alexandria engineering journal最新文献

{"title":"Safe operations of a reach stacker by computer vision in an automated container terminal","authors":"","doi":"10.1016/j.aej.2024.08.080","DOIUrl":"10.1016/j.aej.2024.08.080","url":null,"abstract":"<div><p>Smart ports, utilizing advanced and hybrid technologies, are gaining increasing attention for application in the maritime industry, with driver assistance and autonomous driving being pivotal in container-terminal operations. This study introduces a novel approach for enhancing object detection and distance estimation, focusing principally on decision support for reach stacker container handlers in port terminals by integrating generative and deep learning models. The EfficientDet model, enriched with integrated k-means clustering, is developed to detect and classify objects using a practical dataset of labeled images based on visual features. Moreover, generative models, specifically the diffusion model and generative adversarial network, are utilized to generate depth scenes for estimating object distances. Experimental results indicate that the proposed approach yields superior object detection and distance estimation outcomes in port terminal operations, characterized by high accuracy and reduced computational cost. The proposed method exhibits potential for application across various industries, including transportation, logistics, and security, where precise object detection and distance estimation are vital for efficient and secure operations.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009803/pdfft?md5=460cf74cde423f46c88bd6460b75d707&pid=1-s2.0-S1110016824009803-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148897","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}

{"title":"Letter to editor: ICMAACS and history of its mathematical awards","authors":"","doi":"10.1016/j.aej.2024.08.098","DOIUrl":"10.1016/j.aej.2024.08.098","url":null,"abstract":"","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009967/pdfft?md5=34e15d954be830e8d42d6c533d02abc3&pid=1-s2.0-S1110016824009967-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147624","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}

{"title":"Parameter-based RNN micro-interface inversion model for wet friction components morphology","authors":"","doi":"10.1016/j.aej.2024.09.003","DOIUrl":"10.1016/j.aej.2024.09.003","url":null,"abstract":"<div><p>The interface morphology significantly impact the service life of wet clutches friction components in heavy tracked vehicle transmission systems. This paper designs a sliding test and utilizes a recurrent neural network (RNN) model to construct the three-dimensional morphology of the wet clutch friction interface under specific operating conditions. It also explores the relationship between these factors and clutch performance. The interface morphology characteristics are analyzed by the RNN inversion model to assess the effects of three working condition parameters including rotational speed, pressure, and sliding time. This research provides important primary data for engineering studies and applications aimed at optimizing the design of wet clutches and improving transmission system reliability.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824010159/pdfft?md5=0fd89c4db54d81640158a5bb6a0728b1&pid=1-s2.0-S1110016824010159-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148849","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}

{"title":"State of charge estimation of lithium batteries in wide temperature range based on MSIABC-AEKF algorithm","authors":"","doi":"10.1016/j.aej.2024.08.092","DOIUrl":"10.1016/j.aej.2024.08.092","url":null,"abstract":"<div><p>The key to a Battery Management System (BMS) is the accurate and real-time prediction of the State of Charge (SOC) of the power battery. Currently, there is relatively little research on the construction methods of battery models within a wide temperature range. A second-order RC equivalent circuit is selected to establish an Improved Equivalent Circuit Model (IECM) based on temperature compensation. The identification of IECM parameters is completed by using the multi strategy improvement of Artificial Bee Colony (MSIABC) algorithm combining with pulse discharge experimental data under different temperature conditions (-20 °C to 60 °C). Based on the experimental data of the UDDS condition and the hybrid dynamic condition under low temperature, high temperature, and time-varying temperature environments, the battery SOC is estimated by combining the IECM and Adaptive Extended Kalman Filtering (AEKF) algorithm. The experimental results show that compared with the conventional ECM-AEKF estimation method, IECM-AEKF has higher SOC estimation accuracy and environmental temperature adaptability.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009906/pdfft?md5=6958f4d7df3168f7b2c60ad568e8ff77&pid=1-s2.0-S1110016824009906-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148851","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}

