Data-driven SIRMs-connected FIS for prediction of external tendon stress

作者：Lau See Hung^*; Ng Chee Khoon; Tay Kai Meng

来源：Computers and Concrete, 2015, 15(1): 55-71.

DOI：10.12989/cac.2015.15.1.055

• bond reduction coefficient
• externally prestressed tendon stress
• harmony search
• monotonicity index
• single input rule modules (SIRMs)-connected fuzzy inference system (FIS)

This paper presents a novel harmony search (HS)-based data-driven single input rule modules (SIRMs)-connected fuzzy inference system (FIS) for the prediction of stress in externally prestressed tendon. The proposed method attempts to extract causal relationship of a system from an input-output pairs of data even without knowing the complete physical knowledge of the system. The monotonicity property is then exploited as an additional qualitative information to obtain a meaningful SIRMs-connected FIS model. This method is then validated using results from test data of the literature. Several parameters, such as initial tendon depth to beam ratio; deviators spacing to the initial tendon depth ratio; and distance of a concentrated load from the nearest support to the effective beam span are considered. A computer simulation for estimating the stress increase in externally prestressed tendon, Delta f(ps), is then reported. The contributions of this paper is two folds; (i) it contributes towards a new monotonicity-preserving data-driven FIS model in fuzzy modeling and (ii) it provides a novel solution for estimating the Delta f(ps) even without a complete physical knowledge of unbonded tendons.

• 出版日期2015-1