Life-cycle cost optimal design of passive dissipative devices

The cost-effective performance of structures under natural hazards such as earthquakes and hurricanes has long been recognized to be an important topic in the design of civil engineering systems. A realistic comprehensive treatment of such a design requires proper integration of (i) methodologies for treating the uncertainties related to natural hazards and to the structural behavior over the entire life-cycle of the building, (ii) tools for evaluating the performance using socioeconomic criteria, as well as (iii) algorithms appropriate for stochastic analysis and optimization. A systematic probabilistic framework is presented here for detailed estimation and optimization of the life-cycle cost of engineering systems. This framework is a general one but the application of interest here is the design of passive dissipative devices for seismic risk mitigation. A comprehensive methodology is initially presented for earthquake loss estimation; this methodology uses the nonlinear time-history response of the structure under a given excitation to estimate the damage in a detailed, component level. A realistic probabilistic model is then presented for describing the ground motion time history for future earthquake excitations. In this setting, the life-cycle cost is uncertain and can be quantified by its expected value over the space of the uncertain parameters for the structural and excitation models. Because of the complexity of these models, calculation of this expected value is performed using stochastic simulation techniques. This approach, though, involves an unavoidable estimation error and significant computational cost, features which make efficient design optimization challenging. A highly efficient framework, consisting of two stages, is discussed for this stochastic optimization. An illustrative example is presented that shows the efficiency of the proposed methodology; it considers the seismic retrofitting of a four-story non-ductile reinforced-concrete building with viscous dampers.

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

[2]  Peter Kall,et al.  Stochastic Programming , 1995 .

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

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

[5]  Hyun-Moo Koh,et al.  Integrated optimum design of viscoelastically damped structural systems , 2004 .

[6]  Judith Mitrani-Reiser,et al.  AN OUNCE OF PREVENTION: PROBABILISTIC LOSS ESTIMATION FOR PERFORMANCE - BASED EARTHQUAKE ENGINEERING , 2007 .

[7]  Gerhart I. Schuëller,et al.  Reliability-Based Optimization of structural systems , 1997, Math. Methods Oper. Res..

[8]  J. Beck,et al.  Important sampling in high dimensions , 2003 .

[9]  R. T. Cox Probability, frequency and reasonable expectation , 1990 .

[10]  C. Cornell,et al.  Disaggregation of seismic hazard , 1999 .

[11]  Min Liu,et al.  Optimal seismic design of steel frame buildings based on life cycle cost considerations , 2003 .

[12]  Johannes O. Royset,et al.  Efficient sample sizes in stochastic nonlinear programming , 2008 .

[13]  E. Jaynes Probability theory : the logic of science , 2003 .

[14]  Dimos C. Charmpis,et al.  Application of line sampling simulation method to reliability benchmark problems , 2007 .

[15]  R. T. Cox The Algebra of Probable Inference , 1962 .

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

[17]  Robert V. Whitman,et al.  HAZUS Earthquake Loss Estimation Methods , 2006 .

[18]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[19]  Dan M. Frangopol,et al.  Life-cycle reliability-based maintenance cost optimization of deteriorating structures with emphasis on bridges , 2003 .

[20]  Siu-Kui Au,et al.  Effect of Seismic Risk on Lifetime Property Value , 2004 .

[21]  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 .

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

[23]  James L. Beck,et al.  SUBSET SIMULATION AND ITS APPLICATION TO SEISMIC RISK BASED ON DYNAMIC ANALYSIS , 2003 .

[24]  J. Beck,et al.  Updating Models and Their Uncertainties. I: Bayesian Statistical Framework , 1998 .

[25]  Manolis Papadrakakis,et al.  Performance-based multiobjective optimum design of steel structures considering life-cycle cost , 2006 .

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

[27]  J. Beck,et al.  A new adaptive importance sampling scheme for reliability calculations , 1999 .

[28]  J. Baker,et al.  A vector‐valued ground motion intensity measure consisting of spectral acceleration and epsilon , 2005 .

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

[30]  Alexandros Angelos Taflanidis,et al.  Stochastic System Design and Applications to Stochastically Robust Structural Control , 2007 .

[31]  John Dalsgaard Sørensen,et al.  Reliability-Based Optimization in Structural Engineering , 1994 .

[32]  G. Calafiore,et al.  Probabilistic and Randomized Methods for Design under Uncertainty , 2006 .

[33]  David M. Boore,et al.  Site amplifications for generic rock sites , 1997, Bulletin of the Seismological Society of America.

[34]  Wilfred D. Iwan,et al.  A model for system identification of degrading structures , 1986 .

[35]  J. Spall,et al.  Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers , 1999 .

[36]  Alfredo H-S. Ang,et al.  Cost optimal design of R/C buildings , 2001, Reliab. Eng. Syst. Saf..

[37]  Fatemeh Jalayer,et al.  Effects of two alternative representations of ground‐motion uncertainty on probabilistic seismic demand assessment of structures , 2008 .