Mohanad A. Mohammed^*, Hala B. Abdul Wahab

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1731-1748, 2024, DOI:10.32604/cmes.2023.030528

Abstract Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges. Concurrently, the Internet of Things (IoT) has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services, ultimately enhancing human lives. This paper presents a new approach utilizing lightweight blockchain technology, effectively reducing the computational burden typically associated with conventional blockchain systems. By integrating this lightweight blockchain with IoT systems, substantial reductions in implementation time and computational complexity can be achieved. Moreover, the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm, renowned for… More >

Ying Zhang¹, Xiaoqing Han², Chao Zhang¹, Ying Qu¹, Yang Liu¹, Gengwu Zhang^2,*

Energy Engineering, Vol.120, No.11, pp. 2585-2609, 2023, DOI:10.32604/ee.2023.026816

Abstract More and more uncertain factors in power systems and more and more complex operation modes of power systems put forward higher requirements for online transient stability assessment methods. The traditional model-driven methods have clear physical mechanisms and reliable evaluation results but the calculation process is time-consuming, while the data-driven methods have the strong fitting ability and fast calculation speed but the evaluation results lack interpretation. Therefore, it is a future development trend of transient stability assessment methods to combine these two kinds of methods. In this paper, the rate of change of the kinetic energy method is used to calculate… More >

Xinliang Tang¹, Xiaotong Ru¹, Jingfang Su^1,*, Gabriel Adonis²

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2997-3011, 2023, DOI:10.32604/cmc.2023.038923

Abstract On the transmission line, the invasion of foreign objects such as kites, plastic bags, and balloons and the damage to electronic components are common transmission line faults. Detecting these faults is of great significance for the safe operation of power systems. Therefore, a YOLOv5 target detection method based on a deep convolution neural network is proposed. In this paper, Mobilenetv2 is used to replace Cross Stage Partial (CSP)-Darknet53 as the backbone. The structure uses depth-wise separable convolution toreduce the amount of calculation and parameters; improve the detection rate. At the same time, to compensate for the detection accuracy, the Squeeze-and-Excitation… More >

Uwem O. Ikitde¹, Abayomi A. Adebiyi^1,*, Innocent E. Davidson², Ayodeji S. Akinyemi¹

Energy Engineering, Vol.120, No.9, pp. 1939-1961, 2023, DOI:10.32604/ee.2023.027574

Abstract The integration of solar and wind energy into the electrical grid has received global research attention due to their unpredictable characteristics. Because wind energy varies across all timescales of utility activity, renewable energy generation should be supplemented and enhanced, from real-time, minute-to-minute variations to annual alterations influencing long-term strategy. Wind energy generation does not only fluctuate but is also challenging to accurately forecast the timeframes of significance to electricity decision makers; day-ahead and long-term making plans of framework sufficiency such as meeting the network peak load annually. A utility that integrates wind and solar energy into its electricity mix would… More >

Xinfei Li², Xiaolan Xie^1,2,*, Yigang Tang², Qiang Guo^1,2

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2707-2724, 2023, DOI:10.32604/csse.2023.037351

Abstract Predicting the usage of container cloud resources has always been an important and challenging problem in improving the performance of cloud resource clusters. We proposed an integrated prediction method of stacking container cloud resources based on variational modal decomposition (VMD)-Permutation entropy (PE) and long short-term memory (LSTM) neural network to solve the prediction difficulties caused by the non-stationarity and volatility of resource data. The variational modal decomposition algorithm decomposes the time series data of cloud resources to obtain intrinsic mode function and residual components, which solves the signal decomposition algorithm’s end-effect and modal confusion problems. The permutation entropy is used… More >

Michael Petrucci, Amir Faghri^*

Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-9, 2018, DOI:10.5098/hmt.11.37

Abstract The results of integrating heat pipes into the vanes of a turbofan engine are presented. These Heat Pipe Turbine Vanes (HPTV) are integrated into the compressor exit, turbine inlet, and exhaust flow for vane cooling and waste heat recovery. Thermodynamic analysis of HPTV turbofan engines is done and comparisons are made between heat pipe turbine vane cooling and conventional film cooling techniques. Heat transfer through the vanes is analyzed using a thermal network model. Limitations on the heat transfer caused by various limiting phenomena within the heat pipe are also determined. More >

Loc Vu-Quoc^1,*, Alexander Humer²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130

Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting certain components in the traditional… More >

Misbahudin Alhanif, Gelbert Jethro Sanyoto, Widayat Widayat^*

Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-6, 2020, DOI:10.5098/hmt.15.17

Abstract Development of sulfuric acid production method has taken us to commercial use of contact process in most industries. However, most plants still utilize coolers and steam generators to divert the excess heat. This method of energy recovery is inefficient, thus, this study attempts to redesign commercial heat exchanger network for better efficiency and lower cost. Process integration using composite curve, cascade diagram, heat exchanger network alternatives, completed with improved plant flow diagram are successfully calculated and analyzed by HINT software. Total energy saving can reach up to 74.70% and this results in total cost saving up to $ 18,000/year. More >

Abdulmoseen Segun Giwa^1,*, Mingqiang Sheng², Ndungutse Jean Maurice³, Xinxin Liu¹, Zelong Wang¹, Fengmin Chang⁴, Bo Huang⁴, Kaijun Wang⁴

Journal of Renewable Materials, Vol.11, No.6, pp. 2593-2629, 2023, DOI:10.32604/jrm.2023.026314

Abstract Globally, fossil fuel dependence has created several environmental challenges and climate change. Hence, creating other alternative renewable and ecologically friendly bio-energy sources is necessary. Lignocellulosic biomass has gained significant attention recently as a renewable material for biofuel production. The large amounts of plantain and banana plant parts wasted after harvesting, as well as the peels generated daily by the fruit market and industries, demonstrate the potential of bioenergy resources. This review briefly assesses plantain and banana plant biomass (PBB) generated in the developing, developed, and underdeveloped countries, the consumable parts, and feasible products yield. It emphasized the advantages and disadvantages… More > Graphic Abstract

N. A. Maidin^1,2, S. M. Sapuan^1,*, M. T. Mastura², M. Y. M. Zuhri¹

Journal of Renewable Materials, Vol.11, No.5, pp. 2381-2397, 2023, DOI:10.32604/jrm.2023.026549

Abstract Natural fibre reinforced polymer composite (NFRPC) materials are gaining popularity in the modern world due to their eco-friendliness, lightweight nature, life-cycle superiority, biodegradability, low cost, and noble mechanical properties. Due to the wide variety of materials available that have comparable attributes and satisfy the requirements of the product design specification, material selection has become a crucial component of design for engineers. This paper discusses the study’s findings in choosing the suitable thermoplastic matrices of Natural Fibre Composites for Cyclist Helmet utilising the DMAIC, and GRA approaches. The results are based on integrating two decision methods implemented utilising two distinct decision-making… More >