Modelling wheeled construction plant performance in clay and sandy terrain: a terramechanics perspective

This research has investigated the effect of tyre rutting of wheeled construction plant performance traversing in wet and deformable terrain, specifically clay and sand. The purpose was to translate the wheel rutting into performance reduction measured in drawbar-pull. The ultimate goal was to translate the power loss into practical effects on cost, time and other economic variations on construction projects that are characterised by movement of wheeled plant on long haulage deformable roads. In order to achieve this aim, mathematical modelling was deployed based on Newton’s laws of motion, principles of energy conservation and numerical integration. The model is based on a single rigid wheel because construction plant tyres are inflated to high pressure in order to support heavy loads thereby translating the flexible tyres into rigid mode. The results from the mathematical model were verified using a three stage robust verification process which included computational analysis based on two existing semi-empirical methods and real experimental data. Laboratory experiments using Mobility SF- 3713 were also used to check the validity of the results. The results from the mathematical model verify that a flexible tyre can operate in rigid mode if it encounters softer and wet ground. Results further indicate that the soil cohesion, angle of shearing resistance and moisture content play key roles in the subsequent power loss created by motion resistance. All the results from computational analysis and the experiments were found to be consistent with the mathematical model results. The study concludes that there is ample evidence to suggest that there is significant power loss associated with wheeled construction plant traversing in soft terrain which can be assessed. The study further concludes that a combination of economic decisions on variables must be considered with respect to existing ground conditions. This will considerably reduce uncertainty levels in cost and resource management on construction projects.