Comparing fluid viscous damper placement methods considering total‐building seismic performance

Abstract

Summary Nonstructural damage has been found to critically influence economic losses and building downtime following earthquakes. Attaining a target level of seismic performance mandates the harmonization of structural and nonstructural performance. Retrofitting buildings with fluid viscous dampers (FVDs) can improve interstorey drifts and floor accelerations, 2 structural parameters that characterize seismic demand on structural and nonstructural systems. The distribution of dampers within a building is a critical decision; however, no conclusive optimal placement method has been identified due to performance variations between storeys and between structural parameters. This paper compares 6 frequently used damper placement methods considering structural and nonstructural repair costs calculated using FEMA P‐58. The scope is limited to linear FVDs, concentric braced frames, and regular structures. Comparisons of the placement methods are based on constraining the added viscous damping coefficient to be the same in each case; this may give different results to methods based on damper cost. No placement method produced optimal results for both interstorey drifts and accelerations. Iterative methods that seek to optimize seismic performance did not achieve that objective. The iterative methods optimize local parameters assuming the performance of each is independent, and optimizing for a single parameter may worsen another parameter that impacts earthquake damage. The storey shear strain energy method and uniform damping generally produced repair costs that are more favorable than, or equal to, the other placement methods. It appears unlikely that large repair cost improvements can be achieved using an “optimal” damper placement method for low‐rise and mid‐rise structures.

Fail‐safe optimization of viscous dampers for seismic retrofitting

“…A first group consists of those approaches that rely on continuous design variables (i.e., damping coefficients). [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] This leads to optimization problems that are computationally efficient and applicable also to large-scale problems. The optimized designs attained may consist of a wide variety of different damper sizes.…”

“…These aspects led to the development of several approaches for the sizing and placement of fluid viscous dampers assisted by optimization, as recently reviewed by De Domenico et al 15 The available methodologies can be grouped based on the formulation used in the optimization problem. A first group consists of those approaches that rely on continuous design variables (i.e., damping coefficients) 16‐31 . This leads to optimization problems that are computationally efficient and applicable also to large‐scale problems.…”

Multi-level performance-based design optimisation of steel frames with nonlinear viscous dampers

“…Addionally, nowadays metaheuristics are emerged as very efficient algorithms for tackling complex optimization problems (Fattahi and Gholizadeh 2019;Hassanzadeh and Gholizadeh 2019;Ghaderi and Gholizadeh 2021). Some studies also compared different damper distributions in view of the resulting seismic performance (Hwang et al 2013;Whittle et al 2012;Aguirre et al 2013;Del Gobbo et al 2018b). A recent review paper by De summarised and classified most of the above-mentioned approaches.…”

Distributed Passive Actuation Schemes for Seismic Protection of Multibuilding Systems

“…The combined allocation-tuning problem can be formulated as a constrained optimization problem, with a set of decision variables that describes the different allocation schemes and parameter values of the damping devices, an objective function that allows evaluating the suitability of the corresponding DDSs, and a system of constraints that incorporate relevant features of the considered technical setup. To solve allocation-tuning optimization problems (ATOPs), a wide variety of computational strategies have been proposed, which include specialized optimization methods [8][9][10][11][12] and adaptations of general-purpose optimization algorithms [13][14][15]. Specialized optimization methods are specifically designed for particular kinds of ATOPs and, sometimes, can produce remarkably effective results for the considered problem.…”