Yunyun Song¹, Xu Zhang¹, Jialei Yang¹, Zhongqiang Zhang^1,*, Guanggui Cheng¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09916

Abstract Although floating oil with large particle sizes can easily be separated from water by membrane separation methods, tiny oil droplets with tremendously small volume force and density gradient at oil-water interfaces within water lead to barriers of oil-water separation. Consequently, tiny oil droplets remain in the water, resulting in energy waste, environmental pollution and biological health hazard. Traditional super-wetting membranes with extremely small pore sizes were easily blocked during the oil-water separation process. Inspired by the cactus and rice leaf, we developed a superhydrophobic-superoleophilic surface with conical micro-arrays to realize ultrafast adsorption of tiny oil droplets within the water. The… More >

Pai Liu^1,*, Weida Wu¹, Yangjun Luo¹, Yifan Zhang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09893

Abstract Lightweight metamaterials with negative Poisson’s ratios (NPRs) have great potential for controlling deformation, absorbing energy, etc. The topology optimization [1] technique is an effective way to design metamaterials. However, as studied in [2], the NPR metamaterial configuration obtained under small deformation assumption may not maintain the desired Poisson’s ratio under relatively large deformation conditions. This paper focuses on the large-deformation NPR metamaterial design based on a gradient-free topology optimization method, i.e. the material-field series expansion (MFSE) method [3]. The metamaterial’s performance is evaluated using the finite element method, taking into account the geometry nonlinearity. By considering the spatial correlation of… More >

Yu Zhang^1,2,3, Mingkui Zhang^1,2,*, Jitao Li^1,2, Guangshu Chen^1,2

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1987-2006, 2023, DOI:10.32604/csse.2023.040381

Abstract Rockburst is a phenomenon in which free surfaces are formed during excavation, which subsequently causes the sudden release of energy in the construction of mines and tunnels. Light rockburst only peels off rock slices without ejection, while severe rockburst causes casualties and property loss. The frequency and degree of rockburst damage increases with the excavation depth. Moreover, rockburst is the leading engineering geological hazard in the excavation process, and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering. Therefore, the prediction of rockburst intensity grade is one problem that needs to be… More >

S. Palaniammal¹ , K. Saritha^2,*

Frontiers in Heat and Mass Transfer, Vol.10, pp. 1-10, 2018, DOI:10.5098/hmt.10.1

Abstract This paper investigates heat and mass transfer of a MHD Casson fluid over a permeable stretching surface in the presence of a temperature gradient heat sink. The effects of viscous dissipation, thermal radiation and chemical reaction are also taken into the consideration. The relevant similarity transformations are used to reduce the governing equations into a system of nonlinear ordinary differential equations and then solved analytically. The influence of various physical parameters on the velocity, temperature, concentration, skin friction coefficient, Nusselt and Sherwood numbers are investigated. The numerical results of skin friction factor, Nusselt and Sherwood number are compared with the… More >

Fuyong Su^a,*, Rui Song^a , Peiwei Ni^a , Zhi Wen^b

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-5, 2019, DOI:10.5098/hmt.12.25

Abstract A mathematical model of the inverse heat transfer problem of blast furnace lining is established in this study. Following the identification of the boundary conditions of the model, the inverse problem via the conjugate gradient method was decomposed into three issues: the direct problem, the sensitivity problem, and the adjoint problem. The feasibility of the model was verified through two types of real inner wall boundary shape functions. The effects of the initial inner wall boundary shape function and the number of measuring points are also investigated. Results showed that the accuracy of the inverse solution is independent of the… More >

Hadeel Alsolai¹, Mohammed Rizwanullah^2,*, Mashael Maashi³, Mahmoud Othman⁴, Amani A. Alneil², Amgad Atta Abdelmageed²

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 975-992, 2023, DOI:10.32604/cmc.2023.037936

Abstract Soil classification is one of the emanating topics and major concerns in many countries. As the population has been increasing at a rapid pace, the demand for food also increases dynamically. Common approaches used by agriculturalists are inadequate to satisfy the rising demand, and thus they have hindered soil cultivation. There comes a demand for computer-related soil classification methods to support agriculturalists. This study introduces a Gradient-Based Optimizer and Deep Learning (DL) for Automated Soil Classification (GBODL-ASC) technique. The presented GBODL-ASC technique identifies various kinds of soil using DL and computer vision approaches. In the presented GBODL-ASC technique, three major… More >

Huaxin Zhou^1,2, Ziying Fang³, Yilin Wang⁴, Mengjun Tong^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 175-194, 2023, DOI:10.32604/cmc.2023.037342

Abstract Plant diseases have become a challenging threat in the agricultural field. Various learning approaches for plant disease detection and classification have been adopted to detect and diagnose these diseases early. However, deep learning entails extensive data for training, and it may be challenging to collect plant datasets. Even though plant datasets can be collected, they may be uneven in quantity. As a result, the problem of classification model overfitting arises. This study targets this issue and proposes an auxiliary classifier GAN (small-ACGAN) model based on a small number of datasets to extend the available data. First, after comparing various attention… More >

K.S. Balamurugan^a,*, N. Udaya Bhaskara Varma^b, J.L. Ramaprasad^c

Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-7, 2020, DOI:10.5098/hmt.15.8

Abstract In this paper the entropy generation and temperature gradient heat source effects on MHD couette flow with permeable base in the presence of thermal radiation, viscous and joule's dissipation is studied. An exact solution of governing equations has been attained in closed form. The influences of several parameters on the velocity and temperature profiles and entropy generation are analyzed through graphs. Bejan number for different values have been calculated and displayed pictorially. The skin friction coefficient and Nusselt number at channel walls are derived and discussed their behaviour through tables. The entropy generation increases with intensifying magnetic field or thermal… More >

V. Banupriya^1,*, S. Anusuya²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5597-5613, 2023, DOI:10.32604/cmc.2023.038696

Abstract In the modern world, one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy (DR), which will result in retinal damage, and, thus, lead to blindness. Diabetic retinopathy (DR) can be well treated with early diagnosis. Retinal fundus images of humans are used to screen for lesions in the retina. However, detecting DR in the early stages is challenging due to the minimal symptoms. Furthermore, the occurrence of diseases linked to vascular anomalies brought on by DR aids in diagnosing the condition. Nevertheless, the resources required for manually identifying the lesions are high. Similarly,… More >

Weiguang Zheng^1,2,3, Junzhu Zhang^1,2, Shanchao Wang^2,*, Gaoshan Feng², Xiaohong Xu², Qiuxiang Ma²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 489-508, 2023, DOI:10.32604/cmes.2023.025169

Abstract The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehicle mass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variable slope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicle shifting strategy was formulated according to the identification results. The co-simulation results showed that, compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-time vehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had the following advantages, e.g., avoiding frequent shifting of vehicles… More > Graphic Abstract