Probabilistic software tool for life-cycle assessment of reinforced concrete infrastructure

Project Overview

The deterioration of reinforced concrete (RC) infrastructure due to corrosion and environmental exposure poses a substantial challenge for asset management. This project responds to that challenge through the development of Rational-RC, a Python-based software platform that integrates probabilistic life-cycle modelling with field-based diagnostics.

The tool allows engineers and asset owners to evaluate current structure condition, simulate future deterioration, and make data-driven decisions on repair timing and strategy selection. It supports performance-based planning over the entire life cycle of RC structures.

👉 Access the Rational-RC Software

Engineering Contributions

• Limit-State Probabilistic Framework:
  The software extends the structural reliability concepts of “load” and “resistance” to model various deterioration mechanisms. Failure probability is computed when deterioration demand exceeds material resistance.

• Modular Mechanism-Based Design:
  Deterioration processes are modularized into five stages: membrane degradation, chloride ingress, carbonation, corrosion initiation and propagation, and cracking. Each module operates independently with upgradable code architecture.

• Mechanistic Models Used:

  • Membrane: Statistical performance-based model
  • Chloride: Modified Fick’s law accounting for advection
  • Carbonation: Empirical square-root-of-time model
  • Corrosion: Regressed 2D electrochemical model and a pore-scale mechanistic model incorporating chloride, pH, and moisture
  • Cracking: Thick-walled cylinder stress model

Laboratory and Field Integration

• Electrochemical Testing:
  Experimental work investigated the combined influence of chloride content, pH, and moisture on steel corrosion. Mortar samples embedded with carbon steel rebars were tested under multiple conditioning environments (RH 60%–100%) to support model calibration.

• Custom Sensor Deployment:
  A proprietary time-domain reflectometry (TDR) sensor was used to monitor in-situ moisture in concrete cover layers, enhancing the reliability of deterioration predictions.

Software Capabilities

• Utilizes real-world data such as cover depth, chloride profiles, and half-cell potentials
• Predicts condition across deterioration stages
• Supports rational intervention scheduling and life-extension planning

Related Publications

• Rational-RC: A Practical Life Cycle Deterioration Modelling Framework for Reinforced Concrete Structures
• On the Corrosion Parameters Acquired Through Potentiodynamic Scans of Carbon Steel Rebar in Simulated Pore Solution and Mortar