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A computational framework for micropolar fluid considering chemical reaction in porous media with stagnation point flow over a stretchable sheet in the presence of viscous dissipation 微极流体的计算框架考虑了多孔介质中具有滞止点流动的可拉伸薄板中存在粘性耗散的化学反应
Q1 Chemical Engineering Pub Date : 2025-10-12 DOI: 10.1016/j.ijft.2025.101453
Muhammad Salman Kausar , Ali B.M. Ali , Talha Anwar , Abduvali Sottarov , Tadesse Walelign , M. Waqas

Background

The study of fluid flow over stretchable surfaces is crucial in numerous engineering and industrial applications. Particularly, the behavior of micropolar fluids which account for microstructure effects not captured by Newtonian models, presents a more accurate representation in areas like polymer processing and biological flows. The presence of porous media, stagnation point, thermal radiation and viscous dissipation further complicates the flow dynamics heat and mass transfer characteristics, making their coupled implications a significant area for research. Understanding these combined effects is vital for optimizing system performance in scenarios where chemical reactions are involved.

Objective

The key objective of this study is to explore the implications of a chemically reactive micropolar fluid on a stretchable sheet in the presence of porous media, a stagnation point, thermal radiation and viscous dissipation. The analysis intends to scrutinize how these aspects adjust microrotation, temperature, velocity and concentration fields within boundary-layer.

Methodology

The system of partial differential equations (PDEs) governing the fluid flow, heat and mass transfer is first converted into a system of ordinary differential equations (ODEs) using appropriate similarity transformations. The bvp4c procedure is then deployed to derive the numerical solutions. This method is used to accurately estimate the numerical values of the drag force, heat transmission rate and mass transmission rate for various emerging parameters. The computations are verified with previous research to confirm the outcomes.

Findings

The velocity field increases for higher micropolar parameter but declines with escalating suction parameter and porosity parameter. Temperature field rises with higher Eckert number while it declines for enlarged Prandtl number estimations. An increment in Schmidt number and chemical reaction factor yield lower concentration distribution. The numerical computations of drag force, mass transmission rate and heat transmission rate are estimated with greater accuracy and validated against existing literature. The efficacy of the bvp4c method in providing trustworthy solutions is exhibited.
研究流体在可拉伸表面上的流动在许多工程和工业应用中是至关重要的。特别是,微极性流体的行为解释了牛顿模型没有捕捉到的微观结构效应,在聚合物加工和生物流动等领域呈现出更准确的表现。多孔介质、滞止点、热辐射和粘性耗散的存在使流动动力学、传热传质特性进一步复杂化,使其耦合影响成为一个重要的研究领域。在涉及化学反应的情况下,了解这些综合效应对于优化系统性能至关重要。本研究的主要目的是探讨在多孔介质、驻点、热辐射和粘性耗散存在的情况下,可拉伸薄片上的化学反应性微极流体的影响。分析了这些因素如何调节边界层内的微旋场、温度场、速度场和浓度场。方法:控制流体流动、热量和质量传递的偏微分方程组(PDEs)首先通过适当的相似变换转换为常微分方程组(ode)。然后利用bvp4c程序推导数值解。该方法可以准确地估计出各种新出现参数的阻力、传热率和传质率的数值。计算结果与前人的研究结果进行了验证。结果:微极参数越高,速度场越大,吸力和孔隙度越高,速度场越小。温度场随着Eckert数的增加而升高,而对于扩大普朗特数的估计,温度场则下降。施米特数和化学反应因子的增加使浓度分布减小。对阻力、传质率和传热率的数值计算进行了更精确的估计,并与现有文献进行了验证。证明了bvp4c方法在提供可信解方面的有效性。
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引用次数: 0
Enhanced thermal analysis of thermo-bioconvection flow of water based trihybrid nanofluid with gyrotactic microbes: soret and dufour effects 具有陀螺效应微生物的水基三杂交纳米流体热生物对流流的强化热分析:soret和dufour效应