{"title":"Detailed analysis of a pure hydrogen-fueled dual-fuel engine in terms of performance and greenhouse gas emissions","authors":"","doi":"10.1016/j.aej.2024.08.086","DOIUrl":"10.1016/j.aej.2024.08.086","url":null,"abstract":"<div><p>The current study seeks to greenhouse gas emissions reduction in an existing engine under dual-fuel combustion fueled with diesel fuel and natural gas due to great concerns about global warming. This simulation study focuses on the identification of areas prone to the formation of greenhouse gas emissions in engine cylinders. The simulation results of dual-fuel combustion confirmed that the possibility of incomplete combustion and the formation of greenhouse gas emissions in high levels are not far from expected. Therefore, an efficient combustion strategy along with replacing natural gas with hydrogen was considered. Only changing the combustion mode to reactivity-controlled compression ignition has led to the improvement of the natural gas burning rate and guarantees a 32 % reduction in unburned methane and 50 % carbon monoxide. To further reduce engine emissions, while changing the combustion mode, a part of natural gas replacement with hydrogen to the complete elimination of it was evaluated. Increasing the share of hydrogen energy in the intake air-natural gas mixture up to 54 % without exhaust gas recirculation does not lead to diesel knock. Moreover, improvement of engine load and efficiency can be achieved by up to 18 % and 6 %, respectively. Natural gas consumption can be reduced by up to 67 %. Meanwhile, the unburned methane and carbon dioxide mass, known as greenhouse gas emissions, can be reduced to less than 1 % and up to 50 %, respectively. Continued replacement of natural gas with hydrogen until its complete elimination guarantees a reduction of 92,000 cubic meters of natural gas per year in one engine cylinder. Although, the engine efficiency and load face a decrease of 0.8 % and 5.0 %, respectively; the amount of carbon dioxide can be decreased by about 4.5 times. Unburned methane, carbon monoxide and nitrogen oxides can be reduced to below the relevant EURO VI range while the amount of unburned hydrogen compared to the hydrogen entering the engine is about 0.5 %.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009827/pdfft?md5=b3e99e2e5864ccbe34abb7785c150eaa&pid=1-s2.0-S1110016824009827-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148895","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}

{"title":"Extracting explicit coefficient formulas: A robust approach to the laplace residual power series method","authors":"","doi":"10.1016/j.aej.2024.08.091","DOIUrl":"10.1016/j.aej.2024.08.091","url":null,"abstract":"<div><p>This work presents a novel advancement to the Laplace Residual Power Series Method (LRPSM) for solving fractional differential equations by specifically utilizing the Caputo fractional derivative. The conventional LRPSM relies on iterative calculations of the residual function to determine the series coefficients. We address this limitation by deriving a direct formula that yields all coefficients at once. This innovation significantly streamlines the computational process compared to the traditional LRPSM, leading to a more efficient method.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009888/pdfft?md5=d3e591329c35bded22686c9a4da5c693&pid=1-s2.0-S1110016824009888-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148885","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}

{"title":"Security authentication scheme based on chebyshev chaotic mapping for library network","authors":"","doi":"10.1016/j.aej.2024.08.108","DOIUrl":"10.1016/j.aej.2024.08.108","url":null,"abstract":"<div><p>With the rapid advancement of information technology, the security of digital libraries, as critical platforms for modern knowledge dissemination, has become increasingly significant. User identity authentication in digital libraries is pivotal to ensuring system security. Traditional authentication methods often have security vulnerabilities and cannot effectively prevent unauthorized access. Therefore, this paper proposes a security authentication scheme based on chebyshev chaotic mapping for library. It addresses security issues in identity authentication in digital libraries. The proposed scheme integrates smart card, password and biometric factor, leveraging the chebyshev chaotic mapping algorithm to achieve stringent user authentication and generate secure session keys, thereby effectively countering security threats. Additionally, the scheme employs physical unclonable function (PUF) to enhance the protection of stored confidential data. The security of this scheme is rigorously analyzed using the Scyther. Security analysis and performance experiments indicate that the scheme not only ensures security but also optimizes authentication efficiency.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824010056/pdfft?md5=0ef0904b1b31b3bbe3e9d304c5af5488&pid=1-s2.0-S1110016824010056-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148896","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}

