Development and validation of rolling resistance-based Haul road management
Abstract
Off-highway haul road maintenance is important for earthmoving operations because poor maintenance management can impact economics through excessive expenditure on vehicle operating costs or road maintenance equipment operation. A maintenance management system can help managers decide optimal maintenance strategies to obtain the largest cost savings over conventional maintenance strategies. However, the lack of data makes unpaved haul road maintenance management suboptimal in current practice. Rolling resistance (RR), in particular, is a key factor in field management decisions for construction haul road maintenance that is currently considered without precise quantification, contributing to this suboptimal management. Onboard sensing capabilities can provide opportunities for characterizing the construction environment, with particular emphasis on such parameters related to management decision making. This research develops an analytical framework to help managers optimize haul road management considering the economic efficiency of using construction equipment as a platform for real-time rolling resistance monitoring. Five major tasks for fulfilling the framework are (1) developing a decision model to determine the optimal maintenance trigger, (2) developing a cost-based analysis model to allocate economic impacts for applying a new real-time RR monitoring system, (3) developing a new method to monitor field RR using an instrumentation cart, (4) developing a stochastic RR deterioration prediction model based on the collected field data, and (5) validating the proposed RR-based haul road maintenance framework. An instrumentation cart was developed to measure RR and two factors (tire penetration and tire deflection) that have attested significant relationships to RR. If the relationships between RR and these two factors are strong, there would be no need to measure actual RR; it could be inferred from simpler measurements. The cart was tested in the laboratory and field. The laboratory evaluation results showed that the cart can precisely measure the rolling resistance, tire deflection, and tire penetration. The field tests also showed that relationships between rolling resistance and tire penetration do exist. However, more tests are desired to further develop this relationship. Haul road deterioration experiments for validating the proposed framework were conducted on two off-road sites having different soil characterizations. RR was measured to develop a stochastic RR deterioration model based on the reliability data approach. Then a simulation model that fundamentally tracks the changes of RR and the corresponding expense comparing the sensor-based and conventional maintenance methods was created in MatLab. The potential cost savings associated with adopting an RR monitoring system was estimated and results showed that the RR monitoring system benefits the proposed haul road maintenance management framework.
Degree
Ph.D.
Advisors
Sinfield, Purdue University.
Subject Area
Civil engineering
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