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Al-Ghzawi, M and El-Rayes, K (2023) Optimizing the planning of airport airside expansion projects to minimize air traffic disruptions and construction cost. Journal of Construction Engineering and Management, 149(04).

Barros, B A F S and Sotelino, E D (2023) Constructability and sustainability studies in conceptual projects: A BIM-based approach. Journal of Construction Engineering and Management, 149(04).

Guo, H, Zhang, Z, Yu, R, Sun, Y and Li, H (2023) Action recognition based on 3D skeleton and LSTM for the monitoring of construction workers' safety harness usage. Journal of Construction Engineering and Management, 149(04).

Hassan, F U, Le, T and Le, C (2023) Automated approach for digitalizing scope of work requirements to support contract management. Journal of Construction Engineering and Management, 149(04).

Jeon, J, Zhang, Y, Yang, L, Xu, X, Cai, H and Tran, D (2023) Risk breakdown matrix for risk-based inspection of transportation infrastructure projects. Journal of Construction Engineering and Management, 149(04).

Koc, K, Ekmekcioǧlu, Ö and Gurgun, A P (2023) Developing a national data-driven construction safety management framework with interpretable fatal accident prediction. Journal of Construction Engineering and Management, 149(04).

Li, Y, Ning, Y and Rowlinson, S (2023) Social control in outsourced architectural and engineering design consulting projects: Behavioral consequences and motivational mechanism. Journal of Construction Engineering and Management, 149(04).

Nigra, M and Bossink, B (2023) Cooperative learning in green building demonstration projects: Insights from 30 innovative and environmentally sustainable demonstrations around the world. Journal of Construction Engineering and Management, 149(04).

Pushpakumara, B H J, Gunasekara, M T and Gannile, Y M T D (2023) Variation of mechanical and chemical properties of old and new clay bricks. Journal of Construction Engineering and Management, 149(04).

  • Type: Journal Article
  • Keywords: clay bricks; mechanical and chemical properties; rehabilitation; xrd and xrf testing
  • ISBN/ISSN: 0733-9364
  • URL: http://doi.org/10.1061/JCEMD4.COENG-12950
  • Abstract:
    Clay bricks are a popular building material, especially in historical structures. Understanding the chemical and mechanical properties of bricks is vital in historical structure rehabilitation attempts, because discrepancies in the material could lead to accelerated degradation and structural failure. This research focuses on understanding the mechanical and chemical properties of clay bricks used in the world heritage city of Kandy, Sri Lanka, over the chronological period of the 18th to the 21st centuries. Chronological analysis of brick properties reveals that optimal mechanical properties in bricks are closely related to the water absorption rate and are found to be between 10% and 18% in the analyzed specimens. Further, regional mineralogical properties, such as high concentration of calcium and inclusion of barium (Ba), potassium (K), strontium (Sr), and titanium (Ti) as trace elements, were visible in most samples regardless of the year the brick was produced. The analysis also identified revealed that the inclusion of ferrous (Fe) increases performance. Assuring similar chemical characteristics in restoration material is important to avoid chemical imbalances leading to accelerated deterioration due to the presence of reactive metals in the brick composition.

Shiha, A and Dorra, E M (2023) Resilience index framework for the construction industry in developing countries. Journal of Construction Engineering and Management, 149(04).

Shirazi, D H and Toosi, H (2023) Deep multilayer perceptron neural network for the prediction of Iranian dam project delay risks. Journal of Construction Engineering and Management, 149(04).

Xia, N, Griffin, M A, Xie, Q and Hu, X (2023) Antecedents of workplace safety behavior: Meta-analysis in the construction industry. Journal of Construction Engineering and Management, 149(04).

Xu, W and Wang, T K (2023) Construction worker safety prediction and active warning based on computer vision and the gray absolute decision analysis method. Journal of Construction Engineering and Management, 149(04).