Zhengfan Lyu^1,3, Yulin Li^2,3, Mengmeng Fan^1,3,*, Yan Huang¹, Chenguang Li²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 901-913, 2024, DOI:10.32604/fdmp.2023.043512

Abstract Red mud (RM) is a low-activity industrial solid waste, and its utilization as a resource is currently a hot topic. In this study, the micro characteristics of red mud at different calcination temperatures were analyzed using X-ray diffraction and scanning electron microscopy. The performance of calcined red mud was determined through mortar strength tests. Results indicate that high-temperature calcination can change the mineral composition and microstructure of red mud, and increase the surface roughness and specific surface area. At the optimal temperature of 700°C, the addition of calcined red mud still leads to a decrease More > Graphic Abstract

Dongwei Wang^1,*, Lijian Cao¹, Weidong Wang², Jiajun Hu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1103-1122, 2024, DOI:10.32604/fdmp.2023.042654

Abstract A self-priming pump is a centrifugal pump that has the ability to prime itself. Typically, its performance depends on the configuration of its reflux hole. In this study, the ANSYS FLUENT software is used to investigate the effects of three different radial positions of the reflux hole on gas-liquid two-phase distribution, pressure pulsation, and imp during self-priming. The research results indicate that: (1) The effective channel size for the reflux liquid to enter the volute varies depending on the location of the reflux hole. The effect of the impeller rotation on the reflux liquid becomes… More >

Guanglu Xie¹, Zhimin Xue¹, Bo Xiong¹, Yaowen Huang¹, Chaoming Chen¹, Qing Liao¹, Cheng Yang^2,*, Xiaoqian Ma²

Energy Engineering, Vol.121, No.6, pp. 1495-1519, 2024, DOI:10.32604/ee.2024.047832

Abstract The determination of source-side extracted heating parameters is of great significance to the economic operation of cogeneration systems. This paper investigated the coupling performance of a cogeneration heating and power system multidimensionally based on the operating characteristics of the cogeneration units, the hydraulic and thermodynamic characteristics of the heating network, and the energy loads. Taking a steam network supported by a gas-steam combined cycle cogeneration system as the research case, the interaction effect among the source-side prime movers, the heating networks, and the terminal demand thermal parameters were investigated based on the designed values, the… More >

Xiaofeng Yang^1,3,4, Wei Wang^1,3,4,*, Yujie Shen^2,4, Changning Liu^1,3,4, Tianyi Zhang^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1485-1506, 2024, DOI:10.32604/cmes.2024.049837

Abstract This paper addresses the impact of vertical vibration negative effects, unbalanced radial forces generated by the static eccentricity of the hub motor, and road excitation on the suspension performance of Hub Motor Driven Vehicle (HMDV). A dynamic inertial suspension based on Active Disturbance Rejection Control (ADRC) is proposed, combining the vertical dynamic characteristics of dynamic inertial suspension with the features of ADRC, which distinguishes between internal and external disturbances and arranges the transition process. Firstly, a simulation model of the static eccentricity of the hub motor is established to simulate the unbalanced radial electromagnetic force… More > Graphic Abstract

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini², Sahil Verma³, Abdulatif Alabdulatif⁴, Ruba Abu Khurma^5,7, Maribel Garcia-Arenas⁶, Pedro A. Castillo^6,*

Computer Systems Science and Engineering, Vol.48, No.3, pp. 571-608, 2024, DOI:10.32604/csse.2024.042690

Abstract As cloud computing usage grows, cloud data centers play an increasingly important role. To maximize resource utilization, ensure service quality, and enhance system performance, it is crucial to allocate tasks and manage performance effectively. The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers. The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies, categories, and gaps. A literature review was conducted, which included the analysis of 463 task allocations and 480 performance management papers. The… More >

Ali Shokor Golam^*

Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 633-653, 2024, DOI:10.32604/fhmt.2024.050218

Abstract The thermal-hydraulic performance of plain tubes with and without wire coils in turbulent regimes is investigated experimentally and numerically. The effects of wire coil distribution (circular cross section) within the tube were explored experimentally, and water was employed as the working fluid. The numerical simulation was carried out using software programmer ANSYS Fluent 2019 R3 using the finite-volume approach. In the turbulent regime, six cross-sectioned wire coils were analyzed, including: circular, rectangular, hexagonal, square, star shape, and triangle. The utilization of a tube with a wire coil has been shown to increase heat transfer rate More >

Abeer H. Falih^*, Basima Salman Khalaf, Basim Freegah

Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 597-613, 2024, DOI:10.32604/fhmt.2024.049812

Abstract In this study, the primary objective was to enhance the hydrothermal performance of a dimpled tube by addressing areas with low heat transfer compared to other regions. To accomplish this, a comprehensive numerical investigation was conducted using ANSYS Fluent 2022 R1 software, focusing on different diameters of dimples along the pipe’s length and the distribution of dimples in both in-line and staggered arrangements. The simulations utilized the finite element method to address turbulent flow within the tube by solving partial differential equations, encompassing Re numbers spanning from 3000 to 8000. The study specifically examined single-phase… More > Graphic Abstract

Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 337-352, 2024, DOI:10.32604/iasc.2024.047017

Abstract Multi-Agent Reinforcement Learning (MARL) has proven to be successful in cooperative assignments. MARL is used to investigate how autonomous agents with the same interests can connect and act in one team. MARL cooperation scenarios are explored in recreational cooperative augmented reality environments, as well as real-world scenarios in robotics. In this paper, we explore the realm of MARL and its potential applications in cooperative assignments. Our focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory with minimal damage. To accomplish this, we utilize the StarCraft… More >

Mozamel M. Saeed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 213-231, 2024, DOI:10.32604/iasc.2024.043020

Abstract The study aims to recognize how efficiently Educational Data Mining (EDM) integrates into Artificial Intelligence (AI) to develop skills for predicting students’ performance. The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University. The first step’s initial population placements were created using Particle Swarm Optimization (PSO). Then, using adaptive feature space search, Educational Grey Wolf Optimization (EGWO) was employed to choose the optimal attribute combination. The second stage uses the SVM classifier to forecast classification accuracy. Different classifiers were utilized to evaluate the performance of students. According to… More >

Adil Hussain^1,*, Ayesha Aslam²

Journal on Artificial Intelligence, Vol.6, pp. 129-152, 2024, DOI:10.32604/jai.2024.050277

Abstract The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly. The utilization of machine learning in the medical domain has witnessed a notable surge due to its ability to discern patterns from vast amounts of data. Machine learning algorithms that can categorize cases of cardiovascular illness may help doctors reduce the number of wrong diagnoses. This research investigates the efficacy of different machine learning algorithms in predicting cardiovascular disease in accordance with risk factors. This study utilizes a variety of machine learning models, More >