alexandria engineering journal最新文献_第3页

Particle emission and thermal efficiency analysis of a diesel vehicle using biodiesel and a platinum metallic partial-flow particulate filter 使用生物柴油和铂金属偏流微粒过滤器的柴油车的微粒排放和热效率分析

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-12 DOI: 10.1016/j.aej.2024.10.091

Huy Quang Dang , Mi Zwe Mon Phyo , Poonnut Thaeviriyakul , Plan Teekatasn Cosh , Mek Srilomsak , Therdsak Petblengsri , Ittipol Pawarmart , Sompong Srimanosaowapak , Hidenori Kosaka , Preechar Karin

Harmful emissions from diesel vehicles, particularly unmodified ones, pose significant concerns for human health and the environment, underscoring the urgency to address these issues. This study investigated the effects of commercial fuels, B10, B20, and biodiesel B100, used with a metallic partial-flow catalyzed diesel particulate filter (P-CDPF), on a light-duty unmodified diesel vehicle's thermal efficiency and emissions characteristics. The initial test was conducted on a chassis dynamometer to measure the fuel flow rates at three different engine speeds, 1500, 2000, and 2500 rpm, with four loads, 84, 112, 140, and 160 Nm. This was done to evaluate brake-specific fuel consumption and brake thermal efficiency under steady-state conditions. The second test followed the new European driving cycle to examine emission factors of regulated pollutants under both urban and highway driving conditions. The results indicated that BSFC values increased with the biodiesel ratio in the blends, attributed to lower heating values. However, higher oxygen contents with increasing biodiesel ratios led to more complete combustion and improved brake thermal efficiency. Installation of a P-CDPF had a minimal impact, resulting in less than a 3.4% increase in the BSFC and a 1% decrease in brake thermal efficiency across all tested fuels, owing to its relatively low pressure drop. Increasing the biodiesel ratio from B10 and B20 to B100 resulted in reductions of up to 32% of particulate mass and 45% of particulate number in vehicle emissions. P-CDPF installation further reduced particulate mass by over 60% and particulate number by 36% across all tested fuels, demonstrating its effectiveness in trapping and passively oxidizing particulate matter. Furthermore, the P-CDPF significantly reduced harmful gases with addition of a catalytic coating. A combination of a P-CDPF and commercial biodiesel fuels emerges as an effective solution for reducing regulated emissions from unmodified diesel vehicles.

柴油车（尤其是未改装的柴油车）的有害排放物对人类健康和环境造成了严重影响，因此迫切需要解决这些问题。本研究调查了商用燃料 B10、B20 和生物柴油 B100 与金属部分流量催化柴油微粒过滤器 (P-CDPF) 配合使用对轻型未改装柴油车热效率和排放特性的影响。最初的测试是在底盘测功机上进行的，以测量三种不同发动机转速（1500、2000 和 2500 rpm）和四种负载（84、112、140 和 160 Nm）下的燃油流量。这样做是为了评估稳态条件下的制动油耗和制动热效率。第二项测试采用了新的欧洲驾驶循环，以检查城市和高速公路驾驶条件下受管制污染物的排放系数。结果表明，BSFC 值随着混合燃料中生物柴油比例的增加而增加，这归因于较低的热值。不过，随着生物柴油比例的增加，氧气含量也会增加，从而使燃烧更完全，制动热效率也会提高。由于 P-CDPF 的压降相对较低，因此在所有测试燃料中，安装 P-CDPF 的影响很小，导致 BSFC 增加不到 3.4%，制动热效率降低 1%。将生物柴油的比例从 B10 和 B20 提高到 B100 后，车辆排放的颗粒物质量减少了 32%，颗粒物数量减少了 45%。在所有测试燃料中，P-CDPF 的安装进一步使颗粒物质量减少了 60% 以上，颗粒物数量减少了 36%，证明了其在捕集和被动氧化颗粒物方面的有效性。此外，P-CDPF 还能在添加催化涂层后显著减少有害气体。将 P-CDPF 和商用生物柴油燃料结合使用，是减少未改装柴油车受管制排放物的有效解决方案。

