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Post Operation Clean Out (POCO) is the process to remove hazardous materials and decommission nuclear facilities at the end of a nuclear plant's lifetime. The introduction of Internet of Things (IoT) technologies in the environment, especially radio frequency identification (RFID), would improve efficiency and safety by intelligently monitoring POCO activities. In this paper, we present a passive material identification and crack sensing method developed for the integration of sensing and communication using commercial off-the-shelf (COTS) RFID tags, which is a long-term solution to material property monitoring under insulation for harsh environmental conditions. To validate the effectiveness of material identification and crack monitoring, machine learning techniques have been applied, and the feasibility of the study has been outlined. The result shows that the material identification can be achieved with traditional features and obtain improved accuracy with three-layer multi-layer neural networks (MLNN). In crack characterization, the tree algorithm based on traditional features achieves a reasonable accuracy, while three-layer MLNN is the best solution, which supports the efficiency of traditional feature extraction methods in specific applications. [ABSTRACT FROM AUTHOR]

Composite materials are prone to delamination defects during the preparation process. For the non-destructive testing and evaluation of carbon fiber reinforced polymer (CFRP) delamination defects, a standard specimen with embedded delamination defects was prepared, and then phased array ultrasonic non-destructive testing technology was used to detect the delamination defects. The qualitative assessment and quantitative evaluation of delamination defects were carried out. First, the delamination defect specimen was prepared with the autoclave forming process, and polyimide films were embedded in the specimen before progress; then, the specimen was inspected using phased array ultrasonic technique, qualitative and quantitative measurement of delamination defects were analyzed with ultrasonic S-scan and C-scan image, uncertainty analysis of test results were also discussed in combination with the sound field simulation. The results show that the shapes of the delamination defects in the sample are regular, the embedment depth and size are consistent with the preset. The index direction size of the delamination defect is more accurate, and the scan direction size is larger than the actual size. Phased array ultrasonic technique can accurately identify the shape, size and position of delamination defects with high detection accuracy and still has good detection effects for small defects.

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An experimental method denoted as Impulse Method is proposed as a cost-effective nondestructive technique for the on-site evaluation of concrete elastic modulus in existing structures: on the basis of Hertz's quasi-static theory of elastic impact and with the aid of a simple portable testing equipment, it makes it possible to collect series of local measurements of the elastic modulus an easy way and in a very short time. A Hypothesis Testing procedure is developed in order to provide a statistical tool for processing the data collected by means of the Impulse Method and assessing the possible occurrence of significant variations in the elastic modulus without exceeding some prescribed I error probabilities. It is based on a particular formulation of the renowned sequential probability ratio test and reveals to be optimal with respect to the error probabilities and the required number of observations, thus further improving the time-effectiveness of the Impulse Method. The results of an experimental investigation on different types of plain concrete prove the validity of the Impulse Method in estimating the unknown value of the elastic modulus and attest the effectiveness of the proposed Hypothesis Testing procedure in identifying significant variations in the elastic modulus. [ABSTRACT FROM AUTHOR]