S T G Raghukanth

A novel methodology for obtaining a seismic zone map of India is demonstrated in this study, wherein a concrete theoretical framework is provided for deriving the zones and the respective zonal response spectra. The method involves time series clustering of uniform hazard response spectra (UHRS) that were obtained for the entire country on a 0.1° × 0.1° grid by performing probabilistic analysis corresponding to a 2475-year return period. The Euclidean distance between the UHRS values at all periods (27 data points between 0.01 s and 5 s) was taken as the similarity measure in an evolutionary particle swarm optimization algorithm. The analysis was conducted with a swarm population of 100 over 3000 iterations, and the mean UHRS of the resulting clusters was assumed as the cluster centre. Various quality/validity indices including the compactness measure, similarity measure, combined measure and Dunn Index were used to verify the results of the clustering. Based on these clusters, the entire country can be divided into seven zones, with a unique zonal spectrum for each zone.

In the current study, ground motion models (GMMs) are derived using the European Strong Motion (ESM) database for pseudo-spectral acceleration (PSA), peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement (PGD), cumulative absolute velocity (CAV), arias intensity (Ia), and significant duration. In addition to addressing random effects associated with ground motion regression, such as inter-event, inter-site, inter-locality, and inter-region variabilities, the current study also aims at reducing the standard deviations (STDs) of the GMMs through development of a hybrid non-parametric GMM. The hybrid model is derived through an ensemble-weighted method of five non-parametric machine learning models: shallow neural network, deep neural network (DNN), gated recurrent unit (GRU), support vector, and random forest (RF) regression techniques; with weights based on model performances. The resulting hybrid model, which also accounts for epistemic uncertainty, is compared against other regional models and is found superior for all output variables. The inter-event, inter-site, inter-locality, and inter-region deviations, and total ergodic sigma of PSA for the ensemble model lies between 0.3164–0.4478, 0.4156–0.5339, 0.1449–0.3687, 0.0819–0.2421, and 0.668–0.8545, respectively. The coefficient of determination (R2) between predicted and recorded values lies between 0.8435–0.9114 for all the output variables.

The 2011 great Japan Tohoku earthquake is not only the most devastating but also, one of the best recorded earthquakes in the history of seismology. A thorough study of strong motion characteristics of this earthquake is conducted using 20 well established ground motion parameters (GMPs). The behaviour of these parameters with fault distance and average shear wave velocity is examined and attenuation relationships are developed using the 1172 surface level strong motion records. In addition, all GMPs are categorized on a statistical basis using principal component analysis, which is further used to rate the damage potential of ground motion records.

The present study aims at developing a ground motion model (GMM) for the 5% damped horizontal spectral acceleration, using regression analysis of strong motion records available for the Western Himalayan region. In addition to developing a model using just the regional data, the study also explores three different methods to derive a GMM that can circumvent the limitation of near field data shortage in the Himalayas. The alternatives explored in this study include calibrating a global model to the regional dataset; deriving a GMM by appending a dense near field foreign dataset to that of the regional data; and deriving a near source correction factor to the regional model. These models are applicable for shallow crustal earthquakes of magnitudes between Mw 4.0–7.9 and depth up to 45 km over distances up to 960 km. The efficacy of each of these models is established through comparison with the recorded data and with other regional GMMs. Moreover, the best model among the four proposed GMMs is verified through derivation of rankings based on quantitative analysis of residuals that were obtained between the observations and the respective estimates.

The 25th April 2015 Nepal earthquake was the first major event in the Himalayan orogeny to provide a relatively well-recorded dataset. This paper presents a comprehensive analysis of the mainshock and its five major aftershocks through 21 well-established ground motion parameters. The analysis is presented for near-field stations of the Kathmandu basin and far-field stations of the Indo-Ganga Plains, including the site response behavior with varying sediment depths. Moreover, Hilbert–Huang Transform is used to study site amplifications associated with sediment depth and soil class, especially at long periods. In addition, a new ground motion model (GMM) is derived for all 21 parameters using moment magnitude, source-to-site distance, site class and sediment depth as predictor variables. Further, to ensure that the developed GMM is not biased, an inter-event and intra-event residual analysis is performed. Furthermore, the GMM is compared with other well-established prediction models applicable to the study region. The efficacy of the current model is further addressed by the evaluation of ranking indices.

