Highlights
- •A C++ code for solving free-surface flow phenomena using the mesh-less moving particle semi-implicit (MPS) method.
- •The MPS code includes weakly-compressible and incompressible flow approaches.
- •Solid boundary walls can be modeled by particle or polygon walls.
- •Efficient parallelization using the shared memory OpenMP API.
Abstract
PolyMPS is a C++ code for numerical modeling of free-surface flow using the mesh-less moving particle semi-implicit (MPS) method from two different ways, namely, the incompressible and weakly-compressible approaches. Besides the conventional solid wall boundaries represented by discrete layers of wall and dummy (ghost) particles, boundary walls can be modeled by polygonal mesh of triangles, therefore providing flexibility to model the surface of three-dimensional complex-shaped bodies. The present code has a lightweight and efficient CPU implementation using OpenMP for research and practical applications, while providing reliable results.
Keywords
Code metadata
Tabled
1
| Current code version | 1.0 |
| Permanent link to code/repository used for this code version | https://github.com/SoftwareImpacts/SIMPAC-2022-96 |
| Permanent link to Reproducible Capsule | https://codeocean.com/capsule/5706048/tree/v1 |
| Legal Code License | MIT License |
| Code versioning system used | git |
| Software code languages, tools, and services used | C++, OpenMP |
| Compilation requirements, operating environments & dependencies | C++11, Eigen, libigl, JSON for Modern C++ |
| If available Link to developer documentation/manual | |
| Support email for questions | [email protected] |
1. Introduction
Many numerical methods have been proposed in the context of computational fluid dynamics (CFD) to predict the hydrodynamic flow behavior in hydraulic, coastal, marine, and offshore problems, and grid or mesh-based methods, such as finite difference (FD), finite volume (FV) and finite element (FE), are generally applied for such problems. However, these methods suffer from some limitations, especially for free-surface flow problems characterized by large boundary deformations, fragmentation, merging, or moving interface, and numerical treatments like free surface tracking or re-meshing techniques are required, which increase the computational complexity. Due the easy implementation and flexibility, the mesh-less particle-based methods [,
2
] provide new perspectives for the modeling of free-surface flow. In these methods, all the physical domain is represented by a set of nodal points (particles), without additional mesh constraints.In general, particle-based methods applied to free-surface flows can be categorized into two groups: weakly-compressible and incompressible projection-based methods [
[3]
]. The former such as smoothed particle hydrodynamics (SPH) [4
, 5
] or weakly-compressible moving particle semi-implicit (WC-MPS) [[6]
] methods solve an appropriate equation of state in a fully explicit form. The latter such as moving particle semi-implicit (MPS) [[7]
] or incompressible smoothed particle hydrodynamics (ISPH) [8
, 9
] methods solve a pressure Poisson equation (PPE) through an application of the projection method [10
, 11
, 12
]. The incompressible projection-based methods are generally expected to provide higher accuracy in terms of hydrodynamic pressure calculation and volume conservation. On the other hand, the explicit weakly-compressible particle methods can be more simply parallelized on graphics processing units (GPUs), a cheap and portable alternative to large and expensive high-performance computing (HPC) clusters. Moreover, changes and new formulations are generally easier implemented on weakly-compressible codes.
Fig. 1The steps to carry out a computational fluid analysis with PolyMPS.
In the conventional codes of particle-based methods, wall boundaries are modeled by discrete layers of wall particles. However, from a practical point of view, polygon wall models are more flexible to model the surface of three-dimensional (3D) arbitrary complex-shaped bodies than conventional particle-based representation.
In light of the above, PolyMPS is a lightweight and flexible code for research and practical 3D free-surface flow applications using the mesh-less moving particle semi-implicit (MPS) method with the incompressible and weakly-compressible approaches. Furthermore, solid walls can be modeled by polygonal mesh of triangles or represented by discrete layers of wall and dummy (ghost) particles.