Q1 Chemical Engineering Pub Date : 2025-10-11 DOI: 10.1016/j.ijft.2025.101441
Dürdanə Rustamova Farkhad , Muhammad Sabaoon Khan , Mirjalol Ashurov , Munawar Abbas , Ilyas Khan , Ali Hasan Ali , Nidhal Ben Khedher
The suggested model of thermo-bioconvection flow of a water-based trihybrid nanofluid including gyrotactic microbes under Soret and Dufour effects has important applications in engineering and biomedicine. It can be used to improve mass and heat transmission in bioreactors, microfluidic devices, and wastewater treatment systems, where microbial activity is critical. Furthermore, it offers insights into enhancing thermal management in energy systems, cooling technologies, and sophisticated nanofluid-based biological processes including targeted medication delivery and microbial fuel cells. This study uses Soret and Dufour effects to describe how thermal radiation affects gyrotactic microorganisms in a water-based trihybrid nanofluid across a narrow porous surface. The impacts of magnetic fields and Hall current are all taken into consideration when analyzing fluid flow. The similarity transformation reduces a nonlinear set of PDEs to a dimensionless system of ODEs. We have used the bvp4c approach to numerically evaluate the reduced set of nonlinear ODEs. Thermal and concentration profile decline as augment the values of Marangoni convection parameter. As the values of the Marangoni convection parameter increase, the thermal and concentration profiles decrease.
所建立的Soret和Dufour效应下含陀螺微生物的水基三杂交纳米流体的热-生物对流流动模型在工程和生物医学上具有重要的应用价值。它可用于改善生物反应器,微流控装置和废水处理系统中的质量和传热,其中微生物活性至关重要。此外,它还为加强能源系统的热管理、冷却技术和复杂的基于纳米流体的生物过程(包括靶向药物输送和微生物燃料电池)提供了见解。本研究使用Soret和Dufour效应来描述热辐射如何影响水基三杂交纳米流体中穿过狭窄多孔表面的陀螺微生物。在分析流体流动时,考虑了磁场和霍尔电流的影响。相似变换将非线性偏微分方程集合化为无量纲偏微分方程系统。我们使用bvp4c方法对非线性ode的约简集进行了数值计算。随着Marangoni对流参数值的增大,热剖面和浓度剖面逐渐减小。随着马兰戈尼对流参数的增大,热剖面和浓度剖面减小。
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引用次数: 0
Simulation-based analysis of thermal bridge reduction in multi-storey residential buildings of Bangladesh using recycled plastic waste insulation 基于仿真的孟加拉多层住宅热桥减热分析——利用再生塑料废保温材料
Q1 Chemical Engineering Pub Date : 2025-10-11 DOI: 10.1016/j.ijft.2025.101452
Rid - Wanul Alam Likhon, Md. Abdul Hakim Khan
In tropical climates such as Bangladesh, thermal bridging through wall-floor junctions increases indoor cooling demands and exacerbates energy shortages. Concurrently, uncontrolled plastic waste generation has become a major environmental issue. This study explores the use of post-consumer plastic waste in concrete slabs as a cost-effective and sustainable thermal insulation strategy. A 3D finite element model was developed to simulate steady-state heat transfer in a typical two-story residential building under Bangladeshi climatic conditions. Five common brick types were evaluated, with plastic content ranging from 10 % to 30 % by volume. Simulations revealed that incorporating 30 % plastic waste into Concrete Hollow Block (CHB) walls reduced heat flux by up to 29.1 %, significantly improving thermal stability. Hollow bricks and blocks demonstrated enhanced insulation properties due to air cavities, while Standard Red Bricks showed the highest heat loss. These findings indicate that integrating locally sourced plastic waste into concrete slabs can simultaneously reduce operational energy demand and divert non-biodegradable waste from landfills. The proposed method supports near-zero energy building (nZEB) objectives and provides a scalable, climate-adaptive solution for sustainable urban housing in densely populated regions like Dhaka.
