Development of field-ready AI model for estimation of compressive strength of concrete using non-destructive testing methods

The proposed project aims to apply artificial intelligence methods to augment in-place non-destructive testing technologies in order to reduce or eliminate the need for intrusive methods (i.e. concrete core extraction) for concrete strength estimation. The proposed approach is based on the SonReb method, which combines two non-destructive testing technologies, namely ultrasonic pulse velocity and rebound hammer, for assessing subsurface and near-surface concrete properties. The project will focus on improvements to a previous model developed by the project team to make it suitable for field applications. It is expected that the project will ultimately result in the development of a new software tool that will result in new revenue streams and expanded market share for the project partner.

Faculty Supervisor:

Martin Noel

Student:

Partner:

FPrimeC Solutions Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Ottawa

Program: