• Geomechanics and Engineering
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• v.34 no.6
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• pp.683-696
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• 2023

The destruction and fracture of rock masses are crucial components in engineering and there is an increasing demand for the study of the influence of rock mass heterogeneity on the safety of engineering projects. The numerical manifold method (NMM) has a unified solution format for continuous and discontinuous problems. In most NMM studies, material homogeneity has been assumed and despite this simplification, fracture mechanics remain complex and simulations are inefficient because of the complicated topology updating operations that are needed after crack propagation. These operations become computationally expensive especially in the cases of heterogeneous materials. In this study, a heterogeneous model algorithm based on stochastic theory was developed and introduced into the NMM. A new fracture algorithm was developed to simulate the rupture zone. The algorithm was validated for the examples of the four-point shear beam and semi-circular bend. Results show that the algorithm can efficiently simulate the rupture zone of heterogeneous rock masses. Heterogeneity has a powerful effect on the macroscopic failure characteristics and uniaxial compressive strength of rock masses. The peak strength of homogeneous material (with heterogeneity or standard deviation of 0) is 2.4 times that of heterogeneous material (with heterogeneity of 11.0). Moreover, the local distribution of parameter values can affect the configuration of rupture zones in rock masses. The local distribution also influences the peak value on the stress-strain curve and the residual strength. The post-peak stress-strain curve envelope from 60 random calculations can be used as an estimate of the strength of engineering rock masses.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2968-2976
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• 2021

This paper introduces a method to reconstruct the three-dimensional (3D) microstructure of two-phase materials, e.g., porous materials such as highly irradiated nuclear fuel, from two-dimensional (2D) sections via a multi-objective optimization genetic algorithm. The optimization is based on the comparison between the reference and reconstructed 2D sections on specific target properties, i.e., 2D pore number, and mean value and standard deviation of the pore-size distribution. This represents a multi-objective fitness function subject to weaker hypotheses compared to state-of-the-art methods based on n-points correlations, allowing for a broader range of application. The effectiveness of the proposed method is demonstrated on synthetic data and compared with state-of-the-art methods adopting a fitness based on 2D correlations. The method here developed can be used as a cost-effective tool to reconstruct the pore structure in highly irradiated materials using 2D experimental data.

• Coupled systems mechanics
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• v.8 no.4
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• pp.289-298
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• 2019

Reinforced concrete can be considered as a heterogeneous material consisting of coarse aggregate, mortar mix and reinforcing bars. This paper presents a two-dimensional mesoscopic analysis of reinforced concrete beams using a simple two-phase mesoscopic model for concrete. The two phases of concrete, coarse aggregate and mortar mix are bonded together with reinforcement bars so that inter force transfer will occur through the material surfaces. Monte Carlo's method is used to generate the random aggregate structure using the constitutive model at mesoscale. The generated models have meshed such that there is no material discontinuity within the elements. The proposed model simulates the load-deflection behavior, crack pattern and ultimate load of reinforced concrete beams reasonably well.

• Computers and Concrete
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• v.26 no.1
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• pp.11-20
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• 2020

Concrete are the most widely used manmade materials for infrastructure construction across the world. These constructions gradually aged and damaged due to long-term use. However, there does not exist an efficient concrete recycling method with low energy consumption. In this study, concrete was regarded as a heterogeneous material composed of coarse aggregate and cement mortar. And the failure mode of concrete under ultrasonic dynamic loading was investigated by finite element (FE) analysis. Simultaneously, a 3D random aggregate concrete model was programmed by APDL and imported into ABAQUS software, and the damage plastic constitutive model was applied to each phase to study the damage law of concrete under dynamic loading. Meanwhile, the dynamic damage process of concrete was numerically simulated, which observed ultrasonic propagating and the concrete crushing behavior. Finally, the FE simulation considering the influence of different aggregate volume and aggregate size was carried out to illustrate the damage level of concrete.

