# Accelerated Ballast Tank Corrosion Simulation Protocols: A Critical Assessment

## TL;DR

This paper evaluates and compares different lab protocols for simulating ballast tank corrosion, finding that combining immersion with fog/dry conditions accelerates corrosion testing effectively.

## Contribution

The study introduces a novel fog/dry test protocol that accelerates corrosion simulation with high fidelity and cost-effectiveness.

## Key findings

- Combining immersion with fog/dry conditions achieves a 7.82 times acceleration factor for ballast tank corrosion.
- The fog/dry protocol is more cost-effective and replicable than the AMACORT CIFD-01 protocol.
- Fog/dry conditions closely mimic empty ballast tank environments and accelerate corrosion effectively.

## Abstract

In the realm of accelerated testing within controlled laboratory settings, the fidelity of the service environment assumes paramount importance. It is imperative to replicate real-world conditions while compressing the testing duration to facilitate early evaluations, thereby optimizing time and cost efficiencies. Traditional immersion protocols, reflective solely of full ballast tank conditions, inadequately expedite the corrosion process representative of an average ballast tank environment. Through the integration of immersion with fog/dry conditions, aligning the test protocol more closely with the internal conditions of an average ballast tank, heightened rates of general corrosion are achieved. This augmentation yields an acceleration factor of 7.82 times the standard test duration, under the assumption of a general corrosion rate of 0.4 mm/year for uncoated ballast tank steel, with both sides exposed. Subsequently, the fog/dry test protocol, albeit only resembling the environment of an empty ballast tank, closely trails in terms of acceleration efficacy. The fog/dry test protocol offers cost-effectiveness and replicability compared to the AMACORT CIFD-01 protocol, making it a strong competitor despite the relatively close acceleration factor.