Muhd Hadi Iskandar Abd Razak^*, Motoki Tsuda, Yukio Hayakawa, Shinji Kambara

Energy Engineering, Vol.121, No.2, pp. 259-272, 2024, DOI:10.32604/ee.2023.043615

Abstract Hydrogen is an alternative energy source that has the potential to replace fossil fuels. One of the hydrogen applications is as a material for Polymer Electrolyte Membrane Fuel Cells (PEMFC) in fuel cell vehicles. High-purity hydrogen can be obtained using a hydrogen separation membrane to prevent unwanted contaminants from potentially harming the PEMFC components. In this study, we fabricated a plasma membrane reactor and investigated the permeation performance of a hydrogen separation membrane in a plasma membrane reactor utilizing atmospheric pressure plasma. The result showed the hydrogen permeation rate increasing with time as reactor temperature is increased through joule heating.… More >

Feng Zhao, Jinshuo Zhang^*, Xiaoqiang Chen, Ying Wang

Energy Engineering, Vol.121, No.2, pp. 339-358, 2024, DOI:10.32604/ee.2023.043082

Abstract In the DC microgrid, the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power. To address this issue, the application of a virtual synchronous generator (VSG) in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator (AVSG) control strategy for the interface DC/DC converter of the battery in the microgrid. Besides, a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control. Firstly, a… More >

Jingjing Tian¹, Shenglin Mo^1,*, Feng Zhao¹, Xiaoqiang Chen²

Energy Engineering, Vol.121, No.2, pp. 439-459, 2024, DOI:10.32604/ee.2023.029956

Abstract In this paper, an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load and PV power variations in a stand-alone DC microgrid. The strategy includes primary and secondary control. Among them, the primary control suppresses the DC microgrid voltage fluctuation through the Ⅰ and Ⅱ section control, and the secondary control aims to correct the P-U curve of the energy storage system and the PV system, thus reducing the steady-state bus voltage excursion. The simulation results demonstrate that the… More >

Baogang Chen¹, Fenglin Miao^2,*, Jing Yang¹, Chen Qi², Wenyan Ji¹

Energy Engineering, Vol.121, No.2, pp. 541-555, 2024, DOI:10.32604/ee.2023.028327

Abstract Energy storage systems (ESS) and permanent magnet synchronous generators (PMSG) are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives. The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted. To improve the inertia response and frequency control capability, we propose a short-term frequency support strategy for the ESS and PMSG. To this end, the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion. The effectiveness of the proposed control strategy was… More >

Noman Khan^1,2, Samee Ullah Khan^1,2, Sung Wook Baik^1,2,*

Computer Systems Science and Engineering, Vol.48, No.1, pp. 153-173, 2024, DOI:10.32604/csse.2023.039407

Abstract Energy management systems for residential and commercial buildings must use an appropriate and efficient model to predict energy consumption accurately. To deal with the challenges in power management, the short-term Power Consumption (PC) prediction for household appliances plays a vital role in improving domestic and commercial energy efficiency. Big data applications and analytics have shown that data-driven load forecasting approaches can forecast PC in commercial and residential sectors and recognize patterns of electric usage in complex conditions. However, traditional Machine Learning (ML) algorithms and their features engineering procedure emphasize the practice of inefficient and ineffective techniques resulting in poor generalization.… More >

Yuxuan Ying¹, Wei Huang^1,*, Yu-E Ma¹, Fan Peng¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.010572

Abstract Intensive dynamic loadings are the main threats to the structural damage of protective structures and inner equipment, which has attracted a lot of attention in the field of advance impulsive resistance. Nanofluidic liquid foam (NLF) has become a novel and efficient energy absorption system due to its reusable energy absorption, ultra-high load transfer, and high energy absorption ratio. In order to solve the current problem that the energy absorption mechanism of NLF is still unclear, this paper conducted a systematic experimental study on the dynamic compression and energy absorption behaviours of NLF. The quasi-static cyclic compression experiments with different liquid… More >

Zhongming Hu^1,*, Leilei Chen¹, Delei Yang¹, Jichao Zhang¹, Youyang Xin¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.09340

Abstract Functionally graded materials (FGMs), a kind of composite materials, were proposed to satisfy the requirements of thermal barrier materials initially [1-3]. Compared with traditional composites, the microstructure and mechanical characteristics of FGMs change continuously which make them present excellent performance in deformation resistance or toughness under extreme mechanical and thermal loadings [4]. Therefore, FGMs have been paid much attention and experienced rapid developments in the last decade. Nowadays, various structural components manufactured by FGMs have been used in extensive applications, such as aerospace, bioengineering, nuclear industries, civil constructions etc. [5-7]
While, FG Euler-Bernoulli beams maybe suffer damage in practical… More >

Haiqi Feng¹, Wei Huang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-2, 2023, DOI:10.32604/icces.2023.09347

Abstract Intensive dynamic loadings are the main threats to the structural damage of protective structures and inner equipment, which has attracted a lot of attention in the field of advance impulsive resistance. Nanofluidic liquid foam (NLF) has become a novel and efficient energy absorption system due to its reusable energy absorption, ultra-high load transfer, and high energy absorption ratio [1-7]. In order to solve the current problem that the energy absorption mechanism of NLF is still unclear, this paper conducted a systematic experimental study on the dynamic compression and energy absorption behaviours of NLF. The quasi-static cyclic compression experiments with different… More >

Pingfan Li, Jiumei Xiao^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 999-1016, 2024, DOI:10.32604/cmes.2023.044059

Abstract Thin-walled structures are widely used in cars due to their lightweight construction and energy-absorbing properties. However, issues such as high initial stress and low energy-absorbing efficiency arise. This study proposes a novel energy-absorbing structure in which a straight tube is combined with a conical tube and a bamboo-inspired bulkhead structure is introduced. This configuration allows the conical tube to flip outward first and then fold together with the straight tube. This deformation mode absorbs more energy and less peak force than the conical tube sinking and flipping inward. Through finite element numerical simulation, the specific energy absorption capacity of the… More >

Tuo Ma, Zhiwei Li, Qingjiang Li^*, Haijun Liu, Zhongjin Zhao, Yinan Wang

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3237-3263, 2023, DOI:10.32604/cmc.2023.045948

Abstract With the continuous development of deep learning, Deep Convolutional Neural Network (DCNN) has attracted wide attention in the industry due to its high accuracy in image classification. Compared with other DCNN hardware deployment platforms, Field Programmable Gate Array (FPGA) has the advantages of being programmable, low power consumption, parallelism, and low cost. However, the enormous amount of calculation of DCNN and the limited logic capacity of FPGA restrict the energy efficiency of the DCNN accelerator. The traditional sequential sliding window method can improve the throughput of the DCNN accelerator by data multiplexing, but this method’s data multiplexing rate is low… More >