M. Nagaraj^1,*, A. John Presin Kumar², C. Ezilarasan³, Rishab Betala⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.3, pp. 679-692, 2019, DOI:10.31614/cmes.2019.04924

Abstract The paper proposes a simulated 3D Finite Element Model (FEM) for drilling of Nickel based super alloy known as Nimonic C-263. The Lagrangian finite element model-based simulations were performed to determine the thrust force, temperature generation, effective stress, and effective strain. The simulations were performed according to the L27 orthogonal array. A perfect plastic work piece was assumed, and the shape is considered to be cylindrical. The spindle speed, feed rate, and point angle were considered as the input parameters. The work piece was modeled by Johnson–Cook (JC) material model and tungsten carbide (WC) was More >

Jiayu Lu¹, Siqin Chang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.1, pp. 91-109, 2019, DOI:10.31614/cmes.2019.04190

Abstract In this paper, a trajectory planning-based energy-optimal method is proposed to reduce the energy consumption of novel electromagnetic valve train (EMVT). Firstly, an EMVT optimization model based on state equation was established. Then, the Gauss pseudospectral method (GPM) was used to plan energy-optimal trajectory. And a robust feedforward-feedback tracking controller based on inverse system method is proposed to track the energy-optimal trajectory. In order to verify the effectiveness of the energy-optimal trajectory, a test bench was established. Finally, co-simulations based on MATLAB Simulink and AVL Boost were carried out to illustrate the effect of energy-optimal More >

Jun Du^1,*, Xin Wu¹, Ruonan Li¹, Ranran Cheng¹

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.1, pp. 77-87, 2019, DOI:10.32604/fdmp.2019.05949

Abstract In this paper, we take the mid-temperature gravity heat pipe exchanger as the research object, simulate the fluid flow field, temperature field and the working state of heat pipe in the heat exchanger by Fluent software. The effects of different operating parameters and fin parameters on the heat transfer performance of heat exchangers are studied. The results show that the heat transfer performance of the mid-temperature gravity heat pipe exchanger is the best when the fin spacing is between 5 mm and 6 mm, the height of the heat pipe is between 12 mm and More >

Qiuren Ou^1,2,*, Peijun Ji², Jun Xiao¹, Ling Wu²

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.1, pp. 27-37, 2019, DOI:10.32604/fdmp.2019.04787

Abstract The properties of resin transfer molding (RTM) cyanate ester and its T800 grade carbon fiber composites were studied with the rheometer, differential scanning calorimetry (DSC), FT-IR, dynamic mechanical analyzer (DMA), thermal gravimetric analysis (TGA), mechanical property testing, and scanning electron microscopy (SEM). The results showed that the temperature of cyanate ester suitable for RTM process was 70℃. Curing process of the resin was 130℃/2 h+160℃/2 h+200℃/2 h+220℃/4 h. Glass transition temperature and heat decomposition temperature of the cured resin are 289℃ and 415℃, respectively. Mechanical properties of T800/RTM cyanate composites are 13.5% higher than that More >

Chen Shen^1,*, Youping Chen¹, Bing Chen¹, Jingming Xie¹

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 379-397, 2019, DOI:10.32604/cmc.2019.04883

Abstract Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed. As such, the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system. This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations. The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties. Thus, the controller can reduce the need… More >

Zhe Sun¹, Yunrui Bi², Songle Chen¹, Bing Hu¹, Feng Xiang³, Yawen Ling¹, Zhixin Sun^{1, ∗}

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 119-128, 2019, DOI:10.32604/cmc.2019.05274

Abstract For enhancing the control effectiveness, we firstly design a fuzzy logic based sliding mode controller (FSMC) for nonlinear crane systems. On basis of overhead crane dynamic characteristic, the sliding mode function with regard to trolley position and payload angle. Additionally, in order to eliminate the chattering problem of sliding mode control, the fuzzy logic theory is adopted to soften the control performance. Moreover, aiming at the FSMC parameter setting problem, a DE algorithm based optimization scheme is proposed for enhancing the control performance. Finally, by implementing the computer simulation, the DE based FSMC can effectively More >

Aziguli Wulamu^1,2, Zhenqi Sun^1,2, Yonghong Xie^1,2,*, Cong Xu^1,2, Alan Yang³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1283-1295, 2019, DOI:10.32604/cmc.2019.07722

Abstract At present, End-to-End trainable Memory Networks (MemN2N) has proven to be promising in many deep learning fields, especially on simple natural language-based reasoning question and answer (QA) tasks. However, when solving some subtasks such as basic induction, path finding or time reasoning tasks, it remains challenging because of limited ability to learn useful information between memory and query. In this paper, we propose a novel gated linear units (GLU) and local-attention based end-to-end memory networks (MemN2N-GL) motivated by the success of attention mechanism theory in the field of neural machine translation, it shows an improved More >

Xiaorui Zhang^1,2,3,*, Jiali Duan¹, Jia Liu², Norman I. Badler³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1055-1071, 2019, DOI:10.32604/cmc.2019.03915

Abstract Current research on suture simulation mainly focus on the construction of suture line, and existing suture simulation systems still need to be improved in terms of diversity, soft tissue effects, and stability. This paper presents an integrated liver suture surgery system composed of three consecutive suture circumstances, which is conducive to liver suture surgery training. The physically-based models used in this simulation are based on different mass-spring models regulated by a special constrained algorithm, which can improve the model accuracy, and stability by appropriately restraining the activity sphere of the surrounding mass nodes around the… More >

Zhenqiu Xiao^1,*, Bin Yang², Desy Tjahjadi³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting… More >

Aziguli Wulam^1,2, Yingshuai Wang^1,2, Dezheng Zhang^1,2,*, Jingyue Sang³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1003-1013, 2019, DOI:10.32604/cmc.2019.07704

Abstract In recent years, the models combining traditional machine learning with the deep learning are applied in many commodity recommendation practices. It has been proved better performance by the means of the neural network. Feature engineering has been the key to the success of many click rate estimation model. As we know, neural networks are able to extract high-order features automatically, and traditional linear models are able to extract low-order features. However, they are not necessarily efficient in learning all types of features. In traditional machine learning, gradient boosting decision tree is a typical representative of More >