Comparison Of Acceleration Techniques on CFD Open-Source Software for Aerospace Applications

Mangani, Luca; Romanelli, Giulio; Gaddai, Andrea; Casartelli, Ernesto

doi:10.2514/6.2015-3059

Cited by 3 publications

(6 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…10,11 ), against reference data available in the literature and with those obtained through the Euler flow solver, AeroX (ref. 31,32 ). The aerodynamic analyses performed with both S T and AeroX are carried out with the same grids.…”

Section: Resultsmentioning

confidence: 99%

Flutter Analysis of Propfan–Open Rotors

Prederi¹,

Parrinello

Gadda

et al. 2018

Journal of Aircraft

View full text Add to dashboard Cite

The work aims at showing the importance of flutter predictions in the preliminary design of Propfan-Open Rotors. Both single rotating propellers and contra rotating open rotors are investigated. The related structural sub-systems are modelled through finite element analyses, the aerodynamic sub-systems exploit a finite volume full potential formulation suitable for unsteady transonic flows. An ad hoc technique is developed for simulating the flow field around a contra rotating open rotor configuration. The effectiveness of the proposed aeroelastic analysis is successfully assessed for single propellers through comparisons with reference numerical and experimental data available in the literature, as well as against Euler flow based solutions. Results for contra rotating open rotors cannot be validated because of the lack of corresponding open literature data.

show abstract

Section: Resultsmentioning

confidence: 99%

Flutter Analysis of Propfan–Open Rotors

Prederi¹,

Parrinello

Gadda

et al. 2018

Journal of Aircraft

View full text Add to dashboard Cite

show abstract

“…Functions and types of the OpenCL API are used in the host source code in order to organize the work (kernels executions) that is sent to the device and to exchange "buffers" (basically memory arrays) between the host and the device. Most CPU and GPU vendors, e.g Intel, AMD, NVIDIA, have their own OpenCL-compliant implementations, allowing the solver to be executed natively on a wide range of devices [11,9]. During kernel executions, the whole work is split in chunks, called "work-items", that are executed in parallel by GPU or CPU cores.…”

Section: Hardware and Software Aspectsmentioning

confidence: 99%

“…Here we briefly present the GPU speedup results for the Rotor 67 test case. For more detailed benchmarks regarding the GPU solver, the reader is referred to [9,11]. All the convergence acceleration techniques (MG, RS, LTS) were active during these benchmarks in order to honestly represent a true simulation.…”

Section: Gpu Accelerationmentioning

confidence: 99%

“…This problem is typically addressed by implementing an efficient implicit formulation [7,8] or by accelerating explicit formulations with multiple combined convergence acceleration techniques [9]. Nowadays, GPUs provide a cheap and relatively easy way to obtain great SIMD (Single Instruction Multiple Data) floating point performance at the cost of a limited amount of available memory with respect to the usual amount of system RAM [10,9,11]. Thus, the idea is to exploit GPUs architecture to accelerate an explicit FSI solver, keeping a low memory usage.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A GPU-Accelerated Compressible RANS Solver for Fluid-Structure Interaction Simulations in Turbomachinery

