BEST PRACTICE GUIDELINE FOR THE CFD …

1 best PRACTICE GUIDELINE FOR THE CFD simulation OF FLOWS IN THE URBAN ENVIRONMENT Edited by: J rg Franke, Antti Hellsten, Heinke Schl nzen, Bertrand Carissimo COST Action 732 QUALITY ASSURANCE AND IMPROVEMENT OF MICROSCALE METEOROLOGICAL MODELS 1 May 2007 Legal notice by the COST Office Neither the COST Office nor any person acting on its behalf is responsible for the use which might be made of the information contained in the present publication. The COST Office is not responsible for the external web sites referred to in the present publication.

2 Contact: Carine Petit Science Officer COST Office Avenue Louise 149 1050 Brussels Belgium Tel.: + 32 2 533 38 31 Fax: + 32 2 533 38 90 E-mail: Edited by J rg Franke, Antti Hellsten, Heinke Schl nzen, Bertrand Carissimo Contributing authors: Alexander Baklanov, Photios Barmpas, John Bartzis, Ekaterina Batchvarova, Kathrin Baumann-Stanzer, Ruwim Berkowicz, Carlos Borrego, Rex Britter, Krzysztof Brzozowski, Jerzy Burzynski, Ana Margarida Costa, Bertrand Carissimo, Reneta Dimitrova, J rg Franke, David Grawe, Istvan Goricsan, Antti Hellsten, Zbynek Janour, Ari Karppinen, Matthias Ketzel, Jana Krajcovicova, Bernd Leitl, Alberto Martilli, Nicolas Moussiopoulos, Marina Neophytou.

3 Helge Olesen, Chrystalla Papachristodoulou, Matheos Papadakis, Martin Piringer, Silvana di Sabatino, Mats Sandberg, Michael Schatzmann, Heinke Schl nzen, Silvia Trini-Castelli. COST Office, 2007 No permission to reproduce or utilize the contents of this book by any means is necessary, other than in the case of images, diagrams or other material from other copyright holders. In such cases permission of the copyright holders is required. This book may be cited as: Title of the book and Action Number ISBN: 3-00-018312-4 Distributed by University of Hamburg Meteorological Institute Centre for Marine and Atmospheric Sciences Bundesstra e 55 D 20146 Hamburg, Germany 3 Contents 1 Background and 5 2 6 3 Modelling errors and uncertainties.

4 7 Simplification of physical complexity .. 7 Usage of previous 7 Physical boundary conditions .. 8 Geometric boundary conditions .. 8 4 Numerical errors and uncertainties .. 8 Computer programming .. 8 Computer round-off .. 9 Spatial and temporal discretisation .. 9 Iterative convergence .. 9 5 best PRACTICE 10 Review of existing guidelines .. 10 Choice of target variables .. 11 Choice of approximate equations describing the physics of the flow.

5 12 Steady RANS .. 13 Unsteady RANS (URANS).. 14 Large Eddy simulation (LES) and hybrid RANS-LES approaches .. 15 Choice of the geometrical representation of obstacles etc.. 16 Choice of the computational domain .. 16 Vertical extension of the domain .. 16 Lateral extension of the 17 Extension of the domain in flow 17 Choice of boundary conditions .. 18 Inflow boundary conditions .. 18 Wall boundary conditions .. 19 Top boundary conditions .. 20 Lateral boundary conditions .. 21 Outflow boundary conditions.

6 21 Choice of initial data .. 22 Choice of the computational 23 Choice of numerical approximations .. 25 Choice of the time step size .. 26 Choice of iterative convergence criteria .. 26 6 26 7 27 33 A Verification of CFD codes and numerical simulation results .. 33 Generalised Richardson extrapolation .. 33 Code 36 Solution verification (numerical error estimation) .. 38 B Examples of Common 43 PRACTICE of RANS CFD simulation at the AUTH LHTEE .. 43 Problem definition.

7 43 Specification of boundary conditions .. 44 Choice of the turbulence 44 Grid 45 Time step choice .. 46 Convergence criteria 46 PRACTICE of CFD simulation at IFT, University of 46 Turbulence 47 Domain size .. 47 Grid .. 47 Numerical 47 Convergence criteria .. 48 PRACTICE of CFD simulation with MISKAM .. 48 Computational 48 Grid resolution .. 49 Other MISKAM options.

8 50 Meteorology .. 51 Traffic produced 51 Stability .. 51 Known 51 51 Background and Context The main objective of the COST Action 732 is the improvement and quality assurance of microscale obstacle-accommodating meteorological models and their application to the prediction of flow and transport processes in urban or industrial environments (Schatzmann and Britter, 2005). The name microscale obstacle-accommodating meteorological models is used to discern them from cloud resolving models which are microscale meteorological models as well.

9 Subsequently the short term CFD-code is often used as a synonym for the lengthy name microscale obstacle-accommodating meteorological model . The quality assurance of the application is closely related to the users' knowledge of the models. Actually, numerical simulation is mainly a knowledge based activity as has been stated by Hutton (2005) and Coirier (2005). While both refer to CFD codes, their statement is also valid for non-CFD codes. The knowledge is, in general, most effectively transferred by the formulation of a best PRACTICE GUIDELINE (BPG) for the intended application, which is the prediction of dispersion in urban areas at neighbourhood and street scale (Hanna & Britter, 2003) within this COST Action.

10 However, even for this well-defined application the formulation of BPGs faces the problem of giving general advice for specific problems that may vary substantially although belonging to the same field. The most up to date and complete BPG for industrial CFD from ERCOFTAC (Casey & Wintergerste, 2000) also acknowledges this problem with the introductory statement that it offers roughly those 20% of the most important general rules of advice that cover roughly 80% of the problems likely to be encountered.