Return
New optimization algorithm for optimal spatial sampling during non-destructive testing of concrete structures
DOI:10.1016/j.engstruct.2015.01.014.png)
Abstract
En 中文
Non-destructive Testing (NOT) 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 NOT measurements. The theoretical development and the results obtained with both simulated and real data are presented and discussed. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
NDT
Optimization
Concrete structure
Diagnosis
Spatial variability
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.4
Papers:
2.1W
Citations:
8.7W
Organization
Cited Papers
Reduction of soil water spatial sampling density using scaled semivariograms and simulated annealing
GEODERMA
IF6.6

