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1

Simplified analyses of stress induced anisotropy in remolded soft clay under undrained conditions

Lin P., Li Z.-x., Garg A., Yadav J. S.

Archives of Materials Science and Engineering

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2020

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Vol. 105, nr 2

56--64

EN

Purpose: The soil’s anisotropy induced by stress (i.e. stress induced anisotropy) has an important effect on the behavior of soil. This paper focuses on analyzing the anisotropy of remolded Shantou soft clay under compression stress path. Design/methodology/approach: Experiments were executed by using three axle experimental instruments. The data obtained from the plain strain tests were analyzed and the relationship between stress and strain was calculated by using the modified Duncan- Chang and Lade-Duncan models. The models were modified under the condition of plain strain and cohesion. Findings: It was concluded that in complex stress path conditions, the conventional triaxial tests may not fully reflect the actual stress of soil and its response in the Duncan-Chang and Lade-Duncan models. Research limitations/implications: The formulation of Mohr-Coulomb failure criterion in the plasticity framework is quite diffcult. As a result, dilatancy cannot be described. The properties of soil in unload or drained conditions remain to be part of further investigated. Practical implications: Based upon the two stiffness parameters, the modified Duncan- Chang model has captured the soil behaviour in a very conformable way and is recommened for practical modeling. These constitutive models of soil are widely used in the numerical analyses of soil structure such as embankments. Originality/value: Duncan-Chang and Lade-Duncan models widely used in engineering practices are modes based on conventional triaxial cases. Both models have have some inherent limitations to represent the stress-strain characteristics of soils, such as shear-induced dilatancy and stress path dependency and required corrections. In this investigation, the tests are carried out in undrained conditions. It is related to the properties of soil in load conditions.

2

Analysis of the factors affecting the realization of lambda transition temperature of 4He

Yin L., Lin P., Zhao J. J., Qi X.

Metrology and Measurement Systems

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2011

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Vol. 18, nr 1

13-23

EN

Owing to the dramatic change in the thermal conductivity of 4He when its temperature crosses the transition of superfluid (HeI) and normalfluid (HeII), a sealed-cell with a capillary is used to realize the lambda transition temperature, Tλ. A small heat flow is controlled through the capillary of the sealed-cell so as to realize the coexistence of HeI and HeII and maintain the stay of HeI/HeII interface in the capillary. A stable and flat lambda transition temperature "plateau" is obtained. Because there is a depression effect of Tλ caused by the heat flow through the capillary, a series of heat flows and several temperature plateaus are made and an extrapolation is applied to determine Tλ with zero heat flow. A rhodium-iron resistance thermometer with series number A34 (RIRT A34) has been used in 24 Tλ -realization experiments to derive Tλ with a standard deviation of 0.022mK, which proves the stability and reproducibility of Tλ.

3

Fuzzy c-means clustering algorithm with a novel penalty term for image segmentation

Yang Y., Zheng C., Lin P.

Opto-Electronics Review

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2005

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Vol. 13, No. 4

309-315

EN

Fuzzy clustering techniques, especially fuzzy c-means (FCM) clustering algorithm, have been widely used in automated image segmentation. However, as the conventional FCM algorithm does not incorporate any information about spatial context, it is sensitive to noise. To overcome this drawback of FCM algorithm, a novel penalized fuzzy c-means (PFCM) algorithm for image segmentation is presented in this paper. The algorithm is formulated by incorporating the spatial neighbourhood information into the original FCM algorithm with a penalty term. The penalty term acts as a regularizer in this algorithm, which is inspired by the neighbourhood expectation maximization (NEM) algorithm and is modified in order to satisfy the criterion of the FCM algorithm. Experimental results on synthetic, simulated and real images indicate that the proposed algorithm is effective and more robust to noise and other artifacts than the standard FCM algorithm.

4

X-ray carpal-bone image boundary feature analysis using region statistical feature based level set method for skeletal age assessment application

Lin P., Zheng C., Zhang F., Yang Y.

Optica Applicata

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2005

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Vol. 35, nr 2

283-294

EN

Skeletal age assessment is one of the important applications of hand radiography in the area of pediatric radiology. Feature analysis of the carpal-bones can reveal the important information for skeletal age assessment. The present work in this paper faces the problem of the detection of carpal-bone features from X-ray image. A novel and effective segmentation technique is presented in this work with carpal-bone image for skeletal age estimation. Carpal-bone segmentation is a critical operation of the automatic skeletal age assessment system. This method consists of two procedures. First, the original carpal-bone image is preprocessed via anisotropic diffusion filter. Then, the carpal-bone image is segmented by region based level set method. The basic idea of the region based level set method is to add a force that takes into account the information within the regions in order to add robustness and more efficiently separate homogeneous regions. Experiments are carried out on X-ray images of carpal-bone. The experimental results show that incorporating region statistical information into the level set method, an accurate and robust segmentation can be achieved.

5

Fuzzy clustering with spatial constraints for image thresholding

Yang Y., Zheng C., Lin P.

Optica Applicata

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2005

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Vol. 35, nr 4

943-954

EN

Image thresholding plays an important role in image segmentation. This paper presents a novel fuzzy clustering based image thresholding technique, which incorporates the spatial neighborhood information into the standard fuzzy c-means (FCM) clustering algorithm. The prior spatial constraint, which is defined as weight in this paper, is inspired by the k-nearest neighbor (k-NN) algorithm and is modified from two aspects in order to improve the performance of image thresholding. The algorithm is initialized by a fast FCM algorithm, in which the iteration is carried out with the statistical gray level histogram of image instead of the conventional whole data of image; therefore its convergence is fast. Extensive experiment results and both qualitative and quantitative comparative studies with several existing methods on the thresholding of some synthetic and real images illustrate the effectiveness and robustness of the proposed algorithm.

6

A Novel Statistical Approach for Segmentation of Single-Channel Brain MRI Using an Improved EM algorithm

Yang Y., Zheng Ch., Lin P.

Journal of Applied Computer Science

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2005

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Vol. 13, nr 1

113-125

EN

This paper presents a novel statistical method for segmentation of single-channel brain magnetic resonance (MR) image data. The method based on an improved expectation maximization (EM) algorithm proposed in this paper involves three steps. Firstly, after pre-processing the image with the curvature anisotropic diffusion filter, the background (BG) and brain masks of the image are obtained by applying a combination approach of thresholding with morphology. Secondly, the connected threshold region growing technique is employed to get the preliminary results of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) on a brain MRI. Finally, the previous results are served as the priori knowledge for the improved EM algorithm to segment the brain MRI. The performance of the proposed method is compared with that of the popular used fuzzy-C means (FCM) segmentation. Experimental results show our approach is effective, robust and significantly faster than the conventional EM based method.