Fatemeh Rezaei^1,2,*, Milan Gaff^1,3,4,*, Róbert Nemeth⁵, Jerzy Smardzewski⁶, Peter Niemz⁷, Haitao Li^8,9, Anil Kumar Sethy^1,10, Luigi Todaro¹¹, Gourav Kamboj¹, Sumanta Das¹, Roberto Corleto¹, Gianluca Ditommaso¹, Miklós Bak⁵

Journal of Renewable Materials, Vol.11, No.8, pp. 3277-3296, 2023, DOI:10.32604/jrm.2023.028352

Abstract The performance of engineered wood products is highly associated with proper bonding and an efficient cutting method. This paper investigates the influence of CO₂ laser cutting on the wetting properties, the modified chemical component of the laser-cut surface, and the strength and adhesive penetration near the bondline. Beechwood is cut by the laser with varying processing parameters, cutting speeds, gas pressures, and focal point positions. The laser-cut samples were divided into two groups, sanded and non-sanded samples. Polyvinyl acetate adhesive (PVAc) was used to bond the groups of laser-cut samples. After assembly with cold pressing, the tensile shear test was… More >

Zhiyuan Dai, Tian Li^*, Weihua Zhang, Jiye Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1461-1489, 2023, DOI:10.32604/cmes.2023.028677

Abstract The aerodynamic optimization design of high-speed trains (HSTs) is crucial for energy conservation, environmental preservation, operational safety, and speeding up. This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs. First, the study explores the impact of train nose shape parameters on aerodynamic performance. The parameterization methods involved in the aerodynamic multiobjective optimization of HSTs are summarized and classified as shape-based and disturbance-based parameterization methods. Meanwhile, the advantages and limitations of each parameterization method, as well as the applicable scope, are briefly discussed. In addition, the NSGA-II algorithm, particle swarm optimization algorithm, standard… More >

Pedro Montenegro^1,*, Raphael Heleno², Hermes Carvalho², Diogo Ribeiro³, Rui Calçada¹, Chris Baker⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-2, 2022, DOI:10.32604/icces.2022.08678

Abstract This work consists of evaluating the impact of the most relevant characteristics of railway vehicles, namely geometric, mechanical and aerodynamic properties, in their runnability in the presence of strong winds, more precisely in the risk of derailment. Such objective is achieved by performing several dynamic with a non-linear vehicle-structure interaction model developed by the authors [1,2] and used in other works in this field [3,4], which allows the evaluation of the wheel-rail contact forces and, consequently, the unloading index, as suggested by the European Norm EN 14067-6 [5]. The calculations are carried out for several scenarios characterized by different train… More >

Neelam Mughees^1,2, Mujtaba Hussain Jaffery¹, Abdullah Mughees³, Anam Mughees⁴, Krzysztof Ejsmont^5,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6375-6393, 2023, DOI:10.32604/cmc.2023.038564

Abstract Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by 2050. However, they are exceedingly unpredictable since they rely highly on weather and atmospheric conditions. In microgrids, smart energy management systems, such as integrated demand response programs, are permanently established on a step-ahead basis, which means that accurate forecasting of wind speed and solar irradiance intervals is becoming increasingly crucial to the optimal operation and planning of microgrids. With this in mind, a novel “bidirectional long short-term memory network” (Bi-LSTM)-based, deep stacked, sequence-to-sequence autoencoder (S2SAE) forecasting model… More >

Zhedong Xu^*, Yongbo Su, Fang Yang, Ming Zhang

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5965-5986, 2023, DOI:10.32604/cmc.2023.037611

Abstract Due to the development of digital transformation, intelligent algorithms are getting more and more attention. The whale optimization algorithm (WOA) is one of swarm intelligence optimization algorithms and is widely used to solve practical engineering optimization problems. However, with the increased dimensions, higher requirements are put forward for algorithm performance. The double population whale optimization algorithm with distributed collaboration and reverse learning ability (DCRWOA) is proposed to solve the slow convergence speed and unstable search accuracy of the WOA algorithm in optimization problems. In the DCRWOA algorithm, the novel double population search strategy is constructed. Meanwhile, the reverse learning strategy… More >

