Integrating neural networks, databases and numerical software for managing early age concrete crack prediction

This paper presents an expert system that supports early age concrete crack prediction. The system embodies knowledge gathered from experts both in procedural form (programs and spreadsheets) and declarative form (graphical assistants, users’ guides, documentation). Moreover, processing tasks are performed by neural networks trained on data gathered from experimental and virtual models. The system comprises a large database for storing data about concrete mixes. The procedures of the expert system can access the database and exploit its data for processing purposes.