在孟加拉国等热带气候地区,通过墙-地板连接处的热桥增加了室内冷却需求,加剧了能源短缺。与此同时,不受控制的塑料废物产生已成为一个主要的环境问题。本研究探讨了在混凝土板中使用消费后塑料废物作为一种具有成本效益和可持续的隔热策略。建立了三维有限元模型,模拟了孟加拉国典型两层住宅建筑在气候条件下的稳态传热。评估了五种常见的砖类型,塑料含量从10%到30%不等。模拟结果显示,在混凝土空心砌块(CHB)墙体中加入30%的塑料废物可减少高达29.1%的热流密度,显著提高热稳定性。空心砖和砌块由于空腔而表现出增强的隔热性能,而标准红砖表现出最高的热损失。这些发现表明,将当地的塑料废物整合到混凝土板中,可以同时减少运营能源需求,并转移垃圾填埋场的不可生物降解废物。提出的方法支持近零能耗建筑(nZEB)目标,并为达卡等人口稠密地区的可持续城市住房提供可扩展的气候适应解决方案。
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引用次数: 0
Comparative experimental evaluation of wood charcoal and cocopeat fillers in a pyramid-shaped solar still for enhanced desalination performance 金字塔形太阳能蒸馏器中木质炭和椰子填料增强海水淡化性能的对比实验评价
Q1 Chemical Engineering Pub Date : 2025-10-10 DOI: 10.1016/j.ijft.2025.101447
Arunkumar H. S , Avinash K. Hegde , K.Vasudeva Karanth , Younes Amini , Madhwesh N
Freshwater scarcity remains a persistent challenge in arid and coastal regions, necessitating cost-effective and energy-efficient desalination solutions. This study presents an experimental performance evaluation of a pyramid-shaped solar still (PSS) enhanced with porous fillers cocopeat and wood charcoal to improve distillate productivity. The PSS, fabricated with a black-coated stainless-steel basin and insulated with thermocol and foam, was operated using both tap and saline water under coastal climatic conditions. Incorporation of fillers significantly improved the thermal regime and overall yield compared to the base model. The charcoal–saline water configuration exhibited the best performance, achieving a daily distillate yield of 950 mL and a thermal efficiency of 23.17 %, representing a 34 % enhancement over the base saline-water case (17.3 %). Cocopeat improved heat retention but resulted in slower evaporation and lower yield. The enhanced absorptivity of charcoal promoted higher basin water temperature and better energy utilization. All configurations produced very soft distillate (10–20 mg/L as CaCO₃), meeting WHO potable water standards. The findings demonstrate that low-cost filler materials, particularly wood charcoal, can significantly augment the thermal and distillation efficiency of PSS, highlighting their suitability for decentralized desalination in resource-constrained regions.
