The management of unpaved mine road networks—characterized by high axle loadings, low traffic volumes, variable materials and construction quality, and rapid rates of deterioration—is often inadequate. This situation results in either overmaintenance of the road or failure to recognize significant deterioration, which both lead to the application of suboptimal road maintenance strategies with the attendant increase in total road-user costs. A real-time condition-triggered maintenance management system was identified as a solution, in which onboard monitoring of vehicle dynamic response to road condition forms the basis of road defect recognition and maintenance response. A practical approach to road defect reconstruction using measured truck response is presented. Initially, the application context is introduced, then the field testing program is described, in which data sets were generated that served as the basis for mathematical modeling of the truck response. A modeling approach utilizing the concept of independent front suspension dynamic equilibrium is described as the basis for road defect recognition. On the basis of measured suspension forces and the acceleration of the unsprung mass, the approach to tire force and road defect reconstruction is presented. It is concluded that the methodology developed enables reconstruction of road defect geometries with an accuracy sufficient to allow specific types and dimensions of defects to be recognized for the purpose of road maintenance. By extending the methodology to public unpaved roads, maintenance could be applied as and where needed with a resultant reduction in authority cost and improvement in service provided for the road user.


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    Title :

    Condition-Triggered Maintenance for Mine Haul Roads with Reconstructed-Vehicle Response to Haul Road Defects


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2007-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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