Since 1990 several research projects developing any Pay-Adjustment (PA) procedure for implementing Performance Related Specification (PRS) in Hot-Mix Asphalt (HMA) pavement construction have been issued. Previous studies proved that an approach based on life-cycle cost analysis and Monte Carlo simulation was an effective way to develop rational pay-adjustment procedures. However, the PRS systems developed so far had some significant weaknesses in the modelling of the variability of Materials and Construction (M&C) characteristics with corresponding PA. Furthermore they are mainly based on an empirical approach rather than on a mechanistic one. A new approach to model M&C variability in PRS systems, based on beta distribution, is introduced and a new stochastic method for pay-adjustment evaluation is developed. These criteria were embedded in a mechanistic system framework based on life-cycle cost analysis and Monte Carlo simulation. The model has been recently applied to a real case study and results are reported and analysed in this paperwork.
A new methodology for stochastic modelling of Pay Factors in Hot-Mix asphalt pavements
D'APUZZO, Mauro;
2010-01-01
Abstract
Since 1990 several research projects developing any Pay-Adjustment (PA) procedure for implementing Performance Related Specification (PRS) in Hot-Mix Asphalt (HMA) pavement construction have been issued. Previous studies proved that an approach based on life-cycle cost analysis and Monte Carlo simulation was an effective way to develop rational pay-adjustment procedures. However, the PRS systems developed so far had some significant weaknesses in the modelling of the variability of Materials and Construction (M&C) characteristics with corresponding PA. Furthermore they are mainly based on an empirical approach rather than on a mechanistic one. A new approach to model M&C variability in PRS systems, based on beta distribution, is introduced and a new stochastic method for pay-adjustment evaluation is developed. These criteria were embedded in a mechanistic system framework based on life-cycle cost analysis and Monte Carlo simulation. The model has been recently applied to a real case study and results are reported and analysed in this paperwork.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
