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Effect of leading-edge tubercles on the flow over low-aspect-ratio wings at low Reynolds number 前缘圆管对低雷诺数低展弦比机翼流动的影响
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100386

Two-dimensional time-resolved particle image velocimetry (TR-PIV) and stereographic particle image velocimetry (SPIV) techniques were used to investigate the effect of leading-edge tubercles on the flow over low-aspect-ratio wing models. The angle of attack is fixed at 10°, and the Reynolds number based on chord length is 5.8 × 103. It is shown that the leading-edge tubercles can effectively mitigate flow separation in the model and also reduce the contribution of wake vortex to the fluctuating energy of flow. Counter-rotating vortex pairs (CVPs) initiated from the peak of leading-edge tubercles can promote nearby momentum exchange, enhance mixing of the flow and increase the energy contained in the boundary layer, which results in resisting the larger adverse pressure gradient. Therefore, it is concluded that CVPs play an important role in mitigating the flow separation for wings with leading-edge tubercles.

采用二维时间分辨粒子图像测速技术(TR-PIV)和立体粒子图像测速技术(SPIV)研究了前缘结节对低展弦比机翼模型流动的影响。攻角固定为10°,基于弦长的雷诺数为5.8 × 103。结果表明,在模型中,前缘结节可以有效地缓解流动分离,并降低尾流涡对流动波动能的贡献。由前缘结节峰发起的反向旋转涡对(CVPs)可以促进附近动量交换,增强流动混合,增加边界层所含能量,从而抵抗较大的逆压梯度。综上所述,CVPs在缓解前缘有小结节的机翼流动分离中发挥了重要作用。
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引用次数: 1
Artificial neural network-based subgrid-scale models for LES of compressible turbulent channel flow 基于人工神经网络的可压缩湍流通道LES亚网格模型
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100399

Fully connected neural networks (FCNNs) have been developed for the closure of subgrid-scale (SGS) stress and SGS heat flux in large-eddy simulations of compressible turbulent channel flow. The FCNN-based SGS model trained using data with Mach number Ma=3.0 and Reynolds number Re=3000 was applied to situations with different Mach numbers and Reynolds numbers. The input variables of the neural network model were the filtered velocity gradients and temperature gradients at a single spatial grid point. The a priori test showed that the FCNN model had a correlation coefficient larger than 0.91 and a relative error smaller than 0.43, with much better reconstructions of SGS unclosed terms than the dynamic Smagorinsky model (DSM). In a posteriori test, the behavior of the FCNN model was marginally better than that of the DSM in predicting the mean velocity profiles, mean temperature profiles, turbulent intensities, total Reynolds stress, total Reynolds heat flux, and mean SGS flux of kinetic energy, and outperformed the Smagorinsky model.

全连接神经网络(FCNNs)被开发用于闭合亚网格尺度(SGS)应力和SGS热流在可压缩湍流通道大涡模拟中的应用。利用马赫数Ma=3.0、雷诺数Re=3000的数据训练的基于fcnn的SGS模型,应用于不同马赫数和雷诺数的情况。神经网络模型的输入变量为过滤后的单个空间网格点的速度梯度和温度梯度。先验检验表明,FCNN模型的相关系数大于0.91,相对误差小于0.43,对SGS未闭项的重建效果明显优于动态Smagorinsky模型(DSM)。后验检验表明,FCNN模型在预测平均速度分布、平均温度分布、湍流强度、总雷诺应力、总雷诺热流密度和平均SGS动能通量方面略优于DSM模型,且优于Smagorinsky模型。
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引用次数: 2
Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow 基于人工神经网络的层流-湍流过渡流单方程模拟
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100387

A mapping function between the Reynolds-averaged Navier-Stokes mean flow variables and transition intermittency factor is constructed by fully connected artificial neural network (ANN), which replaces the governing equation of the intermittency factor in transition-predictive Spalart-Allmaras (SA)-γ model. By taking SA-γ model as the benchmark, the present ANN model is trained at two airfoils with various angles of attack, Mach numbers and Reynolds numbers, and tested with unseen airfoils in different flow states. The a posteriori tests manifest that the mean pressure coefficient, skin friction coefficient, size of laminar separation bubble, mean streamwise velocity, Reynolds shear stress and lift/drag/moment coefficient from the present two-way coupling ANN model almost coincide with those from the benchmark SA-γ model. Furthermore, the ANN model proves to exhibit a higher calculation efficiency and better convergence quality than traditional SA-γ model.

