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누브리 해리스(Haris Nubli),손정민(Sohn,JungMin) 한국해양디자인학회 2023 JMDR 해양디자인학연구 Vol.1 No.1
This paper presents a novel approach to address the challenge of efficiently generating thermal load inputs for LS-DYNA, a widely used for finite element analysis software. The manual entry of thermal load data for a large number of elements is quite time-consuming, it is indispensable to utilize an automated solution. To overcome this obstacle, a Python-based algorithm was used to generate thermal load data derived from computational fluid dynamics (CFD) analysis results. Given the disparity in node positions between the CFD software (Kameleom Fire Ex) and LS-DYNA models, a Random Forest regression model was employed to accurately transfer the thermal load data. The transferred thermal load data, consisting of Cartesian coordinate points (X, Y, Z) and temperature, was compiled into an LS-DYNA file (.k). Furthermore, a Tkinter-GUI was implemented to provide a user-friendly interface for the developed algorithms including the Random Forest and LS-DYNA load compiler algorithms. This enables users to easily transfer thermal loads from CFD to LS-DYNA facilitating the creation of input load profiles based on CSV (comma-separated values) files. The effectiveness of the proposed approach was demonstrated through extensive testing and evaluation.
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