Boundary-condition-independent reduced-order modeling of complex 2D objects by POD-Galerkin methodology

The objective of the current work is to introduce the concept of boundary-condition-independent (BCI) reduced-order modeling (ROM) for complex electronic packages by the POD-Galerkin methodology. Detailed models of complex electronic packages are used within system-level models in Computational Fluid Dynamics (CFD)-based heat transfer analysis. At times, these package-level models are complicated, and their simulation tends to consume large amounts of computational resources. This problem is compounded further if multiple instances of these models are used within the system. If a package-level model that reduces computational resources (reduced-order model), and provides results in many different flow situations (boundary-condition-independent model) can be deployed, it will accelerate the design and analysis of the end products that make use of these components. This work focuses on how the Proper Orthogonal Decomposition (POD)-Galerkin methodology can be used with the Finite Volume (FV) method to generate reduced-order models that are boundary-condition-independent. This method is successfully used in the present study to generate boundary-condition-independent reduced-order models for 1D and 2D objects. Successful implementation of the method is also shown on 2D objects made of multiple materials and multiple heat generating sources. Also, the final BCI ROM in each case is found to work extremely well (errors less than 1%) even for boundary conditions outside the range in which it was generated, making it a truly boundary-condition-independent model.