• International Journal of Concrete Structures and Materials
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• v.18 no.1E
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• pp.23-28
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• 2006

In this study, the general theory of fractality is discussed to provide a fundamental understanding of fractal geometry applied to heterogeneous material surfaces like pavement surface and rock surface. It is well known that many physical phenomena and systems are chaotic, random and that the features of roughness are found at a wide spectrum of length scales from the length of the sample to the atomic scales. Studying the mechanics of these physical phenomena, it is absolutely necessary to characterize such multi scaled rough surfaces and to know the structural property of such surfaces at all length scales relevant to the phenomenon. This study emphasizes the role of fractal geometry to characterize the roughness of various surfaces. Pavement roughness and rock surface roughness were examined to correlate their roughness property to fractality.

• Computers and Concrete
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• v.5 no.3
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• pp.175-194
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• 2008

Increasingly numerical (finite element) modeling of concrete hinges on our ability to develop a representative volume element with all its heterogeneity properly discretized. Yet, despite all the sophistication of the ensuing numerical models, the initial discretization has been for the most part simplistic. Whenever the heterogeneity of the concrete is to be accounted for, a mesh is often manually crafted through the arbitrary inclusion of the particles (aggregates and/or voids) in an ad-hoc manner. This paper develops a mathematical strategy to precisely address this limitation. Algorithms for the random generation and placement of elliptical (2D) or ellipsoid (3D) inclusions, with possibly radiating cracks, in a virtual concrete model are presented. Collision detection algorithms are extensively used.

• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.58-66
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• 1998

Purpose : This paper introduces a new three dimensional magnetic Resonance Image classification which is based on Mar kov Random Field-Gibbs Random Field with a line model. Material and Methods : The performance of the Gibbs Classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at the local neighborhood level. This usually involves the construction of a line model for the image. In this paper we construct a line model for multisignature images based on the differential of the image which can provide an a priori estimate of the unobservable line field, which may lie in regions with significantly different statistics. the line model estimated from the original image data can in turn be used to alter the values of the interaction parameters of the Gibbs Classifier. Results : MRF-Gibbs classifier for volumetric MR images is developed under the condition that the domain of the image classification is $E^{3}$ space rather thatn the conventional $E^{2}$ space. Compared to context free classification, MRF-Gibbs classifier performed better in homogeneous and along boundaries since contextual information is used during the classification. Conclusion : We construct a line model for multisignature, multidimensional image and derive the interaction parameter for determining the energy function of MRF-Gibbs classifier.

• Interaction and multiscale mechanics
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• v.3 no.1
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• pp.23-37
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• 2010

Concrete is a heterogeneous material consisting of coarse aggregate, mortar matrix and interfacial zones at the meso level. Though studies have been done to interpret the fracture process in concrete using meso level models, not much work has been done for simulating the macroscopic behaviour of reinforced concrete structures using the meso level models. This paper presents a procedure for the mesoscopic analysis of reinforced concrete beams using a modified micro truss model. The micro truss model is derived based on the framework method and uses the lattice meshes for representing the coarse aggregate (CA), mortar matrix, interfacial zones and reinforcement bars. A simple procedure for generating a random aggregate structure is developed using the constitutive model at meso level. The study reveals the potential of the mesoscopic numerical simulation using a modified micro truss model to predict the nonlinear response of reinforced concrete structures. The modified micro truss model correctly predicts the load-deflection behaviour, crack pattern and ultimate load of reinforced concrete beams failing under different failure modes.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.32-43
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• 2023

Resistive Random Access Memory (RRAM), based on resistive switching characteristics, is emerging as a next-generation memory device capable of efficiently processing large amounts of data through its fast operation speed, simple device structure, and high-density implementation. Interface type resistive switching offer the advantage of low operation currents without the need for a forming process. Especially, for RRAM devices based on transition metal oxides, various studies are underway to enhance the memory characteristics, including precise material composition control and improving the reliability and stability of the device. In this paper, we introduce various methods, such as doping of heterogeneous elements, formation of multilayer films, chemical composition adjustment, and surface treatment to prevent degradation of interface type resistive switching properties and enhance the device characteristics. Through these approaches, we propose the feasibility of implementing high-efficient next-generation non-volatile memory devices based on improved resistive switching properties.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1741-1754
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• 2020

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and -0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.