淡水短缺仍然是干旱和沿海地区的一个持续挑战,因此需要具有成本效益和节能的海水淡化解决方案。本研究提出了一个金字塔形太阳能蒸馏器(PSS)的实验性能评估与多孔填料椰油和木材木炭增强,以提高蒸馏效率。PSS由黑色涂层不锈钢盆制成,并与温冷和泡沫绝缘,在沿海气候条件下使用自来水和盐水进行操作。与基本模型相比,填料的加入显著改善了热状态和总体产量。炭-盐水配置表现出最好的性能,实现了每天950 mL的馏分产率和23.17%的热效率,比基础盐水情况(17.3%)提高了34%。cocopin提高了保热性,但导致蒸发速度变慢,产量降低。木炭吸收率的提高提高了流域水温,提高了能源利用率。所有配置都会产生非常软的馏分(10 - 20mg /L的碳酸钙₃),符合世界卫生组织的饮用水标准。研究结果表明,低成本的填充材料,特别是木质木炭,可以显著提高PSS的热效率和蒸馏效率,突出了它们在资源受限地区分散脱盐的适用性。
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引用次数: 0
Thermo-fluid analysis of a spring fin turbulator placement on the absorber plate of the solar air heater 安装在太阳能空气加热器吸收板上的弹簧翅片紊流器的热流体分析
Q1 Chemical Engineering Pub Date : 2025-10-10 DOI: 10.1016/j.ijft.2025.101444
Subash Acharya, K.Vasudeva Karanth, Shiva Kumar, Arunkumar H․ S․
This study examines the thermal performance of a solar air heater integrated with spring-shaped fins beneath the absorber plate, considering variations in both longitudinal and transverse pitch. The simulations are performed in ANSYS Workbench using the RNG k-ε turbulence model with enhanced wall treatment, accounting for thermal effects and viscous heating. The assumptions considered include steady, turbulent, fully developed flow at the test section inlet, thermally developing conditions, homogeneous and isotropic walls, and no-slip boundary conditions on all fluid-contact surfaces. The fins promote turbulence within the duct, improving convective heat transfer without significantly obstructing the flow. Results show that the Nusselt number increases with a higher number of springs, achieved by reducing either longitudinal or transverse pitch. The effective thermo-hydraulic efficiency rises initially but decreases at higher flow resistance. For varying longitudinal pitch ratios, a pitch of 0.08 produces the highest Nusselt number, while a pitch of 0.16 delivers the maximum thermo-hydraulic enhancement factor (THEF) when two springs are arranged across the width, consistent across the studied flow conditions. Correlations between spring pitch ratios, Nusselt number, and friction factor are developed through regression analysis, exhibiting a maximum deviation of ±10 % from numerical results.
本研究考察了在吸收板下方集成了弹簧形翅片的太阳能空气加热器的热性能,考虑了纵向和横向节距的变化。在ANSYS Workbench中使用RNG k-ε湍流模型进行了模拟,并对壁面进行了强化处理,考虑了热效应和粘性加热。所考虑的假设包括测试段入口处的稳定、湍流、充分发展的流动、热发展条件、均匀和各向同性的壁面以及所有流体接触面上的无滑移边界条件。翅片促进了管道内的湍流,在不显著阻碍流动的情况下改善对流换热。结果表明,通过减小纵向节距或横向节距,努塞尔数随着弹簧数量的增加而增加。当流动阻力增大时,有效热压效率先升高,后降低。对于不同的纵向节距比,当两个弹簧沿宽度排列时,节距为0.08产生最高的努塞尔数,而当两个弹簧沿宽度排列时,节距为0.16提供最大的热水力增强因子(THEF),在研究的流动条件下是一致的。通过回归分析得出了弹簧节距比、努塞尔数和摩擦系数之间的相关性,与数值结果的最大偏差为±10%。
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引用次数: 0
Integrating machine learning and CFD for enhanced trailing edge serration design on a NACA 0012 wind turbine blade 集成了机器学习和CFD的NACA 0012风力涡轮机叶片后缘锯齿形设计
Q1 Chemical Engineering Pub Date : 2025-10-09 DOI: 10.1016/j.ijft.2025.101446
Marwa Khaleel Rashid , Khuder N. Abed , Mohammed Alharbi , Mohammed Waleed Muayad , Tarik Alkharusi , Arman Ameen
This study combines machine learning (ML) techniques with computational fluid dynamics (CFD) simulations using ANSYS Fluent to investigate the impact of different trailing-edge serration designs on a NACA 0012 airfoil, a commonly used design in wind turbine blades. Building on a fundamental CFD analysis, ML-driven data augmentation—including synthetic data creation, geometric transformations, and noise sensitivity analyses—is employed to enhance and accelerate the design process. The CFD simulations utilize the k-omega SST turbulence model to calculate the lift coefficient (CL) and drag coefficient (CD) over a range of angles of attack (0°–20°). The ML framework evaluates the model's robustness and prediction accuracy under various noise levels and augmented training datasets. Results indicate that the rounded serration design achieves the best lift-to-drag ratio (CL/CD), with approximately a 15 % improvement over the baseline at an angle of attack (α) of 12° In contrast, sharp-edged serrations produce more lift at middle angles but generate increased drag at higher angles. Using hyperparameter-tuned ML models—such as Ridge regression, Random Forest, and a feedforward neural network—improves predictive accuracy and facilitates exploration of the complex design space. This combination of CFD and ML provides a robust method for optimizing wind turbine blade performance, striking a balance between aerodynamic efficiency and computational cost. Unlike previous studies that relied solely on CFD or experiments, this research integrates machine learning with CFD. This dual approach aims not only to analyze the serration geometry but also to optimize it effectively through alternative models and data augmentation. By merging fluid dynamics and machine learning, this approach transforms the design process from trial and error to a data-driven, predictive methodology, marking a significant advance in the aerodynamic design of wind turbine blades.