Mangani¹,

Casartelli²,

Romanelli³

et al. 2016

Volume 7B: Structures and Dynamics

View full text Add to dashboard Cite

Computational Fluid Dynamics (CFD) is a fundamental tool for the aerodynamic development in industrial applications. In the usual approach structural deformation due to aerodynamic and thermal loads is often neglected. However, in some cases, where power efficiency is the ultimate goal, an accurate prediction of the structure-flow interaction is essential. This is particularly true for trim and flutter analysis of aircrafts, helicopter and turbomachinery blades. Particularly, turbomachinery trim and flutter predictions still represent a challenge due to phenomena like rotor-stator interaction, separations and shock waves. The usual time-linearised, frequency-domain strategies can be inadequate when this kind of strong non-linear phenomena occur in the flow, making necessary full non-linear time-domain simulations or the harmonic balance technique. Beside flutter, another important aspect, not yet adequately investigated, is the trim analysis, which is fundamental for an accurate steady simulation that aims to consider static blade elasticity for the performance evaluation of turbomachines. Moreover, alongside the obvious contribution given by centrifugal loads to the blade deformation, a not less important source of blade displacement is the thermal effect due to the heat exchanged between the solid and the fluid domains. In particular, for some geometries and operating conditions, thermal effects can be more important than centrifugal effects for the blade deformations. Considering multiple sources of blade deformation (elastic, centrifugal and thermal) in a what is often called “multiphysics” approach is nowadays more and more important, if the goal of the analysis is geometry optimization. To achieve this, next to result’s accuracy also computational efficiency is required, when hundreds of aeroelastic simulations have to be performed in a typical optimization loop. Modern GPUs can be exploited to pursue this goal thanks to their high peak computational power available at relatively low costs and low power consumption with respect to the usual CPUs. In this paper a pioneer work describing the impact of static deformation due to blade elasticity, thermal and centrifugal effects on the performances and power efficiency will be provided. Alongside with accurate results, computational efficiency is taken into account. The purpose of this article is to show the architecture of a GPU-accelerated Fluid-Structure Interaction (FSI) solver for compressible viscous flows. The proposed approach is validated with a typical industrial case, i.e. a turbocharger transonic centrifugal-compressor provided by ABB. The effects of trimmed solutions on the most important integral quantities (i.e. mass flow, characteristic curves, mass-averaged outflow profiles) are investigated and a comparison with pure aerodynamic results is provided. Due to the high blade stiffness and thus the very small displacements obtained with the trim solutions, for the particular case presented in the paper the aeroelastic solutions basically provide nearly the same results as the pure aerodynamic solutions.

show abstract

“…Many scholars have done related research on the parallel calculation of element stiffness matrix [8]- [10]. At the same time, for the solution of sparse linear equations, GPU parallel solving algorithms based on acoustics [11], electromagnetics [12], and fluid mechanics [13] based on finite element or finite volume methods have also been applied. Basermann et al [14] elaborated the implementation strategy of sparse matrix preprocessing conjugate gradient method on large-scale parallel machine in 1995, and discussed the data storage and segmentation problems in detail.…”

Section: Introductionmentioning

confidence: 99%

Strength Check of Aircraft Parts Based on Multi-GPU Clusters for Fast Calculation of Sparse Linear Equations

Zhang

Hu²

2020

IEEE Access

View full text Add to dashboard Cite

In order to improve the cost-effectiveness ratio, the next-generation vehicle needs to meet the requirements of reuse, while adopting a lighter structural weight, so it is necessary to realize the strength calculation and condition monitoring of key components in the digital twin. Most of the current monitoring methods are based on the characteristics of various data acquisition systems, but they need the support of a large number of flight data. The disadvantages of the above strategy can be avoided by reducing the structure of aircraft components to a finite element model and quickly checking the key components in the health management system. In order to solve the problem of fast calculation of the finite element model of the key components of the aircraft, a parallel algorithm and framework of large-scale sparse matrix preprocessing conjugate gradient method based on CUDA(Compute Unified Device Architecture) technology is proposed in the multi GPU(Graphics Processing Unit) workstation cluster environment. Once the sparse matrix is too large to be processed in a single workstation, this paper discusses how to realize the optimized data segmentation in the distributed multi-GPU computing environment. For the problem of iterative solution of matrix preprocessing, two preprocessing strategies of matrix bandwidth reduction parallelization and incomplete Cholesky decomposition are proposed, and asynchronous task concurrency and load balancing strategies are designed on the architecture. The calculation of some examples in the standard sparse matrix database shows that the algorithm and architecture proposed in this paper have the ability to solve large-scale sparse matrix quickly and efficiently, and can complete the fast strength verification of vehicle components.

show abstract

Comparison Of Acceleration Techniques on CFD Open-Source Software for Aerospace Applications

Cited by 3 publications

References 25 publications

Flutter Analysis of Propfan–Open Rotors

Flutter Analysis of Propfan–Open Rotors

A GPU-Accelerated Compressible RANS Solver for Fluid-Structure Interaction Simulations in Turbomachinery

Strength Check of Aircraft Parts Based on Multi-GPU Clusters for Fast Calculation of Sparse Linear Equations

Contact Info

Product

Resources

About