CFD Challenge: Solutions Using an Open-Source Finite Volume Solver, OpenFOAM

Author(s):  
Joris Degroote ◽  
Patrick Segers ◽  
Jan Vierendeels

The Institute Biomedical Technology and the Department of Flow, Heat and Combustion Mechanics of Ghent University have for more than a decade worked on the development and analysis of algorithms for the simulation of computational fluid dynamics (CFD) and fluid-structure interaction (FSI). These algorithms are applied to blood flow in large arteries, among others. For this Challenge, grid generation and CFD simulations have been performed by postdoctoral fellow Joris Degroote, using an open-source finite volume flow solver, OpenFOAM.

Author(s):  
Michael Scha¨fer ◽  
Saim Yigit ◽  
Marcus Heck

The paper deals with an implicit partitioned solution approach for the numerical simulation of fluid-structure interaction problems. The solution procedure involves the finite-volume flow solver FASTEST, the finite-element structural solver FEAP, and the coupling interface MpCCI. The method is verified and validated by comparisons with benchmark results and experimental data. Investigations concerning the influence of the grid movement technique and an underrelaxation on the performance of the method are presented.


2021 ◽  
Author(s):  
Björn Windén

CFD is a useful tool for ship designers looking for accurate predictions of the fuel efficiency achieved by a certain combination of hull, propeller and Energy Saving Devices (ESDs). Such predictions are key to meeting ever-increasing demands for reductions in emissions. However, CFD simulations of propeller-hull interaction can be very costly in terms of computational effort due to the need to resolve the unsteady flow around the rotating propeller. A popular approach to alleviate this cost, that has seen much practical use in industry, is the use of body forces (momentum sources) to represent the rotating propeller. There are many ways to describe the body force distribution in the fluid for a certain propeller and there are many options for what flow solver to use. In a previous meeting of the Society, an open-source framework for easily creating coupled solvers using an arbitrary combination of models was presented. Here, one of these coupled solvers is used to predict the local flow behind the propeller, as well as integral coefficients indicating performance, of four different vessels: a bulk carrier fitted with an Energy Saving Device, a fast container ship, a tanker and a fully appended twin-screw navy destroyer. All simulations are compared to available experimental data. Conclusions are drawn based on the success of the coupled solver to predict the local flow behind the propeller for each individual hull and how this relates to the vessel type and the local stern geometry.


Author(s):  
Emmanuel Guilmineau

Computational Fluid Dynamics (CFD) is used to simulate the flow over a pickup truck. The flow solver used is ISIS-CFD developed by the CFD Department of the Fluid Mechanics Laboratory of Ecole Centrale de Nantes. CFD simulations are carried out with the Explicit Algebraic Reynolds Stress Model (EARSM) turbulence model and the Detached Eddy Simulation (DES). The focus of the simulation is to assess the capabilities of ISIS-CFD for vehicle aerodynamic development for pickup trucks. Detailed comparisons are made between the CFD simulations and the existing experiments for a generic pickup truck. The comparisons between the simulation results and the time-averaged measurements reveals that the CFD calculations are able to track the flow trends.


2014 ◽  
Author(s):  
Grzegorz Filip ◽  
Dae-Hyun Kim ◽  
Sunil Sahu ◽  
Jan de Kat ◽  
Kevin Maki

This paper describes a numerical bulbous bow retrofit analysis for a modern container ship operating under a slow-steaming profile. The retrofit analysis is used as an example of a design process based on high-fidelity CFD simulations and surrogate modelling. The bulbous bow design candidates are generated through a parametric modification of the original bow geometry. The alternative designs are evaluated using the open-source CFD toolbox OpenFOAM and the computed effective power predictions are used to rank each design across the entire operating profile. Additionally, the influence of the alternative bulb designs on the wave-making resistance and the propeller performance is examined in detail. Surrogate models are then used to explore the parameterized design space and to establish a sequence of design exploration and exploitation cycles in the retrofit analysis with the ultimate goal of generating an improved bow shape.


2019 ◽  
Vol 265 ◽  
pp. 99-115 ◽  
Author(s):  
C. Fernandes ◽  
V. Vukčević ◽  
T. Uroić ◽  
R. Simoes ◽  
O.S. Carneiro ◽  
...  

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
D. Langmayr ◽  
R. A. Almbauer ◽  
N. Peller ◽  
W. Puntigam ◽  
A. Lichtenberger

In this paper we introduce a novel method for calculating 3D flow through the underhood compartement of a vehicle. The method is based on the system of Euler equations, which are numerically solved by a finite volume approach. The total number of finite volumes is very low (<1000 cells). The applied numerics are calibrated to recapture a preceding detailed computational fluid dynamics {CFD) simulation. This calibration is established by two sets of factors. The main advantage of the present approach is that the calibration factors can be inter- and extrapolated between different CFD simulations.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Yue Weng ◽  
Xi Zhang ◽  
Xiaohu Guo ◽  
Xianwei Zhang ◽  
Yutong Lu ◽  
...  

AbstractIn unstructured finite volume method, loop on different mesh components such as cells, faces, nodes, etc is used widely for the traversal of data. Mesh loop results in direct or indirect data access that affects data locality significantly. By loop on mesh, many threads accessing the same data lead to data dependence. Both data locality and data dependence play an important part in the performance of GPU simulations. For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics (CFD) program, the performance of hot spots under different loops on cells, faces, and nodes is evaluated on Nvidia Tesla V100 and K80. Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence. Specifically, face loop makes the best data locality, so long as access to face data exists in kernels. Cell loop brings the smallest overheads due to non-coalescing data access, when both cell and node data are used in computing without face data. Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels. Atomic operations reduced the performance of kernels largely in K80, which is not obvious on V100. With the suitable mesh loop mode in all kernels, the overall performance of GPU simulations can be increased by 15%-20%. Finally, the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.


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