A literature review of building energy simulation and computational fluid dynamics co-simulation strategies and its implications on the accuracy of energy predictions

Abstract

The paper presents a review of existing literature in the field of coupling Computational Fluid Dynamics (CFD) with Building Energy Simulations (BES) to better predict indoor environmental conditions and building energy implications. CFD is capable of providing a detailed analysis of airflow profile and temperature gradients in the space as well as better prediction of heat transfer involving convection and radiation. Whereas BES can provide dynamically changing boundary conditions to CFD to facilitate a precise transient analysis. Combining the two simulations provides a powerful framework to accurately predict building performance parameters. The review examines the variables exchanged between the two simulations and establishes that the Convective Heat Transfer Coefficient (CHTC) as the most important exchanged variable that can significantly improve the accuracy of energy simulations. Issues regarding the application of co-simulation mechanism are then discussed in terms of simulation discontinuities, along with strategies adopted by researchers to overcome the same. In the later sections, the review evaluates the applicability of co-simulation from the perspective of year-long building energy simulations and presents an overview of methods used in research to implement the same. Finally, the conclusions are discussed and the scope for future research in the field is presented. Practical implication: The review presents a critical analysis of essentially all major coupling strategies that can be used to perform a BES-CFD coupled analysis along with their strengths, limitations and possible application scenarios. Additionally, the problems associated with establishing the co-simulation are examined and various adopted solutions are presented along with methods implemented towards extending the practical applicability of such an analysis to encapsulate year-long simulations.