%0 Journal Article
%T Prediction of Materials Density according to Number of Scattered Gamma Photons Using Optimum Artificial Neural Network
%A Gholam Hossein Roshani
%A Seyed Amir Hossein Feghhi
%A Farzin Shama
%A Abolfazl Salehizadeh
%A Ehsan Nazemi
%J Journal of Computational Methods in Physics
%D 2014
%R 10.1155/2014/305345
%X Through the study of scattered gamma beam intensity, material density could be obtained. Most important factor in this densitometry method is determining a relation between recorded intensity by detector and target material density. Such situation needs many experiments over materials with different densities. In this paper, using two different artificial neural networks, intensity of scattered gamma is obtained for whole densities. Mean relative error percentage for test data using best method is 1.27% that shows good agreement between the proposed artificial neural network model and experimental results. 1. Introduction The gamma-ray photons lose their energy in a stopping medium by these processes: photoelectric effect, Compton effect, pair production, and photonuclear effect. With the analysis of these interactions, some information about characteristics of materials can be obtained. Compton scattering is strongly dependent on the materials density. Therefore, this method is very good choice for densitometry of unknown materials [1¨C6]. El Abd [7] has shown that scattering photons are more sensitive than transmitted photons in order to density meter and void fraction prediction. In [7], the void fraction has been predicted without using artificial neural network (ANN); therefore the error is considerable. In this paper, experimental data have been obtained from a density measurement tomography system [8]. These data were used for training the ANN. Set-up of this tomography system was shown in Figure 1. Figure 1: Schematic of tomography structure system. In investigated tomography system [8], a NaI (Tl) scintillation detector in 3 ¡Á 3 inch dimensions has been used. The detector records scattered photons from target sample. The source is 137Cs with 8£¿mci activation. Distances between the sample from the source collimator and the detector are 5.56£¿cm and 6£¿cm, respectively. Investigated samples have dimensions and thickness of 1 ¡Á 2£¿cm2 and 1£¿cm, respectively. The time durations of measurement are 100 seconds. Relative stochastic error has inverse relation with the number of registered counts in detector. In this study because the scattering method is used and the number of counts in this method is less in comparison with the transmission method, therefore the measurement time should be increased in order to decrease the stochastic error. By taking 100-second time duration, the stochastic errors are in the range of 0.5%¨C1.5% (5000¨C20000 counts for different materials). The experimental results are shown in Table 1. Table 1: Number of detected photons
%U http://www.hindawi.com/journals/jcmp/2014/305345/