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引用次数: 0

Enhancing global model accuracy in federated learning with deep neuro-fuzzy clustering cyclic algorithm 利用深度神经模糊聚类循环算法提高联合学习中全局模型的准确性

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-11 DOI: 10.1016/j.aej.2024.10.093

Chin-Feng Lai , Ying-Hsun Lai , Ming-Chin Kao , Mu-Yen Chen

In recent years, with the increasing importance of privacy protection, many laws and regulations have standardized data usage, requiring companies to obtain user consent to access personal data. This has become more challenging for models that require large amounts of data for training. Therefore, the concept of federated learning was proposed in 2016, aiming to train models with different clients without sharing data to ensure data privacy. However, federated learning faces several challenges, including heterogeneous devices, data security, data heterogeneity, communication costs, and training time costs. This study focuses on addressing the issue of data heterogeneity, where the data distribution among participating clients differs significantly, leading to poor performance of the aggregated model after training. To tackle this problem, we propose a federated clustering cyclic algorithm, which involves two-step clustering of clients to make the data distribution of each cluster approach independent and identically distributed. We also introduce deep neural fuzzy methods to handle fuzzy, uncertain, or incomplete data. According to experimental results, the proposed deep neuro-fuzzy clustered cyclic algorithm outperforms methods such as FedAvg, FedProx, and CyclicFL on various non-IID datasets, with accuracy approaching that of centralized learning in certain experiments. This indicates that the deep neural fuzzy methods and clustering cyclic algorithm DNCC presented in this study can improve the accuracy of global models, especially in increasingly non-IID scenarios. Furthermore, we extend this method to big data processing to cope with more complex data environments.

近年来，随着隐私保护日益受到重视，许多法律法规都对数据使用进行了规范，要求公司在获取个人数据时必须征得用户同意。这对于需要大量数据进行训练的模型来说，变得更具挑战性。因此，2016 年有人提出了联合学习的概念，目的是在不共享数据的情况下用不同的客户端训练模型，以确保数据隐私。然而，联合学习面临着一些挑战，包括异构设备、数据安全、数据异构性、通信成本和训练时间成本。本研究的重点是解决数据异构问题，即参与学习的客户端之间的数据分布差异很大，导致训练后的聚合模型性能不佳。为解决这一问题，我们提出了一种联合聚类循环算法，即分两步对客户端进行聚类，使每个聚类方法的数据分布独立且同分布。我们还引入了深度神经模糊方法来处理模糊、不确定或不完整的数据。实验结果表明，在各种非 IID 数据集上，所提出的深度神经模糊聚类循环算法优于 FedAvg、FedProx 和 CyclicFL 等方法，在某些实验中，准确率接近集中学习的准确率。这表明，本研究提出的深度神经模糊方法和聚类循环算法 DNCC 可以提高全局模型的准确性，尤其是在越来越多的非 IID 场景中。此外，我们还将这种方法扩展到大数据处理中，以应对更复杂的数据环境。

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引用次数: 0

Pricing strategy of traceable agricultural supply chain decisions considering retailer's overconfidence with government subsidy 考虑到零售商对政府补贴的过度自信，可追溯农产品供应链决策的定价策略

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-11 DOI: 10.1016/j.aej.2024.11.020

Chongfeng Lan, Yaru Lan, Shengde Liu

This study examines pricing strategies within a two-tier traceable agricultural product supply chain, encompassing both the retailer and the supplier. A pricing decision model was developed to evaluate scenarios characterized by the retailer's overconfidence as well as those devoid of such bias. This research employs Stackelberg game theory to investigate the impact of government subsidies, retailer overconfidence and consumer preferences for traceability on the performance of supply chain participants and the overall system. Our analysis derives the following findings: (i) retailer overconfidence strengthens their commitment to traceability, thereby enhancing the overall efficacy of the supply chain. (ii) Additionally, consumer demand for traceability incentivizes retailers to intensify their traceability initiatives, aligning with consumer purchasing expectations. (iii) The pricing decisions made by retailers are influenced by their overconfidence, consumer preferences for traceability, and the presence of government subsidies. (vi) The study also shows that retailer overconfidence and customer demand for traceability have the most effects on supply chain performance when decision-making is centralized.

