Generalized entransy dissipation and its application in heat conduction optimizations with arbitrary boundary conditions

Heat conduction optimization with arbitrary boundary conditions is a challenging problem that lacks a universal optimization criterion. In the present work, the concept of generalized entransy dissipation (GED) is proposed through transforming heat conduction optimization problems with arbitrary boundaries into their homogeneous counterparts. It is demonstrated that minimizing GED leads to optimal thermal performance of heat conduction problems with arbitrary boundary conditions. In addition, GED-based continuous optimization problems are convex, guaranteeing the uniqueness and global optimality of the solution and benefitting numerical calculations. Two typical problems with complex boundary conditions are studied by applying the minimum principle of GED, and the results are compared with other optimization objectives. The numerical results show that GED achieves better thermal performance than entropy generation-(EG) and entransy dissipation-(ED) based optimizations. For the optimization of boundary average temperature under the given input heat flux of 200 W, GED achieves the best result, where the optimized average temperature is 48.8 K and 27.5 K lower compared with EG and ED optimizations, respectively. In general, GED offers a reasonable and easy to implement optimization principle for heat conduction processes with arbitrary boundaries and may provide new insights for heat conduction optimization.

Automated summary

In this study, a concept of generalized entransy dissipation (GED) is proposed to optimize the heat conduction process with arbitrary boundary conditions. The minimum principle of GED is applied to solve complex optimization problems, and the results show that GED achieves better thermal performance compared to other optimization objectives. The GED-based continuous optimization problems are convex, ensuring the uniqueness and global optimality of the solution.