本研究将机器学习(ML)技术与计算流体动力学(CFD)模拟相结合,利用ANSYS Fluent研究了不同后缘锯齿设计对NACA 0012翼型的影响,NACA 0012是风力涡轮机叶片中常用的设计。基于基本的CFD分析,机器学习驱动的数据增强(包括合成数据创建、几何变换和噪声灵敏度分析)可用于增强和加速设计过程。CFD模拟利用k-omega SST湍流模型计算了迎角范围(0°-20°)内的升力系数(CL)和阻力系数(CD)。机器学习框架在各种噪声水平和增强训练数据集下评估模型的鲁棒性和预测精度。结果表明,圆形锯齿设计获得了最佳的升阻比(CL/CD),在攻角(α)为12°时,比基线提高了约15%。相比之下,锋利的锯齿在中角时产生更多的升力,但在高角时产生更多的阻力。使用超参数调优的机器学习模型(如Ridge回归、随机森林和前馈神经网络)可以提高预测精度,并促进对复杂设计空间的探索。这种CFD和ML的结合为优化风力涡轮机叶片性能提供了一种强大的方法,在气动效率和计算成本之间取得了平衡。与以往仅依靠CFD或实验的研究不同,本研究将机器学习与CFD相结合。这种双重方法不仅旨在分析锯齿形几何,而且还通过替代模型和数据增强有效地优化它。通过结合流体动力学和机器学习,这种方法将设计过程从试错转变为数据驱动的预测方法,标志着风力涡轮机叶片气动设计的重大进步。
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引用次数: 0
Dynamic modelling with optimal integration of solar PV, hydro power & wind turbine hybrid system for enhanced power quality 动态建模,优化太阳能光伏、水力发电和风力发电混合系统的集成,以提高电能质量
Q1 Chemical Engineering Pub Date : 2025-10-09 DOI: 10.1016/j.ijft.2025.101445
Akhil Nigam , Kamal Kant Sharma , Anum Shafiq , Moh Yaseen , Tabassum Naz Sindhu , Muhammad Ahmad Iqbal
Due to the presence of alternate energy sources such as solar PV cell, wind, hydro etc. it is the ability of the power system to attain feasible operation and maintain the reliability of the system. These renewable energy sources provide many benefits with advanced technologies for overcoming pollution problems and maintenance costs. Since the energy demands increase then hybrid energy systems have been introduced for continuous power supply between the grid and consumer. These local non-conventional energy sources are properly used by using the concept of micro grid so this problem can be optimized even in remote area applications. Through such hybrid energy system, it provides improves reliability and power quality with better utilization efficiency. This paper emphasizes the interfacing of various energy sources to make hybrid power systems and simulation study for enhancing stability, power quality in order to optimize energy sources.