本研究探讨了包括零售商和供应商在内的双层可追溯农产品供应链中的定价策略。研究开发了一个定价决策模型，以评估零售商过度自信和不存在过度自信的情况。本研究采用斯泰克尔伯格博弈论来研究政府补贴、零售商过度自信和消费者对可追溯性的偏好对供应链参与者和整个系统绩效的影响。我们的分析得出以下结论：(i) 零售商的过度自信会加强他们对可追溯性的承诺，从而提高供应链的整体效率。(ii) 此外，消费者对可追溯性的需求激励零售商加强其可追溯性举措，从而与消费者的购买期望保持一致。(iii) 零售商的定价决策受其过度自信、消费者对可追溯性的偏好以及政府补贴的影响。(vi) 研究还表明，当决策集中时，零售商的过度自信和消费者对可追溯性的需求对供应链绩效的影响最大。

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引用次数: 0

Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings 预测高层建筑风压的深度学习和机器学习方法比较研究

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-11 DOI: 10.1016/j.aej.2024.10.047

Mosbeh R. Kaloop , Abidhan Bardhan , Pijush Samui , Jong Wan Hu , Mohamed Elsharawy

Wind-structures interaction has been extensively examined in the last few decades using field measurements, full scale measurements and wind tunnel testing. These experimental approaches are considered costly and time consuming. The need for a reliable analytical approach that can be used for examining wind-effects on buildings is clear. Although Computational Fluid Dynamics (CFD) is one of the other alternative numerical options yet might not reached the level of confidence to be reliably used to finalize the structural design. On the other hand, a limited number of studies have been carried out using soft computing methods to examine wind-induced loads on structures. However, its promising results, more work is still required towards achieving the full analytical prediction of wind effects on structures. This study investigates the use of different soft-computing techniques in predicting wind pressures on tall buildings. Two deep learning methods viz deep belief network (DBN) and deep neural network (DNN), and five machine learning methods namely feedforward neural network, extreme learning machine, weighted extreme learning machine, random forest, and gradient boosting machine were evaluated, and compared in predicting the design wind pressures on tall buildings. Wind tunnel datasets, used in the current study to develop the proposed computing models, were collected from testing three tall buildings having the same full-scale horizontal dimensions of (40 m and 80 m) and different heights of (80 m, 120 m and 160 m). The buildings were tested at a scale of 1:400 in urban terrain exposure. Mean and fluctuating wind pressure coefficients on the building with the height of 120 m are herein predicted using the seven computing methods and the results were compared to the corresponding measured pressures. Overall, the examined methods performed well in the wind pressure prediction process. Furthermore, the employed DNN was found to have the best performance in predicting mean and fluctuating wind pressures with the highest correlation coefficients. Hence, the DNN was also used in predicting the mean and fluctuating wind pressures on the two other buildings with heights of 80 m and 160 m. Experimental results indicate that the employed DNN model can be effectively used in predicting wind-induced pressures on tall buildings.

