This thesis is concerned with advancing the modelling of indoor air flow and internal surface convection within dynamic whole-building simulation. The path taken is the conflation of computational fluid dynamics (CFD) techniques with dynamic whole-building simulation, with an accurate treatment of the co-dependencies between these modelling domains. Two flow responsive modelling techniques were devised and implemented within the ESP-r simulation program to achieve the research objectives. The adaptive convection algorithm enhances ESP-r's thermal simulation domain by dynamically controlling the simulation of internal surface convection. Empirical methods were extracted from the literature and a new method for characterizing mixed flow convective regimes was created to provide the algorithm with a basis of 28 convection coefficient correlations. Collectively these methods can calculate convection coefficients for most flows of practical interest. Working with this suite of correlations, the algorithm assigns appropriate equations to each internal surface and adapts the selection in response to the room's evolving flow regime. The adaptive conflation controller manages all interactions between the thermal and CFD modelling domains. The controller incorporates the latest turbulence modelling advancements applicable for room air flow simulation and possesses a suite of handshaking and thermal boundary condition treatments. The job of this adaptive conflation controller is to monitor the evolving thermal and air flow conditions in the room and dynamically select an appropriate combination of modelling approaches for the prevailing conditions. The two control schemes implemented to demonstrate the controller make use of a double-pass modelling approach. Each time-step that the thermal domain handshakes with CFD, the adaptive conflation controller performs an investigative simulation to approximate the room's flow and temperature field. Using these estimates, the controller calculates dimensionless groupings to determine the nature of the flow (forced, buoyant, mixed, fully turbulent, weakly turbulent) adjacent to each internal surface. This information is used to select suitable boundary condition treatments for each surface. A second CFD simulation is then performed using the refined modelling approach to more accurately resolve the room's air flow and temperature distribution, and to predict surface convection. In order to protect the thermal domain, a two-stage screening process is used to assess (and where necessary reject) the CFD-predicted surface convection estimates. These adaptive modelling techniques advance the modelling of indoor air flow and internal surface convection within whole-building simulation.

<p>The fluid simulation in computer generates realistic animations of fluids by solving Navier-Stokes equation. The methods of simulation are divided into two types. The grid-based methods and particle-based methods. The former one is wildly used for scientific computation because of its precision of simulation while the latter one is used in visual effects, games and other areas requiring real-time simulation because of the less computation time it has. </p> <p> </p><p>The indoor airflow simulations with HVAC system in construction design is one specific application in scientific computation and uses grid-based simulation as the general-purpose simulation does. This study addresses the problem that this kind of airflow simulations in construction design using grid-based methods are very time consuming and always need designers to do pretreatment of the building model, which takes time, money, and effort. On the other hand, the particle-based methods would have less computation time with an acceptable accuracy in indoor airflow simulations because this kind of simulation does not require very high precision.</p> <p><br></p><p>Then this study conducts a detailed and practical comparison of different fluid simulation algorithms in both grid-based methods and particle-based ones. This study's deliverable is a comparison between particle-based and grid-based methods in indoor airflow simulations with HVAC system.</p> <p><br></p><p>The overall methodology used to arrive at the deliverables of this study will need two parts of work. The benchmark data is gathered from a CFD software simulation using FVM with a decent grid resolution. The particle-based data will be generated by simulation algorithms over the same set of room and furniture models implemented by OpenGL and CUDA. After the benchmark FVM simulation being conducted in a CFD software, the temperature field of airflow will be measured. After simulation, the temperature field are gained on each one of 4 particle-based simulation. A comparison standard is set and data will be analyzed to get the conclusion. The result shows that in a short simulation time period, after finding a proper number of particles, the particle-based method will achieve acceptable accuracy of temperature and velocity field while using much less time.</p><p></p>