由于存在替代能源,如太阳能光伏电池,风能,水力发电等,它是电力系统实现可行运行和保持系统可靠性的能力。这些可再生能源提供了许多好处与先进的技术,克服污染问题和维护成本。由于能源需求的增加,混合能源系统已被引入电网和消费者之间的连续供电。通过使用微电网的概念,这些当地的非常规能源得到了适当的利用,因此即使在偏远地区的应用也可以优化这个问题。通过这种混合能源系统,提高了可靠性和电能质量,提高了利用效率。本文强调了各种能源的接口,使混合电力系统和仿真研究,以提高稳定性,电能质量,以优化能源。
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引用次数: 0
Research on peak-valley optimization of distributed photovoltaic energy storage systems based on an improved particle swarm algorithm 基于改进粒子群算法的分布式光伏储能系统峰谷优化研究
Q1 Chemical Engineering Pub Date : 2025-10-06 DOI: 10.1016/j.ijft.2025.101443
Yagang An, Bo Feng, Mengyu Li, Xuezhe Gao, Hongxi Wang, Ji Li
This paper proposes an improved particle swarm optimization (PSO) algorithm for optimizing the coordinated operation of energy storage systems and photovoltaic (PV) systems to address load fluctuations caused by distributed PV grid connection. First, the impact of PV grid connection on the power system is assessed, and the improved PSO algorithm is used to regulate the charging and discharging power of the energy storage system to balance supply and demand, reduce load fluctuations, and enhance peak shaving efficiency. Experimental results demonstrate that the proposed method effectively smooths the load curve, reducing the peak-to-valley difference by 23 %, improving the charging and discharging efficiency of energy storage devices by 18 %, and lowering system operating costs by 12 %. It accurately determines energy storage charging and discharging strategies and effectively controls grid load.
针对分布式光伏并网带来的负荷波动问题,提出了一种改进的粒子群优化算法(PSO)来优化储能系统与光伏系统的协同运行。首先,评估光伏并网对电力系统的影响,利用改进的粒子群算法调节储能系统的充放电功率,平衡供需,降低负荷波动,提高调峰效率。实验结果表明,该方法有效地平滑了负载曲线,将峰谷差降低了23%,将储能装置的充放电效率提高了18%,将系统运行成本降低了12%。准确确定储能充放电策略,有效控制电网负荷。
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引用次数: 0
Regression analysis to predict the performance of acetone and SWCNT nano fluids in oscillating heat pipe 丙酮和swcnts纳米流体在振荡热管中的性能预测的回归分析
Q1 Chemical Engineering Pub Date : 2025-10-04 DOI: 10.1016/j.ijft.2025.101442
Parashuram A Kutakanakeri , K.Rama Narasimha , Roopa D , Vijay Kumar S , Praveen Kumar M V , Vanitha K , C.Durga Prasad , Nagabhushana Pulla , Adem Abdirkadir Aden
This work evaluates the heat transfer capabilities of a closed-loop oscillating heat pipe (OHP) filled with acetone and SWCNT during phase change. The OHP, with four turns, was tested for its thermal performance. The study varied the acetone filler ratio from 50 % to 80 % in 10 % steps, using a copper tube with an inner diameter of 1.7 mm. Heat inputs ranging from 25 W to 40 W in 5 W steps were tested. Results show that a 70 % filler ratio of acetone and SWCNT improves thermal performance. This setup lowers the average temperature difference between the condenser and evaporator by 2.8 %, increases the heat transfer coefficient by 13.69 % and 18.6 %, and reduces thermal resistance by 4.6 % and 5.4 %, respectively. With a p-value of 0.05, a mathematical model predicting heat transfer performance was developed, indicating that the independent variables are statistically significant. The experimental value differs from the predicted value by <10 %.
