MEGAFLOW: Parallel complete aircraft CFD (original) (raw)
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Development and Validation of a Massively Parallel Flow Solver for Turbomachinery Flows
Journal of Propulsion and Power, 2001
This paper presents the development and validation of the unsteady, three-dimensional, multiblock, parallel turbomachinery flow solver, TFLO. The Unsteady Reynolds Averaged Navier-Stokes (Unsteady RANS) equations are solved using a cell-centered discretization on arbitrary multiblock meshes. The solution procedure is based on efficient explicit Runge-Kutta methods with several convergence acceleration techniques such as multigrid, residual averaging, and local time-stepping. The algebraic Baldwin-Lomax, the one-equation Spalart-Allmaras, and the two-equation Wilcox k-w turbulence models are implemented. The solver is parallelized using domain decomposition, an SPMD (Single Program Multiple Data) strategy, and the Message Passing Interface (MPI) Standard. A mixing model and a sliding mesh interface approach have been implemented to exchange flow information between blade rows in both steady and unsteady rotor/stator interaction flows. The dual-time stepping technique is applied to advance unsteady computations in time. This paper focuses heavily on the initial validation of the flow solver, TFLO, with emphasis on steady-state calculation of multiple blade-row flows. For validation and verification purposes, results from TFLO are compared with both existing experimental data and computational results from other software used in industry. The large set of cases tested increases our confidence in the ability of TFLO to accurately predict flows inside typical turbomachinery geometries, and sets the stage for the large-scale computation of unsteady, multiple blade-row flows.
High performance parallel computing of flows in complex geometries
Comptes Rendus Mécanique, 2011
Informatique, algorithmique Calcul parallèle Dynamique des fluides numérique Efficient numerical tools taking advantage of the ever increasing power of high-performance computers, become key elements in the fields of energy supply and transportation, not only from a purely scientific point of view, but also at the design stage in industry. Indeed, flow phenomena that occur in or around the industrial applications such as gas turbines or aircraft are still not mastered. In fact, most Computational Fluid Dynamics (CFD) predictions produced today focus on reduced or simplified versions of the real systems and are usually solved with a steady state assumption. This article shows how recent developments of CFD codes and parallel computer architectures can help overcoming this barrier. With this new environment, new scientific and technological challenges can be addressed provided that thousands of computing cores are efficiently used in parallel. Strategies of modern flow solvers are discussed with particular emphases on meshpartitioning, load balancing and communication. These concepts are used in two CFD codes developed by CERFACS: a multi-block structured code dedicated to aircrafts and turbomachinery as well as an unstructured code for gas turbine flow predictions. Leading edge computations obtained with these high-end massively parallel CFD codes are illustrated and discussed in the context of aircrafts, turbo-machinery and gas turbine applications. Finally, future developments of CFD and high-end computers are proposed to provide leading edge tools and end applications with strong industrial implications at the design stage of the next generation of aircraft and gas turbines.
Parallelization of a three-dimensional flow solver for Euler rotorcraft aerodynamics predictions
AIAA Journal, 1996
An approach for parallelizing the three-dimensional Euler/Navier-Stokes rotorcraft computational fluid dynamics flow solver transonic unsteady rotor Navier-Stokes (TURNS) is introduced. Parallelization is performed using a domain decomposition technique that is developed for distributed-memory parallel architectures. Communication between the subdomains on each processor is performed via message passing in the form of message passing interface subroutine calls. The most difficult portion of the TURNS algorithm to implement efficiently in parallel is the implicit time step using the lower-upper symmetric Gauss-Seidel (LU-SGS) algorithm. Two modifications of LU-SGS are proposed to improve the parallel performance. First, a previously introduced Jacobi-like method called data-parallel lower upper relaxation (DP-LUR) is used. Second, a new hybrid method is introduced that combines the Jacobi sweeping approach in DP-LUR for interprocessor communications and the symmetric Gauss-Seidel algorithm in LU-SGS for on-processor computations. The parallelized TURNS code with the modified implicit operator is implemented on two distributed-memory multiprocessor, the IBM SP2 and Thinking Machines CM-5, and used to compute the three-dimensional quasisteady and unsteady flowfield of a helicopter rotor in forward flight. Good parallel speedups with a low percentage of communication are exhibited by the code. The proposed hybrid algorithm requires less CPU time than DP-LUR while maintaining comparable parallel speedups and communication costs. Execution rates found on the IBM SP2 are impressive; on 114 processors of the SP2, the solution time of both quasisteady and unsteady calculations is reduced by a factor of about 12 over a single processor of the Cray C-90.
