A nonlinear multi-spring tire model for dynamic analysis of vehicle-bridge interaction system considering separation and road roughness

To reduce weight, in last decade the transport industry had recourse to the use of more lightweight material. Currently, several static elements of the vehicles are made of aluminum. However, the dynamic elements such as suspension parts cause difficulties due to high solicitations from vibration and road roughness. To better assess this damage in depth, the modeling of a full suspension system is more than necessary. In this work, a full quarter vehicle model while considering the motion of suspension along three axes is developed. This system is composed of an upper arm, lower arm, the spring, the damper, the wheel and the fastening elements. By using this full analytical model, all parameters such as, velocities, accelerations and forces can be determined.

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Hybrid probabilistic interval dynamic analysis of vehicle–bridge interaction system with uncertainties

International Journal of Structural Stability and Dynamics ◽

10.1142/s0219455413500697 ◽

2014 ◽

Vol 14 (03) ◽

pp. 1350069 ◽

Cited By ~ 1

Author(s):

N. Liu ◽

W. Gao ◽

C. Song ◽

N. Zhang

Keyword(s):

Dynamic Analysis ◽

Random Variables ◽

Simulation Method ◽

Mean Value ◽

Random Interval ◽

Moving Vehicle ◽

Interaction System ◽

Individual System ◽

Interval Variables ◽

Interval Width

This paper presents the hybrid probabilistic interval dynamic analysis of vehicle–bridge interaction system with a mixture of random and interval properties. The vehicle's parameters are considered as interval variables and the bridge's parameters are treated as random variables. A half car model is used to represent a moving vehicle and the bridge is modeled as a simply supported Euler–Bernoulli beam. By introducing the random interval moment method (RIMM) into the dynamic analysis of vehicle–bride interaction system, the expressions for the mean value and standard deviation of the random interval bridge dynamic response are developed. The midpoint and interval width of the first two statistical moments are then determined. Examples are used to illustrate the effectiveness of the presented method. A hybrid simulation method combining direct simulations for interval variables and Monte Carlo simulations for random variables is implemented to validate the computational results. The effects of individual system parameters on bridge response are also investigated.

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Hybrid Probabilistic and Non-Probabilistic Dynamic Analysis of Vehicle-Bridge Interaction System with Uncertainties

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.553.545 ◽

2014 ◽

Vol 553 ◽

pp. 545-550

Author(s):

Neng Guang Liu ◽

Wei Gao ◽

Chong Ming Song ◽

Nong Zhang

Keyword(s):

Finite Element ◽

Dynamic Analysis ◽

Random Variables ◽

Element Model ◽

Simulation Method ◽

Mean Value ◽

Element Analysis ◽

Moving Vehicle ◽

Interaction System ◽

Interval Variables

A hybrid probabilistic interval dynamic analysis of vehicle-bridge interaction system with a mixture of random and interval properties is studied based on finite element analysis framework. A half car model is used to represent a moving vehicle and the bridge is modeled as a simply supported Euler-Bernoulli beam. The vehicle’s parameters are considered as interval variables and the bridge’s parameters are treated as random variables. The mathematical model of vehicle-bridge interaction system is established based on the finite element model. By introducing the random interval perturbation method into the dynamic analysis of vehicle-bride interaction system, the expressions for the mean value and variance of the bridge dynamic response are developed. Examples are used to illustrate the effectiveness of the presented method. The accuracy and effectiveness of the numerical results are verified by a hybrid simulation method combining direct simulations for interval variables and Monte-Carlo simulations for random variables.

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Validation of a FEA Tire Model for Vehicle Dynamic Analysis and Full Vehicle Real Time Proving Ground Simulations

10.4271/971100 ◽

1997 ◽

Cited By ~ 8

Author(s):

Chang-Ro Lee ◽

Jeong-Won Kim ◽

John O. Hallquist ◽

Yuan Zhang ◽

Akbar D. Farahani

Keyword(s):

Dynamic Analysis ◽

Real Time ◽

Tire Model ◽

Vehicle Dynamic ◽

Full Vehicle

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Transient dynamic analysis of a floating beam–water interaction system excited by the impact of a landing beam

Journal of Sound and Vibration ◽

10.1016/j.jsv.2007.01.026 ◽

2007 ◽

Vol 303 (1-2) ◽

pp. 371-390 ◽

Cited By ~ 18

Author(s):

J.Z. Jin ◽

J.T. Xing

Keyword(s):

Dynamic Analysis ◽

Transient Dynamic Analysis ◽

Transient Dynamic ◽

Water Interaction ◽

Interaction System ◽

The Impact

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Analytical Modeling of Bridge-Road-Vehicle Dynamic Interaction System

Journal of Vibration and Control ◽

10.1177/1077546304033950 ◽

2004 ◽

Vol 10 (2) ◽

pp. 215-241 ◽

Cited By ~ 10

Author(s):

Hani H Nassif ◽

Ming Liu

Keyword(s):

Dynamic Load ◽

Dynamic Models ◽

Dynamic Interaction ◽

Suspension System ◽

Load Factor ◽

Vehicle Dynamic ◽

Road Vehicle ◽

Interaction System ◽

Road Roughness ◽

Dynamic Load Factor

We present a three-dimensional (3D) dynamic model for the bridge-road-vehicle interaction system. A slab-on-girder bridge is modeled as a grillage system subjected to multiple moving truck loads. Multi-axle semi-tractor-trailer is idealized as a 3D vehicle model with a nonlinear tire-suspension system, having eleven independent degrees of freedom. Road roughness profiles are generated from the random Gaussian process as well as limited measurements of actual road profiles. Truck wheel loads are applied at any point and then transferred to nodes as equivalent nodal forces. The Newmark-\#946; integration method is applied as a numerical algorithm for solving the bridge-road-vehicle dynamic interaction equations. The major parameters affecting the bridge dynamic response (or the dynamic load factor) include road roughness, truck weight, speed and mechanical properties of the tire-suspension system and bridge stiffness and boundary conditions. Results from other dynamic models as well as field tests are compared with those from the current 3D model. The results show that the dynamic load factor is highly dependent on road roughness, vehicle suspension, and bridge geometry.

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