本研究评估了一个充满丙酮和swcnts的闭环振荡热管(OHP)在相变过程中的传热能力。对四圈OHP进行了热性能测试。本研究采用内径为1.7 mm的铜管,分10步将丙酮填充率从50%变化到80%。热输入范围从25w到40w,以5w的步骤进行测试。结果表明,70%的丙酮和swcnts填充率提高了热工性能。冷凝器和蒸发器的平均温差降低了2.8%,换热系数分别提高了13.69%和18.6%,热阻分别降低了4.6%和5.4%。在p值为0.05的情况下,建立了预测传热性能的数学模型,表明自变量具有统计学意义。实验值与预测值相差10%。
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引用次数: 0
AI-assisted CFD optimisation of multi-element wing angle of attack for enhanced formula SAE aerodynamic performance 基于ai辅助的多单元翼攻角CFD优化,提高公式SAE气动性能
Q1 Chemical Engineering Pub Date : 2025-10-03 DOI: 10.1016/j.ijft.2025.101440
Chakrit Suvanjumrat , Sirawit Namchanthra , Tinnapob Phengpom , Jetsadaporn Priyadumkol , Watcharapong Chookaew , Sarawoot Watechagit , Sherman C.P. Cheung , Machimontorn Promtong
This study presents a multi-level aerodynamic optimisation framework that integrates Computational Fluid Dynamics (CFD) with Artificial Intelligence (AI) techniques to enhance the performance of Formula SAE vehicles. Unlike conventional CFD or empirical approaches, the proposed framework employs a hybrid Genetic Algorithm–Artificial Neural Network (GA–ANN) model to optimise design parameters with greater accuracy and efficiency. Initial investigations refined the angles of attack (AoA) and airfoil geometries to maximise downforce while reducing drag and energy consumption. Two-dimensional CFD simulations established the baseline aerodynamic characteristics, which were subsequently extended to full three-dimensional analyses. Among turbulence models, the Menter k–ω SST demonstrated superior predictive capability compared to the standard k–ε, with discrepancies in drag and downforce below 15 %. The MSHD and Selig 1223 airfoils emerged as the most aerodynamically efficient candidates. Systematic AoA adjustments from 4.5°, 28.0°, and 56.0° to 5.5°, 33.0°, and 59.5° for the front wing, and from 9.5° and 40.0° to 12.2° and 41.9° for the rear wing produced CFD predictions validated within a 5 % error margin. The GA–ANN optimisation further enhanced aerodynamic performance, yielding a 14.8 % increase in front-wing downforce and a 28.4 % increase in rear-wing downforce, alongside reduced drag and improved energy efficiency. These findings demonstrate the potential of AI-assisted CFD optimisation to bridge high-fidelity simulations with tangible performance gains, offering a promising pathway for hybrid airfoil design and active control strategies in high-performance automotive applications.
本研究提出了一个多层次的空气动力学优化框架,该框架将计算流体动力学(CFD)与人工智能(AI)技术相结合,以提高SAE方程式赛车的性能。与传统的CFD或经验方法不同,该框架采用遗传算法-人工神经网络(GA-ANN)混合模型,以更高的精度和效率优化设计参数。初步调查细化迎角(AoA)和翼型几何形状,以最大限度地提高下压力,同时减少阻力和能源消耗。二维CFD模拟建立了基准气动特性,随后扩展到全三维分析。在湍流模型中,Menter k -ω海表温度的预测能力优于标准k -ε,阻力和下压力的差异低于15%。MSHD和Selig 1223翼型成为空气动力学效率最高的候选机型。前翼的AoA从4.5°、28.0°和56.0°调整到5.5°、33.0°和59.5°,后翼的AoA从9.5°和40.0°调整到12.2°和41.9°,得出的CFD预测误差在5%以内。GA-ANN优化进一步增强了气动性能,前翼下压力增加了14.8%,后翼下压力增加了28.4%,同时减少了阻力,提高了能效。这些发现证明了人工智能辅助CFD优化在高保真仿真与实际性能提升之间的桥梁潜力,为高性能汽车应用中的混合动力翼型设计和主动控制策略提供了一条有希望的途径。
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引用次数: 0
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International Journal of Thermofluids
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