Optimised Hybrid Parallelisation of a CFD Code on Many Core Architectures
2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2013
Reliable aerodynamic and aeroelastic design of wind turbines, aircraft wings and turbomachinery blades increasingly relies on the use of high-fidelity Navier-Stokes Computational Fluid Dynamics codes to predict the strongly nonlinear periodic flows associated with structural vibrations and periodically varying farfield boundary conditions. On a single computer core, the harmonic balance solution of the Navier-Stokes equations has been shown to significantly reduce the analysis runtime with respect to the conventional time-domain approach. The problem size of realistic simulations, however, requires high-performance computing. The Computational Fluid Dynamics COSA code features a novel harmonic balance Navier-Stokes solver which has been previously parallelised using both a pure MPI implementation and a hybrid MPI/OpenMP implementation. This paper presents the recently completed optimisation of both parallelisations. The achieved performance improvements of both parallelisations highlight the effectiveness of the adopted parallel optimisation strategies. Moreover, a comparative analysis of the optimal performance of these two architectures in terms of runtime and power consumption using some of the current common HPC architectures highlights the reduction of both aspects achievable by using the hybrid parallelisation with emerging many-core architectures.
Discussion of the NAS Parallel Benchmark for CFD
1994
Abstract The Numerical Aerodynamics Simulation (NAS) group at NASA Ames has developed a" pencil and paper" benchmark for Computational Fluid Dynamics (CFD) Applications. A set of synthetic Partial Di erential Equations (PDE's) and the solution methodology, embodying many salient features of a typical application code, are specified. In the benchmark specification, the derivation of the discretized equations and the solution algorithm are not considered.
Journal of Parallel and Distributed Computing, 1999
The complexity of characterizing both parallel hardware and software makes it very difficult to explain and predict the performances of parallel programs for real industrial CFD applications. A performance model based on a generalized Amdahl's formulation has been developed and applied to a flow solver. The present formulation allows us to explain the behavior of a typical CFD explicit multiblock solver when the program is run on a multiprocessor distributed-memory system. Using this approach, it is possible to gain an insight on the performance limitations of this class of parallel solvers, by considering the impact of larger and larger number of processors on fixedscaled problems.
Implementation of a parallel framework for aerodynamic design optimization on unstructured meshes
A parallel framework for performing aerodynamic design optimizations on unstructured meshes is described. The approach utilizes a discrete adjoint formulation which has previously been implemented in a sequential environment and is based on the three-dimensional Reynoldsaveraged Navier-Stokes equations coupled with a one-equation turbulence model. Here, only the inviscid terms are treated in order to develop a basic foundation for a multiprocessor design methodology. A parallel version of the adjoint solver is developed using a library of MPI-based linear and nonlinear solvers known as PETSc, while a shared-memory approach is taken for the mesh movement and gradient evaluation codes. Parallel efficiencies are demonstrated and the linearization of the residual is shown to remain valid.
CFD codes and applications at boeing
Sadhana, 1991
The use of computational methods for three-dimensional flow design and analysis at the Boeing Company is presented. A range of computational "tools" consisting of "production" tools for everyday use by project engineers, "expert user" tools for special applications by computational researchers, and a new "emerging" tool which may see considerable use in the near future is described. These methods include full potential and Euler solvers, some coupled to three-dimensional boundary layer analysis methods, for transonic flow analysis about nacelle, wing/body, wing/body/strut/nacelle, and complete airplane configurations.
Parallel single grid and multigrid solution of industrial compressible flow problems
Computers & Fluids, 1997
The Euler and Navier-Stokes equations with a k-e turbulence model are solved numerically in parallel on a distributed memory machine IBM SP2, a shared memory machine SGI Power Challenge, and a cluster of SGI workstations. The grid is partitioned into blocks and the steady state solution is computed usin,: single grid and multigrid iteration. The multigrid algorithm is analyzed leading to an estimate of the elapsed time per iteration. Based on this analysis, a heuristic algorithm is devised for distributing and splitting the blocks for a good static load balance. Speed-up results are presented for a wing, a complete aircraft and an air inlet.
Design of a massively parallel CFD code for complex geometries
Comptes Rendus Mécanique, 2011
A strategy to build the next generation of fluid dynamics solvers able to fully benefit from high-performance computing is discussed. The procedure relies on a domain decomposition of unstructured meshes that is organized in two levels. The computing cells are first gathered at an elementary level in cell groups; at a second level, cell groups are dispatched over processors. Compared to the usual single-level domain decomposition, this double domain decomposition allows for easily optimizing the use of processor memory and therefore load balancing in both Eulerian and Lagrangian contexts. Specific communication procedures to handle faces, edges and nodes are associated to this double domain decomposition, which strongly reduce the computing cost; input-output times are optimized as well. In addition, any multi-level solution techniques, as deflated preconditioned conjugate gradient, are well-adapted to such mesh decomposition. This approach has been used to develop the YALES2 code, which also benefits from a non-degenerescent tessellation algorithm for tetrahedra to automatically generate highresolution meshes on super-computers. To illustrate the capabilities of the YALES2 algorithmic, an aeronautical burner is fully simulated with a mesh of 2.6 billion cells, followed by a demonstration test over 21 billion cells.