Development of Bolted Flange Design Tool Based on Artificial Neural Network

Yıldırım, Alper
Akay, Ahmet Arda
Gülaşık, Hasan
Çöker, Demirkan
Gürses, Ercan
Kayran, Altan
<jats:p>Finite element analysis (FEA) of bolted flange connections is the common methodology for the analysis of bolted flange connections. However, it requires high computational power for model preparation and nonlinear analysis due to contact definitions used between the mating parts. Design of an optimum bolted flange connection requires many costly finite element analyses to be performed to decide on the optimum bolt configuration and minimum flange and casing thicknesses. In this study, very fast responding and accurate artificial neural network-based bolted flange design tool is developed. Artificial neural network is established using the database which is generated by the results of more than 10,000 nonlinear finite element analyses of the bolted flange connection of a typical aircraft engine. The FEA database is created by taking permutations of the parametric geometric design variables of the bolted flange connection and input load parameters. In order to decrease the number of FEA points, the significance of each design variable is evaluated by performing a parameter correlation study beforehand, and the number of design points between the lower and upper and bounds of the design variables is decided accordingly. The prediction of the artificial neural network based design tool is then compared with the FEA results. The results show excellent agreement between the artificial neural network-based design tool and the nonlinear FEA results within the training limits of the artificial neural network.</jats:p>
Journal of Pressure Vessel Technology


Yildirim, Alper; Kayran, Altan; Gulasik, Hasan; Çöker, Demirkan; Gürses, Ercan (2015-11-19)
In bolted flange connections, commonly utilized in aircraft engine designs, structural integrity and minimization of the weight are achieved by the optimum combination of the design parameters utilizing the outcome of Many structural analyses. Bolt size, the number of bolts, bolt locations, casing thickness, flange thickness, bolt preload, and axial external force are some of the critical design parameters in bolted flange connections. Theoretical analysis and finite element analysis (FEA) are two main appr...
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In this thesis, a design tool using artificial neural network (ANN) is developed for the bolted flange connections, which enables the user to analyze typical aircraft engine connections subjected to combined axial and bending moment in a fast yet very accurate way. The neural network trained for the design tool uses the database generated by numerous finite element analyses for different combinations of parametric design variables of the bolted flange connection. The defined parameters are the number of bol...
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Citation Formats
A. Yıldırım, A. A. Akay, H. Gülaşık, D. Çöker, E. Gürses, and A. Kayran, “Development of Bolted Flange Design Tool Based on Artificial Neural Network,” Journal of Pressure Vessel Technology, 2019, Accessed: 00, 2020. [Online]. Available: