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.
Nicolosi, V., D'Apuzzo, M. (2010). A for new methodology stochastic modelling of pay factors in hot-mix asphalt pavements. ROAD MATERIALS AND PAVEMENT DESIGN, 11(S1), 559-585.
A for new methodology stochastic modelling of pay factors in hot-mix asphalt pavements
NICOLOSI, VITTORIO;
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.