论文标题
在大型复杂结构域中沉浸生物胶囊的笛卡式尾部自适应前轨求解器
A Cartesian-octree adaptive front-tracking solver for immersed biological capsules in large complex domains
论文作者
论文摘要
我们提出了一个开源的自适应前轨求解器，用于粘性流中的生物胶囊。使用线性有限元法和抛物面拟合方法，在拉格朗日三角测量上解决了膜弹性和弯曲力。使用开源平台basilisk在OCTREE自适应网格上求解流体流。 Lagrangian和Eulerian网格通过佩皮样的正则迪拉克三角洲函数使用沉浸式边界方法进行通信。我们通过广泛的验证证明了我们的求解器的准确性：在针对边界积分方法的条件下，以及在存在惯性的情况下与相似（但不是自适应）前轨求解器的惯性。显示了出色的定性和定量协议。然后，我们在充满挑战的极端膜变形的情况下证明了本求解器的鲁棒性，并说明了其在复杂的STL定义的几何形状中模拟载有惯性胶囊的流量的能力，为具有具有三维大型通道结构的生物工程应用打开了大门。源代码和本文中介绍的所有测试用例都是免费的。
We present an open-source adaptive front-tracking solver for biological capsules in viscous flows. The membrane elastic and bending forces are solved on a Lagrangian triangulation using a linear Finite Element Method and a paraboloid fitting method. The fluid flow is solved on an octree adaptive grid using the open-source platform Basilisk. The Lagrangian and Eulerian grids communicate using an Immersed Boundary Method by means of Peskin-like regularized Dirac delta functions. We demonstrate the accuracy of our solver with extensive validations: in Stokes conditions against the Boundary Integral Method, and in the presence of inertia against similar (but not adaptive) front-tracking solvers. Excellent qualitative and quantitative agreements are shown. We then demonstrate the robustness of the present solver in a challenging case of extreme membrane deformation, and illustrate its capability to simulate inertial capsule-laden flows in complex STL-defined geometries, opening the door for bioengineering applications featuring large three-dimensional channel structures. The source code and all the test cases presented in this paper are freely available.
