Xinlong Wang¹, Xiaohang Qu¹, Chuandong Lin^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011311

Abstract The lattice Boltzmann method (LBM) has been extensively utilized in various fields, including the droplet dynamics [1–4]. At present, significant challenges persist in accurately resolving interfacial dynamics during droplet collisions—including deformation [5], breakup process [6] and capturing microscale details [7] of contact line motion during droplet-wall interactions. In this work, the non-orthogonal multiple relaxation time lattice Boltzmann method is used to study droplets impacting superhydrophobic walls with different characteristic of surface protrusion. The horizontal displacement, maximum spreading length, and the contact time are probed in the process of droplet collisions under various conditions of Weber More >

Jinhua Lu^1,*, Song Zhao¹, Pierre Boivin¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.011180

Abstract The hybrid lattice Boltzmann model [1] for compressible flows uses the lattice Boltzmann method (LBM) to simulate the flow field and the finite volume scheme for the energy field. It inherits the good numerical stability and low dissipation [2] of LBM and avoids the complexity of solving all governing equations within the LBM framework. However, it still faces three issues. First, for compressible flows, the equilibrium distribution functions must exactly recover third-order moments, but it cannot be achieved for the simple DmQn (m dimensions and n discrete phase velocities) models involving only neighboring nodes [3],… More >

Noura Alsedais¹, Mohamed Ahmed Mansour², Abdelraheem M. Aly³, Sara I. Abdelsalam^4,5,*

Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1277-1307, 2024, DOI:10.32604/fhmt.2024.056087 - 30 October 2024

Abstract The research examines fluid behavior in a porous box-shaped enclosure. The fluid contains nanoscale particles and swimming microbes and is subject to magnetic forces at an angle. Natural circulation driven by biological factors is investigated. The analysis combines a traditional numerical approach with machine learning techniques. Mathematical equations describing the system are transformed into a dimensionless form and then solved using computational methods. The artificial neural network (ANN) model, trained with the Levenberg-Marquardt method, accurately predicts values, showing high correlation (R = 1), low mean squared error (MSE), and minimal error clustering. Parametric analysis reveals significant… More >

Dongmin Wang^1,2,*, Gaoshuai Lin¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 299-318, 2023, DOI:10.32604/cmes.2023.027280 - 23 April 2023

Abstract There are five most widely used contact angle schemes in the pseudopotential lattice Boltzmann (LB) model for simulating the wetting phenomenon: The pseudopotential-based scheme (PB scheme), the improved virtual-density scheme (IVD scheme), the modified pseudopotential-based scheme with a ghost fluid layer constructed by using the fluid layer density above the wall (MPB-C scheme), the modified pseudopotential-based scheme with a ghost fluid layer constructed by using the weighted average density of surrounding fluid nodes (MPB-W scheme) and the geometric formulation scheme (GF scheme). But the numerical stability and accuracy of the schemes for wetting simulation remain… More >

G. Naveen Sundar¹, Stalin Selvaraj², D. Narmadha¹, K. Martin Sagayam³, A. Amir Anton Jone³, Ayman A. Aly⁴, Dac-Nhuong Le^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 31-46, 2022, DOI:10.32604/cmes.2022.019914 - 18 July 2022

Abstract Hepatocellular carcinoma (HCC) is one major cause of cancer-related mortality around the world. However, at advanced stages of HCC, systematic treatment options are currently limited. As a result, new pharmacological targets must be discovered regularly, and then tailored medicines against HCC must be developed. In this research, we used biomarkers of HCC to collect the protein interaction network related to HCC. Initially, DC (Degree Centrality) was employed to assess the importance of each protein. Then an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target More >

Yuling Zhai^*, Long Li, Zihao Xuan, Mingyan Ma, Hua Wang

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 629-646, 2022, DOI:10.32604/fdmp.2022.017485 - 22 February 2022

Abstract The thermo-physical properties of nanofluids are highly dependent on the used base fluid. This study explores the influence of the mixing ratio on the thermal conductivity and viscosity of ZnO-CuO/EG (ethylene glycol)-W (water) hybrid nanofluids with mass concentration and temperatures in the ranges 1-5 wt.% and 25-60°C, respectively. The characteristics and stability of these mixtures were estimated by TEM (transmission electron microscopy), visual observation, and absorbance tests. The results show that 120 min of sonication and the addition of PVP (polyvinyl pyrrolidone) surfactant can prevent sedimentation for a period reaching up to 20 days. The… More >

Xuehui Wang¹, Edward Wright¹, Zeyu Liu¹, Neng Gao^2,*, Ying Li³

Energy Engineering, Vol.119, No.2, pp. 801-814, 2022, DOI:10.32604/ee.2022.018241 - 24 January 2022

Abstract The pulsating heat pipe is a very promising heat dissipation device to address the challenge of higher heat-flux electronic chips, as it is characterised by excellent heat transfer ability and flexibility for miniaturisation. To boost the application of PHP, reliable heat transfer performance evaluation models are especially important. In this paper, a heat transfer correlation was firstly proposed for closed PHP with various working fluids (water, ethanol, methanol, R123, acetone) based on collected experimental data. Dimensional analysis was used to group the parameters. It was shown that the average absolute deviation (AAD) and correlation coefficient More >

Tanzila Saba¹, Mirza Naveed Shahzad^2,*, Sonia Iqbal^2,3, Amjad Rehman¹, Ibrahim Abunadi¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4785-4801, 2022, DOI:10.32604/cmc.2022.022309 - 14 January 2022

Abstract Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In… More >

Mohammad B. Khan¹, Abdul R. Khan^2,*, Hasan Alkahtani²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2333-2346, 2022, DOI:10.32604/cmc.2022.020623 - 07 December 2021

Abstract Architectures based on the data flow computing model provide an alternative to the conventional Von-Neumann architecture that are widely used for general purpose computing. Processors based on the data flow architecture employ fine-grain data-driven parallelism. These architectures have the potential to exploit the inherent parallelism in compute intensive applications like signal processing, image and video processing and so on and can thus achieve faster throughputs and higher power efficiency. In this paper, several data flow computing architectures are explored, and their main architectural features are studied. Furthermore, a classification of the processors is presented based… More >

Nawaf N. Hamadneh¹, Waqar A. Khan², Waqar Ashraf³, Samer H. Atawneh⁴, Ilyas Khan^5,*, Bandar N. Hamadneh⁶

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2787-2796, 2021, DOI:10.32604/cmc.2021.013228 - 28 December 2020

Abstract In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. More >