Tajmal Hussain, Jongwon Seok^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 231-250, 2025, DOI:10.32604/cmes.2024.056621 - 17 December 2024

Abstract Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence (AI) and internet of things (IoT) to enhance efficiency, reduce costs, and ensure product quality. In light of the recent advancement of Industry 4.0, identifying defects has become important for ensuring the quality of products during the manufacturing process. In this research, we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network (CNN) architectures: VGG16, VGG19, Xception, and Mobile-Net V2, compensating for their… More >

Ryan Randall¹, Chunmei Chen^1,*, Mesfin Belayneh Ageze^2,3, Muluken Temesgen Tigabu⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2657-2691, 2024, DOI:10.32604/fdmp.2024.058169 - 23 December 2024

Abstract Vertical Axis Wind Turbines (VAWTs) offer several advantages over horizontal axis wind turbines (HAWTs), including quieter operation, ease of maintenance, and simplified construction. Surprisingly, despite the prevailing belief that HAWTs outperform VAWTs as individual units, VAWTs demonstrate higher power density when arranged in clusters. This phenomenon arises from positive wake interactions downstream of VAWTs, potentially enhancing the overall wind farm performances. In contrast, wake interactions negatively impact HAWT farms, reducing their efficiency. This paper extensively reviews the potential of VAWT clusters to increase energy output and reduce wind energy costs. A precise terminology is introduced More >

Salma Kouzzi^1,*, Mouniba Redah¹, Souad Morsli², Mohammed El Ganaoui³, Mohammed Lhassane Lahlaouti¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2741-2755, 2024, DOI:10.32604/fdmp.2024.055890 - 23 December 2024

Abstract This study investigates the potential for enhancing the thermal performance of external walls insulation in warmer climates through the combination of phase change materials (PCMs) and bio-based materials, specifically hemp wool and wood wool. Experimental tests using the heat flow method (HFM), and numerical simulations with ANSYS Fluent software were conducted to assess the dynamic thermal distribution and fluid-mechanical aspects of phase change materials (PCMs) within composite walls. The results demonstrate a notable reduction in peak indoor temperatures, achieving a 58% reduction with hemp wool with a close 40% reduction with wood wool when combined More >

Yuzhe Ma, Jiye Zhang^*, Jiawei Shi

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2843-2865, 2024, DOI:10.32604/fdmp.2024.055205 - 23 December 2024

Abstract The large number and dense layout of rail fastening can significantly affect the aerodynamic performance of trains. Utilizing the Improved Delayed Detached Eddy Simulation (IDDES) approach based on the SST (Shear Stress Transport) k-ω turbulent model, this study evaluates the effects of the rail fastening system on the aerodynamic force, slipstream and train wake under crosswind conditions. The results indicate that in such conditions, compared to the model without rails, the rail and the fastening system reduce the drag force coefficient of the train by 1.69%, while the lateral force coefficients increase by 1.16% and… More >

Victor Kozlov^1,*, Alsu Zimasova¹, Nikolai Kozlov²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2693-2707, 2024, DOI:10.32604/fdmp.2024.052398 - 23 December 2024

Abstract The behavior of a viscous liquid film on the wall of a rapidly rotating cylinder subjected to angular vibrations is experimentally studied. The cavity is filled with an immiscible low-viscosity liquid of lower density. In the absence of vibrations, the high viscosity liquid covers the inner surface of the cylinder with a relatively thin axisymmetric film; the low-viscosity liquid is located in the cavity interior. It is found that with an increase in the amplitude of rotational vibrations, the axisymmetric interphase boundary loses stability. An azimuthally periodic 2D “frozen wave” appears on the film surface… More >

Buchi Reddy Ramakantha Reddy, Ramasamy Lokesh Kumar^*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4081-4107, 2024, DOI:10.32604/cmc.2024.057071 - 19 December 2024

Abstract Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products, leading to suboptimal user experiences. To address this, our study presents a Personalized Adaptive Multi-Product Recommendation System (PAMR) leveraging transfer learning and Bi-GRU (Bidirectional Gated Recurrent Units). Using a large dataset of user reviews from Amazon and Flipkart, we employ transfer learning with pre-trained models (AlexNet, GoogleNet, ResNet-50) to extract high-level attributes from product data, ensuring effective feature representation even with limited data. Bi-GRU captures both spatial and sequential dependencies in user-item interactions. The innovation of this study lies… More >

Ting Chen¹, Shujiao Wang², Xin Fan^3,*, Xiujuan Zhang², Chuanwen Luo³, Yi Hong³

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3927-3950, 2024, DOI:10.32604/cmc.2024.056961 - 19 December 2024

Abstract This paper investigates an unmanned aerial vehicle (UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything (V2X) systems. Due to the presence of an eavesdropper (Eve), the system’s communication links may be insecure. This paper proposes deploying an intelligent reflecting surface (IRS) on the UAV to enhance the communication performance of mobile vehicles, improve system flexibility, and alleviate eavesdropping on communication links. The links for uploading task data from vehicles to a base station (BS) are protected by IRS-assisted physical layer security (PLS). Upon receiving task data, the computing resources provided by the edge computing servers (MEC)… More >

Xin Qi^1,2, Xingtao Shi¹, Yingwen Liu^1,*

Frontiers in Heat and Mass Transfer, Vol.22, No.6, pp. 1661-1678, 2024, DOI:10.32604/fhmt.2024.058959 - 19 December 2024

Abstract After optimizing the compressor design, condenser tube diameter, and tube row arrangement, air supply volumetric flow rate, and refrigerant charge of the domestic dehumidifier. The optimized design schemes were obtained from the original combinations by non-dominated sorting, and the optimized design schemes were experimentally verified under three environmental conditions according to the test method of T/CAS 342-2020 to obtain a complete idea of dehumidifier multi-component improvement. The results show that the dehumidifying capacity of Scheme 5 is slightly increased by 2.5% at 27°C/60% RH, and its energy factor is significantly increased by 24.6%. When the… More >

Long Huang^1,2,3,*, Junjia Zou³, Baoqing Liu¹, Zhijiang Jin^1,2, Jinyuan Qian¹

Frontiers in Heat and Mass Transfer, Vol.22, No.6, pp. 1613-1643, 2024, DOI:10.32604/fhmt.2024.058231 - 19 December 2024

Abstract This study explores the effectiveness of machine learning models in predicting the air-side performance of microchannel heat exchangers. The data were generated by experimentally validated Computational Fluid Dynamics (CFD) simulations of air-to-water microchannel heat exchangers. A distinctive aspect of this research is the comparative analysis of four diverse machine learning algorithms: Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forest (RF), and Gaussian Process Regression (GPR). These models are adeptly applied to predict air-side heat transfer performance with high precision, with ANN and GPR exhibiting notably superior accuracy. Additionally, this research further delves into… More >

P. Saila Kumari¹, S. Mohammed Ibrahim¹, Giulio Lorenzini^2,*

Frontiers in Heat and Mass Transfer, Vol.22, No.6, pp. 1839-1863, 2024, DOI:10.32604/fhmt.2024.057760 - 19 December 2024

Abstract A wide range of technological and industrial domains, including heating processors, electrical systems, mechanical systems, and others, are facing issues as a result of the recent developments in heat transmission. Nanofluids are a novel type of heat transfer fluid that has the potential to provide solutions that will improve energy transfer. The current study investigates the effect of a magnetic field on the two-dimensional flow of Williamson nanofluid over an exponentially inclined stretched sheet. This investigation takes into account the presence of multi-slip effects. We also consider the influence of viscous dissipation, thermal radiation, chemical… More >