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Calibration of Structural Models Using Fuzzy Mathematics
Author(s) -
WadiaFascetti Sara,
Smith H. Allison
Publication year - 1996
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.1996.tb00306.x
Subject(s) - a priori and a posteriori , calibration , fuzzy logic , identification (biology) , fuzzy set , stiffness , set (abstract data type) , computer science , structural system , system identification , algorithm , mathematics , vibration , data mining , engineering , statistics , artificial intelligence , structural engineering , philosophy , botany , physics , epistemology , quantum mechanics , measure (data warehouse) , biology , programming language
A calibration model is presented that quantifies the uncertainties associated with structural free vibration analysis. System identification objectives and fuzzy set mathematics are integrated to formulate an analysis methodology that enables the a priori prediction of the most probable sources of modeling error. By first developing fundamental fuzzy sets defining uncertainty in structural parameters such as stiffness and design loading, higher‐level fuzzy sets governing dynamic behavior are obtained using the vertex method. Uncertainty in the dynamic parameters (natural frequency, frequency ratio, and structural response) are each represented using fuzzy mathematics, where membership functions are determined by performing multiple dynamic analyses involving confidence levels of model assumptions. A numerical example is presented to demonstrate the calibration model for a 13‐story steel structure located in San Jose, California. Results show that the calibration model is capable of quantifying uncertainties in structural properties and behavior without requiring the measured data necessary for conventional system identification procedures.