{"title":"A novel generalized nonlinear fractional grey Bernoulli model and its application","authors":"","doi":"10.1016/j.aej.2024.08.096","DOIUrl":"10.1016/j.aej.2024.08.096","url":null,"abstract":"<div><p>Considering that the existing fractional order grey prediction models are difficult to directly handle the shortcomings of seasonal time series, a novel generalized nonlinear fractional grey Bernoulli model capable of handling both seasonal and conventional time series is constructed. The structure of the new model adopts a more flexible nonlinear Bernoulli equation and a novel adaptive fractional accumulation operation, which endows it with stronger nonlinear fitting capabilities. Furthermore, the introduction of a dynamic parameter endows it with the capability to handle both seasonal and conventional time series simultaneously. Specifically, the structural parameters of the model are no longer obtained through traditional least squares method but instead through a moving average trend removal method and intelligent optimization algorithms, which greatly improves the computational efficiency of the model. Therefore, the practicality of the novel model surpasses that of all existing fractional grey prediction models. Experimental results on two types of datasets demonstrate that the proposed method outperforms existing machine learning models, fractional grey prediction models and statistical prediction model in terms of generalization ability, validating its effectiveness.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009931/pdfft?md5=a4a4145151029818122497c79081e9c7&pid=1-s2.0-S1110016824009931-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148850","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}

{"title":"Marine diesel engine piston ring fault diagnosis based on LSTM and improved beluga whale optimization","authors":"","doi":"10.1016/j.aej.2024.08.075","DOIUrl":"10.1016/j.aej.2024.08.075","url":null,"abstract":"<div><p>The operational state of piston rings in marine diesel engines significantly influences the overall performance of the machinery. However, traditional data-driven diagnosis methods have problems with relying on manual feature extraction and failing to adequately leverage the temporal characteristics inherent in fault vibration signals. Therefor a fault diagnosis method based on long short-term memory neural network (LSTM) optimized by the improved beluga whale optimization algorithm (IBWO) is proposed in this paper. The LSTM process vibration signals, leveraging their gating mechanism for temporal feature extraction before classification via softmax. Setting optimal combinations of hidden layers and learning rates is difficult due to complexity and lengthy training times, making parameter optimization a significant challenge. The beluga whale optimization (BWO) algorithm for parameter optimization is employed to address this. Additionally, to reduce the risk of convergence to local optima, the balance factor is improved by replacing the linear function with a nonlinear function in the original algorithm. Finally, IBWO-LSTM is compared with BWO-LSTM, FOA-LSTM, PSO-LSTM and LSTM. Experimental validation shows that IBWO-LSTM outperforms BWO-LSTM, FOA-LSTM, PSO-LSTM, and standard LSTM, with an average accuracy higher than 90 %. Therefore, the IBWO-LSTM demonstrates better fault identification accuracy, providing a more precise solution for marine diesel engine piston ring fault diagnosis.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009633/pdfft?md5=f886f6e64a8c099460e5b363b15e75c5&pid=1-s2.0-S1110016824009633-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148848","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}

{"title":"GSK-LocS: Towards a more effective generalisation in population-based neural network training","authors":"","doi":"10.1016/j.aej.2024.08.097","DOIUrl":"10.1016/j.aej.2024.08.097","url":null,"abstract":"<div><p>Despite the effectiveness of deep neural networks, feed-forward neural networks (FFNNs) continue to play a crucial role in many applications, especially when dealing with limited data availability. The primary challenge in FFNNs is determining the optimal weights during the training process, aiming to minimise the disparity between actual and predicted outputs. Although gradient-based techniques like backpropagation (BP) have traditionally been popular for FFNN training, they come with inherent limitations, such as sensitivity to initial weights and susceptibility to getting trapped in local optima. To overcome these challenges, we introduce a novel approach based on the Gaining-Sharing Knowledge-based(GSK) algorithm. To the best of our knowledge, this paper represents the first exploration of GSK for neural network training. After obtaining the appropriate weights for the FFNN by the GSK, the weights and biases are utilised to initialise a Levenberg–Marquardt backpropagation (LMBP) algorithm, serving as a local search component. In other words, our proposed algorithm, GSK-LocS, leverages the global search capabilities of the GSK algorithm and combines them with the local search capabilities of LMBP for neural network training. This integration mitigates sensitivity to initial values and reduces the risk of being trapped in local optima. Experimental results conducted on classification and approximation problems provide compelling evidence that our proposed algorithm is highly competitive compared to other existing methods.</p></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":null,"pages":null},"PeriodicalIF":6.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1110016824009955/pdfft?md5=0f96e454392525252e9bacfd690a86ba&pid=1-s2.0-S1110016824009955-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129801","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}