Cellular Automaton Simulation of Corrosion in 347H Steel Exposed to Molten Solar Salt at Pilot-Plant Scale

The fast-paced depletion of fossil fuels and environmental concerns have intensified interest in renewable energies, with dispatchable solar energy emerging as a key alternative. Concentrated solar power (CSP) technology, utilizing thermal energy storage (TES) systems with molten salts at 560 °C, offers significant potential for large-scale energy generation. However, these extreme conditions pose challenges related to material corrosion, which is critical for maintaining the efficiency and lifespan of CSP. This research modeled the corrosion process of 347H stainless steel in molten solar salt (60% NaNO<sub>3</sub> + 40% KNO<sub>3</sub>) melted at 400 °C using a cellular automaton (CA) algorithm. The CA model simulated oxide growth under pilot-plant conditions in a lattice of 400 × 400 cells. SEM-EDS imaging compared the model with a mean squared error of 2%, corresponding to a corrosion layer of 4.25 µm after 168 h. The simulation applied von Neumann and Margolus neighborhoods for the ion movement and reaction rules, achieving a cell size of 0.125 µm and 10.08 s per iteration. This study demonstrates the CA model's effectiveness in replicating corrosion processes, offering a tool to optimize material performance in CSP systems. Additionally, continuing this investigation could contribute to the development of industrial applications, enabling the design of preventive strategies for large-scale operations.

Authors

Institutions

Publication Details

Journal
Materials
Published
2025-02-06
DOI
https://doi.org/10.3390/ma18030713
Primary Topic
Phase Change Materials Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cellular Automaton Simulation of Corrosion in 347H Steel Exposed to Molten Solar Salt at Pilot-Plant Scale

Mauro Henríquez, Felipe M. Galleguillos Madrid, Marcelo Cortés-Carmona, Luis Guerreiro et al.
Materials
Phase Change Materials Research
article

Cellular Automaton Simulation of Corrosion in 347H Steel Exposed to Molten Solar Salt at Pilot-Plant Scale

Mauro Henríquez, Felipe M. Galleguillos Madrid, Marcelo Cortés-Carmona, Luis Guerreiro, Carlos Soto, Edward Fuentealba, Carlos Durán, Juan C. Reinoso-Burrows, Raúl Pastén, Andrés Alvear
article en

Abstract

The fast-paced depletion of fossil fuels and environmental concerns have intensified interest in renewable energies, with dispatchable solar energy emerging as a key alternative. Concentrated solar power (CSP) technology, utilizing thermal energy storage (TES) systems with molten salts at 560 °C, offers significant potential for large-scale energy generation. However, these extreme conditions pose challenges related to material corrosion, which is critical for maintaining the efficiency and lifespan of CSP. This research modeled the corrosion process of 347H stainless steel in molten solar salt (60% NaNO<sub>3</sub> + 40% KNO<sub>3</sub>) melted at 400 °C using a cellular automaton (CA) algorithm. The CA model simulated oxide growth under pilot-plant conditions in a lattice of 400 × 400 cells. SEM-EDS imaging compared the model with a mean squared error of 2%, corresponding to a corrosion layer of 4.25 µm after 168 h. The simulation applied von Neumann and Margolus neighborhoods for the ion movement and reaction rules, achieving a cell size of 0.125 µm and 10.08 s per iteration. This study demonstrates the CA model's effectiveness in replicating corrosion processes, offering a tool to optimize material performance in CSP systems. Additionally, continuing this investigation could contribute to the development of industrial applications, enabling the design of preventive strategies for large-scale operations.

MaterialsVol. 18(3)
Universidad de Antofagasta (CL), University of Évora (PT)
European Commission, Universidad de Antofagasta, Agencia Nacional de Investigación y Desarrollo, Comisión Nacional de Investigación Científica y Tecnológica, Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias
Openalex Percentile: Top 98%
Phase Change Materials Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.