在过去的几十年里，人们利用现场测量、全尺寸测量和风洞试验对风-结构相互作用进行了广泛的研究。这些实验方法被认为既昂贵又耗时。因此，显然需要一种可靠的分析方法来研究风对建筑物的影响。虽然计算流体动力学（CFD）是其他数值方法的替代选择之一，但可能还没有达到可靠的水平，无法用于最终的结构设计。另一方面，使用软计算方法来研究风引起的结构荷载的研究数量有限。然而，尽管取得了可喜的成果，但要全面分析预测风对结构的影响，还需要做更多的工作。本研究调查了不同软计算技术在预测高层建筑风压中的应用。在预测高层建筑的设计风压时，评估和比较了两种深度学习方法，即深度信念网络（DBN）和深度神经网络（DNN），以及五种机器学习方法，即前馈神经网络、极限学习机、加权极限学习机、随机森林和梯度提升机。风洞数据集是本次研究中用于开发计算模型的数据集，这些数据集是从三座高层建筑的测试中收集的，三座建筑的全尺寸水平尺寸相同（40 米和 80 米），高度不同（80 米、120 米和 160 米）。这些建筑物是在城市地形中以 1:400 的比例进行测试的。使用七种计算方法预测了高度为 120 米的建筑物上的平均风压系数和波动风压系数，并将结果与相应的实测压力进行了比较。总体而言，所研究的方法在风压预测过程中表现良好。此外，采用的 DNN 在预测平均风压和波动风压方面表现最佳，相关系数最高。因此，DNN 也被用于预测另外两座高度分别为 80 米和 160 米的建筑物的平均风压和波动风压。实验结果表明，所采用的 DNN 模型可有效用于预测高层建筑的风致压力。

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引用次数: 0

A new probabilistic model with properties and Monte Carlo simulation: Its explorations in dance education and music engineering 具有特性和蒙特卡罗模拟的新概率模型：在舞蹈教育和音乐工程中的探索

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-10 DOI: 10.1016/j.aej.2024.10.095

Hualong Zhong , Yuanjun Xue , Tmader Alballa , Wafa F. Alfwzan , Somayah Abdualziz Alhabeeb , Hamiden Abd El-Wahed Khalifa

In the examination of real-life situations, the application of probability distributions is often crucial for statistical analysis of the real-life scenarios. Many models based on probability have been utilized in disciplines such as music education, music engineering, and other music-related areas. Hence, acknowledging the significance of probability-based approaches, this article introduces an innovative probability model known as a new generalized Rayleigh distribution. The suggested model is established on merging the generalized Rayleigh distribution with a prominent weighted probabilistic method. The mathematical properties, specifically the quartile-based features of the novel generalized Rayleigh distribution, are investigated. Moreover, we outline the derivation of the point estimators for the unknown parameters of the new model. A thorough simulation study is also conducted to examine the performances of these point estimators. Within the music industry, specifically in music education and music engineering, we examine the practical implications of the new generalized Rayleigh distribution. We observe that it offers a superior fit when contrasted with other distributions. Our findings demonstrate that the new distribution is a inclusion to the group of probability distributions that can be applied in music engineering and other closely connected engineering fields for the statistical analysis of real-life events.

在对现实情况进行研究时，概率分布的应用往往对现实情况的统计分析至关重要。许多基于概率的模型已被用于音乐教育、音乐工程和其他音乐相关领域。因此，考虑到基于概率的方法的重要性，本文介绍了一种创新的概率模型，即新的广义瑞利分布。所建议的模型是将广义瑞利分布与一种突出的加权概率方法相结合而建立的。我们研究了新广义瑞利分布的数学特性，特别是基于四分位数的特性。此外，我们还概述了新模型未知参数点估计器的推导过程。我们还进行了全面的模拟研究，以检验这些点估计器的性能。在音乐行业，特别是音乐教育和音乐工程领域，我们研究了新的广义瑞利分布的实际意义。我们发现，与其他分布相比，它具有更高的拟合度。我们的研究结果表明，新分布是一组概率分布的新成员，可用于音乐工程和其他密切相关的工程领域，对现实生活中的事件进行统计分析。

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引用次数: 0

RAM-MEN: Robust authentication mechanism for IoT-enabled edge networks RAM-MEN：适用于物联网边缘网络的稳健认证机制

