A Recognition Technique for the Generative Tessellations of Geometric Patterns in Islamic Architectural Ornaments; Case Study: Southern Iwan of the Grand Mosque of Varamin
Author(s): |
Mehdi Sheikhi Nashalji
Fatemeh Mehdizadeh Saradj |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 25 August 2024, n. 9, v. 14 |
Page(s): | 2723 |
DOI: | 10.3390/buildings14092723 |
Abstract: |
The ornamentation of historical buildings in Iran often features geometric patterns, which hold cultural and architectural significance. These patterns, rooted in Islamic tradition, are widely used in contemporary Middle Eastern architecture. By employing regular polygons, intricate designs emerge, forming interconnected tessellations and repeating modules. This paper focuses on uncovering hidden tessellations and geometric patterns within the southern Iwan of the Grand Mosque of Varamin. Through photography and field measurements, 82.4 and 36 tessellations were identified. Using the Revit 2024 program, a novel method was introduced to model these patterns. By manipulating repeating units, designers can create diverse geometric latticework, preserving Islamic architectural heritage. Furthermore, these patterns offer practical applications beyond ornamentation. They can serve as architectural elements in urban environments, such as fences or enclosures, enhancing privacy in residential spaces and contributing to urban aesthetics. This approach facilitates the integration of historical patterns into contemporary architectural designs, enriching both cultural identity and urban landscapes and is a step toward smart cities. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
12.92 MB
- About this
data sheet - Reference-ID
10795223 - Published on:
01/09/2024 - Last updated on:
01/09/2024