Portorož, Slovenia Laboratory test method for the prediction of the evolution of road skid-resistance with traffic Minh-Tan DoMinh-Tan Do LCPCLCPC Research engineerResearch engineer :

Portorož, Slovenia Scope Need to predict skid-resistance evolution Existing empirical tools LCPC polishing tests From laboratory simulation to road prediction Conclusions

Portorož, Slovenia Need to predict skid-resistance evolution Road skid-resistance evolves with time due to mechanical actions (traffic) due to climate effects Prediction of skid-resistance evolution is needed: to forecast road maintenance to ensure long-term performance to optimize material choice

Portorož, Slovenia Existing empirical tools Experimental sites tracked over time drawbacks: costs , time  Aggregate testing (i.e. PSV) drawback: transposition aggregates  mixes?

Portorož, Slovenia LCPC polishing tests – Objectives Quick laboratory tests Able to test concrete-asphalt mixes and aggregates Comparable results with road data Means to predict skid-resistance evolution

Portorož, Slovenia LCPC polishing tests – Test machine Wehner/Schulze machine Origin: University of Berlin (70’s) Functions: polishing & friction measurement Specimens: cores Ø 22.5 cm Tested materials: concrete asphalt, aggregates, sand

Portorož, Slovenia LCPC polishing tests – Wehner/Schulze machine “Polishing” function Principle: rolling rubber cones with (water + abrasive) mix Cone contact pressure: 0.4 N.mm -2 Rotation speed: 500 rpm “Friction measurement” function Principle: sliding rubber pads with water full « braking » curve (µ-time) from 100 km/h to complete stopping

Portorož, Slovenia LCPC polishing tests – Specimens Concrete asphalt Cores taken from pavements or laboratory-made slabs Aggregates Mosaic discs (fraction 7.2/10 mm) 22,5 cm

Portorož, Slovenia LCPC polishing tests – Test procedure Friction-time plot Friction measurement every 1000 passes  µ max is reached Next stops: passes End: 180,000 passes µ max 15 profiles, spaced every 0.5 mm L = 76 mm, x = 0.01 mm Microtexture measurements (polished part) Initial state (0 pass) At µ max 90,000 and 180,000 passes

Portorož, Slovenia LCPC polishing tests – Laboratory results (1/2) Aggregates vs asphalt mixes

Portorož, Slovenia LCPC polishing tests – Laboratory results (2/2) Wehner/Schulze vs PSV µ WS = 1.06(PSV/100) – 0.20

Portorož, Slovenia From laboratory to road Core sampling on new roads tracked over time Wheel paths Polishing tests (just after road construction) Ageing effect (every 6 months) Skid-resistance evolution (every 6 months) simulation vs actual evolution Traffic count

Portorož, Slovenia From laboratory to road Core sampling on circulated roads Wheel paths Polishing tests Friction measurements (Wehner/Schulze machine) polishing duration  traffic Traffic count

Portorož, Slovenia From laboratory to road Relationship polishing duration – traffic N = k.T N: number of passes T: cumulated truck number k = constant = Calibrated from 13 sites (source from Tang PhD thesis, 2007)

Portorož, Slovenia From laboratory to road Simulation vs actual evolution

Portorož, Slovenia From laboratory to road Towards a prediction of skid-resistance evolution Problem statement ? Simulation from Wehner/Schulze machine Measurement by means of ADHERA device (blank PIARC tyre, locked wheel)

Portorož, Slovenia From laboratory to road Towards a prediction of skid-resistance evolution Approach N = T ?

Portorož, Slovenia From laboratory to road Towards a prediction of skid-resistance evolution Relationship µ WS – LFC/SFC (source from Huschek, 2004) LFC (80 km/h) = 1.04 µ WS – 0.01 LFC from Stuttgart Friction Tester, ribbed tyres SFC (80 km/h) = 0.96 µ WS SFC from SCRIM

Portorož, Slovenia From laboratory to road Towards a prediction of skid-resistance evolution Comparison prediction/measurement Overestimation µ WS -N plot converted into equivalent LFC-T plot actual LFC-T plot

Portorož, Slovenia Conclusions – Where are we / objectives? Quick laboratory tests ½ day to plot a full friction-time curve, could be  depending (N = 0.024T) on anticipated traffic Able to test concrete-asphalt mixes and aggregates Yes, except very aggressive surfaces Comparable results with road data Yes, first tendencies to be supported by other experiments Means to predict skid-resistance evolution Promising first results

Portorož, Slovenia Conclusions – Next step Investigate the relationship polishing duration  traffic “k” (N = kT) should be constant ? Relationship µ WS  LFC/SFC Relative influences light vehicles/trucks Prediction model, taking into account other mechanisms (seasonal variations, ageing)