alexandria engineering journal最新文献_第8页

Multifidelity co-kriging metamodeling based on multivariate data fusion for dynamic fit improvement of injection mechanism in squeeze casting 基于多变量数据融合的多保真共混元建模，用于改善挤压铸造中喷射机制的动态拟合效果

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-19 DOI: 10.1016/j.aej.2024.10.058

{"title":"Multifidelity co-kriging metamodeling based on multivariate data fusion for dynamic fit improvement of injection mechanism in squeeze casting","authors":"","doi":"10.1016/j.aej.2024.10.058","DOIUrl":"10.1016/j.aej.2024.10.058","url":null,"abstract":"<div><div>To improve the dynamic fit the injection mechanism in a squeeze casting machine, this paper proposes a novel multifidelity co-kriging (MFCK) metamodeling method, which fuses high-fidelity measured data with low-fidelity simulated data and considers data uncertainty and multivariate correlation influence to accurately predict response values when experimental sample data are insufficient. An MFCK model was established to predict the deformation and dynamic fit clearance, by selecting experimental and simulated values of deformation and temperature as the principal and covariates for correlation testing. The results indicate that the proposed MFCK model significantly improved the prediction accuracy by 34.18 %, 73.53 %, 41.57 % and 37.93 %, respectively, compared with the ordinary kriging model and finite element method. This method was applied to the multicycle injection process of a 2,500-kN squeeze casting machine, revealing the variation law of the fit clearance. The MFCK model improved the prediction accuracy of the fit clearance by 72.7 %, which is beneficial for process control. The accuracy and industrial applicability of the proposed MFCK method was thus verified.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retraction notice to “Optimal energy modeling and planning in the power system via a hybrid firefly and cuckoo algorithm in the presence of renewable energy sources and electric vehicles” [Alex. Eng. J. 76 (2023) 333–348] 关于 "在可再生能源和电动汽车存在的情况下，通过萤火虫和布谷鸟混合算法优化电力系统的能源建模和规划 "的撤稿通知 [Alex.

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-19 DOI: 10.1016/j.aej.2024.10.071

引用次数: 0

Energy-efficient unequal multi-level clustering for underwater wireless sensor networks 水下无线传感器网络的高能效不平等多级聚类

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-19 DOI: 10.1016/j.aej.2024.10.026

{"title":"Energy-efficient unequal multi-level clustering for underwater wireless sensor networks","authors":"","doi":"10.1016/j.aej.2024.10.026","DOIUrl":"10.1016/j.aej.2024.10.026","url":null,"abstract":"<div><div>Underwater Wireless Sensor Networks (UWSNs) have emerged as a critical piece of technology for a wide range of maritime applications, including environmental monitoring, resource exploration, and catastrophe avoidance. An Energy Efficient Unequal Multilevel Clustering (EEUMC) algorithm tailored to UWSNs is proposed in this study. The EEUMC's primary purpose is to enhance the efficiency of data movement inside the network while decreasing the amount of energy lost. The proposed method employs a multilevel clustering framework, which divides the network into hierarchical groups based on node attributes and residual energy content. EEUMC introduces an unequal clustering technique, which differs from traditional clustering approaches. Cluster heads (CHs) are dynamically selected in this technique based on their energy levels as well as their proximity to sink nodes. The EEUMC integrates sophisticated routing protocols and adaptive data aggregation techniques in order to boost the energy economy even further. The routing algorithms route data flows across energy-efficient channels automatically, and adaptive data aggregation reduces redundant transmissions to conserve energy and keep the system functioning smoothly. This particular configuration of unequal clustering, intelligent routing, and adaptive aggregation all work together to improve data-collecting efficiency and network’s lifespan. The efficiency of the proposed EEUMC scheme was thoroughly tested through a number of simulations and head-to-head comparisons with alternative clustering approaches. When compared to more traditional approaches, the findings reveal that EEUMC greatly increases network longevity and data transmission rates. Furthermore, the scheme is robust in the sense that it can withstand changing network conditions while still ensuring a balanced consumption of energy across all nodes.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction OPEC oil price utilizing long short-term memory and multi-layer perceptron models 利用长短期记忆和多层感知器模型预测欧佩克石油价格

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-18 DOI: 10.1016/j.aej.2024.10.057

