Imaging and measuring methods for coating layer thickness of TRISO-coated fuel particles with high accuracy

Yang, Min; Zhang, Jianhai; Song, Sung‐Jin; Li, Xingdong; Meng, Fanqi; Ting, Kang; Liu, Wenli; Wei, Dongbo

doi:10.1016/j.ndteint.2013.01.016

Cited by 28 publications

(7 citation statements)

References 15 publications

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“…In this section we will show that these effects will be reduced effectively by using the proposed diffusion coefficient. PM equation is widely used in the image denoising applications [32][33][34]. We implement our method similar to PM.…”

Section: Resultsmentioning

confidence: 99%

Efficient diffusion coefficient for image denoising

Rafsanjani

Sedaaghi

Saryazdi

2016

Computers & Mathematics with Applications

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a b s t r a c tDiffusion coefficient has an important role in the performance of partial differential equation (PDE) based image denoising techniques. Commonly, the classical Perona-Malik (PM) diffusion coefficient is widely used in PDE-based noise removal algorithms. In this paper, PM diffusion coefficient is analyzed regarding to its flux. Based on the analysis, PM flux for regions where the gradient magnitude is higher than smoothing threshold may lead to undesirable blurring effect and edge displacement. To address these issues, the image is divided into three segments based on the gradient magnitude: regions where the gradient is lower than the smoothing threshold, regions where the gradient is between the smoothing threshold and inflection point of flux, and regions where the gradient magnitude is higher than inflection point. We define the conditions that should be considered in these three segments. Then, a diffusion coefficient, satisfying all these conditions, is computed. Experimental results confirm the performance of the proposed method with regard to peak signal-to-noise ratio (PSNR), mean structural similarity (MSSIM), universal quality index (UQI), visual information fidelity (VIF), feature similarity (FSIM), information content weighted SSIM (IW-SSIM) and visual quality.

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Section: Resultsmentioning

confidence: 99%

Efficient diffusion coefficient for image denoising

Rafsanjani

Sedaaghi

Saryazdi

2016

Computers & Mathematics with Applications

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“…Here we used NL-means (Non-local means) algorithm to realize the reduction of image noise [15][16][17]. Noise reduction, When the detector captures DR projections with a high acquisition frame frequency, images with high-level noise will be produced due to short exposure time and quantum noise from the X-ray source.…”

Section: Extra Projection Data Identification Methodsmentioning

confidence: 99%

Extra projection data identification method for fast-continuous-rotation industrial cone-beam CT

Yang

Duan

et al. 2013

Journal of X-Ray Science and Technology

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Fast-continuous-rotation is an effective measure to improve the scanning speed and decrease the radiation dose for cone-beam CT. However, because of acceleration and deceleration of the motor, as well as the response lag of the scanning control terminals to the host PC, uneven-distributed and redundant projections are inevitably created, which seriously decrease the quality of the reconstruction images. In this paper, we first analyzed the aspects of the theoretical sequence chart of the fastcontinuous-rotation mode. Then, an optimized sequence chart was proposed by extending the rotation angle span to ensure the effective 2π-span projections were situated in the stable rotation stage. In order to match the rotation angle with the projection image accurately, structure similarity (SSIM) index was used as a control parameter for extraction of the effective projection sequence which was exactly the complete projection data for image reconstruction. The experimental results showed that SSIM based method had a high accuracy of projection view locating and was easy to realize. M. Yang et al. / Extra projection data identification method for fast-continuous-rotation industrial cone-beam CTFig. 1. The principal diagram of a cone-beam CT scanning system. (Colours are visible in the online version of the article; http://dx.

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“…The use of phase contrast [5] combined with high resolution instruments can be used to clearly define the TRISO layer boundaries, while the use of appropriate filters [6,11] such as those used in this study can be used to amplify this effect to simplify the data post processing.…”

Section: Quantifying Layer Thicknessesmentioning

confidence: 99%

“…Consequently, a number of researchers [5,6] have developed laboratory based X-ray CT and radiography techniques for characterising the TRISO layer structure. Until recently these techniques have been hampered by significantly inferior spatial resolution, limiting the accuracy of the layer profiles that can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography

Lowe

Bradley

Sheng

et al. 2015

Journal of Nuclear Materials

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TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3–10 μm and 3–100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions

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Imaging and measuring methods for coating layer thickness of TRISO-coated fuel particles with high accuracy

Cited by 28 publications

References 15 publications

Efficient diffusion coefficient for image denoising

Efficient diffusion coefficient for image denoising

Extra projection data identification method for fast-continuous-rotation industrial cone-beam CT

Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography

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