README.md

metadata

title: DBFT Pavement Strain Predictor
emoji: 🛣️
colorFrom: green
colorTo: gray
sdk: gradio
sdk_version: 5.24.0
app_file: app.py
pinned: false
license: mit

DBFT — Pavement Strain Predictor

Predicts the two critical pavement strains directly from a Falling Weight Deflectometer (FWD) test — no backcalculation step:

• ε_t — horizontal tensile strain at the bottom of the asphalt layer (fatigue-cracking criterion)
• ε_c — vertical compressive strain at the top of the subgrade (rutting criterion)

Model: DBFT (Deflection-Basin Fusion Transformer), ~150k parameters, trained with a combined surrogate + field loss (λ = 1.0) on an extended layered-elastic surrogate (14,174 PyMastic/EVERSTRESS solutions) plus 7,651 Thai DOH field measurements. Held-out-route field performance: R² = 0.96 (AC) / 0.88 (subgrade).

Every prediction includes a local SHAP attribution (KernelExplainer over the 12 field-measurable inputs: 9 deflections D0–D1800 + 3 layer thicknesses) showing how each input pushed the prediction away from the model baseline.

Inputs

Input	Unit	Note
D0 … D1800	μm	deflection basin, normalized to 707 kPa plate pressure
h_AC, h_Base, h_Subbase	mm	h_Subbase = 0 for structures without a subbase

Run locally

pip install -r requirements.txt gradio
python app.py