{"title":"Prediction OPEC oil price utilizing long short-term memory and multi-layer perceptron models","authors":"","doi":"10.1016/j.aej.2024.10.057","DOIUrl":"10.1016/j.aej.2024.10.057","url":null,"abstract":"<div><div>The present study undertakes a comprehensive assessment of two predictive models, namely Long Short-Term Memory (LSTM) and Multi-layer Perceptron (MLP), with a specific emphasis on their effectiveness in predicting oil prices, particularly those of the Petroleum Exporting Countries (OPEC). In this study, three fundamental statistical measures are utilized: The Symmetric Mean Absolute Percentage Error (SMAPE), the Mean Squared Error (MSE), and the Mean Absolute Percentage Error (MAPE). The results demonstrate that the LSTM model regularly surpasses the MLP model in the three benchmarks. In particular, the LSTM model demonstrates lower values for SMAPE, MSE, and MAPE, indicating higher prediction accuracy. The decreased error scores linked to the LSTM model highlight its improved capacity for precise oil price prediction in comparison to the MLP model. These results signify a notable progress in the use of machine learning techniques for predicting OPEC oil prices. Moreover, this study provides invaluable perspectives for OPEC management, policymakers, and organizations focused on oil price fluctuations, therefore contributing to the wider endeavour of enhancing the stability and economic sustainability of the oil pricing system in OPEC countries. The consequences of the study include the promotion of a pricing system that facilitates the achievement of economic and social development goals in these countries.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical comparison of aerodynamic performance between stationary and moving trains with varied-height windbreak wall under crosswind 横风条件下带有不同高度挡风墙的静止列车和动车组空气动力性能的数值比较

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-18 DOI: 10.1016/j.aej.2024.10.050

{"title":"Numerical comparison of aerodynamic performance between stationary and moving trains with varied-height windbreak wall under crosswind","authors":"","doi":"10.1016/j.aej.2024.10.050","DOIUrl":"10.1016/j.aej.2024.10.050","url":null,"abstract":"<div><div>This paper investigates the impact of windbreak wall’s heights on the aerodynamic characteristics’ difference of trains between moving and stationary numerical simulation methods. The 1/8 scaled train model with windbreak wall at three heights under crosswind was simulated based on the IDDES turbulence model. The results found that the error of aerodynamic loads between two simulation methods increases with the elevation of the windbreak wall’s height with the largest value observed in the tail car. Comparing the time-averaged pressure on the train body in the two simulation methods, the most notable disparity manifests in the head car. The negative pressure around head car in stationary case is larger than that in moving case. For stationary simulation, the flow field is primarily influenced by the vortex structures generated at the end of the windbreak wall. In contrast, for moving simulation, the vortex structures on the leeward side of the train are predominantly formed by the detachment from the train’s top. In conclusion, the aerodynamic loads and flow field characteristics of the train exhibit noticeable discrepancies under two simulation methods, and the disparities increase with the elevation of the windbreak wall’s height.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation on the performances of thrust ball bearing with a novel oil self-transportation biomimetic composite guiding surface 带有新型油自运输仿生复合导向面的推力球轴承性能研究

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-17 DOI: 10.1016/j.aej.2024.10.052

引用次数: 0

Analytical and numerical calculation and simulation of heat transfer in a composite wall made of polyethylene terephthalate bottle 聚对苯二甲酸乙二酯瓶复合壁传热的分析和数值计算与模拟

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-17 DOI: 10.1016/j.aej.2024.10.023

{"title":"Analytical and numerical calculation and simulation of heat transfer in a composite wall made of polyethylene terephthalate bottle","authors":"","doi":"10.1016/j.aej.2024.10.023","DOIUrl":"10.1016/j.aej.2024.10.023","url":null,"abstract":"<div><div>The dynamics of heat transfer in composite walls made of Polyethylene Terephthalate (PET) bottles is studied using the energy conservation model. Ten walls of different structures were studied, including two control walls made of compressed earth brick (CEB) and cementitious material, cement-sand brick (CSB) and eight composite walls made of PET bottles filled with thermal insulation and/or mechanical stabilisation materials. The model equation is solved analytically using the separation of variables method and numerically using the finite difference method, and they are confirmed using CASTEM finite element software. As boundary conditions, a constant temperature (Text) is applied at one end of the wall, and the constant temperature (T0) is applied at any other point at the initial time. The effect of PET bottles filling on the thermal behaviour of the wall was then carried out to determine the optimum design that would give the wall better thermal inertia. The results obtained with CASTEM is fairly in agreement with the results obtained analytically and numerically, with a maximum relative error closed to that of the spatial evolution and 3.310<sup>−2</sup> for the temporal one. It is found that heterogeneous filling of PET bottles provides better thermal inertia at the wall.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MoE-NuSeg: Enhancing nuclei segmentation in histology images with a two-stage Mixture of Experts network MoE-NuSeg：利用两级专家混合网络增强组织学图像中的细胞核分割功能

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-16 DOI: 10.1016/j.aej.2024.10.011

