Conclusions
1. The 0.45 Power Curve Void Prediction Method yields more accurate predictions of aggregate voids than the Coarseness Factor Method of aggregate voids.
2. The 0.45 Power Curve Void Prediction Method must be calibrated for different combined aggregate types (e.g. limestone/sand or granite/sand).
3. The Coarseness Factor Method of Void Prediction requires a suite of previously tested aggregate voids. Higher order regression may be used to increase the R2 value. 4. The Coarseness Factor Method should be used only for one type of combined aggregate (e.g. limestone/sand or granite/sand). 5. Well-graded aggregate percent voids vary less – and are predicted more accurately – than not well-graded aggregate.