Yang Chen¹, Baobin Xie¹, Weizheng Lu¹, Jia Li^1,*, Qihong Fang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.011624

Abstract In order to accurately predict and evaluate the mechanical properties of multi-principal element alloys (MPEAs), some new models and simulation methods need to be developed to solve the problems caused by its unique natural characteristics, such as severe lattice distortion. The existing models are based on the development of low concentration alloys, and cannot be well applied to MPEAs. Here, we develop i) the random field theory informed discrete dislocation dynamics simulations based on high-resolution transmission electron microscopy, to systematically clarify the role of heterogeneous lattice strain on the complex interactions between the dislocation loop… More >

Xinmeng Zha¹, Huilin Ren^1,*, Yi Xiong^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011371

Abstract Additive manufacturing of continuous fiber composites is an emerging field that enables the tunable mechanical performance of composite structure by flexibly controlling the spatial layout of continuous fibers. Transverse isotropic strengthening is advantageous property of continuous fiber, which is favorable to align with the principal stress orientation. However, the accuracy and efficiency of traditional methods for calculating principal stress field are unguaranteed due to the inherent complexity and variability of geometries, material properties, and operational conditions in additive manufacturing. Therefore, a machine learning-assisted path planning method is proposed to robustly and efficiently generate the continuous… More >

Qi An^1,*, Lihua Cui¹, Lujun Huang¹, Lin Geng¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011973

Abstract Ti-6.5Al-2.5Zr-1Mo-1V alloy is a near α titanium alloy, which has been widely used in aerospace fields due to its low density, high specific strength, good corrosion resistance and high-temperature durability. To further improve the strength and high-temperature durability of Ti-6.5Al-2.5Zr-1Mo-1V complex components, the spherical Ti-6.5Al-2.5Zr-1Mo-1V alloy powder with a particle size of 15~53 μm and TiB2 powder with a particle size of 0.5~1 μm were used to fabricate in-situ TiBw reinforced Ti-6.5Al-2.5Zr-1Mo-1V composites through low energy ball milling and selective laser melting (SLM). The results show that the TiB whiskers are uniformly distributed in the 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

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

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 >

Jia Li¹, Yang Chen¹, Baobin Xie¹, Weizheng Lu¹, Qihong Fang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-2, 2023, DOI:10.32604/icces.2023.010064

Abstract The high-profile high-entropy alloy shows outstanding mechanical properties. However, the accurate and reasonable models for describing the mechanical behavior of HEAs are still scarce due to their distinctive characteristics such as serious lattice distortion, which limit the engineering application. We have developed a new general framework combining atomic simulation, discrete dislocation dynamics and crystal plasticity finite element method, to study the deformation behaviour and strengthening mechanism of HEAs, and realized the influence of complex cross-scale factors on material deformation [1-3]. Compared with the classic crystal plasticity finite element, the bottom-up hierarchical multiscale model could couple… More >

Mao Li¹, Xiaobao Tian¹, Wentao Jiang¹, Qingyuan Wang¹, Haidong Fan^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09981

Abstract Poor ductility heavily limits the industrial application of magnesium (Mg) alloys, and pyramidal dislocations are an important deformation mode for ductility enhancement. In this work, discrete dislocation dynamics (DDD) simulations were performed to study the mechanical behavior and dislocation evolution of Mg singlecrystals compressed along c-axis. Especially, basal-transition and cross-slip algorithms of pyramidal dislocations were proposed and introduced in the DDD method. Simulation results show that basaltransition is an important mechanism for the strong strain hardening observed during c-axis compression of Mg single-crystals. Since the basal-transition events are thermally activated, increasing temperature leads to a More >

Zihang Li^1,#, Zexin Wang^1,#, Zi Wang², Zijun Qin¹, Feng Liu¹, Liming Tan^1,*, Xiaochao Jin^3,*, Xueling Fan³, Lan Huang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1521-1538, 2023, DOI:10.32604/cmes.2022.021639 - 27 October 2022

Abstract Solid solution strengthening (SSS) is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks. The value of SSS can be calculated by using Fleischer’s and Labusch’s theories, while the model parameters are incorporated without fitting to experimental data of complex alloys. In this work, four diffusion multiples consisting of multicomponent alloys and pure Ni are prepared and characterized. The composition and microhardness of single γ phase regions in samples are used to quantify the SSS. Then, Fleischer’s and Labusch’s theories are examined based on high-throughput experiments, More >