{"title":"MoE-NuSeg: Enhancing nuclei segmentation in histology images with a two-stage Mixture of Experts network","authors":"","doi":"10.1016/j.aej.2024.10.011","DOIUrl":"10.1016/j.aej.2024.10.011","url":null,"abstract":"<div><div>Accurate nuclei segmentation is essential for extracting quantitative information from histology images to support disease diagnosis and treatment decisions. However, precise segmentation is challenging due to the presence of clustered nuclei, varied morphologies, and the need to capture global spatial correlations. While state-of-the-art Transformer-based models employ tri-decoder architectures to decouple the segmentation task into nuclei, edges, and cluster edges segmentation, their complexity and long inference times hinder clinical integration. To address this, we introduce MoE-NuSeg, a novel Mixture of Experts (MoE) network that consolidates the tri-decoder into a single decoder. MoE-NuSeg employs three specialized experts for nuclei segmentation, edge delineation, and cluster edge detection, thereby mirroring the functionality of tri-decoders while surpassing their performance and reducing parameters by sharing attention heads. We propose a two-stage training strategy: the first stage independently trains the three experts, and the second stage fine-tunes their interactions to dynamically allocate the contributions of each expert using a learnable attention-based gating network. Evaluations across three datasets demonstrate that MoE-NuSeg outperforms the state-of-the-art methods, achieving an average increase of 0.99% in Dice coefficient, 1.14% in IoU and 0.92% in F1 Score, while reducing parameters by 30.1% and FLOPs by 40.2%. The code is available at <span><span>https://github.com/deep-geo/MoE-NuSeg</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EITNet: An IoT-enhanced framework for real-time basketball action recognition EITNet：用于实时篮球动作识别的物联网增强框架

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-16 DOI: 10.1016/j.aej.2024.09.046

{"title":"EITNet: An IoT-enhanced framework for real-time basketball action recognition","authors":"","doi":"10.1016/j.aej.2024.09.046","DOIUrl":"10.1016/j.aej.2024.09.046","url":null,"abstract":"<div><div>Integrating IoT technology into basketball action recognition enhances sports analytics, providing crucial insights into player performance and game strategy. However, existing methods often fall short in terms of accuracy and efficiency, particularly in complex, real-time environments where player movements are frequently occluded or involve intricate interactions. To overcome these challenges, we propose the EITNet model, a deep learning framework that combines EfficientDet for object detection, I3D for spatiotemporal feature extraction, and TimeSformer for temporal analysis, all integrated with IoT technology for seamless real-time data collection and processing. Our contributions include developing a robust architecture that improves recognition accuracy to 92%, surpassing the baseline EfficientDet model’s 87%, and reducing loss to below 5.0 compared to EfficientDet’s 9.0 over 50 epochs. Furthermore, the integration of IoT technology enhances real-time data processing, providing adaptive insights into player performance and strategy. The paper details the design and implementation of EITNet, experimental validation, and a comprehensive evaluation against existing models. The results demonstrate EITNet’s potential to significantly advance automated sports analysis and optimize data utilization for player performance and strategy improvement.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized design of a fault-tolerant 12-slot/10-pole six-phase surface permanent magnet motor with asymmetrical winding configuration for electric vehicles 用于电动汽车的具有非对称绕组配置的 12 槽/10 极六相表面永磁电机的容错优化设计

IF 6.2 2区工程技术

alexandria engineering journal Pub Date : 2024-10-16 DOI: 10.1016/j.aej.2024.10.025

{"title":"Optimized design of a fault-tolerant 12-slot/10-pole six-phase surface permanent magnet motor with asymmetrical winding configuration for electric vehicles","authors":"","doi":"10.1016/j.aej.2024.10.025","DOIUrl":"10.1016/j.aej.2024.10.025","url":null,"abstract":"<div><div>This paper presents a comprehensive methodology for optimizing the design of a 12-slot/10-pole permanent magnet (PM) motor with a six-phase winding configuration tailored for electric vehicles (EVs). The design aims to enhance motor performance under both healthy and fault conditions. While the single neutral configuration offers superior torque during faults, it also introduces zero sequence currents and additional space harmonics, which can lead to increased torque ripple that is difficult to control. This study addresses these challenges through innovative machine design optimization. The optimization process begins with sizing equations to establish an initial design. K-means clustering techniques are then employed to identify distinct loading points that accurately represent the full EV driving cycle, effectively minimizing computational power requirements. Following this, the Full Range Minimum Loss (FRML) strategy is applied to determine optimal current profiles across these loading points, significantly reducing copper losses. Finally, a multi-objective optimization approach is utilized to minimize torque ripple, enhance average torque, and optimize machine losses. The results demonstrate substantial improvements in torque and reduced ripple, validated through experiments conducted with a 2 kW lab-scale motor. This integrated approach not only ensures a robust and efficient motor design but also enhances fault tolerance, making it well-suited for advanced EV applications.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0