Vector-IM-based assessment of alternative framing systems under bi-directional ground-motion

This paper examines the seismic performance of steel buildings with alternative framing systems subjected to bi-directional ground-motion. Peak drifts of one-way (perimeter framing) and two-way (space framing) systems are assessed by means of scalar and vector-valued probabilistic methods. Extensive non-linear response history analyses over idealized 3D structures representing 6- and 9-storey buildings are performed under pairs of linearly scaled ground-motions. Both far-field and near-field non-pulselike acceleration series are considered. The spectral acceleration of the geometric mean of the two horizontal components (Sa,GM) is taken as the primary intensity measure (IM) while four other ground-motion parameters are employed to construct IM-vectors including: the spectral acceleration ratio (RT3,T1), the spectral shape parameter (Np), and two frequency content parameters (Tm and To). This paper shows that incorporating the vector ⟨Sa,GM,Np⟩ into the assessment of bi-directionally loaded 3D buildings yields up to 40 % lower conditional standard deviations than a purely scalar formulation at large drift levels while the vector ⟨Sa,GM, RT3,T1⟩ is more efficient at smaller drifts. The effects of alternative framing systems on structural fragilities are found to differ depending on the number of storeys. For 6-storey structures, consistently higher capacities are observed in two-way layouts with respect to one-way systems but they are associated with increasing variabilities at larger demand levels. Conversely, the 9-storey two-way building experiences 5 % lower mean capacities than its one-way counterpart. Finally, drift hazard curves are calculated by combining the building fragilities with idealized ground-motion hazard estimates. The results indicate that one-way buildings experience consistently lower drift exceedance rates regardless of the ground-motion type, especially for drift levels larger than 2 % although the differences are larger for the 9-storey frames in comparison with their 6-storey counterparts. This study represents a first attempt to implement vector-valued analysis in the context of bi-directionally loaded structures and its results constitute an important step towards discerning the most favourable framing system at different seismic performance levels

Seismic control of rocking structures via external resonators

Tall rigid blocks are prevalent in ancient historical constructions. Such structures are prone to rocking behaviour under strong ground motion, which is recognisably challenging to predict and mitigate. Our study is motivated by the need to provide innovative non-intrusive solutions to attenuate the rocking response of historical buildings and monuments. In this paper, we examine a novel scheme that employs external resonators buried next to the rocking structure as a means to control its seis- mic response. The strategy capitalizes on the vibration absorbing potential of the structure-soil-resonator interaction. Advanced numerical analyses of discrete mod- els under coherent acceleration pulses with rocking bodies of different slenderness ratios under various ground motion intensities highlight the significant vibration absorbing qualities of the external resonating system. The influence of key system parameters such as the mass, stiffness and damping of the resonator and those of the soil-structure-resonator arrangement are studied. Finally, a case study on the evaluation of the response of rocking structures with external resonators under real pulse-like ground-motion records confirms the important reductions in peak seismic rotational demands obtained with the proposed arrangement

Seismic shear and acceleration demands in multi-storey cross-laminated timber buildings

A realistic estimation of seismic shear demands is essential for the design and assessment of multi-storey buildings and for ensuring the activation of ductile failure modes during strong ground-motion. Likewise, the evaluation of seismic floor accelerations is fundamental to the appraisal of damage to non-structural elements and building contents. Given the relative novelty of tall timber buildings and their increasing popularity, a rigorous evaluation of their shear and acceleration demands is all the more critical and timely. For this purpose, this paper investigates the scaling of seismic shear and acceleration demands in multi- storey cross-laminated timber (CLT) buildings and its dependency on various structural properties. Special attention is given to the influence of the frequency content of the ground-motion. A set of 60 CLT buildings of varying heights representative of a wide range of structural configurations is subjected to a large dataset of 1656 real earthquake records. It is demonstrated that the mean period (Tm) of the ground-motion together with salient structural parameters such as building aspect ratio (λ), design force reduction factor (q) and panel subdivision (β) influence strongly the variation of base shear, storey shears and acceleration demands. Besides, robust regression models are used to assess and quantify the distribution of force and acceleration demands on CLT buildings. Finally, practical expressions for the estimation of base shears, inter-storey shears and peak floor accelerations are offered

Interpretable machine learning models for the estimation of seismic drifts in CLT buildings

An accurate estimation of drift demands is crucial for designing and assessing structures under seismic loads. Given the novelty of massive timber buildings, predictive models for the estimation of drifts in mid- to high-rise CLT structures are lacking, particularly in the form of simple models suitable for preliminary design evaluations or regional seismic assessments. In this paper, we present and compare several Machine Learning (ML) models for the estimation of peak inter-storey and roof drifts in multi-storey Cross-Laminated Timber (CLT) walled structures. The ML techniques used include: Multiple Linear Regression, Regression Trees, Random Forest, K-nearest Neighbour, and Support Vector Regression. To this end, 69 structures spanning mid-rise to tall timber buildings are subjected to a large collection of acceleration records and used to create the training and testing datasets. Different structural configurations and behaviour factors, related to the assumed energy dissipation capacity of the buildings, are considered. A diversity of feature selection techniques informs our choice of parameters to the reduced input space leading to a set of six most efficient features: the spectral acceleration at the building’s fundamental period (Sa(T1)), the Peak Ground Velocity (PGV), tuning ratio (T1/Tm), behaviour factor (q), wall height (Hw), and the wall subdivision ratio (Wr). After verifying the high accuracy of our model predictions, the SHapley Additive exPlanation method (SHAP) is used to gain insight into the influence of key input features on the ML model outputs. Finally, our ML drift estimations are compared against previous proposals and design code assumptions, and the potential causes of disagreement are discussed