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Numerical simulations and optimization of impinging jet configuration

机译:撞机配置的数值模拟与优化

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Purpose - Numerical simulations are performed to determine the heat transfer characteristics of slot jet impingement of air on a concave surface. The purpose of this paper is to investigate the effect of protrusions on the heat transfer by placing semi-circular protrusions on the concave surface at several positions. After identifying appropriate locations where the heat transfer is a maximum, multiple protrusions are placed at desired locations on the plate. The gap ratio, curvature ratio (d/D) and the dimensions of the plate are varied so as to obtain heat transfer data. The curvature ratio is varied first, keeping the concave diameter (D) fixed followed by a fixed slot width (d). A surrogate model based on an artificial neural network is developed to determine optimum locations of the protrusions that maximize the heat transfer from the concave surface. Design/methodology/approach - The scope and objectives of the present study are two-dimensional numerical simulations of the problem by considering all the geometrical parameters (H/d, d_p, Re, θ) affecting heat transfer characteristics with the help of networking tool and numerical simulation. Development of a surrogate forward model with artificial neural networks (ANNs) with a view to explore the full parametric space. To quantitatively ascertain if protrusions hurt or help heat transfer for an impinging jet on a concave surface. Determination of the location of protrusions where higher heat transfer could be achieved by using exhaustive search with the surrogate model to replace the time consuming forward model. Findings - A single protrusion has nearly no effect on the heat transfer. For a fixed diameter of concave surface, a smaller jet possesses high turbulence kinetic energy with greater heat transfer. ANN is a powerful tool to not only predict impingement heat transfer characteristics by considering multiple parameters but also to determine the optimum configuration from many thousands of candidate solutions. A maximum increase of 8 per cent in the heat transfer is obtained by the best configuration constituting of multiple protrusions, with respect to the baseline smooth configuratioa Even this can be considered as marginal and so it can be concluded that first cut results for heat transfer for an impinging jet on a concave surface with protrusions can be obtained by geometrically modeling a much simpler plain concave surface without any significant loss of accuracy. Originality/value - The heat transfer during impingement cooling depends on various geometrical parameters but, not all the pertinent parameters have been varied comprehensively in previous studies. It is known that a rough surface may improve or degrade the amount of heat transfer depending on their geometrical dimensions of the target and the rough geometry and the flow conditions. Furthermore, to the best of authors' knowledge, scarce studies are available with inclusion of protrusions over a concave surface. The present study is devoted to development of a surrogate forward model with ANNs with a view to explore the full parametric space.
机译:目的 - 执行数值模拟以确定凹面上的空气冲击的传热特性。本文的目的是探讨突起对若干位置凹面上的半圆形突起对传热的影响。在识别热传递是最大值的适当位置之后,将多个突起放置在板上的所需位置。间隙比,曲率比(D / D)和板的尺寸变化,以获得传热数据。首先改变曲率比,保持凹入的直径(D)固定,然后固定槽宽度(D)。开发了一种基于人工神经网络的代理模型,以确定最大化从凹面的热传递的突起的最佳位置。设计/方法/方法 - 本研究的范围和目标是通过考虑在网络工具的帮助下影响传热特性的所有几何参数(H / D,D_P,RE,θ)来解决问题的二维数值模拟和数值模拟。具有人工神经网络(ANNS)的代理前瞻模型的发展,以探索全参数空间。定量地确定突起是否有突起或帮助凹陷射流在凹面上的传热。通过利用替代模型使用穷举搜索来替换前向模型的耗时来实现较高传热的突出位置的确定。调查结果 - 单突起对传热几乎没有影响。对于凹面的固定直径,较小的射流具有高湍流动能,具有更大的传热。 ANN是一种强大的工具,不仅通过考虑多个参数来预测冲击传热特性,还可以确定来自数以千计的候选解决方案的最佳配置。通过最佳的传热中的最大增加80%通过多种突起的最佳配置而获得,相对于基线平滑配置,即使这也可以被认为是边缘的,因此可以得出结论,传热的首先切割结果通过几何模拟更简单的柔性凹面而没有任何显着的精度损失,可以获得凹凸表面上的凹凸射流。原创性/值 - 冲击冷却期间的传热取决于各种几何参数,但在先前的研究中,并非所有相关参数都已全面多样化。已知粗糙表面可以根据目标的几何尺寸和粗糙的几何形状和流动条件来改善或降低传热量。此外,据作者的知识,稀缺研究可用凹面上的突起包含在凹面上。本研究致力于通过ANNS开发代理前瞻模型,以探索完整的参数空间。

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