., column and bearing deformations). Addressing the existing disadvantages of unidimensional metamodels and lack of systematic exploration of different metamodeling strategies to predict bridge responses, this study analyzes four different metamodels, namely, polynomial response surface models as a reference to classical surrogate models, along with emerging multivariate adaptive regression splines, radial basis function networks, and support vector machines. These metamodels are used to develop multi-dimensional seismic demand models for critical components of a multi-span simply supported concrete girder bridge class. The predictive capabilities of the metamodels are assessed by comparing cross-validated goodness-of-fit estimates, and benchmark Monte Carlo simulations. Failure surfaces of bridges under seismic loads are explored for the first time to reveal low curvature the multi-dimensional limit state function and confirm the applicability of metamodels. Lastly, logistic regression is employed to develop parameterized fragility models which offer several advantages over “classical” unidimensional fragility curves. The results and methodologies presented in this study can be applied to efficiently estimate bridge-specific failure probabilities during seismic events.

The variability of deformation demand with ground motion intensity

The use of Nonlinear Dynamic Analyses is coupled to the demands produced by earthquakes of different intensities. The uncertainties associated with the demands are highly dependent on the variable adopted as the intensity measure (IM). This generates the need to compare different IMs and in particular the dispersion of the demand measure in relation to each IM. For this purpose correlations between maximum inter-story drift demand of nine reinforced concrete Multiple Degree of Freedom tridimensional structures and a number of widely used ground motion intensity parameters have been investigated. To determine the optimum parameter to be used as the IM, two additional intensity parameters are analyzed, the spectral acceleration corresponding to the cracked and non-linear period of each structure, Sa(Tcrack) and Sa(T∗), respectively. The results showed that these two IMs have the best correlation with the deformation demand and their use produces a lower variability of structural response.

Uncertainty treatment in earthquake modelling using Bayesian probabilistic networks

A probabilistic description of potential ground motion intensity is computed using a Bayesian probabilistic network (BPN) representing the standard probabilistic seismic hazard analysis (PSHA). Two earthquake ground motion intensity parameters are used: response spectral values for structural failures and peak ground acceleration for geotechnical failures. The correlation of these parameters is also considered within a BPN. It is further shown how deaggregation of the seismic hazard could be easily performed using BPNs. A systematic consideration of uncertainty in the values of the parameters of a particular seismic hazard model can be described by PSHA. But the correct choices for elements of the seismic hazard model are uncertain. Logic trees provide a convenient framework for the treatment of model uncertainty. The paper illustrates an alternative way of incorporating the model uncertainty by extending the developed BPN. Incorporation of time-dependent seismic hazard using a BPN is also illustrated. Finally, the uncertainty treatment in earthquake modelling using BPNs is illustrated on the region Adapazari, which is located close to the western part of the North Anatolian Fault in Turkey.

Spectral Ground Motion Intensity Based on Capacity and Period Elongation

Ground motion intensity parameters are used to express the relationship between expected structural damage and the seismic forces imposed. The graphical representation of damage probability as a function of ground motion intensity leads to fragility curves that are generally used in loss estimation studies. The most typical parameters used to represent the ground motion intensity are peak ground acceleration, peak ground velocity, spectral acceleration, and spectral displacement. Other parameters obtained from the ground motion trace and response spectra have been recommended in literature, but no consensus on which intensity parameter to use exists because of the various drawbacks of these ground motion intensities. A new spectrum ground motion intensity parameter that relies on the expected elongated period of the structure under seismic forces has been developed. This intensity measure takes into account the approximate yield capacity of the structure and the area between the fundamental and elongated ...

Correlation of Deformation Demands with Ground Motion Intensity

A comprehensive study has been carried out to investigate the correlation between maximum interstory drift demand of frame structures and a number of widely used ground motion intensity parameters. Nonlinear time–history analyses of 16 reinforced concrete frames were performed under a set of 80 ground motion records. The frames were selected to represent features of typical low- to mid-rise reinforced concrete structures. The records contained in the ground motion database were compiled from recorded ground motions with the intention to represent a wide range of seismic forces that impose various degrees of elastic as well as inelastic response of the frames. The maximum interstory drift ratios computed were compared with the ground motion intensity parameters employed and correlations between them were investigated through coefficients of correlation and determination. The results revealed that spectrum intensity parameters, having the strongest correlation, are superior to other parameters such as peak ground velocity, peak ground acceleration, and spectral acceleration.

Probabilistic structural response assessment using vector‐valued intensity measures

AbstractMethods for using scalar and vector ground motion intensity parameters to estimate the probabilistic relationship between ground motion intensity and structural response are described and compared. Options include using regression analysis on structural analysis results from a set of unscaled (or uniformly scaled) ground motions, or fitting a probability distribution to the analysis results from scaled ground motions analysed using incremental dynamic analysis and related methods. Past methods for using scalar ground motion intensity are reviewed, and methods for utilizing improved vector‐valued intensity measures (IMs) are proposed. ‘Hybrid’ estimation methods that obtain the benefit of vector‐valued IMs using simplified techniques such as careful record selection are also discussed. The results are then combined with models for ground motion occurrence obtained from probabilistic seismic hazard analysis to compute seismic reliability, and the results obtained from the various methods are compared. In general, a tradeoff must be made between the accuracy of the functional relationship between ground motion intensity and structural response versus the number of structural analyses needed for estimation. Copyright © 2007 John Wiley & Sons, Ltd.

Fragility estimation for seismically isolated nuclear structures by high confidence low probability of failure values and bi-linear regression

A method for the fragility estimation of seismically isolated nuclear power plant structure is proposed. The relationship between the ground motion intensity parameter (e.g. peak ground velocity or peak ground acceleration) and the response of isolated structures is expressed in terms of a bi-linear regression line, whose coefficients are estimated by the least-square method in terms of available data on seismic input and structural response. The notion of high confidence low probability of failure (HCLPF) value is also used for deriving compound fragility curves for coupled subsystems.