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-09 DOI: 10.1016/j.aej.2024.10.116

Muhammad Tanveer , Saud Alhajaj Aldossari

The rapid expansion of Mobile Edge Computing (MEC) and the Internet of Things (IoT) has revolutionized technology by enabling real-time data processing at the network edge, which is essential for applications such as autonomous vehicles and smart cities. With the advent of 6G networks, which promise ultra-fast speeds, vast connectivity, and low-latency communication, MEC-IoT systems are becoming more powerful but also face significant security challenges. Existing authentication mechanisms (AMs) are often vulnerable to attacks like impersonation and insider threats. This paper introduces a novel lightweight AM, called RAM-MEN that employs cryptography and physically unclonable functions (PUFs) to secure IoT-enabled MEC environments in the 6G era. It protects against insider threats and fake MEC access points while ensuring efficiency and scalability. Additionally, the proposed RAM-MEN establishes a secure communication channel (session key) between IoT devices and the MEC server, enabling secure offloading of computationally intensive tasks. The security of the session is rigorously evaluated using formal methods, including Scyther and the random or real model, alongside informal approaches. Comparative performance evaluations show that the proposed RAM-MEN reduces communication costs by 21.54% to 45.53% and computational costs by 17.09% to 83.72%, while providing enhanced security features.

移动边缘计算（MEC）和物联网（IoT）的快速发展带来了技术革命，使网络边缘的实时数据处理成为可能，这对自动驾驶汽车和智能城市等应用至关重要。随着有望实现超高速、广泛连接和低延迟通信的 6G 网络的出现，MEC-物联网系统正变得越来越强大，但也面临着巨大的安全挑战。现有的身份验证机制（AM）往往容易受到冒名顶替和内部威胁等攻击。本文介绍了一种名为 RAM-MEN 的新型轻量级 AM，它采用密码学和物理不可克隆函数（PUF）来确保 6G 时代物联网 MEC 环境的安全。它可防止内部威胁和伪造的 MEC 接入点，同时确保效率和可扩展性。此外，拟议的 RAM-MEN 还能在物联网设备和 MEC 服务器之间建立安全通信通道（会话密钥），从而实现计算密集型任务的安全卸载。会话的安全性使用正式方法（包括 Scyther 和随机或真实模型）和非正式方法进行了严格评估。性能对比评估表明，拟议的 RAM-MEN 可将通信成本降低 21.54% 至 45.53%，将计算成本降低 17.09% 至 83.72%，同时提供更强的安全功能。

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引用次数: 0

Construction of optimised theoretical model using ANOVA -Taguchi methodology for transient flow of Carreau nanofluid through microchannel prone to radiation 利用方差分析--塔口方法构建易受辐射影响的微通道中卡里奥纳米流体瞬态流动的优化理论模型

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-09 DOI: 10.1016/j.aej.2024.10.111

Pradeep Kumar , Felicita Almeida , Ajaykumar AR , Qasem Al-Mdallal

The current study intends to predict the optimised condition to attain the objective of acquiring highest heat transfer rate to develop an efficient model. The transient flow of Carreau nanofluid within a microchannel when channel walls are susceptible to radiation is contemplated. Buongiorno model is employed, which emphasizes the repercussions of Brownian motion and thermophoresis phenomena; also, mixed-convective flow is accounted. The modelled problem gives rise to partial differential equations, which are non-dimensionalized employing non-dimensional quantities. The resultant equations are solved numerically using the finite difference method. Results of analysis demonstrate that the Weissenberg number for

n < 1

depicts shear thinning nature, and for

n > 1

, depicts shear thickening nature, decreasing velocity. The skin friction coefficient increases when solutal Grashof number rises for the high range of the Reynolds number. The Sherwood number increases when Schmidt number is less for increased value of Reynolds number. Optimization method reveals the highest heat transfer rate of 7.3687 for the considered model. ANOVA results show that the manipulation of Reynolds number is crucial with

57.29 %

impact and the manipulation of Prandtl number has minor impact of

1.41 %

on Nusselt number. Shear thinning nature of Carreau fluid finds its application in extrudability, printability and injectability and shear thickening nature is extensively used in industrial polishing, explosion resistance.

