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A Total Lagrangian upwind Smooth Particle Hydrodynamics algorithm for large strain explicit solid dynamics

机译:大拉力显式固体动力学的总拉格朗日上风光滑粒子流体动力学算法

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In previous work (Lee et al., 2016, 2017), Lee et al. introduced a new Smooth Particle Hydrodynamics (SPH) computational framework for large strain explicit solid dynamics with special emphasis on the treatment of near incompressibility. A first order system of hyperbolic equations was presented expressed in terms of the linear momentum and the minors of the deformation, namely the deformation gradient, its co-factor and its Jacobian Taking advantage of this representation, the suppression of numerical deficiencies (e.g. spurious pressure, long term instability and/or consistency issues) was addressed through well-established stabilisation procedures. In Lee et al. (2016), the adaptation of the very efficient Jameson-Schmidt-Turkel algorithm was presented. Lee et al. (2017) introduced an adapted variationally consistent Streamline Upwind Petrov-Galerkin methodology. In this paper, we now introduce a third alternative stabilisation strategy, extremely competitive, and which does not require the selection of any user-defined artificial stabilisation parameter. Specifically, a characteristic-based Riemann solver in conjunction with a linear reconstruction procedure is used, with the aim to guarantee both consistency and conservation of the overall algorithm. We show that the proposed SPH formulation is very similar in nature to that of the upwind vertex centred Finite Volume Method presented in Aguirre et al. (2015). In order to extend the application range towards the incompressibility limit, an artificial compressibility algorithm is also developed. Finally, an extensive set of challenging numerical examples is analysed. The new SPH algorithm shows excellent behaviour in compressible, nearly incompressible and truly incompressible scenarios, yielding second order of convergence for velocities, deviatoric and volumetric components of the stress. (C) 2018 Elsevier B.V. All rights reserved.
机译:在先前的工作中(Lee et al。,2016,2017),Lee et al。介绍了一种用于大应变显式固体动力学的新的光滑粒子流体动力学(SPH)计算框架,其中特别强调了对近不可压缩性的处理。提出了用线性动量和变形的次要形式表示的一阶双曲方程组,即变形梯度,其辅因子及其雅可比矩阵。利用这种表示,可以抑制数值缺陷(例如,杂散压力) ,长期不稳定和/或一致性问题)已通过完善的稳定程序解决。在李等人。 (2016年),提出了非常有效的Jameson-Schmidt-Turkel算法的改编。 Lee等。 (2017)引入了一种适应性变化一致的Streamline Upwind Petrov-Galerkin方法。在本文中,我们现在介绍第三种替代稳定策略,该策略极具竞争力,并且不需要选择任何用户定义的人工稳定参数。具体来说,结合线性重构程序使用基于特征的黎曼求解器,以确保整体算法的一致性和节省性。我们表明,所提出的SPH公式与Aguirre等人提出的以迎风顶点为中心的有限体积法非常相似。 (2015)。为了将应用范围扩展到不可压缩极限,还开发了一种人工可压缩算法。最后,分析了大量具有挑战性的数值示例。新的SPH算法在可压缩,几乎不可压缩和真正不可压缩的场景中表现出出色的性能,从而对应力的速度,偏向和体积分量产生了二阶收敛性。 (C)2018 Elsevier B.V.保留所有权利。

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