Surface Estimation via Analysis Method: A Constrained Inverse Problem Approach

An inverse problem is analyzed where corrosion of rebars is detected from a small number of potential data measured at the surface of concrete structure. Because the shape and number of corrosion in rebars are not known in advance, usual inverse analysis method in which the shape and number of corroded part are assumed is not available. In this research, the genetic algorithm (GA) is employed without any assumption. The fitness in the multi-step GA is defined as the inverse of difference between experimental and numerical potential values, and is evaluated by the boundary element method (BEM). To reduce the computational time, the net elements, which have been recently developed by the authors for corrosion analysis of net structures, is used together with the multi-step GA. It is shown by a simulation that the multi-step GA with net elements are successfully employed in the inverse analysis.

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An Integrated Single-Step Gamma Spectrum Analysis Method Based on Bregmanized Variational Deconvolution

Volume 1: Plant Operations, Maintenance, Engineering, Modifications, Life Cycle and Balance of Plant; Nuclear Fuel and Materials; Radiation Protection and Nuclear Technology Applications ◽

10.1115/icone21-16280 ◽

2013 ◽

Author(s):

Bingchen Feng ◽

Sheng Fang ◽

Liguo Zhang ◽

Hong Li ◽

Jiejuan Tong ◽

...

Keyword(s):

Inverse Problem ◽

Spectrum Analysis ◽

Simulation Experiment ◽

Single Step ◽

Gamma Spectrum ◽

Total Variation Regularization ◽

Statistical Fluctuation ◽

Analysis Method ◽

Statistical Fluctuations ◽

Gamma Spectrum Analysis

Gamma spectrum analysis is an important technique in many radiation measurement contexts. Current gamma spectrum analysis consists of several separate procedures such as linear smoothing and peak fitting. Although widely used, this routine may give incorrect results when the peak is weak or when several peaks are overlapped together. This problem becomes more severe if the statistical fluctuation of the spectrum is large. To simultaneously resolve overlapping peaks and reduce fluctuations, an integrated gamma spectrum analysis method that can obtain peak information of gamma spectrum in a single step was proposed in this study. The proposed method models both physical modulation of gamma spectrometer and the statistical fluctuations into a single linear equation, and converts the gamma spectrum analysis into an inverse problem. Bregman iteration and total variation regularization are utilized to solve this inverse problem under the framework of variational deconvolution, so that the true spectrum can be directly obtained. The feasibility and performance of the proposed method was evaluated by both numerical simulation experiment and Monte Carlo simulation experiment. The experiment results demonstrate that the proposed method can simultaneously resolve overlapping peak and reduce the fluctuations in gamma spectra while preserves both qualitative and quantitative peak information precisely. The proposed method may provide a new way for the development of gamma spectrum analysis method.

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