Qing Zhu^1,*, Linlin Gu^1,2, Huijie Lin^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 577-591, 2024, DOI:10.32604/cmes.2023.043307

Abstract With the rapid development of electric power systems, load estimation plays an important role in system operation and planning. Usually, load estimation techniques contain traditional, time series, regression analysis-based, and machine learning-based estimation. Since the machine learning-based method can lead to better performance, in this paper, a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed. First, an image fingerprint construction is proposed for training data. After the data preprocessing, the training data matrix is constructed by the cyclic shift and cubic spline interpolation. Then, the linear mapping and the gray-color transformation method are proposed to… More >

S. MATHIVANAN^*, R. MOHAN, RAMES C PANDA, P. BALACHANDER¹

Journal of Polymer Materials, Vol.39, No.3-4, pp. 195-204, 2022, DOI:10.32381/JPM.2022.39.3-4.2

Abstract Optimum-designed footwear with polyurethane (PU) material for comfort is an important requirement for obese. Investigations on compressive behavior of varied designed footwear using 120 D PU material have been carried out. The energy absorption primarily depends on heel height, slope angle and load applied or body mass index of obese. Statistical analysis has been used to formulate the prediction of absorbed energy wherein a heel height of 30 mm with 20-degree angle provides optimum value with the incorporation of 120 D PU material. A coefficientof-determination (R² ) value of 0.9406 confirms the suitability of the statistical regression model. Hence, the… More >

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 >

Keqiang Wang¹, Pengyang Zhao¹, Changjian Wang², Zimeng Zhang¹, Yu Zhang¹, Jia Lu¹, Zedong Yang^2,*

Energy Engineering, Vol.121, No.4, pp. 1091-1108, 2024, DOI:10.32604/ee.2023.044016

Abstract The rising frequency of extreme disaster events seriously threatens the safe and secure operation of the regional integrated electricity-natural gas system (RIENGS). With the growing level of coupling between electric and natural gas systems, it is critical to enhance the load restoration capability of both systems. This paper proposes a coordinated optimization strategy for resilience-enhanced RIENGS load restoration and repair scheduling and transforms it into a mixed integer second-order cone programming (MISOCP) model. The proposed model considers the distribution network reconfiguration and the coordinated repair strategy between the two systems, minimizing the total system load loss cost and repair time.… More >

Zhongping Liu¹, Enhui Sun^2,*, Jiahao Shi², Lei Zhang², Qi Wang¹, Jiali Dong¹

Energy Engineering, Vol.121, No.4, pp. 913-932, 2024, DOI:10.32604/ee.2023.043973

Abstract There is a growing need to explore the potential of coal-fired power plants (CFPPs) to enhance the utilization rate of wind power (wind) and photovoltaic power (PV) in the green energy field. This study developed a load regulation model for a multi-power generation system comprising wind, PV, and coal energy storage using real-world data. The power supply process was divided into eight fundamental load regulation scenarios, elucidating the influence of each scenario on load regulation. Within the framework of the multi-power generation system with the wind (50 MW) and PV (50 MW) alongside a CFPP (330 MW), a lithium-iron phosphate… More > Graphic Abstract

Hongzhang Wang¹, Jing Guo¹, Shanjun Yang¹, Chaoheng Cheng², Jing Chen^3,*, Zhihao Chen³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 181-196, 2024, DOI:10.32604/sdhm.2024.044628

Abstract Pitting corrosion is harmful during bridge construction, which will lead to uneven roughness of steel surfaces and reduce the thickness of steel. Hence, the effect of pitting corrosion on the mechanical properties of cold-formed thin-walled steel stub columns is studied, and the empirical formulas are established through regression fitting to predict the ultimate load of web and flange under pitting corrosion. In detail, the failure modes and load-displacement curves of specimens with different locations, area ratios, and depths are obtained through a large number of non-linear finite element analysis. As for the specimens with pitting corrosion on the web, all… More > Graphic Abstract

Rohollah Fallah Madvari¹, Hamideh Bidel², Ahmad Mehri³, Fatema Babaee⁴, Fereydoon Laal^5,*

Sound & Vibration, Vol.58, pp. 119-131, 2024, DOI:10.32604/sv.2024.048861

Abstract Noise is one of the environmental factors with mental and physical effects. The workload is also the multiple mental and physical demands of the task. Therefore, his study investigated the relationship between noise exposure and mood states at different levels of workload. The study recruited 50 workers from the manufacturing sector (blue-collar workers) as the exposed group and 50 workers from the office sector (white-collar workers) as the control group. Their occupational noise exposure was measured by dosimetry. The Stress-Arousal Checklist (SACL) and the NASA Task Load Index (NASA-TLX) were used to measure mood and workload, respectively. The equivalent noise… More >

Kuosheng Jiang¹, Chengrui Han¹, Yasheng Chang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3329-3352, 2024, DOI:10.32604/cmes.2024.046729

Abstract Angular contact ball bearings have been widely used in machine tool spindles, and the bearing preload plays an important role in the performance of the spindle. In order to solve the problems of the traditional optimal preload prediction method limited by actual conditions and uncertainties, a roller bearing preload test method based on the improved D-S evidence theory multi-sensor fusion method was proposed. First, a novel controllable preload system is proposed and evaluated. Subsequently, multiple sensors are employed to collect data on the bearing parameters during preload application. Finally, a multisensor fusion algorithm is used to make predictions, and a… More >

Yuantian Qin^1,2, Yucheng Zhang^1,*, Vadim V. Silberschmidt²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2865-2891, 2024, DOI:10.32604/cmes.2024.046113

Abstract This paper proposes a novel approach for identifying distributed dynamic loads in the time domain. Using polynomial and modal analysis, the load is transformed into modal space for coefficient identification. This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force, thereby achieving dimensionality reduction. The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain. Firstly, the algorithm establishes a recursion scheme based on convolution integral, enabling it to identify loads with a long history and rapidly changing forms over… More >

Asier Garmendia-Orbegozo¹, Jose David Nunez-Gonzalez^1,*, Miguel Angel Anton²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2649-2671, 2024, DOI:10.32604/cmes.2024.045912

Abstract In a network environment composed of different types of computing centers that can be divided into different layers (clod, edge layer, and others), the interconnection between them offers the possibility of peer-to-peer task offloading. For many resource-constrained devices, the computation of many types of tasks is not feasible because they cannot support such computations as they do not have enough available memory and processing capacity. In this scenario, it is worth considering transferring these tasks to resource-rich platforms, such as Edge Data Centers or remote cloud servers. For different reasons, it is more exciting and appropriate to download various tasks… More > Graphic Abstract