L. Cheng^a , Y. L. Zhang^a,† , J. F. Li^b

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-7, 2022, DOI:10.5098/hmt.19.32

Abstract The internal characteristics during rotational speed fluctuation have an important influence on centrifugal pump to avoid or utilize its transient performance. In this paper, a circulation piping system that includes a low-specific-speed centrifugal pump is established to study the energy distribution characteristics in a centrifugal pump during speed fluctuation. The unsteady flow in the entire system is numerically calculated with a user-defined function, the sliding grid method, and the RNG k-ε turbulence model. Then, the energy distribution of the transient flow field in the centrifugal pump model during speed fluctuation is diagnosed with vortex dynamics by using flow section and… More >

R. Surendran^1,*, Youseef Alotaibi², Ahmad F. Subahi³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3371-3386, 2023, DOI:10.32604/csse.2023.034465

Abstract High precision and reliable wind speed forecasting have become a challenge for meteorologists. Convective events, namely, strong winds, thunderstorms, and tornadoes, along with large hail, are natural calamities that disturb daily life. For accurate prediction of wind speed and overcoming its uncertainty of change, several prediction approaches have been presented over the last few decades. As wind speed series have higher volatility and nonlinearity, it is urgent to present cutting-edge artificial intelligence (AI) technology. In this aspect, this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning (IWSP-CSODL) method. The presented IWSP-CSODL model… More >

Yiguo Chen^1,2,3,*, Congjun Feng^1,2, Yonghong He³, Zhijun Chen³, Xiaowei Fan³, Chao Wang³, Xinmin Ge⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2451-2463, 2023, DOI:10.32604/cmes.2023.021145

Abstract The low-field nuclear magnetic resonance (NMR) technique has been used to probe the pore size distribution and the fluid composition in geophysical prospecting and related fields. However, the speed and accuracy of the existing numerical inversion methods are still challenging due to the ill-posed nature of the first kind Fredholm integral equation and the contamination of the noises. This paper proposes a novel inversion algorithm to accelerate the convergence and enhance the precision using empirical truncated singular value decompositions (TSVD) and the linearized Bregman iteration. The L1 penalty term is applied to construct the objective function, and then the linearized… More > Graphic Abstract

Daoming Shen^1,*, Jinhong Xia¹, Chao Gui¹, Songtao Xue²

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.7, pp. 1863-1873, 2023, DOI:10.32604/fdmp.2023.024925

Abstract In order to ensure the safe operation of the compressors used in water chillers, in the present study some interlock protections have been added to the related design. These include a low pressure protection, a high pressure protection, an exhaust temperature protection and a differential pressure protection. Some tests have been conducted by tuning the saturation suction and exhaust temperatures of the compressor through adjustment of the cold source outlet temperature and the ambient temperature. The results show that the ambient temperature increases with decreasing device load and increasing fan speed under the same saturated suction temperature; the device refrigerating… More > Graphic Abstract

Shafiqur Rehman^1,*, Hilal H. Nuha², Ali Al Shaikhi³, Satria Akbar², Mohamed Mohandes^1,3

Energy Engineering, Vol.120, No.4, pp. 775-789, 2023, DOI:10.32604/ee.2023.026185

Abstract An accurate vertical wind speed (WS) data estimation is required to determine the potential for wind farm installation. In general, the vertical extrapolation of WS at different heights must consider different parameters from different locations, such as wind shear coefficient, roughness length, and atmospheric conditions. The novelty presented in this article is the introduction of two steps optimization for the Recurrent Neural Networks (RNN) model to estimate WS at different heights using measurements from lower heights. The first optimization of the RNN is performed to minimize a differentiable cost function, namely, mean squared error (MSE), using the Broyden-Fletcher-Goldfarb-Shanno algorithm. Secondly,… More >