Yuxuan Wu, Sirish Namilae^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2067-2090, 2025, DOI:10.32604/cmes.2024.059091 - 27 January 2025

Abstract Powder bed fusion (PBF) in metallic additive manufacturing offers the ability to produce intricate geometries, high-strength components, and reliable products. However, powder processing before energy-based binding significantly impacts the final product’s integrity. Processing maps guide efficient process design to minimize defects, but creating them through experimentation alone is challenging due to the wide range of parameters, necessitating a comprehensive computational parametric analysis. In this study, we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders. Uniform lattice parameter sweeps are often used for parametric… More >

Saeed Dinarvand^*, Amirmohammad Abbasi, Sogol Gharsi

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 37-60, 2025, DOI:10.32604/fdmp.2024.057545 - 24 January 2025

Abstract The present review explores the promising role of nanofluids and related hybrid variants in enhancing the efficiency of flat tube car radiators. As vehicles become more advanced and demand better thermal performance, traditional coolants are starting to fall short. Nanofluids, which involve tiny nanoparticles dispersed into standard cooling liquids, offer a new solution by significantly improving heat transfer capabilities. The article categorizes the different types of nanofluids (ranging from those based on metals and metal oxides to carbon materials and hybrid combinations) and examines their effects on the improvement of radiator performance. General consensus More >

Syed Tasnimul Karim Ayon^1,#, Farhan Md. Siraj^1,#, Jia Uddin^2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 499-520, 2025, DOI:10.32604/cmc.2025.058361 - 03 January 2025

Abstract This study investigates the application of Learnable Memory Vision Transformers (LMViT) for detecting metal surface flaws, comparing their performance with traditional CNNs, specifically ResNet18 and ResNet50, as well as other transformer-based models including Token to Token ViT, ViT without memory, and Parallel ViT. Leveraging a widely-used steel surface defect dataset, the research applies data augmentation and t-distributed stochastic neighbor embedding (t-SNE) to enhance feature extraction and understanding. These techniques mitigated overfitting, stabilized training, and improved generalization capabilities. The LMViT model achieved a test accuracy of 97.22%, significantly outperforming ResNet18 (88.89%) and ResNet50 (88.90%), as well… More >

Petr Opěla^1,*, Josef Walek^1,*, Jaromír Kopeček²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 713-732, 2025, DOI:10.32604/cmes.2024.055219 - 17 December 2024

Abstract In engineering practice, it is often necessary to determine functional relationships between dependent and independent variables. These relationships can be highly nonlinear, and classical regression approaches cannot always provide sufficiently reliable solutions. Nevertheless, Machine Learning (ML) techniques, which offer advanced regression tools to address complicated engineering issues, have been developed and widely explored. This study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic materials. The ML-based regression methods of Artificial Neural Networks (ANNs), Support Vector Machine (SVM), Decision Tree Regression (DTR), and Gaussian Process Regression More >

Dongdong Gu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.013403

Abstract In this presentation, we will report our recent research progress and prospect in the fields of laser additive manufacturing (AM) / 3D printing (3DP) of high-performance/multi-functional lightweight metallic components for aerospace applications. The innovative elements of AM including multi-material layout, innovative structural design, tailored printing process, and resultant high performance and multiple functions of components will be addressed. For a tailored printing process, some key scientific issues in AM process control deserve to be studied, including interaction of energy and printed matter, thermodynamic and dynamic behavior of printing, relationship of process parameters, microstructure and properties. More >

Ivan Lobzenko^1,*, Tomohito Tsuru¹, Yoshinori Shiihara², Takuya Iwashita³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012770

Abstract Revealing the origin of the mechanical properties of metallic glasses (MG) is a long-standing problem. MGs respond to the external strain with the activation of collective atomic motion, but the triggers of such motions are not revealed yet, in contrast to the well-defined dislocations in crystals. In the present study we show that the change of atomic Von Mises stress is one of the key local parameters to indicate the stress response to a shear strain in metallic glass. Four random Cu50%Zr50% structures were prepared in first-principles molecular dynamics cooling process. Structures were then put… 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 >

Bosong Li¹, Jamie J. Kruzic^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.011331

Abstract Additive manufacturing has made the fabrication of large-dimensioned bulk metallic glasses (BMGs) achievable; however, questions remain regarding how to control the processing parameters to obtain dense and fully amorphous BMGs with desirable mechanical properties. Here, laser powder bed fusion (LPBF) was used to produce dense and fully amorphous Zr_59.3Cu_28.8Nb_1.5Al_10.4 BMG samples from two different starting powders within a large processing window of laser powers and scanning speeds. X-ray diffraction (XRD) revealed that fully amorphous materials with high relative densities (>99%) were obtained when the LPBF energy density ranged from ~20 J/mm³ up to ~33 J/mm³ for coarse… More >

Lu Liu¹, Bo Li^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012741

Abstract Powder-Bed Fusion (PBF) is a prominent metal additive manufacturing technology known for its adaptability and commercial viability. However, it is often hindered by defects such as voids, un-melted particles, microcracking, and columnar grains, which are generally more pronounced than those found in traditional manufacturing methods. Microcracking, in particular, poses a significant challenge, limiting the use of PBF materials in safety-critical applications across various industries. This study presents an advanced computational framework that effectively addresses the complex interactions of thermal, fluid dynamics, structural mechanics, crystallization, and fracture phenomena at meso and macroscopic levels. This framework has More >

Yoshitaka Umeno^1,*, Atsushi Kubo², Emi Kawai¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.012708

Abstract Fatigue fracture accounts for a substantial fraction of failure cases in industrial products, especially in metal materials. While the mechanism of fatigue crack propagation can be understood in the mechanical point of view considering the effect of microstructures and crystal orientations on crack growth, there is still much room for investigations of the mechanism of fatigue crack formation under cyclic loading. It is widely understood that the fatigue crack formation in macroscopic metal materials originates in the persistent slip band (PSB) formed as a result of self-organization of dislocation structures [1]. Nevertheless, the PSB formation… More >