Nguyen Thanh Hoan¹, Nguyen Van Dung¹, Ho Le Thu¹, Hoa Thuy Quynh¹, Nadhir Al-Ansari^2,*, Tran Van Phong³, Phan Trong Trinh³, Dam Duc Nguyen⁴, Hiep Van Le⁴, Hanh Bich Thi Nguyen⁴, Mahdis Amiri⁵, Indra Prakash⁶, Binh Thai Pham^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1431-1449, 2022, DOI:10.32604/cmes.2022.018699

Abstract Water level predictions in the river, lake and delta play an important role in flood management. Every year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high tides. Land subsidence may also aggravate flooding problems in this area. Therefore, accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and property. There are so many methods available to predict the water levels based on historical data but nowadays Machine Learning (ML) methods are considered the best… More >

Shuangxin He¹, Chaoyang Wang¹, Xuan Zhou^1,*, Leiting Dong^1,*, Satya N. Atluri²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1857-1882, 2022, DOI:10.32604/cmes.2022.019160

Abstract The Symmetric Galerkin Boundary Element Method is advantageous for the linear elastic fracture and crackgrowth analysis of solid structures, because only boundary and crack-surface elements are needed. However, for engineering structures subjected to body forces such as rotational inertia and gravitational loads, additional domain integral terms in the Galerkin boundary integral equation will necessitate meshing of the interior of the domain. In this study, weakly-singular SGBEM for fracture analysis of three-dimensional structures considering rotational inertia and gravitational forces are developed. By using divergence theorem or alternatively the radial integration method, the domain integral terms caused by body forces are transformed… More >

Xiaobing Mao, Hao Wu, Shuping Wan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1751-1792, 2022, DOI:10.32604/cmes.2022.019501

Abstract This paper proposes a personalized comprehensive cloud-based method for heterogeneous multi-attribute group decision-making (MAGDM), in which the evaluations of alternatives on attributes are represented by LTs (linguistic terms), PLTSs (probabilistic linguistic term sets) and LHFSs (linguistic hesitant fuzzy sets). As an effective tool to describe LTs, cloud model is used to quantify the qualitative evaluations. Firstly, the regulation parameters of entropy and hyper entropy are defined, and they are further incorporated into the transformation process from LTs to clouds for reflecting the different personalities of decision-makers (DMs). To tackle the evaluation information in the form of PLTSs and LHFSs, PLTS… More >

Rana Muhammad Zulqarnain¹, Imran Siddique², Aiyared Iampan³, Dumitru Baleanu^4,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1717-1750, 2022, DOI:10.32604/cmes.2022.019408

Abstract Interval-valued Pythagorean fuzzy so set (IVPFSS) is a generalization of the interval-valued intuitionistic fuzzy so set (IVIFSS) and interval-valued Pythagorean fuzzy set (IVPFS). The IVPFSS handled more uncertainty comparative to IVIFSS; it is the most signicant technique for explaining fuzzy information in the decision-making process. In this work, some novel operational laws for IVPFSS have been proposed. Based on presented operational laws, two innovative aggregation operators (AOs) have been developed such as interval-valued Pythagorean fuzzy so weighted average (IVPFSWA) and interval-valued Pythagorean fuzzy so weighted geometric (IVPFSWG) operators with their fundamental properties. A multi-attribute group decision-making (MAGDM) approach has been… More >

Arfan Shahzad^1,2, Muhammad Imran^1,*, Muhammad Nawaz Naeem¹, Mohsan Raza¹

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1669-1692, 2022, DOI:10.32604/cmes.2022.017914

Abstract In current study, the numerical computations of Reiner–Rivlin nanofluid flow through a rotational disk under the influence of thermal radiation and Arrhenius activation energy is considered. For innovative physical situations, the motile microorganisms are incorporated too. The multiple slip effects are considered in the boundary conditions. The bioconvection of motile microorganism is utilized alongside nanofluids to provide stability to enhanced thermal transportation. The Bioconvection pattern in various nanoparticles accredits novel applications of biotechnology like the synthesis of biological polymers, biosensors, fuel cells, petroleum engineering, and the natural environment. By deploying some suitable similarity transformation functions, the governing partial differential equations… More >

Jiali Yu, Zhili Xiang, Defeng Zhang, Yubing Gong^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1653-1667, 2022, DOI:10.32604/cmes.2022.019280

Abstract Automotive dry clutches have been found to produce a low frequency sliding noise in many applications, which challenges the ride comfort of vehicles. In order to study this clutch sliding noise, a detailed finite element model including both a pressure plate assembly and a driven plate assembly was developed. Based on this model, a complex eigenvalue analysis is performed in this research. The effect of several major factors on the clutch sliding noise, such as the coefficient of friction, the clamping force, the geometric imperfection of the friction plate, and the thermal deformation of the pressure plate, were investigated numerically.… More >

Changkye Lee¹, Sundararajan Natarajan², Seong-Hoon Kee³, Jurng-Jae Yee^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1615-1634, 2022, DOI:10.32604/cmes.2022.020377

Abstract The aim of this work is to employ a modified cell-based smoothed finite element method (S-FEM) for topology optimization with the domain discretized with arbitrary polygons. In the present work, the linear polynomial basis function is used as the weight function instead of the constant weight function used in the standard S-FEM. This improves the accuracy and yields an optimal convergence rate. The gradients are smoothed over each smoothing domain, then used to compute the stiffness matrix. Within the proposed scheme, an optimum topology procedure is conducted over the smoothing domains. Structural materials are distributed over each smoothing domain and… More >

Shaohua Gu^1,2, Jiabao Wang³, Liang Xue^3,*, Bin Tu³, Mingjin Yang³, Yuetian Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1579-1599, 2022, DOI:10.32604/cmes.2022.019435

Abstract Production performance prediction of tight gas reservoirs is crucial to the estimation of ultimate recovery, which has an important impact on gas field development planning and economic evaluation. Owing to the model’s simplicity, the decline curve analysis method has been widely used to predict production performance. The advancement of deep-learning methods provides an intelligent way of analyzing production performance in tight gas reservoirs. In this paper, a sequence learning method to improve the accuracy and efficiency of tight gas production forecasting is proposed. The sequence learning methods used in production performance analysis herein include the recurrent neural network (RNN), long… More >

Weiwei Cai^1,2, Yaping Song¹, Huan Duan¹, Zhenwei Xia¹, Zhanguo Wei^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1539-1555, 2022, DOI:10.32604/cmes.2022.019785

Abstract In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However, most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in production environments, and changing lighting conditions. This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention (MFMBA) neural network for logistics pallet segmentation. To better predict… More >

Aniket N. Sharma¹, Shilpa R. Dongre¹, Rajesh Gupta¹, Prerna Pandey¹, Neeraj Dhanraj Bokde^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1515-1537, 2022, DOI:10.32604/cmes.2022.018867

Abstract Water distribution network (WDN) leakage management has received increased attention in recent years. One of the most successful leakage-control strategies is to divide the network into District Metered Areas (DMAs). As a multi-staged technique, the generation of DMAs is a difficult task in design and implementation (i.e., clustering, sectorization, and performance evaluation). Previous studies on DMAs implementation did not consider the potential use of existing valves in achieving the objective. In this work, a methodology is proposed for detecting clusters and reducing the cost of additional valves and DMA sectorization by considering existing valves as much as possible. The procedure… More >