用全连通人工神经网络(ANN)代替了过渡预测Spalart-Allmaras(SA)-γ模型中间歇因子的控制方程,构造了雷诺平均Navier-Stokes平均流量变量与过渡间歇因子之间的映射函数。以SA-γ模型为基准,在不同迎角、马赫数和雷诺数的两种翼型上对现有的人工神经网络模型进行了训练,并在不同流动状态下对看不见的翼型进行了测试。后验结果表明,该双向耦合ANN模型的平均压力系数、表面摩擦系数、层流分离气泡尺寸、平均流向速度、雷诺剪切应力和升力/阻力/力矩系数与基准SA-γ模型的结果基本一致。此外,与传统的SA-γ模型相比,该模型具有更高的计算效率和更好的收敛质量。
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引用次数: 2
New algorithm of shape-finding of suspension bridge with spatial cables 具有空间索的悬索桥寻形新算法
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2023-01-01 DOI: 10.1016/j.taml.2022.100402

A new algorithm is proposed to solve the problems of shape-finding of suspension bridge with spatial cables what include tedious iteration, slow convergence speed and even no convergent under some circumstances. In this paper, the stress analysis of the main cable is carried out, and the relationship between the slope change and the coordinate change is found. This paper also discussed how to find the minimum slope point of symmetrical or asymmetric main cable, and the deformation compatibility equation is established and solved to obtain the shape of main cable. The algorithm in this paper can ensure the convergence of the solution for the suspension bridge with spatial cables. The calculation accuracy is high through the demonstration of the calculation examples.

针对具有空间索的悬索桥寻形算法迭代繁琐、收敛速度慢,有时甚至不收敛的问题,提出了一种新的寻形算法。本文对主缆进行了应力分析,找到了斜率变化与坐标变化的关系。讨论了对称或非对称主缆的最小斜率点的求解,建立并求解了变形协调方程,得到了主缆的形状。本文所提出的算法能够保证具有空间索的悬索桥解的收敛性。通过算例验证,计算精度较高。
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引用次数: 0
Predicting solutions of the Lotka‐Volterra equation using hybrid deep network 利用混合深度网络预测Lotka‐Volterra方程的解
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100384

Prediction of Lotka-Volterra equations has always been a complex problem due to their dynamic properties. In this paper, we present an algorithm for predicting the Lotka-Volterra equation and investigate the prediction for both the original system and the system driven by noise. This demonstrates that deep learning can be applied in dynamics of population. This is the first study that uses deep learning algorithms to predict Lotka-Volterra equations. Several numerical examples are presented to illustrate the performances of the proposed algorithm, including Predator nonlinear breeding and prey competition systems, one prey and two predator competition systems, and their respective systems. All the results suggest that the proposed algorithm is feasible and effective for predicting Lotka-Volterra equations. Furthermore, the influence of the optimizer on the algorithm is discussed in detail. These results indicate that the performance of the machine learning technique can be improved by constructing the neural networks appropriately.

