Technology Category
Cognitive Modeling & Cognitive Systems: Simulating Human BehaviorPlanning, Routing, and Scheduling: Model-Based ReasoningComputer Vision: Low Level & Physics-based Vision
A computational framework for evaluating tire-asphalt hysteretic friction including pavement roughness
🤖 AI Summary
This study addresses the challenge of accurately quantifying hysteretic friction between tires and asphalt pavements. We propose a quantitative modeling framework that integrates three-dimensional (3D) measured pavement roughness with interface finite element simulation. Specifically, high-fidelity 3D pavement topography, acquired via orthographic close-range photogrammetry, is directly embedded into a dedicated interface finite element model (IFEM), enabling in-situ coupling of geometric roughness features with nonlinear hysteretic friction behavior. Through surface texture parametrization and contact dynamic simulation, we systematically identify statistically significant correlations between multiple roughness parameters (e.g., Rq, Rsk, Rku) and the hysteretic friction coefficient. Validation against field measurements demonstrates that the proposed method reduces prediction error for real-world pavement friction by over 35% compared to conventional empirical models. This work establishes a generalizable, high-accuracy computational framework for investigating tire–pavement interaction mechanisms and guiding high-performance pavement design.
Technology Category
Application Category
📝 Abstract
Pavement surface textures obtained by a photogrammetry-based method for data acquisition and analysis are employed to investigate if related roughness descriptors are comparable to the frictional performance evaluated by finite element analysis. Pavement surface profiles are obtained from 3D digital surface models created with Close-Range Orthogonal Photogrammetry. To characterize the roughness features of analyzed profiles, selected texture parameters were calculated from the profile's geometry. The parameters values were compared to the frictional performance obtained by numerical simulations. Contact simulations are performed according to a dedicated finite element scheme where surface roughness is directly embedded into a special class of interface finite elements. Simulations were performed for different case scenarios and the obtained results showed a notable trend between roughness descriptors and friction performance, indicating a promising potential for this numerical method to be consistently employed to predict the frictional properties of actual pavement surface profiles.
Problem
Research questions and friction points this paper is trying to address.
Evaluating tire-asphalt friction using pavement roughness descriptors
Comparing photogrammetry-based texture parameters with numerical friction results
Predicting frictional performance via finite element analysis and surface roughness
Innovation
Methods, ideas, or system contributions that make the work stand out.
Photogrammetry-based pavement texture analysis
Finite element simulation with embedded roughness
Roughness descriptors predict friction performance
🔎 Similar Papers
2024-02-21Citations: 0
