Efficiency of tuned mass dampers with uncertain parameters on the performance of structures under stochastic excitation

Abstract Tuned mass dampers serve the purpose of damping vibrations of structures such as earthquake-induced vibrations. In their design, two types of uncertainty are relevant: the stochastic excitation (e.g. earthquake record) and the inherent uncertainty of internal parameters of the devices themselves. This paper presents a new framework that admits the combination of stochastic processes and interval-type parameter uncertainty, modelled by random sets. The approach is applied to show how the efficiency of tuned mass dampers can be realistically assessed in the presence of uncertainty.

[1]  Armando Mammino,et al.  Reliability analysis of rock mass response by means of Random Set Theory , 2000, Reliab. Eng. Syst. Saf..

[2]  G. B. Warburton,et al.  Minimizing structural vibrations with absorbers , 1980 .

[3]  Yozo Fujino,et al.  Optimal tuned mass damper for seismic applications and practical design formulas , 2008 .

[4]  Aihong Ren,et al.  Representation theorems, set-valued and fuzzy set-valued Ito integral , 2007, Fuzzy Sets Syst..

[5]  Armando Mammino,et al.  Determination of parameters range in rock engineering by means of Random Set Theory , 2000, Reliab. Eng. Syst. Saf..

[6]  Bernhard Schmelzer On solutions of stochastic differential equations with parameters modeled by random sets , 2010, Int. J. Approx. Reason..

[7]  Mehdi Setareh,et al.  TMDs for Vibration Control of Systems with Uncertain Properties , 1992 .

[8]  Michael Oberguggenberger,et al.  The mathematics of uncertainty: models, methods and interpretations , 2005 .

[9]  Nam Hoang,et al.  Design of multiple tuned mass dampers by using a numerical optimizer , 2005 .

[10]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[11]  P. Kloeden,et al.  Numerical Solution of Stochastic Differential Equations , 1992 .

[12]  T. T. Soong,et al.  Passive Energy Dissipation Systems in Structural Engineering , 1997 .

[13]  Wolfgang Fellin,et al.  Reliability bounds through random sets , 2008 .

[14]  Michael Oberguggenberger,et al.  Propagation of uncertainty through multivariate functions in the framework of sets of probability measures , 2004, Reliab. Eng. Syst. Saf..

[15]  Michael Oberguggenberger,et al.  Classical and imprecise probability methods for sensitivity analysis in engineering: A case study , 2009, Int. J. Approx. Reason..

[16]  Yen-Po Wang,et al.  Optimal design theories and applications of tuned mass dampers , 2006 .

[17]  B. F. Spencer,et al.  Active Structural Control: Theory and Practice , 1992 .

[18]  J. Kim,et al.  On Set-Valued Stochastic Integrals , 2003 .

[19]  Jungang Li,et al.  Set-Valued Stochastic Lebesgue Integral And Representation Theorems , 2008, Int. J. Comput. Intell. Syst..

[20]  Ioannis Karatzas,et al.  Brownian Motion and Stochastic Calculus , 1987 .

[21]  C. Adam,et al.  Seismic Performance of Tuned Mass Dampers , 2010 .

[22]  Hung T. Nguyen,et al.  Fuzziness and randomness , 2002 .

[23]  D. Williams STOCHASTIC DIFFERENTIAL EQUATIONS: THEORY AND APPLICATIONS , 1976 .

[24]  Eva Rubio,et al.  Random sets of probability measures in slope hydrology and stability analysis , 2004 .

[25]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.