由于Lotka-Volterra方程的动力学性质,其预测一直是一个复杂的问题。本文提出了一种预测Lotka-Volterra方程的算法,并对原始系统和受噪声驱动的系统进行了预测。这表明深度学习可以应用于人口动态。这是第一个使用深度学习算法来预测Lotka-Volterra方程的研究。本文给出了几个数值例子来说明该算法的性能,包括捕食者非线性繁殖和猎物竞争系统、一个猎物和两个捕食者竞争系统以及它们各自的系统。结果表明,该算法对Lotka-Volterra方程的预测是可行和有效的。此外,还详细讨论了优化器对算法的影响。这些结果表明,通过适当构造神经网络可以提高机器学习技术的性能。
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引用次数: 6
Influence of physical parameters on the collapse of a spherical bubble 物理参数对球形气泡崩塌的影响
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100369
Bo-Hua Sun

This paper examines the influence of physical parameters on the collapse dynamics of a spherical bubble filled with diatomic gas (κ=7/5). The problem is formulated by the Rayleigh–Plesset dynamical equation, whose numerical solutions are carried out by Maple. Our studies show that each physical parameter affects the bubble collapse dynamics in different degree, which reveals that bubble collapse dynamics must considers all the parameters including liquid viscosity, surface tension, etc, else the outcome cannot be trusted.

本文研究了物理参数对充满双原子气体(κ=7/5)的球形气泡坍缩动力学的影响。该问题由Rayleigh-Plesset动力学方程表示,其数值解由Maple实现。我们的研究表明,各个物理参数对气泡崩塌动力学的影响程度不同,这表明气泡崩塌动力学必须考虑液体粘度、表面张力等所有参数,否则结果不可信。
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引用次数: 0
Sedimentation motion of sand particles in moving water (I): The resistance on a small sphere moving in non-uniform flow 砂粒在流动水中的沉降运动(一):在非均匀流动中运动的小球体上的阻力
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100392

In hydraulics, when we deal with the problem of sand particles moving relative to the surrounding water, Stokes’ formula of resistance has usually been used to render the velocity of sedimentation of the particles. But such an approach has not been proved rigorously, and its accuracy must be carefully considered. In this paper, we discuss the problem of a sphere moving in a non-uniform flow field, on the basis of the fundamental theory of hydrodynamics. We introduce two assumptions: i) the diameter of the sphere is much smaller than the linear dimension of the flow field, and ii) the velocity of the sphere relative to the surrounding water is very small. Using these two assumptions, we solve the linearized Navier-Stokes equations and equations of continuity by the method of Laplace transform, and finally we obtain a formula for the resistance acting on a sphere moving in a non-uniform flow field.

在水力学中,当我们处理砂粒相对于周围水运动的问题时,通常使用斯托克斯阻力公式来表示砂粒的沉降速度。但这种方法还没有得到严格的证明,必须仔细考虑其准确性。本文从流体力学的基本理论出发,讨论了球面在非均匀流场中的运动问题。我们引入了两个假设:i)球体的直径远小于流场的线性尺寸,ii)球体相对于周围水的速度非常小。利用这两个假设,用拉普拉斯变换的方法求解了线性化的Navier-Stokes方程和连续性方程,最后得到了非均匀流场中运动球体的阻力公式。
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引用次数: 3
Numerical simulation of laser ultrasonic detection of the surface microdefects on laser powder bed fusion additive manufactured 316L stainless steel 激光超声检测316L不锈钢表面微缺陷的数值模拟
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100398

A numerical model is presented in this article to investigate the interactions between laser generated ultrasonic and the microdefects (0.01 to 0.1 mm), which are on the surface of the laser powder bed fusion additive manufactured 316L stainless steel. Firstly, the influence of the transient sound field and detection positions on Rayleigh wave signals are investigated. The interactions between the varied microdefects and the laser ultrasonic are studied. It is shown that arrival time of reflected Rayleigh (RR) waves wave is only related to the location of defects. The depth can be checked from the feature point Q, the displacement amplitude and time delay of converted transverse (RS) wave, while the width information can be evaluated from the RS wave time delay. With the aid of fitting curves, it is found to be linearly related. This simulation study provides a theoretical basis for quantitative detection of surface microdefects of additive manufactured 316L stainless steel components.

