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Hot-Mix Asphalt and Flexible Pavement Design: the MEPDG

Hot-Mix Asphalt and Flexible Pavement Design: the MEPDG. Kevin D. Hall, Ph.D., P.E. Professor and Head, Dept. of Civil Engineering University of Arkansas Flexible Pavement Research Symposium Denver, Colorado -- February 18, 2009. The Plan for Today….

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Hot-Mix Asphalt and Flexible Pavement Design: the MEPDG

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  1. Hot-Mix Asphalt and Flexible Pavement Design: the MEPDG Kevin D. Hall, Ph.D., P.E. Professor and Head, Dept. of Civil Engineering University of Arkansas Flexible Pavement Research Symposium Denver, Colorado -- February 18, 2009

  2. The Plan for Today… • A Stroll Down Memory Lane(where we’ve been) • A Look Up the Road(where we’re going) • A Peek at Arkansas’ MEPDG Efforts(how we are trying to get there)

  3. Memory Lane: the AASHO Road Test (late 1950s) (AASHO, 1961)

  4. Memory Lane: AASHTO Pavement Design (Current – 1993 Edition) Flexible pavement design: the answer is structural number (SN) Then you break SN into layers: SN ≤ (aACHM * dACHM) + (abase * dbase) The design is layer thickness

  5. Materials Structure Damage Time Response Damage Accumulation Distress Looking Ahead: M-E Pavement Design Climate Level 1: I know a lot about this input… Level 2: I know some about this input… Level 3: I know very little about this input… Traffic

  6. Looking Ahead: MEPDG • Distress Prediction Models • Fatigue Cracking • Rutting • Thermal Cracking • IRI

  7. Looking Ahead: National MEPDG Efforts • FHWA Design Guide Implementation Team (DGIT) • NCHRP • 1-37: Development of M-E Design Guide • 1-39: Traffic Data Collection, Analysis, and Forecasting • 1-40A: Independent Review of MEPDG • 1-40B: User Manual and Local Calibration Guide • 1-40D: Technical Assistance to NCHRP 1-40A • 1-41: Models for Predicting Reflection Cracking of HMA Overlays • 1-42A: Models for Predicting Top-Down Cracking of HMA • 1-47: Sensitivity Analysis of the MEPDG • 9-30: Experimental Plan for Calibration & Validation of HMA Performance Models • 9-30A: Calibration of Rutting Models for HMA • 9-44: Development of Work Plan for Validating Endurance Limit for HMA • “Lead States” activities

  8. A Quick Peek at Arkansas’ Efforts  • Sensitivity Analyses • Materials Inputs • HMA Dynamic Modulus • Unbound (Soil & Aggregate) Resilient Modulus • Traffic Inputs • Design Studies • Local Calibration • Database / Support Software Development • Section I.D. • Data Collection • Analysis   

  9. Arkansas: Dynamic Modulus (E*) • Level 1 Catalog • Validation of Level 3Prediction Models

  10. Arkansas: Dynamic Modulus (E*)

  11. Arkansas: Binder (DSR)

  12. Arkansas: Traffic

  13. Arkansas: Database Development

  14. Arkansas: HMA Database • HMA Design • Binder Conventional • Brookfield • DSR • Mixture Properties • Dynamic Modulus • Creep Compliance • Indirect Tension • Construction • Core Thickness • Bulk Gravity • Max Gravity • Binder Content • Binder Grade • Volumetrics • Aggregate Gradation • Compaction • HMA Performance • Cracking • Rutting • IRI • Other • FWD/GPR Tests • Friction Results • Maintenance • Crack Sealing • Patching • Seal Coats • Milling • Overlay

  15. Arkansas: MEPDG Calibration NCHRP 1-40: Recommended Practice for Local Calibration of the Mechanistic-Empirical Pavement Design Guide “The calibration and validation of the performance prediction model is a mandatory step…to establish confidence in the design and analysis procedure and facilitate its acceptance and use.” Calibration: the mathematical process through which total (residual) error – the difference between observed and predicted values of distress – is minimized. Validation: the process to confirm that the calibrated model can produce robust and accurate predictions for cases other than those used for model calibration.

  16. Arkansas: MEPDG Calibration • Select Hierarchical Input Level for Each Input Parameter • Develop Experimental Design and Matrix • Estimate Sample Size for Each Distress Model • Select Roadway Segments • Extract and Evaluate Roadway Segment/Test Section Data • Conduct Field Investigations of Test Sections to Define Missing Data • Assess Bias for the Experimental Matrix • Determine Local Calibration Coefficient to Eliminate Bias of Transfer Function • Assess Standard Error for Transfer Function • Improve Precision of Model: modify coefficients and exponents of transfer functions • Interpretation of Results: decide on adequacy of calibration coefficients

  17. Arkansas: MEPDG Calibration • Sample size (minimum) • Distortion (total rutting or faulting) 20 roadway segments • Load-related cracking 30 roadway segments • Non-load-related cracking 25 roadway segments • Reflection cracking (HMA only) 15 roadway segments • Roadway Segment / Condition Surveys • At least 3 condition surveys available for a roadway segment • Condition surveys cover at least 10 years • Increased number of surveys for higher levels of distress • Range of distress magnitudes – minor to “close to” design criteria • Distress definitions/measurements consistent with MEPDG(Data Collection Guide for Long Term Pavement Performance)

  18. A Long-Term Effort??? THANK YOU !!!

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