Siwen Xu¹, Hanning Chen², Rui Ni¹, Maowei He², Zhaodi Ge³, Xiaodan Liang^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-25, 2026, DOI:10.32604/cmc.2025.071398 - 09 December 2025

Abstract Selective Laser Melting (SLM), an advanced metal additive manufacturing technology, offers high precision and personalized customization advantages. However, selecting reasonable SLM parameters is challenging due to complex relationships. This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm. JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones, but it is prone to premature convergence thus leading to insufficient global search. To overcome limitations, this research proposes a Differential Evolution-framed JAYA algorithm (DEJAYA). DEJAYA incorporates four key enhancements More >

Zhijie Lin¹, Chao Yang^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-33, 2026, DOI:10.32604/cmc.2025.070735 - 09 December 2025

Abstract Sustainable aluminum alloys, renowned for their lower energy consumption and carbon emissions, present a critical path towards a circular materials economy. However, their design is fraught with challenges, including complex performance variability due to impurity elements and the time-consuming, cost-prohibitive nature of traditional trial-and-error methods. The high-dimensional parameter space in processing optimization and the reliance on human expertise for quality control further complicate their development. This paper provides a comprehensive review of Artificial Intelligence (AI) techniques applied to sustainable aluminum alloy design, analyzing their methodologies and identifying key challenges and optimization strategies. We review how… More >

Ehsan Akbari¹, Tajbakhsh Navid Chakherlou¹, Hamed Tabrizchi^2,3,*, Amir Mosavi^3,4,5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 305-325, 2025, DOI:10.32604/cmes.2025.068581 - 30 October 2025

Abstract The ability to predict multiaxial fatigue life of Al-Alloy 7075-T6 under complex loading conditions is critical to assessing its durability under complex loading conditions, particularly in aerospace, automotive, and structural applications. This paper presents a physical-informed neural network (PINN) model to predict the fatigue life of Al-Alloy 7075-T6 over a variety of multiaxial stresses. The model integrates the principles of the Geometric Multiaxial Fatigue Life (GMFL) approach, which is a novel fatigue life prediction approach to estimating fatigue life by combining multiple fatigue criteria. The proposed model aims to estimate fatigue damage accumulation by the More >

Fengjuan Ding¹, Lu Suo², Tengjiao Hong^1,3,*, Fulong Dong¹, Dong Huang¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4551-4570, 2025, DOI:10.32604/cmc.2025.069565 - 23 October 2025

Abstract The complex phenomena that occur during the plastic deformation process of aluminum alloys, such as strain rate hardening, dynamic recovery, recrystallization, and damage evolution, can significantly affect the properties of these alloys and limit their applications. Therefore, studying the high-temperature flow stress characteristics of these materials and developing accurate constitutive models has significant scientific research value. In this study, quasi-static tensile tests were conducted on 5754 aluminum alloy using an electronic testing machine combined with a high-temperature environmental chamber to explore its plastic flow behavior under main deformation parameters (such as deformation temperatures, strain rates,… More >

Xuewei Fang^1,2,*, Jiannan Yang¹, Ke Huang¹, Bingheng Lu^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012410

Abstract Wire and Arc Additive Manufacturing (WAAM) technology has the advantages of high-efficiency and low-cost to fabricate large-scaled components with medium-complexity. 2319 aluminum alloy is a widely used in aerospace and military industries. Problems of porosity, residual stress, distortion, and poor mechanical properties were focused on in this paper. The mechanism of defect formation during fabrication and strengthening mechanism of peening process were investigated. In order to learn the droplet transfer and molten pool flow behavior, CFD models of molten pools for the pulse mode of CMT (CMT + P) and pulse reverse polarity CMT mode… More >

Zhiheng Hu^1,*, Hang Li Seet¹, Sharon Mui Ling Nai¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012118

Abstract Heat treatment is a common way for enhancing the mechanical properties of the aluminum alloys. For the alloys developed for laser powder bed fusion, changes in chemical composition, together with the non-equilibrium microstructures resulting from the ultrafast cooling rate during the process, potentially alter the effectiveness of heat treatment. This study investigates the effect of the heat treatments on a Al6xxx alloy fabricated by LPBF. The response to the same heat treatment varies depending on the initial microstructure, and similarly, different heat treatments yield distinct outcomes when applied to the same original microstructures. While there… More >

Wenjun Zhou^1,2, Mingzhi Yang¹, Qian Peng², Yong Peng^1,*, Kui Wang¹, Qiang Xiao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 735-755, 2024, DOI:10.32604/cmes.2024.047258 - 16 April 2024

Abstract The widespread adoption of aluminum alloy electric buses, known for their energy efficiency and eco-friendliness, faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel. This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries, necessitating robust frame protection. Our study aims to optimize the connectors of aluminum alloy bus frames, emphasizing durability, energy efficiency, and safety. This research delves into Multi-Objective Coordinated Optimization (MCO) techniques for lightweight design in aluminum alloy bus body connectors. Our goal is to enhance lightweighting, reinforce energy absorption,… More >

Da Cai, Yinlong Song, Hao Jiang, Guangyao Li, Junjia Cui^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 873-887, 2024, DOI:10.32604/fdmp.2023.025833 - 28 March 2024

Abstract Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness. They can be produced at room temperature by the electrohydraulic forming process. In the present study, the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed. In particular, the orthogonal experimental design (OED) and central composite design (CCD) methods have been used. Through the range analysis and variance analysis of the experimental data, the influence degree of wire diameter (WD) and discharge energy More >

Wei Li^1,2, Benjian Zou¹, Yuxiang Luo², Ning Yang², Faye Zhang^1,*, Mingshun Jiang¹, Lei Jia¹

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 485-500, 2023, DOI:10.32604/sdhm.2023.025989 - 17 November 2023

Abstract As a critical structure of aerospace equipment, aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the system. In this study, a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of spacecraft. Firstly, together with numerical simulation, the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed, to establish the damage data. Subsequently, the amplitude-frequency characteristics of impact damage signals are extracted and put… More >

Mustafa Sami Abdullatef^*, Faten N. Alzubaidi, Anees Al-Tamimi, Yasser Ahmed Mahmood

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2083-2107, 2023, DOI:10.32604/fdmp.2023.027266 - 04 April 2023

Abstract The ongoing effort to create methods for detecting and quantifying fatigue damage is motivated by the high levels of uncertainty in present fatigue-life prediction approaches and the frequently catastrophic nature of fatigue failure. The fatigue life of high strength aluminum alloy 2090-T83 is predicted in this study using a variety of artificial intelligence and machine learning techniques for constant amplitude and negative stress ratios (). Artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), support-vector machines (SVM), a random forest model (RF), and an extreme-gradient tree-boosting model (XGB) are trained using numerical and experimental input… More > Graphic Abstract