2. Description
The moving particle semi-implicit (MPS) method was originally proposed for modeling incompressible free-surface flows [
[7]
]. The MPS represents the continuum with a set of mobile particles (without any connectivity) over which the flow governing equations are solved. The particles containing a set of continuum material properties, interact with each other within a range (compact support) controlled by a weight function (also referred to as kernel function), and move in a Lagrangian system according to the particle interactions and external forces. Fluid particles move in a natural way so that free surface, fluid–fluid interfaces or moving boundaries do not need to be explicitly tracked. Moreover, as a mesh-less method, MPS can effectively avoid the mesh tangling and consequently re-meshing process is not required. In this way, MPS is very effective for the simulations of flows involving large deformation of free surfaces, fragmentation, and merging, or involving complex shaped multi-bodies, multi-phase flows, and multi-physic problems.The pressure is typically computed using incompressible or weakly-compressible approaches. A predictor–corrector semi-implicit algorithm was originally adopted for the temporal integration of the governing equations in the incompressible MPS. Moreover, a linear pressure Poisson equation (PPE) system, formulated to keep the particle number density as a constraint condition of incompressibility, is solved to obtain the pressures [
[7]
]. On the other hand, a fully explicit algorithm is adopted in the weakly-compressible approach, and the incompressibility is weakly enforced by particle number density deviation, which provides the pressure of the particles computed by an equation of state (EOS) [[6]
].PolyMPS stands for Polygon walls in Moving Particle Semi-implicit method. The numerical algorithms for the modeling of the fluid dynamics equations are based on weakly-compressible [
6
, 13
, 14
] and incompressible [7
, 15
, 16
] MPS formulations. In addition to the particle-based wall modeling, solid boundaries can be represented by a triangulated surface using the explicitly represented polygon (ERP) wall boundary model [[17]
] with free and no-slip boundary conditions. The detection of free-surface particles can be done by: PND + number of neighbors conditions [[18]
], the neighborhood particles centroid deviation (NCPD) technique [[19]
] or a scanning region [[20]
]. To improve the numerical stabilization, particle shifting [21
, 22
] and particle collision [18
, 23
] models can be adopted. Furthermore, in PolyMPS it is possible to impose periodic boundary conditions in X, Y or Z axis.In order to achieve a better performance over interpreted languages, PolyMPS is an framework implemented in the compiled language C++. Moreover, to minimize hard dependencies on external libraries during the code compilation, only header-only libraries, namely, Eigen, libigl, and JSON for Modern C++, are required, i.e., there is no need to compile these libraries separately. PolyMPS supports parallelization with hardware using the shared memory OpenMP approach.
A set of C++ source files need to be compiled to generate the PolyMPS binary. We provide a Makefile that can be used to compile the code, and that the user can modify to suit his needs. The source files have comments describing the MPS formulations and the algorithms.
Fig. 1 illustrates the workflow to carry out a computational fluid analysis with PolyMPS.
The input files used in PolyMPS are of three types: JSON, GRID and STL. The JSON (JavaScript Object Notation) is a textual data format that is completely language independent and can easily be read or written using any standard text editor. The JSON file contains all the names of files and folders, as well as the physical and numerical parameters of the simulation case. The GRID file has a structure like XYZ files with initial coordinates of the particles and numerical and physical parameters, such as material id, initial velocity and initial pressure. The STL file contains information of the unit normal and vertices of the triangles which approximate the solid walls by a unstructured triangulated surface. The user should specify these files according to the initial conditions of the problem.
The output consist of PVD and VTU files, both XML-based format. The PVD (ParaView Data) provides pointers to the collection of VTU files. The VTU files store the physical values numerically obtained for the particles at different instants of the simulation: output00000.vtu, output00001.vtu, output00002.vtu, . These files can be loaded in the scientific visualization software ParaView.
3. Impact overview
Motivated by the challenging coupling between mesh-less particle-based along with mesh-based methods, and practical hydraulic and geotechnical engineering problems, PolyMPS has been used in several works [
14
, 24
, 25
]. Aiming to illustrate the applicability of PolyMPS, numerical simulations obtained from a variety of physical phenomena are shown in Fig. 2. In the first example, a front wave impacts on the downstream wall and generates a vertical run-up jet. In the second one, after the collapsing column of the fluid, the periodic open boundaries at the lateral limits allow the wavefront encounter that resulting in a vertical jet. Finally, the third example shows a flooded area due to a tailings dam collapse.To the best of our knowledge, there is no available a free MPS code that includes weakly-compressible and incompressible flows, as well as particle and polygon walls. In this way, PolyMPS has high potential to be used by the broad scientific community of fluid mechanics.
Fig. 2Snapshots of simulations to show the capabilities of PolyMPS. Color scale of the particles represents the velocity. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4. Future improvements of the software
As next steps and future improvements, we can mention:
- •Extension of the code to modeling non-Newtonian fluids [[23]].
- •Coupling with open-source FE solver, then providing a free numerical platform to simulate highly non-linear hydro-elastic problems.
- •Implementation of parallel solver by using a massively parallel code [[26]] and many-core combined with GPU architectures [[27]], capable of handling practical large-scale problems.
- •Boundary walls represented by a scalar field with discrete signed distance functions (SDF) [[28]], aiming to improve the efficiency in calculate the distances between the particles and mesh.
- •Accuracy improvement of the polygon wall formalism by adopting numerical boundary integrations [[29]], semi-analytical boundary integrations [[30]] or analytical volume integrations [[31]].
- •Inclusion of multi-resolution techniques (see Table 1 in [[32]]) should also be evaluated with respect to adaptivity and versatility of our code.
CRediT authorship contribution statement
Rubens Augusto Amaro Junior: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing – original draft, Visualization. Liang-Yee Cheng: Conceptualization, Methodology, Writing – review & editing, Supervision, Funding acquisition.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The authors would like to thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. We are grateful to Seiichi Koshizuka, Kazuya Shibata, Masahiro Kondo and Takuya Matsunaga for providing, together with their MPS Book [
[33]
], a basic MPS code upon which the current improvements and several features were implemented.References
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Article Info
Publication History
Published online: July 14, 2022
Accepted:
July 11,
2022
Received:
June 15,
2022
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