Peak ground motions and spectral accelerations estimated from the prediction equations are highly significant in earthquake hazard studies. Recently, these predictive relationships developed for higher-order parameters obtained paramount importance as they describe different ground motion characteristics. The northeastern region of India experiences extreme seismicity due to the Indian plate subduction under the South Asian plate. However, only a few ground motion prediction equations (GMPEs) are available for such tectonic environments due to insufficient ground motion data. In this regard, it is noticed that the tectonic environment experienced by New Zealand is similar to that of northeast India. So, in this paper, two GMPE models for New Zealand are developed with the help of the artificial neural network (ANN) technique using the GeoNet database. Model-1 corresponds to various higher-order parameters, whereas model-2 developed for spectral accelerations (Sa) between 0.01 and 5s. Further, these models are compared against global and region-specific GMPEs. The developed models shows good agreement with other GMPEs and the data but slightly over predicts at distances greater than 300 km. Additional consideration of site-to-site variability in the current models reduced the total standard deviations of model-1 by 19–22 % and model-2 by 20%–23 %. Further, the estimates of these developed models are compared with some of the significant earthquakes in northeast India, and from these results, it is concluded that the current models can be adapted in such regions to estimate ground motion.

This paper presents the results of a study on the characteristics of vertical-to-horizontal ratio (V/H) of 5% damped acceleration spectra for Indian ground motion records. Preliminary analysis indicates that at least 50% of the records exceed the Indian seismic design code considered norm of 2/3 at both the short and long period ranges. In addition, currently there are no V/H spectral ratio models available for India and the global models do not capture the trend across all the periods efficiently. Therefore, new ground motion models for the V/H spectral ratio are derived for two of the active tectonic regions of India: the Western Himalayas and the North-East India. Moment magnitude, focal depth, distance, site soil class, and focal mechanism are considered while deriving these models for a wide range of spectral periods (0.01–10s). The goodness of these models is verified through comparison with other globally available V/H models.

A nonlinear dynamic analysis method in earthquake-resistant design requires real-time ground motion records. However, a definite criterion is required for ground motion selection. In the present study, a damage potential measure ‘distance from zero-amplitude axis (dZ-A)’ is developed through multivariate analysis of 21 different ground motion parameters for ground motion rating. These 21 parameters include peak ground acceleration, peak ground velocity, arias intensity, acceleration spectrum intensity, significant duration, predominant period, etc. along with moment magnitude, site class and hypocentral distance. The analysis is carried out in an orthogonal principal component space, using 433 Indian ground motions, recorded over magnitudes of Mw 4.5–7.2. Further, the goodness of dZ-A is validated through comparison with MMI values.

Amplitude, duration and frequency content are the three key characteristics of a ground motion time history. Few ground motion parameters quantifies two and rarely three of these features. There are even fewer ground motion prediction equations (GMPEs) available for these ground motion parameters. In this study, new GMPEs are derived for a total of 21 parameters representing peak amplitude, energy, intensity, frequency, duration and evolutionary characteristics of a ground motion acceleration time history. An extensive dataset of Japan, comprising 96880 ground motions with magnitudes ranging from M w 5.0 to M w 9.0 is used to calibrate the model. The model includes the effects of magnitude saturation, tectonic source mechanism, focal mechanism, geometric and anelastic attenuation, volcanic arc and site effects. Median results of estimates are compared against recorded data of the twin Kumamoto earthquakes of M w 7.3 and 6.5. These results are also compared against previously developed GMPEs of the region. Further, towards the verification of the functional form, behavior of inter and intra event residuals is verified against magnitude (M w ), distance and shear wave velocity (V s30 ) respectively.

According to the current Indian Standard earthquake-resistant design code (IS 1893, 2016), the vertical design spectrum is assumed as two-thirds of the horizontal spectrum. However, a previous investigation of the Indian ground motion records suggests that the vertical spectra exceeded the horizontal in many instances, which would render the previous consideration inadequate. Therefore, the current study aims at developing an appropriate recommendation for obtaining vertical design spectra, through development of hazard consistent vertical design spectra for the active regions of India. The vertical design spectrum is generated through scaling of a weighted average vertical-to-horizontal ratio (V/H) ground motion prediction equation (GMPE) to the horizontal component of the uniform hazard spectrum. The uniform hazard spectrum is obtained for the two active regions of India– the Western Himalayas and the North East India through probabilistic seismic hazard analysis and the weighted average V/H model is obtained by combining the V/H GMPE developed for India with several global models. Based on the proposed relations, a structural engineer can obtain site-specific vertical design spectra with ease and accuracy.