Paper 8: Volume 4 No.3 December 2005 Edition
Study on the Numerical Predictive Accuracy of Wind
Pressure Distribution and Air Flow Characteristics - Part 1 Optimization
of Turbulence Models for Practical Use; Part 2 Prediction Accuracy of Wind
Pressure Distribution of Various Shaped Buildings
Tomoyuki
Endo1, Takashi Kurabuchi1, Mizuki Ishii1,
Kazuhiko Komamura2,
Eizo Maruta3 and Takao Sawachi4
1Tokyo
University of Science
,
Japan
2University of
Tokyo
,
Japan
3Nihon
University
,
Japan
4National
Institute
of
Land
and Infrastructure Management, Japan
Abstract
To evaluate wind pressure distribution on a building by using CFD
(computational fluid dynamics), it has been general practice to use k-e models. However, it is known that the use of the standard k-e model has disadvantages such as overestimation of wind pressure
coefficient and turbulent kinetic energy on the windward surface where
wind impinges on the building. To overcome these problems, various
modifications of the k-e
model have been proposed. In the present study, a number of modified k-e
models and a k-ω model were applied for the estimation of wind
pressure distribution on a parallelepiped shaped building. The
characteristics of each of these turbulence models were confirmed using a
wind tunnel model. The results suggest that a modified k-e
model incorporating Durbin’s limiter (model parameter a=0.5) showed satisfactory results for the estimation of wind pressure
distribution. In the overall evaluation, the modified k-e
models (incorporating Durbin’s limiter (a=0.65),
RNG model (renormalization group theory) and Quadratic model provided good
results.
Part one of the study was performed on an object of extremely simple
shape, and questions may arise if this is applied on an actual building.
In this respect, Part 2 of the paper covers a similar evaluation on a
complicated shaped object. For this case, it was found that a RNG model
provides high reproduction accuracy just as in the case of the object with
simple shape. Also, a problem
with the model incorporating Durbin’s limiter (α=0.65) was found
when considering the object with a complicated shape. Consequently, a
modified model incorporating Durbin’s limiter with a higher value for
α shows better results when compared to the RNG model.
Key words: Computational
fluid dynamics, CFD, turbulence models, wind pressure distribution,
turbulent kinetic energy, reattachment point, air flow characteristics, k-e
model, Durbin’s model, RNG model, detached house, wind tunnel
experiment.
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IJV Volume 4 No 3
Contents
Paper
1: Vent Configuration
Paper
2: Passive Cooling
Paper
3: Post Occupancy
Paper
4: Hybrid Ventilation
Paper
5: Bioclimate
Paper
6: Human Factors
Paper
7: CFD Reliability
Paper
8: Wind Pressure
Paper 9: Similarity
Concept
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