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Njock Bayock, Francois, NLEND, Ruben, Mbou Tiaya, Elvis, Appiah Kesse, Martin, Kamdem, Bertrand, Kah, Paul. (1403). Development of an Artificial Intelligence-Based Algorithm for Predicting the Mechanical Properties of Weld Joints of Dissimilar S700MC-S960QC Steel Structures. , (), -. doi: 10.22059/ceij.2025.374700.2044
Francois Njock Bayock; Ruben NLEND; Elvis Mbou Tiaya; Martin Appiah Kesse; Bertrand Kamdem; Paul Kah. "Development of an Artificial Intelligence-Based Algorithm for Predicting the Mechanical Properties of Weld Joints of Dissimilar S700MC-S960QC Steel Structures". , , , 1403, -. doi: 10.22059/ceij.2025.374700.2044
Njock Bayock, Francois, NLEND, Ruben, Mbou Tiaya, Elvis, Appiah Kesse, Martin, Kamdem, Bertrand, Kah, Paul. (1403). 'Development of an Artificial Intelligence-Based Algorithm for Predicting the Mechanical Properties of Weld Joints of Dissimilar S700MC-S960QC Steel Structures', , (), pp. -. doi: 10.22059/ceij.2025.374700.2044
Njock Bayock, Francois, NLEND, Ruben, Mbou Tiaya, Elvis, Appiah Kesse, Martin, Kamdem, Bertrand, Kah, Paul. Development of an Artificial Intelligence-Based Algorithm for Predicting the Mechanical Properties of Weld Joints of Dissimilar S700MC-S960QC Steel Structures. , 1403; (): -. doi: 10.22059/ceij.2025.374700.2044

Development of an Artificial Intelligence-Based Algorithm for Predicting the Mechanical Properties of Weld Joints of Dissimilar S700MC-S960QC Steel Structures

Civil Engineering Infrastructures Journal
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 12 دی 1403    اصل مقاله (686.22 K)
شناسه دیجیتال (DOI): 10.22059/ceij.2025.374700.2044
نویسندگان
Francois Njock Bayock* 1؛ Ruben NLEND2؛ Elvis Mbou Tiaya3؛ Martin Appiah Kesse4؛ Bertrand Kamdem1؛ Paul Kah5
1Department of Mechanical Engineering, ENSET Douala, University of Douala, Cameroon
2Department of Mechanical Engineering, University of Douala, Douala, Cameroon
3Laboratory of Mechanics (LM), University of Douala-Cameroon, PoBox: 1872, Douala, Cameroon
4Kwame Nkrumah University of Science and Technology, Mechanical Engineering Department
5Department of Engineering Science, University West, Gustava Melius Gata 2 S-461 32, Trollhättan, Sweden
چکیده
This study focuses on the development of an artificial intelligence (AI) algorithm designed to determine the mechanical properties of high-strength steels, particularly in weld joints created through dissimilar gas metal arc welding of S700MC and S960QC steels. To achieve this goal, a mathematical model based on artificial neural networks (ANNs) was employed. Sixteen experiments were conducted, generating data on the yield strength and tensile strength concerning the welding parameters and a filler wire with a similar carbon equivalent. Initially, the algorithm was set up to predict joint characteristics using only welding parameters as input variables. However, to enhance the accuracy of the predictions, the carbon equivalent of the filler metal was incorporated as an additional input variable. This adjustment resulted in improved prediction outcomes compared to those obtained without considering the filler wire. The implementation of the AI algorithm was carried out using MATLAB, specifically its R2017b version. The algorithm's ability to predict mechanical properties based on the given input variables showcases its potential utility in optimizing welding processes and ensuring the desired mechanical properties of weld joints in high strength steels.
کلیدواژه‌ها
Gas-arc welding؛ dissimilar welding؛ artificial neural network؛ S700MC؛ S960QC
آمار
تعداد مشاهده مقاله: 111
تعداد دریافت فایل اصل مقاله: 126





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