Pavement Life Predictor | IRC:37 Professional

Pavement Life Predictor

IRC:37-2018 Mechanistic-Empirical Framework

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App Documentation: Pavement Life Predictor (PLP)

A Mechanistic-Empirical analysis tool based on IRC:37-2018 guidelines.

1. Key Features

  • IRC:37 Compliance: Utilizes the Indian Roads Congress framework for flexible pavement life estimation.
  • Dynamic Soil Stiffness: Automatically calculates the Resilient Modulus ($M_r$) based on Subgrade CBR and Soil Type.
  • Traffic Growth Modeling: Includes a non-linear annual growth rate (5%) to solve for exact failure timelines.
  • Real-time Visualization: Generates a deterioration curve showing failure probability over a 30-year span.
  • Maintenance Intelligence: Suggests specific treatments (Micro-surfacing vs. DBM) based on the calculated structural health.
  • PDF Reporting: One-click export for professional documentation and research sharing.

2. Engineering Methodology

The app follows a three-step mechanistic process to determine the pavement’s structural longevity:

Step A: Subgrade Characterization & Soil Impact

The foundation strength is determined via the Resilient Modulus ($M_r$). Soil classification is critical here as it determines the stiffness constant:

  • Fine-Grained (Clayey): Uses $M_r (MPa) = 17.6 \times CBR^{0.64}$ (Sensitive to moisture).
  • Coarse-Grained (Sandy): Uses $M_r (MPa) = 20 \times CBR$ (High particle interlock).
Step B: Strain Analysis

Using the thickness and load parameters, the app estimates the Vertical Subgrade Strain ($\epsilon_v$). This is the primary predictor for rutting failure. As thickness increases, the strain decreases exponentially, following Boussinesq’s distribution principles.

Step C: Cumulative Damage (MSA)

The structural capacity is expressed in Million Standard Axles (MSA). We utilize the IRC:37 rutting transfer function:
$N_r = 1.41 \times 10^{-8} \times (1/\epsilon_v)^{4.533}$.

3. Deterioration Modeling

The app visualizes the “Failure Probability” using a Sigmoid Logistic Function centered at the calculated design life. This models the real-world behavior where pavement damage is slow initially but accelerates rapidly as it nears its structural MSA capacity.

4. Technical Units & Definitions

ParameterUnitDescription
AADTVehicles/DayAverage Annual Daily Traffic for the design lane.
CBRPercentage (%)California Bearing Ratio, indicating subgrade strength.
Structural CapacityMSAMillion Standard Axles the pavement can sustain before failure.
$\epsilon_v$Micro-strainVertical strain at the top of the subgrade.
$M_r$MPaResilient Modulus; a measure of material stiffness.
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