The structural response of buildings to earthquake shaking is of critical importance for seismic design purposes. Research on the relationship between earthquake ground motion intensity, building response, and seismic risk is ongoing, but not yet fully conclusive. Often, probability demand models rely on one ground motion intensity measure (IM) to predict the engineering demand parameter (EDP). The engineering community has suggested several IMs to account for different ground motion characteristics, but there is no single optimal IM. For this study, we compile a comprehensive list of IMs and their characteristics to assist engineers in making an informed decision. We discuss the ground motion selection process used for dynamic analysis of structural systems. For illustration, we compute building responses of 2D frames with different natural period subjected to more than 3500 recorded earthquake ground motions. Using our analysis, we examine the effects of different structural characteristics and seismological parameters on EDP-IM relationships by applying multi-regression models and statistical inter-model comparisons. As such, our results support and augment previous studies and suggest further improvements on the relationship between EDP and IM in terms of efficiency and sufficiency. Finally, we provide guidance on future approaches to the selection of both optimal intensity measures and ground motions using newer techniques.

<p>Seismic hazards analysis relies on accurate knowledge of ground motions arising from potential earthquakes to assess the risk of damage to buildings and infrastructure. It is necessary to perform ground motion simulations because recorded strong-motion data from specific combinations of earthquake magnitudes, epicentral distances, and site conditions are still limited. Physics-based simulations provide reliable ground motion estimates, but their application in practice is limited to frequency ranges f < 1Hz, largely due to limited computational resources and lack of information regarding earthquake sources and medium. While hybrid ground-motion computations combining deterministic low frequency components with stochastic high frequency components are often used,  their stochastic high frequency components fail to correctly account for source and path effects and lead to inconsistent building responses.</p> <p>The large database of ground motion records from Japan lends itself to develop machine learning approaches to estimate high frequency ground motions. Applying state-of-the-art machine learning techniques, like Fourier neural operators (FNOs) and Generative Adversarial Networks (GANs), we estimate seismograms at higher frequencies from their low frequency counterparts. In our approach, the time and frequency properties of ground motions are estimated using two different FNO models. In the time domain, a relationship is established between normalised low pass filtered and broadband waveforms. Frequency domain analysis involves the learning of high frequency spectrum from low frequency spectrum. Finally, the time and frequency properties are combined to produce broadband ground motions. Source, site, and path aspects are naturally incorporated into the training process.</p> <p>We use ground motion data collected between 1996 and 2020 at 18 stations in the Ibaraki province of Japan to train our models and validate them on different events (Mw 4 to 7) around Japan. Using goodness of fit measures (GOFs), we show that the resulting ground motions match the recorded observations with good to acceptable GOF values for most of the predictions. To enhance our predictions, we include uncertainty estimation by utilizing a conditioned GAN approach. Lastly, to demonstrate the practicality of the approach, we compute high frequency components for a physics based simulated hypothetical Mw 5.0 earthquake in Japan.</p>

Unreinforced masonry (URM) structures comprise over 60% of the building stock of India. URM structures are highly vulnerable under earthquake loads. Their seismic behaviour is highly complex due to the non-linear and composite nature of masonry which comprises brick units, mortar and the unit-mortar interface. Experimental studies on URM walls with openings are inadequate with varying experimental procedures. In this paper, a two-dimensional unreinforced masonry wall with a central window opening is subjected to an in-plane lateral pushover loading. For modelling bricks, three material models are used, namely the linear-elastic model, the engineering masonry model and the total strain crack model. For modelling the interface, four approaches are used, namely the linear-elastic model, the combined cracking-shearing-crushing plastic material model, the Coulomb friction model and the no-tension nonlinear elastic model. The pushover curves indicate the significant effect of the opening on the capacity of the URM wall. The stress contours obtained from the various methods predict the crack pattern and modes of failure. These results are analysed to discuss the effect of the material models and interface properties on the results obtained from the numerical modelling. The results indicate that the selection of the micro-modelling technique for numerical modelling of URM walls has a significant influence on the observed strength, stiffness and ductility characteristics.

<p>Two powerful earthquakes (magnitudes 7.8 and 7.6) struck south-central Türkiye on February 6, 2023, causing significant damage across an extensive area of at least ten provinces in Türkiye as well as in multiple cities in northwestern Syria, making them one of the deadliest earthquakes in Türkiye for multiple centuries. The first mainshock started close to the well-known East Anatolian Fault (EAF) and then rupturing more than 300 km of that fault, whereas the second large earthquake occurred nine hours later around 90 km north of the first mainshock, on an east-west trending fault. In this study, we analysed recorded strong ground motions from the two events to better understand the factors contributing to the devastation caused by the earthquakes.</p> <p> </p> <p>For this, we collected 250 and 200 strong ground motion records for the first and the second event, respectively, from the Disaster and Emergency Management Authority (AFAD) in Türkiye. Maximum peak ground accelerations (PGA) of 2g were observed at a distance of 31 km northeast of the first mainshock epicenter and 0.6g for the second event 65km west to its epicenter. In addition, we find particularly high amplitude ground motions in the Hatay province for the first event, which is consistent with the extent of damage reported in that region. High shaking levels in Antakya and other parts of Hatay can be explained by a combination of strong directivity and local site effects.</p> <p> </p> <p>The results of our analysis imply that the PGA values derived from two local ground motion models (GMMs), adopted for the 2018 Turkish hazard map, are underestimated in comparison to observed strong motion recordings. In addition, we also compared observed peak and spectral ground motion characteristics with estimated seismic hazard values (10% probability to exceed in 50 years) in the East Anatolian Fault region (extracted from the 2018 Turkish seismic hazard map). Furthermore, we compare the recorded response spectra with the Turkish design code for several locations around the main faults.  The results show that the observations greatly exceed the hazard values and code guidelines in the Hatay province.</p>