目前的研究旨在预测优化条件，以实现获得最高传热率的目标，从而开发出一种有效的模型。研究考虑了当通道壁易受辐射影响时，Carreau 纳米流体在微通道内的瞬态流动。采用的 Buongiorno 模型强调了布朗运动和热泳现象的影响，并考虑了混合对流。建模问题产生了偏微分方程，这些方程采用了非尺寸量进行非尺寸化。使用有限差分法对结果方程进行数值求解。分析结果表明，韦森伯格数 n<1 表示剪切变薄，n>1 表示剪切变厚，速度减小。在高雷诺数范围内，当溶质格拉肖夫数升高时，表皮摩擦系数增大。当雷诺数增加时，施密特数降低，谢伍德数增加。优化方法显示，所考虑模型的最高传热率为 7.3687。方差分析结果表明，雷诺数的调节对努塞尔特数的影响最大，为 57.29%，而普朗特数的调节对努塞尔特数的影响较小，仅为 1.41%。Carreau 流体的剪切稀化特性可用于挤出、印刷和注射，而剪切增稠特性则可广泛用于工业抛光和防爆。

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引用次数: 0

Nonlinear vibration of wire-wrapped fuel rod subjected to axial flow 受轴向流动影响的线包燃料棒的非线性振动

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-09 DOI: 10.1016/j.aej.2024.11.001

Yu Zhang , Pengzhou Li

Wire-wrapped fuel rods are widely utilized in lead-bismuth reactors and subjected to high kinetic energy fluid flow, significantly influencing the reactor's safe operation. This study addresses the increasing interest in fuel assemblies by developing a theoretical fluid-structure interaction model to elucidate the dynamic behavior of wire-wrapped fuel rods. Newton's law is employed to derive the governing equation, with fluid force coefficients determined through widely accepted numerical simulations, while the impact and downstream nonlinear boundary condition are incorporated. Two comparative analyses robustly validate the reliability of the proposed model. Building on this model, the study investigates the nonlinear vibration characteristics (amplitude, phase space, impact forces, etc.) of the structure, considering the effects of gap size and streamlining parameter. Moreover, the theoretical derivation of this model provides a foundational and dependable mathematical framework to facilitate further research on fretting wear.

铅铋反应堆中广泛使用线包燃料棒，它受到高动能流体流的作用，对反应堆的安全运行有重大影响。针对人们对燃料组件日益增长的兴趣，本研究开发了流固相互作用理论模型，以阐明线绕燃料棒的动态行为。该模型采用牛顿定律推导控制方程，流体力系数通过广泛接受的数值模拟确定，同时还纳入了冲击和下游非线性边界条件。两项对比分析有力地验证了所提模型的可靠性。在此模型的基础上，考虑到间隙大小和流线参数的影响，研究了结构的非线性振动特性（振幅、相空间、冲击力等）。此外，该模型的理论推导为进一步研究摩擦磨损提供了一个基础和可靠的数学框架。

引用次数: 0

Lie-symmetry analysis of a three dimensional flow due to unsteady stretching of a flat surface with non-uniform temperature distribution 温度分布不均匀的平面非稳定拉伸引起的三维流动的李对称分析

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-09 DOI: 10.1016/j.aej.2024.10.121

