Performance assessment and optimization of fluid viscous dampers through life-cycle cost criteria and comparison to alternative design approaches

The performance assessment and optimal design of fluid viscous dampers through life-cycle cost criteria is discussed in this paper. A probabilistic, simulation-based framework is described for estimating the life-cycle cost and a stochastic search approach is developed to support an efficient optimization under different design scenarios (corresponding to different seismicity characteristics). Earthquake losses are estimated using an assembly-based vulnerability approach utilizing the nonlinear dynamic response of the structure whereas a point source stochastic ground motion model, extended here to address near-fault pulse effects, is adopted to describe the seismic hazard. Stochastic simulation is utilized for estimation of all the necessary probabilistic quantities, and for reducing the computational burden a surrogate modeling methodology is integrated within the framework. Two simplified design approaches are also examined, the first considering the optimization of the stationary response, utilizing statistical linearization to address nonlinear damper characteristics, and the second adopting an equivalent lateral force procedure that defines a targeted damping ratio for the structure. These designs are compared against the optimal life-cycle cost one, whereas a compatible comparison is facilitated by establishing an appropriate connection between the seismic input required for the simplified designs and the probabilistic earthquake hazard model. As an illustrative example, the retrofitting of a three-story reinforced concrete office building with nonlinear dampers is considered.

[1]  Anne S. Kiremidjian,et al.  Assembly-Based Vulnerability of Buildings and Its Use in Performance Evaluation , 2001 .

[2]  Andrew S. Whittaker,et al.  Energy dissipation systems for seismic applications: Current practice and recent developments , 2008 .

[3]  James L. Beck,et al.  Probabilistically robust nonlinear design of control systems for base‐isolated structures , 2008 .

[4]  G. Schuëller,et al.  Equivalent linearization and Monte Carlo simulation in stochastic dynamics , 2003 .

[5]  Jonathan D. Bray,et al.  Empirical attenuation relationship for Arias Intensity , 2003 .

[6]  Anil K. Chopra,et al.  Earthquake response of elastic SDF systems with non‐linear fluid viscous dampers , 2002 .

[7]  Mayssa Dabaghi,et al.  Stochastic simulation of near-fault ground motions for specified earthquake and site characteristics , 2011 .

[8]  James L. Beck,et al.  Life-cycle cost optimal design of passive dissipative devices , 2009 .

[9]  W. Silva,et al.  Stochastic Modeling of California Ground Motions , 2000 .

[10]  Izuru Takewaki Building Control with Passive Dampers: Optimal Performance-based Design for Earthquakes , 2009 .

[11]  Mahendra P. Singh,et al.  Optimal placement of dampers for passive response control , 2002 .

[12]  Diego Lo´pez Garci´a A Simple Method for the Design of Optimal Damper Configurations in MDOF Structures , 2001 .

[13]  Shih-sheng Paul Lai,et al.  Statistical characterization of strong ground motions using power spectral density function , 1982 .

[14]  William T. Holmes,et al.  The 1997 NEHRP Recommended Provisions for Seismic Regulations for New Buildings and Other Structures , 2000 .

[15]  M. D. Martínez-Rodrigo,et al.  An optimum retrofit strategy for moment resisting frames with nonlinear viscous dampers for seismic applications , 2003 .

[16]  G. Atkinson,et al.  Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 s and 10.0 s , 2008 .

[17]  Søren Nymand Lophaven,et al.  DACE - A Matlab Kriging Toolbox , 2002 .

[18]  Martin S. Williams,et al.  A Comparison of Viscous Damper Placement Methods for Improving Seismic Building Design , 2012 .

[19]  D. P. Taylor,et al.  Viscous damper development and future trends , 2001 .

[20]  Alexandros A. Taflanidis,et al.  Life-cycle seismic loss estimation and global sensitivity analysis based on stochastic ground motion modeling , 2013 .

[21]  Donald R. Jones,et al.  A Taxonomy of Global Optimization Methods Based on Response Surfaces , 2001, J. Glob. Optim..

[22]  George P. Mavroeidis,et al.  A Mathematical Representation of Near-Fault Ground Motions , 2003 .

[23]  James L. Beck,et al.  An efficient framework for optimal robust stochastic system design using stochastic simulation , 2008 .

[24]  James C. Spall,et al.  Introduction to stochastic search and optimization - estimation, simulation, and control , 2003, Wiley-Interscience series in discrete mathematics and optimization.

[25]  David M. Boore,et al.  Estimating Unknown Input Parameters when Implementing the NGA Ground-Motion Prediction Equations in Engineering Practice , 2011 .

[26]  A. Chu,et al.  Multiple linear regression models to fit magnitude using rupture length, rupture width, rupture area, and surface displacement , 2015 .

[27]  M. Di Paola,et al.  Stochastic seismic analysis of MDOF structures with nonlinear viscous dampers , 2009 .

[28]  Oded Amir,et al.  Simultaneous topology and sizing optimization of viscous dampers in seismic retrofitting of 3D irregular frame structures , 2014 .

[29]  Alexandros A. Taflanidis,et al.  Kriging metamodeling for approximation of high-dimensional wave and surge responses in real-time storm/hurricane risk assessment , 2013 .

[30]  S. Kramer Geotechnical Earthquake Engineering , 1996 .

[31]  Jonathan P. Stewart,et al.  Evaluation of the seismic performance of a code‐conforming reinforced‐concrete frame building—from seismic hazard to collapse safety and economic losses , 2007 .

[32]  Andrew S. Whittaker,et al.  Evaluation of Simplified Methods of Analysis of Yielding Structures with Damping Systems , 2002 .

[33]  Erik H. Vanmarcke,et al.  Strong-motion duration and RMS amplitude of earthquake records , 1980 .

[34]  Shahram Sarkani,et al.  Random Vibrations: Analysis of Structural and Mechanical Systems , 2003 .

[35]  Alexandros A. Taflanidis,et al.  Parsimonious modeling of hysteretic structural response in earthquake engineering: Calibration/validation and implementation in probabilistic risk assessment , 2013 .

[36]  D. Wells,et al.  New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement , 1994, Bulletin of the Seismological Society of America.

[37]  Andrew S. Whittaker,et al.  Equivalent Lateral Force and Modal Analysis Procedures of the 2000 NEHRP Provisions for Buildings with Damping Systems , 2003 .

[38]  Oren Lavan,et al.  Optimal design of supplemental viscous dampers for irregular shear‐frames in the presence of yielding , 2005 .

[39]  James L. Beck,et al.  Sensitivity of Building Loss Estimates to Major Uncertain Variables , 2002 .

[40]  David M. Boore,et al.  Simulation of Ground Motion Using the Stochastic Method , 2003 .

[41]  Alexandros A. Taflanidis,et al.  Performance measures and optimal design of linear structural systems under stochastic stationary excitation , 2010 .

[42]  Jack W. Baker,et al.  An Empirically Calibrated Framework for Including the Effects of Near-Fault Directivity in Probabilistic Seismic Hazard Analysis , 2011 .