Oppdatering av grenseverdien for å måle bæreevne for asfalt med Raptor

Abstract

This study comprehensively investigated the relationships between various pavement parameters and Temperature-Modified Bearing Capacity (TMBC) using a correlation matrix and multiple regression models. Important parameters, such as curvature indices, EDIM, ROC, and deflection measurements, showed clear positive and negative relationships through the first correlation matrix analysis. These correlations provided the foundation for additional research using a variety of regression models, including polynomial, nonlinear, and linear methods. The most useful technique among them for capturing the complex relationships between parameters, especially the strong correlations between TMBC and EDIM, and ROC was polynomial regression. Further analysis revealed that deflection measurements at various depths, curvature indices, and horizontal strain significantly influence TMBC. Notably, surface deflections (D0) exhibited the highest negative correlation with TMBC, indicating a decrease in load-bearing capacity as deflection increases. Conversely, positive correlations with EDIM and ROC suggest that material stiffness and reduced deformation under load are crucial for maintaining pavement performance. The study additionally highlighted the significance of taking into consideration the combined impacts of using multi-linear regression models, which found that EDIM and ROC were the most important factors affecting TMBC. Based on these findings, the study proposed threshold values for EDIM and ROC tailored to Norway's environmental conditions, which significantly impact pavement stiffness and bearing capacity. These thresholds provide an efficient method for assessing and maintaining pavement conditions, ensuring effectiveness and durability in a range of environmental circumstances