Amirkabir University of Technology Amirkabir Journal of Mechanical Engineering 2008-6032 53 2 2021 04 21 Designing Optimum Multi-Domain System by Integrating Bond Graph and Genetic Programming Designing Optimum Multi-Domain System by Integrating Bond Graph and Genetic Programming 1015 1038 3581 10.22060/mej.2019.16086.6267 FA Behzad Bahrami Joo PhD Candidate, Guilan University/ Faculty of Mechanical Engineering Ali Jamali Associate Professor, Guilan University/ Faculty of Mechanical Engineering Nader Nariman-zadeh Professor, Guilan University/ Faculty of Mechanical Engineering Journal Article 2019 04 06 Integrated modeling of multi-domain physical systems requires a common language. One of the methods which has been used to do so is called the bond graph. The bond graph provides a common and core language for describing basic elements and connections across different fields by using its elements, bonds and junctions. Also, by using genetic programming as an evolutionary method, an initial model can be evolved into a final model. The initial model of a system in a bond graph called Embryo and must have input, output and basic elements of the desired model. By defining a series of operational functions in genetic programming, an embryo model evolves and a final model obtained in one objective and multi-objective approaches. The current research presents an optimized design tool by the integration of a bond graph and a Pareto multi-objective genetic programming for guiding automated topology synthesis. In order to evaluate the performance of the proposed method, obtained results were first compared to the 20-sim software and then two models of electric filter and a mass, spring and damper system compared to the reference.<br />  Integrated modeling of multi-domain physical systems requires a common language. One of the methods which has been used to do so is called the bond graph. The bond graph provides a common and core language for describing basic elements and connections across different fields by using its elements, bonds and junctions. Also, by using genetic programming as an evolutionary method, an initial model can be evolved into a final model. The initial model of a system in a bond graph called Embryo and must have input, output and basic elements of the desired model. By defining a series of operational functions in genetic programming, an embryo model evolves and a final model obtained in one objective and multi-objective approaches. The current research presents an optimized design tool by the integration of a bond graph and a Pareto multi-objective genetic programming for guiding automated topology synthesis. In order to evaluate the performance of the proposed method, obtained results were first compared to the 20-sim software and then two models of electric filter and a mass, spring and damper system compared to the reference.<br />  https://mej.aut.ac.ir/article_3581_67606d48e361ce176ca71fd54fcf4286.pdf