The Canadian Society for Civil Engineers Annual Conference
The rapid growth of urban population and the associated environmental concerns are partly influencing city planners and construction stakeholders to consider “Sustainable Urbanization” alternatives. In this regard, recent urban design strategies are entertaining the use of “tall timber buildings.” Generally, tall mass-timber buildings (MTBs) utilize pre-engineered wood panels to form their main gravity and lateral load resisting systems, which makes them lighter and more flexible than buildings made from concrete, masonry or steel. As a result, frequent exposure to excessive wind-induced vibrations can cause occupant discomfort and possible inhabitability of the buildings. This paper attempts to apply a risk-based procedure to design a 102-meter tall MTB by adapting and extending the Alan G. Davenport Wind Loading Chain as a probabilistic performance-based wind engineering framework. The structural systems of the study building are composed of Cross Laminated Timber (CLT) shear walls, CLT floors, glulam columns, and reinforced-concrete link beams. Initially, aerodynamic wind tunnel tests were carried out at the Boundary Layer Wind Tunnel Laboratory of Western University on the 1:200 scale MTB model to obtain transient wind loads. Subsequently, using the wind tunnel data, the study MTB was structurally designed. In the riskbased performance assessment, uncertainties were incorporated at each step of the Wind Loading Chain, i.e., local wind, exposure, aerodynamics, dynamic effects, and criteria. These uncertainties were explicitly modeled as random variables. Dynamic structural analyses were carried out in the frequency domain to include the amplification due to the resonance component of the excitation. Structural reliability analysis through Monte Carlo sampling was used to propagate the uncertainties through the Wind Loading Chain to quantify the risk of inhabitability and excessive deflection. The results of reliability analysis were used to develop fragility curves for wind vulnerability estimations. Based on the results, the effects of various uncertainties are discussed, and risk-based design decisions are forwarded.