A Hybrid Mechanistic–Empirical and Neural Network Model Framework for Forecasting Fatigue Crack Deterioration in Ethiopian Flexible Pavements

Autor: Mekonnen, A. A.; Yehualaw, M. D.; Melaku, R. S.; Gebissa Guta, A.
In:

MDPI Applied SCjiences

Bandangabe: 16
Auflage: 16
ISBN: 2076-3417
DOI: https://doi.org/10.3390/app16115288
Seite: 1 - 32
Jahr: 2026

Einordung:
Institut: Professur Geotechnik und Küstenwasserbau

Abstract:
Fatigue crack deterioration in flexible pavements results from structural loading, traffic
demand, material aging, and climatic exposure; yet, Ethiopian pavement models remain
largely empirical, with little mechanistic foundation. This study develops a hybrid
mechanistic–empirical and artificial neural network framework to forecast fatigue
crack progression along a five-kilometer segment of theWoldia–Jeneto road in northern
Ethiopia, built in 2015 and assessed after ten years of service. ERAPave layered elastic
analysis computed critical horizontal tensile strain at the asphalt base, using the ERA
manual recommendation of the Australian fatigue criterion for tropical areas, deriving
cumulative damage indices via Miner’s rule. These outputs, alongside material properties,
soil indices, traffic, climate, and temporal variables, formed an 18-feature input
vector, which was trained using Latin–Hypercube Sampling and leave-one-out crossvalidation
under data-scarce conditions. Critical tandem-axle loads of 200.2 kN produced
tensile strains of 182.7–199.83 με and damage ratios of 0.39–0.76 within fatigue lifetimes of
10.46–20.12 million ESALs, exceeding the 7.93 million ESAL design threshold. The model
achieved R2 = 0.9997 and MAPE = 1.64%; these figures reflect five-station training conditions
and synthetic augmentation rather than unconditional generalization accuracy. Ten-year
forecasts place Station 5 at structural failure within three years, supporting evidence-based
pavement maintenance planning.
Keywords: fatigue cracking; flexible pavement; mechanistic–empirical; artificial neural
network; ERAPave; Ethiopia

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