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Automotive Water Pump Methodology using Head Pump and Rotor Power for Correlations
Technical Paper
2017-36-0398
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Aiming the decrease of manufacturing costs, the automotive industry uses Computational Aided Engineering (CAE) and prototype testing for product development. In the field of simulation CAE could be performed using FEA (finite element analysis) or CFD (Computational Fluid Dynamic), the last one is the analysis of systems involving fluid flow, heat transfer and associated phenomena such as chemical reactions by means of computer-based simulation. One of the most important components of cooling system is a water pump which is evaluated through the fluid dynamic analysis. Therefore, this work aims to analyze the fluid flow inside an automotive water pump considering a three-dimensional steady-state using CFD, but also developing a methodology to evaluate it. The parameters of the analysis and the volumetric mesh were according to the simulated results approached the experimental results. After correlating the simulation with the physical test, other simulations were carried out, using the same methodology, but changing the volumetric flow rates and rotor rotations. With this work, it was possible to construct the characteristic curve of the pump in study, as well as calculating the head pump and its efficiency and become possible the application for new development of water pumps.
Authors
- Luiz Guilherme de Oliveira e Caldeira - Centro Federal de Educação Tecnológica de Minas Gerais
- Bruno Cesar Pockszevnicki - Pontifícia Universidade Católica de Minas Gerais
- Geisiel Moreira de Assis - Pontifícia Universidade Católica de Minas Gerais
- Daniella Fernanda dos Santos Magalhães - Universidade Federal de Minas Gerais
Topic
Citation
de Oliveira e Caldeira, L., Pockszevnicki, B., de Assis, G., and Magalhães, D., "Automotive Water Pump Methodology using Head Pump and Rotor Power for Correlations," SAE Technical Paper 2017-36-0398, 2017, https://doi.org/10.4271/2017-36-0398.Data Sets - Support Documents
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