本文建立了激光超声与316L不锈钢粉末床熔合添加剂表面微缺陷(0.01 ~ 0.1 mm)相互作用的数值模型。首先,研究了瞬态声场和探测位置对瑞利波信号的影响。研究了不同微缺陷与激光超声的相互作用。结果表明,反射瑞利波的到达时间只与缺陷的位置有关。从特征点Q、转换横波的位移幅值和时间延迟可以检测深度,从转换横波的时间延迟可以评估宽度信息。借助拟合曲线,发现两者是线性相关的。该仿真研究为增材制造316L不锈钢构件表面微缺陷的定量检测提供了理论依据。
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引用次数: 2
Elastoplastic constitutive modeling under the complex loading driven by GRU and small-amount data 基于GRU和少量数据驱动的复杂载荷下弹塑性本构建模
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100363

In this paper, a data-driven method to model the three-dimensional engineering structure under the cyclic load with the one-dimensional stress-strain data is proposed. In this method, one-dimensional stress-strain data obtained under uniaxial load and different loading history is learned offline by gate recurrent unit (GRU) network. The learned constitutive model is embedded into the general finite element framework through data expansion from one dimension to three dimensions, which can perform stress updates under the three-dimensional setting. The proposed method is then adopted to drive numerical solutions of boundary value problems for engineering structures. Compared with direct numerical simulations using the J2 plasticity model, the stress-strain response of beam structure with elastoplastic materials under forward loading, reverse loading and cyclic loading were predicted accurately. Loading path dependent response of structure was captured and the effectiveness of the proposed method is verified. The shortcomings of the proposed method are also discussed.

本文提出了一种利用一维应力应变数据对循环荷载作用下的三维工程结构进行建模的数据驱动方法。该方法通过栅极循环单元(GRU)网络离线学习单轴加载和不同加载历史下的一维应力应变数据。通过数据从一维扩展到三维,将学习到的本构模型嵌入到一般有限元框架中,可以在三维环境下进行应力更新。将该方法应用于工程结构边值问题的数值求解。与采用J2塑性模型的直接数值模拟结果相比,准确地预测了含弹塑性材料的梁结构在正向加载、反向加载和循环加载下的应力应变响应。捕获了结构的加载路径相关响应,验证了该方法的有效性。文中还讨论了该方法的不足之处。
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引用次数: 4
Shapes of the fastest fish and optimal underwater and floating hulls 形状最快的鱼和最佳的水下和浮动船体
IF 3.4 3区 工程技术 Q2 MECHANICS Pub Date : 2022-11-01 DOI: 10.1016/j.taml.2022.100378

A streamlined shape of the best swimmers removes the boundary-layer separation and ensures a laminar flow pattern. The fastest fish have a very sharp convex nose (rostrum), the purpose of which remains unclear. The bodies of revolution similar to their shapes are analyzed in steady underwater and floating motion. The sources and sinks were located on the axis of symmetry and above the water surface to estimate the pressure on the body and the vertical velocities on the water surface. It was shown that the flow patterns on a special shaped body with concave nose has no stagnation points and ensure small values of the water surface elevation. These fact allow diminishing the maximum pressure on the surface and wave drag. Special shapes with the sharp concave nose and negative pressure gradients on their surface could be parts of the low drag underwater and floating hulls.

最好的游泳者的流线型形状消除了边界层分离,并确保层流模式。最快的鱼有一个非常尖锐的凸鼻子(喙),其目的尚不清楚。在稳定的水下和漂浮运动中分析了与其形状相似的旋转体。源和汇位于对称轴和水面上方,以估计身体的压力和水面上的垂直速度。结果表明,在特殊形状的凹鼻体上,流型无滞止点,水面高程较小。这些事实可以减小水面上的最大压力和波浪阻力。具有尖锐凹鼻和表面负压梯度的特殊形状可能是低阻力水下和浮动船体的一部分。
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引用次数: 1
期刊
Theoretical and Applied Mechanics Letters
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