This paper presents a comprehensive review of the open literature on motivations, methods and applications of linking stratified airflow simulation to building energy simulation (BES). First, we review the motivations for coupling prediction models for building energy and indoor environment. This review classified various exchanged data in different applications as interface data and state data, and found that choosing different data sets may lead to varying performance of stability, convergence, and speed for the co-simulation. Second, our review shows that an external coupling scheme is substantially more popular in implementations of co-simulation than an internal coupling scheme. The external coupling is shown to be generally faster in computational speed, as well as easier to implement, maintain and expand than the internal coupling. Third, the external coupling can be carried out in different data synchronization schemes, including static coupling and dynamic coupling. In comparison, the static coupling that performs data exchange only once is computationally faster and more stable than the dynamic coupling. However, concerning accuracy, the dynamic coupling that requires multiple times of data exchange is more accurate than the static coupling. Furthermore, the review identified that the implementation of the external coupling can be achieved through customized interfaces, middleware, and standard interfaces. The customized interface is straightforward but may be limited to a specific coupling application. The middleware is versatile and user-friendly but usually limited in data synchronization schemes. The standard interface is versatile and promising, but may be difficult to implement. Current applications of the co-simulation are mainly energy performance evaluation and control studies. Finally, we discussed the limitations of the current research and provided an overview for future research.

This paper describes a coupled dynamic simulation of indoor environment with HVAC systems, controls and building envelope heat transfer. The coupled simulation can be used for the design and control of ventilation systems with stratified air distributions. Those systems are commonly used to reduce building energy consumption while improving the indoor environment quality. The indoor environment was simulated using the fast fluid dynamics (FFD) simulation program. The building fabric heat transfer, HVAC and control system were modelled using the Modelica Buildings library. After presenting the concept, the mathematical algorithm and the implementation of the coupled simulation were introduced. The coupled FFD-Modelica simulation was then evaluated using three examples of room ventilation with complex flow distributions with and without feedback control. Further research and development needs were also discussed.

Details of particle shape, including surface roughness or texture, curvature or sharpness of surface features and edges, are known to have an impact on particle packing structure. In different computer models, shape is represented using different approaches to varying degrees of precision. Thus, it is to be expected that different approaches, or rather their precision of shape representation, can affect not only how computationally demanding the simulation model is but also how accurate the model prediction can be. This paper examines two different approaches to shape representation, and their effects on the accuracy of model predictions, in the context of non-spherical particle packing. To this end, two commercially available discrete element method (DEM) based software packages, EDEM and DigiDEM, are used. The former, referred to here as sphere-composite approach, represents one extreme where a shape is typically coarsely represented by clumping together a small number of primary spheres. The latter, known as voxel-based approach, represents the other extreme where a shape is typically finely represented by a huge number of voxels (3D pixels). Both are used to simulate packing of cylinders -the most common shape of catalyst pellets in packed column reactors widely used in chemical, oil refinery and process industries. Previously reported X-ray CT scan of a packed bed provides the experimental measurements for both to compare with, in terms of bulk packing fraction, axial and radial packing fraction profiles, and pellet orientation distributions. Eight sphere-composite representations of the same cylindrical pellet were tested. Two of them gave results that quantitatively (i.e., within 5% margin of error) follow experimental measurements. A range of factors that in theory could affect accuracy of the simulation results have been examined in detail, including edge roundedness, surface roughness and restitutional behaviour as a function of sphere-composite representations. The conclusion therefore is that, for packing at least, matching the object's overall shape and dimensions is not enough, only when a high enough resolution is applied to corners and edges, could the sphere-composite approach possibly 2 match the experimental data quantitatively.

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