Ibrahim H. Guzelbey

Soft computing based formulation for strength enhancement of CFRP confined concrete cylinders

This study presents the application of soft computing techniques namely as genetic programming (GP) and stepwise regression (SR) for formulation of strength enhancement of carbon-fiber-reinforced polymer (CFRP) confined concrete cylinders. The proposed soft computing based formulations are based on experimental results collected from literature. The accuracy of the proposed GP and SR formulations are quite satisfactory as compared to experimental results. Moreover, the results of proposed soft computing based formulations are compared with 15 existing models proposed by various researchers so far and are found to be more accurate.

A new formulation for longitudinally stiffened webs subjected to patch loading using stepwise regression method

This study proposes a new formulation for patch loading of longitudinally stiffened webs using stepwise regression (SR) for the first time in literature. The database for the SR formulation is based on extensive experimental results from literature. The results of the SR formulation are compared with existing models and design codes. It is found that SR formulation gives more accurate results than existing models and design codes.

Boundary element analysis of contact problems using artificial boundary node approach

An improved version of the regular boundary element method, the artificial boundary node approach, is derived. A simple contact algorithm is designed and implemented into the direct boundary element, regular boundary element and artificial boundary node approaches. The exisiting and derived approaches are tested using some case studies. The results of the artificial boundary node approach are compared with those of the existing boundary element program, the regular element approach, ANSYS and analytical solution whenever possible. The results show the effectiveness of the artificial boundary node approach for a wider range of boundary offsets.

Flexural buckling load prediction of aluminium alloy columns using soft computing techniques

This paper presents the application of soft computing techniques for strength prediction of heat-treated extruded aluminium alloy columns failing by flexural buckling. Neural networks (NN) and genetic programming (GP) are presented as soft computing techniques used in the study. Gene-expression programming (GEP) which is an extension to GP is used. The training and test sets for soft computing models are obtained from experimental results available in literature. An algorithm is also developed for the optimal NN model selection process. The proposed NN and GEP models are presented in explicit form to be used in practical applications. The accuracy of the proposed soft computing models are compared with existing codes and are found to be more accurate.

Boundary element analysis using artificial boundary node approach

The conventional regular boundary element method has been implemented in direct boundary element method. A new approach of regular element is designed and called as artificial boundary node approach. The existing and derived approaches are tested using a case study. The results of the suggested new approach have been compared with the existing boundary element program, conventional regular boundary element method, ANSYS and analytical solution. The results encourage the usage of the approach for a wider range of boundary offset.

An experimental study of investigating the relationships between structures and properties of al alloys included with high Mg and high Ti

In this study, the influences of high magnesium (Mg) and high titanium (Ti) additions on aluminium (Al) alloys were investigated to peruse the relationship between the structure and properties of the new alloys. Microstructural analyses were performed using X-ray diffraction (XRD), the polarised optical microscope, and scanning electron microscope (SEM) equipped with energy dispersive spectrometry (EDS). In the microstructure of the alloys, the β-phase (Al3M2) α-solid solution, Ti2Mg3Al18 and TiAl3 particles were revealed. Results showed that the average grain size of Al-Mg-Ti alloys was found to be different in each composition, and the smallest grain size was obtained at Al-12Mg-3Ti alloy as 88 μm. The highest tensile strength (170 MPa) was attained with additions of 8 wt.% Mg and 1 wt.% Ti, but the highest hardness value (125 HBN) was obtained with additions of 14 wt.% Mg and 3 wt.% Ti. It was noted that the smallest average grain size did not behave in accordance with the highest mechanical properties. For the work, the optimal ratios of magnesium and titanium entrained into Al alloys were 8 wt.%, and 1 wt.%, respectively.