New optimization algorithm for optimal spatial sampling during non-destructive testing of concrete structures

•NDT’s spatial sampling helps to improve the inspection strategy of concrete structures.•An original algorithm was developed for optimizing the number and the position of NDTs.•The developed algorithm is based on the spatial variability analysis.•The fitness functions showed a high improvement in the NDT measurements positions.•The methodology allows the optimal localization of NDT for an efficient diagnosis. Non-destructive Testing (NDT) techniques are essential in order to assess properties or detect anomalies (cracks, pathologies, etc.) in concrete during the diagnosis of structures. However, due to budget limitations, an optimal methodology to estimate the integrity of a structure at minimum cost is required. This paper presents a spatial optimization of NDT measurements (ultrasound) based on their spatial correlation. The optimization is performed in two steps. First, the relationship between the number of measurements organized in a regular grid and the fitness function value are determined using spatial interpolation (kriging method). Then, using an Optimization Spatial Sampling Method developed for this study (OSSM), the fitness function is minimized by changing the positions of a chosen number of NDT measurements. The theoretical development and the results obtained with both simulated and real data are presented and discussed.