The contribution of steel wallposts to out-of-plane behavior of non-structural masonry walls

For years,non-structural masonry walls have received little attention by code developers and professional engineers.Recently,significant efforts have been made to shed more light on out-of-plane(OOP)behavior of non-structural masonry walls.In updated provisions of the Iranian seismic code,bed joint reinforcements(BJRs)and steel wallposts have been suggested for use.BJRs are horizontal reinforcements;steel wallposts are vertical truss-like elements intended to provide additional OOP restraints for a wall.The contribution of BJRs has previously been investigated by the authors.This study is devoted to investigating the contribution of steel wallposts to the OOP behavior of non-structural masonry walls.Using pre-validated 3D finite element(FE)models,the OOP behavior of 180 non-structural masonry walls with varying configurations and details are investigated.The OOP pressure-displacement curve,ultimate strength,the response modification factor,and the cracking pattern are among the results presented in this study.It is found that steel wallposts,especially those with higher rigidity,can improve the OOP strength of the walls.The contribution of wallposts in the case of shorter length walls and walls with an opening are more pronounced.Results also indicate that masonry walls with wallpost generally have smaller modification factors compared to similar walls without wallpost.

Prediction of seismic collapse risk of steel moment frame mid-rise structures by meta-heuristic algorithms

Different performance levels may be obtained for sideway collapse evaluation of steel moment frames depending on the evaluation procedure used to handle uncertainties. In this article, the process of representing modelling uncertainties, record to record （RTR） variations and cognitive uncertainties for moment resisting steel frames of various heights is discussed in detail. RTR uncertainty is used by incremental dynamic analysis （IDA）, modelling uncertainties are considered through backbone curves and hysteresis loops of component, and cognitive uncertainty is presented in three levels of material quality. IDA is used to evaluate RTR uncertainty based on strong ground motion records selected by the k-means algorithm, which is favoured over Monte Carlo selection due to its time saving appeal. Analytical equations of the Response Surface Method are obtained through IDA results by the Cuckoo algorithm, which predicts the mean and standard deviation of the collapse fragility curve. The Takagi-Sugeno-Kang model is used to represent material quality based on the response surface coefficients. Finally, collapse fragility curves with the various sources of uncertainties mentioned are derived through a large number of material quality values and meta variables inferred by the Takagi-Sugeno-Kang fuzzy model based on response surface method coefficients. It is concluded that a better risk management strategy in countries where material quality control is weak, is to account for cognitive uncertainties in fragility curves and the mean annual frequency.