Artificial Neural Networks to Assess the Effect of Window Parameters on Indoor Natural Ventilation in “Sultan Al-Ashraf Qaytbay” Mosque

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Mechanical Power Engineering Dept., Faculty of Engineering, Zagazig University, Egypt

Abstract

The Mosque of Sultan al-Ashraf Qaytbay is seen as one of the most beautiful features
of late Egyptian Mamluk architecture. The architectural design of the mosque is
exceptional due to its fine ranges and wonderful decoration. In this paper, Artificial
Neural Networks (ANN) model was incorporated with wind tunnel experiments to
investigate the properties of airflow within the Sultan al-Ashraf Mosque Qaytbay due
to the natural ventilation caused by window openings. Wind tunnel experiments were
utilized to supply the ANN model with the required data essential for the model
training and establishment. The outcomes from the ANN model were validated using
the results from the wind tunnel experiments. The comparison confirms the veracity
of the ANN model results. Present results assured that it is very important to
consider the aerodynamics and the bases of the natural ventilation when carrying out
the restoration process by specialists to maintain the same performance of the
original construction. ANN enables to easy predict the flow field when operating
conditions are changed much easier and faster than the traditional computational and
experimental methods.

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