卡松纳米流体随机非稳态混合对流的两阶段可靠计算方案

IF 1.7 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yasir Nawaz, Muhammad Shoaib Arif, Amna Nazeer, Javeria Nawaz Abbasi, Kamaleldin Abodayeh
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引用次数: 0

摘要

由于采用了随机模拟,研究人员可以在计算流体动力学(CFD)中加入不确定性因素,而这些不确定性因素超出了数值离散化造成的误差。本研究通过提供随机模拟与不可压缩流数值求解相结合的实例,证实了当前随机建模工具的有效性。本研究开发了一种用于求解确定性和随机模型的数值技术。我们的方法采用欧拉-Maruyama 方法进行随机建模,代表了三阶显隐方案的随机版本。对于确定性模型,该方案具有三阶精度。所构建方案的一致性和稳定性是在均方意义上提供的。该方案是建立在两个时间层次上的预测-校正类型。此外,在化学反应的影响下,给出了导热系数可变的 Casson 纳米流体流动的数学模型。通过适当的变换,将偏微分方程(PDE)浓缩为无量纲方程。该方案适用于无量纲流动问题的确定性和随机模型。等值线图显示了速度剖面的确定性和随机性行为。结果表明,热混合对流参数值的增加会增强速度剖面。本文介绍了在随机计算流体动力学(SCFD)方面取得的进展,并重点介绍了我们发现的与能量相关的方面。我们的计算方法和随机建模技术为卡松纳米流体流动的能量特性,特别是热导率和化学过程的可变性提供了新的见解。我们的目标是阐明这些因素对能量动力学的复杂相互作用。本文总结了 SCFD 的最新进展。此外,它还强调了未来研究的潜在方向以及需要计算数学领域成员关注的未决问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A two-stage reliable computational scheme for stochastic unsteady mixed convection flow of Casson nanofluid

A two-stage reliable computational scheme for stochastic unsteady mixed convection flow of Casson nanofluid

Researchers can incorporate uncertainties in computational fluid dynamics (CFD) that go beyond the inaccuracies caused by numerical discretization thanks to stochastic simulations. This study confirms the validity of current stochastic modeling tools by providing examples of stochastic simulations in conjunction with numerical solutions for incompressible flows. A numerical technique for solving deterministic and stochastic models is developed in this work. Our approach employs the Euler-Maruyama method for stochastic modeling, representing a stochastic version of the third-order explicit-implicit scheme. For the deterministic model, the scheme is third-order accurate. The consistency and stability of the constructed scheme are provided in the mean square sense. The scheme is the predictor–corrector type that is built on two time levels. Moreover, a mathematical model of the Casson nanofluid flow with variable thermal conductivity is given with the effect of the chemical reaction. The appropriate transformations are used to condense the set of partial differential equations (PDEs) down to one that is dimensionless. The scheme is applied for the deterministic and stochastic models of dimensionless flow problems. The velocity profile's deterministic and stochastic behavior are shown using contour plots. Results show that growing values of the thermal mixed convection parameter enhance the velocity profile. This article presents the progress made in stochastic computational fluid dynamics (SCFD) and highlights the energy-related aspects of our discoveries. Our computational approach and stochastic modeling techniques provide new insights into the energy properties of Casson nanofluid flow, specifically regarding the variability of thermal conductivity and chemical processes. Our objective is to clarify the complex interaction of these factors on energy dynamics. This article presents a contemporary summary of the latest SCFD advancements. Additionally, it highlights potential directions for future research and unresolved issues that require attention from the members of the field of computational mathematics.

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来源期刊
International Journal for Numerical Methods in Fluids
International Journal for Numerical Methods in Fluids 物理-计算机:跨学科应用
CiteScore
3.70
自引率
5.60%
发文量
111
审稿时长
8 months
期刊介绍: The International Journal for Numerical Methods in Fluids publishes refereed papers describing significant developments in computational methods that are applicable to scientific and engineering problems in fluid mechanics, fluid dynamics, micro and bio fluidics, and fluid-structure interaction. Numerical methods for solving ancillary equations, such as transport and advection and diffusion, are also relevant. The Editors encourage contributions in the areas of multi-physics, multi-disciplinary and multi-scale problems involving fluid subsystems, verification and validation, uncertainty quantification, and model reduction. Numerical examples that illustrate the described methods or their accuracy are in general expected. Discussions of papers already in print are also considered. However, papers dealing strictly with applications of existing methods or dealing with areas of research that are not deemed to be cutting edge by the Editors will not be considered for review. The journal publishes full-length papers, which should normally be less than 25 journal pages in length. Two-part papers are discouraged unless considered necessary by the Editors.
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