Ximin Cao^*, Xinglong Chen, He Huang, Yanchi Zhang, Qifan Huang

Energy Engineering, Vol.121, No.4, pp. 1067-1089, 2024, DOI:10.32604/ee.2023.046783

Abstract Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals. Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system, a multi-time scale optimal scheduling strategy based on model predictive control (MPC) is proposed under the consideration of load optimization. First, load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature, and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost. Second, considering inter-day to… More >

Shichao Cao^*, Yonggang Dong, Xiaoying Liu

Energy Engineering, Vol.121, No.4, pp. 1109-1125, 2024, DOI:10.32604/ee.2023.043004

Abstract The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine. It also has the same inertia, damping, frequency, voltage regulation, and other external performance as the generator. It is the key technology to realize new energy grid connections’ stable and reliable operation. This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor. A new energy storage method is proposed. The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power, state of charge,… More >

J.N. Chung^a,†, Tailian Chen^b, Shalabh C. Maroo^c

Frontiers in Heat and Mass Transfer, Vol.2, No.2, pp. 1-19, 2011, DOI:10.5098/hmt.v2.2.3004

Abstract Recent research progress in the area of nano/micro scale nucleate boiling is reviewed and an up-to-date summary is provided with a focus on the advances of fundamental boiling physics. This review examines nano/micro scale pool boiling experimental and theoretical/numerical work reported in the open literature. On the experimental side, the topics covered are moving contact line, critical heat flux, boiling curve, nucleation, single bubble boiling cycle, bubble coalescence boiling cycle, heater size effect, nanofluid, and nanoscale-structured heater surface. For the theoretical/numerical work, continuum mechanics modeling of the micro-region and molecular dynamics modeling of the nano-region are included. More >

Mingzhe Huang, Mi Xiao^*, Liang Gao, Mian Zhou, Wei Sha, Jinhao Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2479-2505, 2024, DOI:10.32604/cmes.2023.045735

Abstract Cellular thin-shell structures are widely applied in ultralightweight designs due to their high bearing capacity and strength-to-weight ratio. In this paper, a full-scale isogeometric topology optimization (ITO) method based on Kirchhoff–Love shells for designing cellular tshin-shell structures with excellent damage tolerance ability is proposed. This method utilizes high-order continuous nonuniform rational B-splines (NURBS) as basis functions for Kirchhoff–Love shell elements. The geometric and analysis models of thin shells are unified by isogeometric analysis (IGA) to avoid geometric approximation error and improve computational accuracy. The topological configurations of thin-shell structures are described by constructing the effective density field on the control… More >

Chili Li¹, Xinxin Zhao², Ziwen Pan³, Ting Yi⁴, Long Qian^5,6,*

International Journal of Mental Health Promotion, Vol.26, No.2, pp. 161-175, 2024, DOI:10.32604/ijmhp.2023.029896

Abstract While a plethora of studies has been conducted to explore demotivation and its impact on mental health in second language (L2) education, scanty research focuses on demotivation in L2 speaking learning. Particularly, little research explores the measures to quantify L2 speaking demotivation. The present two-phase study attempts to develop and validate an English Speaking Demotivation Scale (ESDS). To this end, an independent sample of 207 Chinese tertiary learners of English as a Foreign Language (EFL) participated in the development phase, and another group of 188 Chinese EFL learners was recruited for the validation of the scale. Exploratory Factor Analysis (EFA)… More >

Yanjun Yu¹, Lei Yu^1,*, Huiqi Wang², Haodong Zheng¹, Yi Deng¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2225-2243, 2024, DOI:10.32604/cmc.2024.047641

Abstract Bone age assessment (BAA) helps doctors determine how a child’s bones grow and develop in clinical medicine. Traditional BAA methods rely on clinician expertise, leading to time-consuming predictions and inaccurate results. Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations. This operation is costly and subjective. To address these problems, we propose a multi-scale attentional densely connected network (MSADCN) in this paper. MSADCN constructs a multi-scale dense connectivity mechanism, which can avoid overfitting, obtain the local features effectively and prevent gradient vanishing even in limited training data. First, MSADCN designs… More >

Yuchun Li^1,4, Mengxing Huang^1,*, Yu Zhang², Zhiming Bai³

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1649-1668, 2024, DOI:10.32604/cmc.2023.046883

Abstract The precise and automatic segmentation of prostate magnetic resonance imaging (MRI) images is vital for assisting doctors in diagnosing prostate diseases. In recent years, many advanced methods have been applied to prostate segmentation, but due to the variability caused by prostate diseases, automatic segmentation of the prostate presents significant challenges. In this paper, we propose an attention-guided multi-scale feature fusion network (AGMSF-Net) to segment prostate MRI images. We propose an attention mechanism for extracting multi-scale features, and introduce a 3D transformer module to enhance global feature representation by adding it during the transition phase from encoder to decoder. In the… More >

Dongmei Chen¹, Peipei Cao¹, Lijie Yan¹, Huidong Chen¹, Jia Lin¹, Xin Li², Lin Yuan³, Kaihua Wu^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 261-275, 2024, DOI:10.32604/phyton.2024.046331

Abstract Tea leaf picking is a crucial stage in tea production that directly influences the quality and value of the tea. Traditional tea-picking machines may compromise the quality of the tea leaves. High-quality teas are often handpicked and need more delicate operations in intelligent picking machines. Compared with traditional image processing techniques, deep learning models have stronger feature extraction capabilities, and better generalization and are more suitable for practical tea shoot harvesting. However, current research mostly focuses on shoot detection and cannot directly accomplish end-to-end shoot segmentation tasks. We propose a tea shoot instance segmentation model based on multi-scale mixed attention… More >

Jun Zhao^*, Chaoying Yang, Ran Li, Jinge Song

Energy Engineering, Vol.121, No.3, pp. 747-767, 2024, DOI:10.32604/ee.2023.042806

Abstract Due to the impact of source-load prediction power errors and uncertainties, the actual operation of the park will have a wide range of fluctuations compared with the expected state, resulting in its inability to achieve the expected economy. This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control (MPC). In the day-ahead stage, an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min. In… More >

Lei Fang^*, Haiying Dong, Xiaofei Zhen, Shuaibing Li

Energy Engineering, Vol.121, No.3, pp. 661-679, 2024, DOI:10.32604/ee.2023.029823

Abstract According to the multi-time-scale characteristics of power generation and demand-side response (DR) resources, as well as the improvement of prediction accuracy along with the approaching operating point, a rolling peak shaving optimization model consisting of three different time scales has been proposed. The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination, generation power, and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response… More >