Hantao Huang, Zhifang Zhang^*, Zhenhua Wu, Yao Liu

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 409-423, 2024, DOI:10.32604/sdhm.2024.048597 - 05 June 2024

Abstract In this paper, recycled carbon fiber reinforced polymer (CFRP) mixture (CFRP-M, including recycled carbon fiber and powder) and refined recycled CFRP fiber (CFRP-F, mostly recycled carbon fiber) were added to cement to study the influence of addition on the flexural strength, compressive strength, and fluidity of cement-based materials. The recycled CFRP were prepared by mechanically processing the prepreg scraps generated during the manufacture of CFRP products. For comparison, commercial carbon fiber powder was also added in cement and the performance was compared to that of addition of recycled CFRP. The hydration products and strengthening mechanism… More >

Wei Chen^*, Dingdan Liu, Yue Liang

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 915-938, 2024, DOI:10.32604/fdmp.2024.046335 - 07 June 2024

Abstract This study focuses on the effect of ultrafine waste glass powder on cement strength, gas permeability and pore structure. Varying contents were considered, with particle sizes ranging from 2 to 20 μm. Moreover, alkali activation was considered to ameliorate the reactivity and cementitious properties, which were assessed by using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and specific surface area pore size distribution analysis. According to the results, without the addition of alkali activators, the performance of glass powder mortar decreases as the amount of glass powder increases, affecting various aspects such as strength… More >

Dominique Vervoort^1,2,3,*, Amy Verstappen³, Sreehari Madhavankutty Nair⁴, Chong Chin Eu⁵, Bistra Zheleva^3,6

Congenital Heart Disease, Vol.19, No.2, pp. 131-138, 2024, DOI:10.32604/chd.2024.049814 - 16 May 2024

Abstract This article has no abstract. More >

Parth Khandelwal¹, Harshit², Indranil Manna^1,3,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1727-1755, 2024, DOI:10.32604/cmc.2024.042752 - 25 April 2024

Abstract Metallic alloys for a given application are usually designed to achieve the desired properties by devising experiments based on experience, thermodynamic and kinetic principles, and various modeling and simulation exercises. However, the influence of process parameters and material properties is often non-linear and non-colligative. In recent years, machine learning (ML) has emerged as a promising tool to deal with the complex interrelation between composition, properties, and process parameters to facilitate accelerated discovery and development of new alloys and functionalities. In this study, we adopt an ML-based approach, coupled with genetic algorithm (GA) principles, to design… More > Graphic Abstract

Junjie Zhao, Diyuan Li^*, Jingtai Jiang, Pingkuang Luo

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 275-304, 2024, DOI:10.32604/cmes.2024.046960 - 16 April 2024

Abstract Traditional laboratory tests for measuring rock uniaxial compressive strength (UCS) are tedious and time-consuming. There is a pressing need for more effective methods to determine rock UCS, especially in deep mining environments under high in-situ stress. Thus, this study aims to develop an advanced model for predicting the UCS of rock material in deep mining environments by combining three boosting-based machine learning methods with four optimization algorithms. For this purpose, the Lead-Zinc mine in Southwest China is considered as the case study. Rock density, P-wave velocity, and point load strength index are used as input variables,… More > Graphic Abstract

Susi Susi^1,2,*, Makhmudun Ainuri^3,*, Wagiman Wagiman³, Mohammad Affan Fajar Falah³

Journal of Renewable Materials, Vol.12, No.3, pp. 513-537, 2024, DOI:10.32604/jrm.2024.045586 - 11 April 2024

Abstract Microcrystalline cellulose (MCC) is one of the cellulose derivatives produced as a result of the depolymerization of a part of cellulose to achieve high crystallinity. When implemented in other polymers, high crystallinity correlates with greater strength and stiffnes, but it can reduce the water-holding capacity. The acid concentration and hydrolysis time will affect the acquisition of crystallinity and water absorption capacity, both of which have significance as properties of hydrogel filler. The study aimed to evaluate the properties and select the MCC generated from varying the proportion of hydrochloric acid (HCl) and the appropriate hydrolysis… More > Graphic Abstract

Ran Wang¹, Aimin Gong^1,*, Shanqing Shao¹, Baoli Qu², Jing Xu³, Fulai Wang¹, Feipeng Liu^3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 749-769, 2024, DOI:10.32604/fdmp.2023.042566 - 28 March 2024

Abstract The mechanical properties of cementitious sand and gravel damming material have been experimentally determined by means of microscopic SEM (Scanning Electron Microscopy) image analysis. The results show that the combination of fly ash and water can fill the voids in cemented sand and gravel test blocks because of the presence of hydrated calcium silicate and other substances; thereby, the compactness and mechanical properties of these materials can be greatly improved. For every 10 kg/m³ increase in the amount of cementitious material, the density increases by about 2%, and the water content decreases by 0.2%. The amount More > Graphic Abstract

Wei Chen^*, Wuwen Liu, Yue Liang

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 859-872, 2024, DOI:10.32604/fdmp.2023.029310 - 28 March 2024

Abstract River sand is an essential component used as a fine aggregate in mortar and concrete. Due to unrestrained exploitation, river sand resources are gradually being exhausted. This requires alternative solutions. This study deals with the properties of cement mortar containing different levels of manufactured sand (MS) based on quartzite, used to replace river sand. The river sand was replaced at 20%, 40%, 60% and 80% with MS (by weight or volume). The mechanical properties, transfer properties, and microstructure were examined and compared to a control group to study the impact of the replacement level. The More >

Bayi Xu¹, Lei Sun^2,*, Xiuqing Mao², Chengwei Liu³, Zhiyi Ding²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1995-2022, 2024, DOI:10.32604/cmc.2023.046478 - 27 February 2024

Abstract In recent years, frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security. This paper presents a novel intrusion detection system consisting of a data preprocessing stage and a deep learning model for accurately identifying network attacks. We have proposed four deep neural network models, which are constructed using architectures such as Convolutional Neural Networks (CNN), Bi-directional Long Short-Term Memory (BiLSTM), Bidirectional Gate Recurrent Unit (BiGRU), and Attention mechanism. These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the More >

Liang Zeng^1,2, Junyang Shi¹, Yanyan Li¹, Shanshan Wang^1,2,*, Weigang Li³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803 - 30 January 2024

Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III… More >