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Founded in 1904 and headquartered in Farmington Hills, Michigan, USA, the American Concrete Institute is a leading authority and resource worldwide for the development and distribution of consensus-based standards, technical resources, educational programs, and proven expertise for individuals and organizations involved in concrete design, construction, and materials, who share a commitment to pursuing the best use of concrete.
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Home > Publications > International Concrete Abstracts Portal
The International Concrete Abstracts Portal is an ACI led collaboration with leading technical organizations from within the international concrete industry and offers the most comprehensive collection of published concrete abstracts.
Title: Towards a Service Life Prediction System of Concrete Structures Based on a Neural-Computing Approach
Author(s): Bakhta Boukhatem, Arezki Tagnit-Hamou, Mohamed Chekired and Mohamed Ghrici
Publication: Special Publication
Appears on pages(s): 45.1-45.12
Keywords: carbonation, concrete structure, corrosion, durability, fly ash, neural network, service life, sulfate attack
Abstract:The cost of repairing and rehabilitating damaged reinforced-concrete structures in Canada and elsewhere continues to rise. Predicting the service life and life-cycle cost of these structures can help identify the most cost-effective solution. Many companies have joined with research partners on projects to develop reliable tools to predict the service life of concrete structures. Given the problem’s complexity, most of these projects are based on different modeling approaches producing widely different values, greatly limiting their application.
Therefore, our project consisted in applying a connectionist approach, including artificial neural networks (ANNs) models and a database, to create an intelligent system. In addition, each ANN model better grasps the complex mechanisms of concrete degradation (carbonation, sulfate expansion, chloride-induced corrosion, etc.). The proposed system will yield a powerful solution for predicting the service life of concrete structures and be useful in designing new structures. It will significantly improve codes by contributing more realistic
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