Our Expertise | AUTOMOTIVE

Fuel tank sloshing: digital modelling with meshless CFD

Futurities Year 21 n°4
By G. Usai | Dallara Automobili, Italy
M. Merelli | Particleworks Europe, Italy
Thermal management: challenges in and strategies for developing electrified products
Thermal management: challenges in and strategies for developing electrified products

Abstract

Motorsport's competitive demands drive innovation, such as optimizing fuel tank performance by reducing sloshing and ensuring efficient fuel extraction. This study explores a meshless CFD approach using Moving Particle Simulation (MPS) to streamline workflows and reduce computational costs compared to traditional finite volume method (FVM) CFD.

Key findings include:

  • Efficiency Gains: MPS enables faster simulations with reduced hardware needs, allowing Dallara Automobili to analyze sloshing over more tracks in less time.
  • Optimal Particle Size: A 3.5mm particle size strikes a balance between accuracy and computational efficiency.
  • Teflon Sphere Innovation: Adding solid spheres reduces sloshing (14% in x, 8% in y, 17% in z directions) without affecting fuel flow, offering performance advantages in partially filled tanks.

This approach provides actionable insights for enhancing racing fuel tank design, advancing precision and efficiency in motorsport engineering.

Read the article

Find out more

software

Particleworks

An advanced CFD Software solution, based on the Moving Particle Simulation (MPS) method

Particleworks is an advanced CFD Software solution, based on the Moving Particle Simulation (MPS) method.

particleworks

NEWSROOM

Stay connected with us: news, analysis and trends from our experts.

Newsroom  

MEDIA CENTER

Scroll through our Media Center to view all the videos, video-tutorials and recorded webinars.

Media Center  

CASE STUDY

Optimizing a cam mechanism using Adam and MATLAB

The design of a cam for high-speed production machines with various operating criteria imposes various conflicting objectives

This technical case study explains the application of a two-step methodology using the MATLAB and Adam algorithms in the modeFRONTIER software platform.

optimization modefrontier automotive