Quynh-Anh Thi Bui^1,*, Dam Duc Nguyen¹, Hiep Van Le¹, Indra Prakash², Binh Thai Pham^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 691-712, 2025, DOI:10.32604/cmes.2024.054766 - 17 December 2024

Abstract Determination of Shear Bond strength (SBS) at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures. The study used three Machine Learning (ML) models, including K-Nearest Neighbors (KNN), Extra Trees (ET), and Light Gradient Boosting Machine (LGBM), to predict SBS based on easily determinable input parameters. Also, the Grid Search technique was employed for hyper-parameter tuning of the ML models, and cross-validation and learning curve analysis were used for training the models. The models were built on a database of 240 experimental results and three input variables: temperature, normal pressure, and tack coat… More >

Weiwei Hu¹, Kiran Sree Pokkuluri², Rajesh Arunachalam^3,*, Bander A. Jabr⁴, Yasser A. Ali⁴, Preethi Palanisamy⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4833-4851, 2024, DOI:10.32604/cmc.2024.055561 - 19 December 2024

Abstract Wireless Sensor Network (WSNs) consists of a group of nodes that analyze the information from surrounding regions. The sensor nodes are responsible for accumulating and exchanging information. Generally, node localization is the process of identifying the target node’s location. In this research work, a Received Signal Strength Indicator (RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models. Initially, the RSSI value is identified using the Deep Neural Network (DNN). The RSSI is conceded as the range-based method and it does not require special hardware for the node… More >

Pengda Niu¹, Ruidi Li^1,*, Tiechui Yuan¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012243

Abstract In terms of grain refinement and component shape complexity, laser additive manufacturing (AM) is unmatched. This is exemplified by laser powder bed fusion (LPBF), whose rapid solidification and non-equilibrium metallurgy have expanded the understanding of ultra-fine grains and sub-stable organization among academics. At present, the reliability of LPBF components is being questioned by the industry due to the rapid heating and cooling cycles in AM processing, coupled with the extreme non-equilibrium heat-fluid-mass process, which renders LPBF printing vulnerable to metallurgical defects like microcracks and porosity. A significant impediment to the development of LPBF lies in… More >

Shouyin Zhang^1,*, Zhifeng Xu¹, Qiangwei Xiao²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012141

Abstract 3D printing sand mold has been widely used in casting production. However, there exist some problems hindering its application for titanium alloy casting, such as the large amount of gas evolution, cannot withstand high temperature impact, easy to react with titanium alloy melt, etc. This work develops a high-temperature resistance SLS (selective laser sintering) sand mold process by introducing inorganic binder in two different ways, i.e., bi-binder SLS process and SLS infiltration process. After sintering at 1100 ℃, SLS sand mold or core possesses high tensile strength and can be used for titanium alloy casting. More >

Gwang Mok Kim^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012583

Abstract This study summarized a part of the research conducted by Kim et al. [1]. The utilization of low-lime calcium silicate cement presents a promising avenue for reducing CO2 emissions in construction fields. Ordinary Portland cement pastes with the type of calcium silicate cement powder were fabricated and solidified under carbonation curing conditions. The physicochemical characteristics of the pastes were examined via variable tests including initial setting and flow characteristics, compressive strength and so on. Limestone and silica fume were employed for the synthesis of the calcium silicate cement used here. The content of calcium silicate More >

Jianfeng Zhao^1,*, Xu Zhang², Guozheng Kang², Michael Ziaser³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012582

Abstract A continuum model of dislocation transport incorporating grain boundary transmission was developed within a dislocation-based crystal plasticity framework, which was then adopted to study the deformation mechanisms of gradient-structured material and bimodal-grained material. The nonlocal nature of the model on the slip system level enables the direct investigation of strain gradient effects caused by internal deformation heterogeneities. Furthermore, the interaction between dislocations and grain boundaries leads to the formation of pileups near grain boundaries, which is key to studying the grain size effects in polycrystals. Finite element implementation of the model for polycrystals with different… More >

Ken-ichi Saitoh^1,*, Makoto Watanabe²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012624

Abstract Natural nanofibers, e.g., cellulose nanofiber (CNF) of plant, collagen fibril in human body and fibroin fiber in spider silk, show interesting and distinctive atomistic mechanisms in deformation under mechanical loading as well as exhibition of extraordinary strength. These fibers are comprising more larger bulk and wire materials by constructing structural hierarchy. However, the initiation of unique behavior of these materials largely originates from atomic-scale and chemical energetics in loading. Besides, the experimental approach is often difficult and is too limited to reveal the basic mechanism. Therefore, it is crucial to clarify atomic behavior of these… More >

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 >

Wei Song^1,*, Xiaojian Shi², Shoupan Wei²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012236

Abstract Different post-welding treatments, such as TIG-Dressing, blinding, HFMI et.al are often used for steel welded joints in construction machinery manufacturing as an effective and reliable method for fatigue strength improvement. This paper investigates the fatigue performance of thick Q355D cruciform joints in heavy load-carrying steel structures under different treatments. Two TIG-Dressing treatments, blinding and HFMI for the full-penetration welded joints were used for fatigue tests. Experimental tests studied the fatigue strength of cruciform welded joints of Q355D structural steel under different treatments. The geometric parameters and relevant statistical analyses were performed by actual 3D optical 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 >