Ghani Khan , Muhammad Safdar , Safia Taj , Adnan Munir , Muhammad Tauseef Nasir

Various mathematical frameworks have been developed to study dynamics of the fluid flow in stretching films. In this work, a three–dimensional flow induced by an unsteady stretching of an infinite flat sheet is analyzed through the Lie symmetry approach. Twelve Lie point symmetries for the nonlinear partial differential equations describing the considered flow and heat transfer phenomena are derived. Invariants for these Lie symmetries are obtained to construct a new class of similarity transformations. With the deduced similarity transformations, the flow equations are converted to ordinary differential equations which are solved using the Homotopy analysis method. The deduced analytic solution enables an exploration of the effects of various parameters on the flow and heat transfer, which have not been revealed previously using the Lie method as per the authors’ knowledge. The influences of the stretching rate, parameters that maintain the non-uniformity and unsteadiness of sheet temperature, and the Prandtl number, are demonstrated with the help of graphs and tables. These results show that for certain values of the system parameters, heat transfer reverses its direction and occurs from the fluid to the sheet. At these values, maximum heat transfer does not occur at the sheet but rather slightly above it.

为研究拉伸薄膜中的流体流动动力学，人们开发了各种数学框架。在这项工作中，通过李对称方法分析了无限平片非稳定拉伸引起的三维流动。推导出了描述所考虑的流动和传热现象的非线性偏微分方程的 12 个 Lie 点对称性。通过获取这些李对称性的不变量，构建了一类新的相似性变换。利用推导出的相似性变换，将流动方程转换为常微分方程，并使用同调分析方法进行求解。根据推导出的解析解，可以探索各种参数对流动和传热的影响。拉伸率、保持片材温度不均匀性和不稳定性的参数以及普朗特数的影响通过图表和表格得到了证明。这些结果表明，在系统参数达到一定值时，热量传递方向会发生逆转，从流体传递到薄片。在这些值下，最大传热不是发生在薄片上，而是稍高于薄片。

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引用次数: 0

Analysis of the physical properties of a boron meter based on He-3 neutron detector 基于氦-3 中子探测器的硼测量仪物理性质分析

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-08 DOI: 10.1016/j.aej.2024.11.013

Qi-Dong Dai , Guo-En Fu , Can-Hui Wang , Xun-Cheng Zong , Hong-Bo Wang , Can Cui

Boron meter is commonly used for real-time monitoring of boron concentration in the primary circuit water of pressurized water reactors to ensure the safe operation of the reactor. This paper introduces the use of Am-Be neutron source and He-3 neutron detector for a boron meter. It analyzes the physical properties of a boron meter, including the energy spectrum characteristics of Am-Be neutron sources, the sensitivity of He-3 neutron detector, radiation shielding of the boron meter’s detection device, and the fitting relationship between neutron count rate and boron concentration. The boron meter was accurately physically modeled using the MCNP program, and the calculated results were comprehensively compared with experimental results. A method using correction factor μ to adjust the count rate’s calculated results was proposed. The research results show that the sensitivity of He-3 neutron detectors, the dose rate on the surface of the boron meter detection device, neutron count rate, and other calculated results are consistent with the experimental results, verifying the accuracy of the boron physical model. This physical model can be used for more refined computational analysis or to optimize the current physical design of the boron meter, thus saving experimental costs.

硼计通常用于实时监测压水反应堆一回路水中的硼浓度，以确保反应堆的安全运行。本文介绍了硼计使用 Am-Be 中子源和 He-3 中子探测器的情况。它分析了硼计的物理特性，包括 Am-Be 中子源的能谱特性、He-3 中子探测器的灵敏度、硼计探测装置的辐射屏蔽以及中子计数率与硼浓度之间的拟合关系。利用 MCNP 程序对硼仪进行了精确的物理建模，并将计算结果与实验结果进行了综合比较。提出了使用修正系数 μ 来调整计数率计算结果的方法。研究结果表明，氦-3 中子探测器的灵敏度、硼表探测装置表面的剂量率、中子计数率等计算结果与实验结果一致，验证了硼物理模型的准确性。该物理模型可用于更精细的计算分析或优化当前硼计的物理设计，从而节省实验成本。

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引用次数: 0