Bowen Yu, Chunli Xie^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1329-1343, 2024, DOI:10.32604/cmc.2023.046248

Abstract With the advent of Industry 4.0, marked by a surge in intelligent manufacturing, advanced sensors embedded in smart factories now enable extensive data collection on equipment operation. The analysis of such data is pivotal for ensuring production safety, a critical factor in monitoring the health status of manufacturing apparatus. Conventional defect detection techniques, typically limited to specific scenarios, often require manual feature extraction, leading to inefficiencies and limited versatility in the overall process. Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes. Our… More >

Ali Akbar Firoozi^1,*, Ali Asghar Firoozi²

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573

Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous More >

Haiyu Chen¹, Haijian Shao^1,2,*, Xing Deng¹, Lijuan Wang¹, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 125-165, 2024, DOI:10.32604/cmes.2023.027834

Abstract The concept of the digital twin, also known colloquially as the DT, is a fundamental principle within Industry 4.0 framework. In recent years, the concept of digital siblings has generated considerable academic and practical interest. However, academia and industry have used a variety of interpretations, and the scientific literature lacks a unified and consistent definition of this term. The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature, beginning with its origins in the aerospace domain and extending to its contemporary interpretations in More >

Baisen Gao¹, Wei Huang^1,*, Shengnan Wang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.010553

Abstract Additive manufacturing of metallic components can result in initial defects that significantly reduce their mechanical properties [1]. Therefore, there has been considerable interest in studying the fracture and damage behavior of such components through theoretical and experimental studies [2, 3]. Developing a reliable model for predicting the ductile fracture of additively manufactured components is currently of great importance. In this study, we conducted unit cell calculations with the calibration of experimental tests to investigate the ductile fracture of Ti-6Al-4V alloy fabricated through additive manufacturing. The stress triaxiality and Lode parameter were enforced constant for the… More >

Shi Dai¹, Yanping Lian^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010175

Abstract In recent years, metal additive manufacturing (AM) has gained increasing attention from various industries. However, there are few studies on the thermal deformation behavior of additively manufactured metallic components, which is vital to pushing its applications’ boundary. In this work, we first experimentally investigate the mechanical behavior of AlSi10Mg produced by laser powder bed fusion under different temperatures and strain rates. A crystal plasticity finite element model is adopted to provide insights into the intrinsic deformation mechanisms. The model is validated by comparing it with the flow behaviors and dislocation evolutions observed in experiments at More >

Enzoh Langi¹, Liguo Zhao^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010163

Abstract Additive manufacturing emerges as an innovative technology to fabricate medical stents used to treat blocked arteries. However, there is a lack of study of underlying microstructure and mechanical properties of additively manufactured stent. In this work, additively manufactured 316L stainless steel stent was investigated, with electrochemical polishing being used to improve the surface finish. Microstructural characterisation was carried out using optical microscopy, scanning electron microscopy, and electron backscatter diffraction. The hardness and elastic modulus were measured using Berkovich nanoindentation, with an emphasis on the effect of grain orientation. In addition, spherical nanoindentation was used to… More >

Huitian Wang¹, Junjie You¹, Sha Yin^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.010417

Abstract Strong and tough mechanical metamaterials are highly demanded in engineering application. Nature inspired dual-phase metamaterial composites was developed and examined, by employing architectured lattice materials with different mechanical properties respectively as the constituent matrix and reinforcement phases. Then, the reinforcement phase was incorporated into the matrix phase with specific patterning. The composite metamaterials were simply fabricated using additive manufacturing. From quasistatic compression tests, the strength and toughness could be simultaneously enhanced after the addition of reinforcement phase grains. Through simulation modeling, effects of dual-phase distribution, elementary architecture, parent material and defects on mechanical properties of More >

Yabin Yang^1,*, Yanfei Wang¹, Quan Li²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09842

Abstract Residual stresses and deformations are one of the challenges needs to solve for metal additive manufacturing part. Finite element method plays an important role in predicting the residual stresses and deformations to reduce the experimental costs, and provides a powerful tool for the optimization of process parameters and scanning strategies of heat source. However, the key problem in simulation is the mismatch between the melt pool and the built part in both spatial and temporal scale. This would result in large discretization in both spatial and temporal domains in the simulation, which gives rise to… More >

Wen Gu^#, Xinyue Ding^#, Min Tang^*, Feiyan Gong^*, Shuangshuang Yuan, Jintao Duan

Journal of Renewable Materials, Vol.11, No.8, pp. 3245-3259, 2023, DOI:10.32604/jrm.2023.027461

Abstract Biomass adhesive is conducive to decreasing the dependence of the wood adhesive industry on synthetic resin based on fossil resources and improving the market competitiveness of adhesives. It is also a critical breakthrough to realize the goal of carbon peaking and carbon neutrality in the wood industry. In this study, a full biomass wood adhesive composed of tannin and sucrose was developed and applied successfully to the preparation of plywood. The preparation technique of plywood was optimized, and the chemical structure, curing performance, crystallization property and thermal performance of the adhesive were investigated. Results showed… More >

Wenlong Ma^1,2,*, Youhong Xu¹, Jianwei Zheng², Sadaqat ur Rehman³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1499-1512, 2023, DOI:10.32604/iasc.2023.030484

Abstract In a cloud manufacturing environment with abundant functionally equivalent cloud services, users naturally desire the highest-quality service(s). Thus, a comprehensive measurement of quality of service (QoS) is needed. Optimizing the plethora of cloud services has thus become a top priority. Cloud service optimization is negatively affected by untrusted QoS data, which are inevitably provided by some users. To resolve these problems, this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms. Untrusted data are assessed by an information correction method. The weights discovered by the variable precision Rough Set, More >