Editorial Type:
Article Category: Research Article
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Online Publication Date: 01 Sept 2011

Parallel Computing for Tire Simulations

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Page Range: 193 – 209
DOI: 10.2346/1.3637743
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Abstract

Over the last few decades, finite element analysis has become an integral part of the overall tire design process. Engineers need to perform a number of different simulations to evaluate new designs and study the effect of proposed design changes. However, tires pose formidable simulation challenges due to the presence of highly nonlinear rubber compounds, embedded reinforcements, complex tread geometries, rolling contact, and large deformations. Accurate simulation requires careful consideration of these factors, resulting in the extensive turnaround time, often times prolonging the design cycle. Therefore, it is extremely critical to explore means to reduce the turnaround time while producing reliable results.

Compute clusters have recently become a cost effective means to perform high performance computing (HPC). Distributed memory parallel solvers designed to take advantage of compute clusters have become increasingly popular. In this paper, we examine the use of HPC for various tire simulations and demonstrate how it can significantly reduce simulation turnaround time. Abaqus/Standard is used for routine tire simulations like footprint and steady state rolling. Abaqus/Explicit is used for transient rolling and hydroplaning simulations. The run times and scaling data corresponding to models of various sizes and complexity are presented.

Keywords: simulation; Abaqus; tire; HPC; DMP; parallel; performance
Copyright: The Tire Society
FIG. 1
FIG. 1

Schematic describing the overall tire design workflow.

FIG. 2
FIG. 2

Finite element mesh corresponding to Model-1.

FIG. 3
FIG. 3

Lateral force versus slip angle for Model-1.

FIG. 4
FIG. 4

Cleat impact in Abaqus/Explicit.

FIG. 5
FIG. 5

Vertical reaction force at the hub versus time for the curb impact simulation.

FIG. 6
FIG. 6

Schematic describing the excitation applied to the rolling tire.

FIG. 7
FIG. 7

Vertical transmissibility for the tire-air cavity system.

FIG. 8
FIG. 8

Finite element mesh corresponding to Model-4.

FIG. 9
FIG. 9

Finite element mesh corresponding to Model-5.

FIG. 10
FIG. 10

Hydroplaning simulation in Abaqus/Explicit.

FIG. 11
FIG. 11

Contact force between the tire and the road; the force reduces due to the lift from the puddle of water.

FIG. 12
FIG. 12

Scaling data for simulations using the STATIC procedure in Abaqus/Standard. The curve y = 1.5(log(x)/log(2)-2)) represents a scaling of 1.5 every time the number of cores is doubled.

FIG. 13
FIG. 13

Scaling data for simulations using the steady state transport procedure in Abaqus/Standard.

FIG. 14
FIG. 14

Scaling data corresponding to the dynamic procedures (Abaqus/Explicit and steady state dynamics, direct in Abaqus/Standard).

FIG. 15
FIG. 15

Scaling data corresponding to hydroplaning analysis.

FIG. 16
FIG. 16

Stack plot comparing the software cost associated with multicore execution relative to the cost on four cores.

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