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RESEARCH

We specialize in studying chemical leaks, fires, and explosions using CFD simulations and machine learning, to enhance the safety of chemical processes in various industries, including petrochemicals, refining, and batteries. By advancing the smart and digital transformation of chemical processes, our group strives to propose new paradigms for next-generation process safety and develop innovative process safety systems.

Research Fields

" We study approaches to simulation and machine learning techniques in the field of chemical safety."

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Research Field 1.
Process safety
with CFD simulation

Leakage & Dispersion

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Application 1

Quantitative Risk Assessment 

Analysis of Chemical Release and Dispersion Behavior Using FLACS

- Related works

§ Simulation based technical support

   (LG Chem, BASF, Air Liquide ...)

​

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Application 2

Ventilation Optimization

Optimization of Ventilation Placement Using Ansys Fluent

- Related works

§ Seulgi Lee, A study on the Location of Supply and Exhaust prots for general ventilation of flammable gas, Master's thesis, 2024

Fire & Explosion

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Application 1

Chemical Accident Investigation

Reconstruction of Fire and Explosion Scenarios During Chemical Accidents Using FLACS

- Related works

§ Sehyeon Oh et al,, Damage mitigation method studies through simulation modeling of chemical accidents, Process Saf. Prog., 2024

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Application 2

Optimization of Barrier Design 

Designing Barrier to Minimize Fire and Explosion Risks at Hydrogen Refueling Stations Using FLACS

- Related works

§ Sehyeon Oh et al., Methodology for optimally designing hydrogen refueling station barriers ..., Int. J. Hydrogen Energy, 2024

Research Field 2.
Battery safety
with CFD simulation

Battery Thermal Management System

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Application 1

Optimization of Operating Conditions in Immersion Cooling Systems

Thermal Flow Analysis Inside a Battery Pack Using the Battery Model in Ansys Fluent

- Related works

§ Seongheon Baek et al., Optimization of thermal management for immersion cooled lithium-ion batteries..., Journal of the Korea Academia-Industrial cooperation Society,2025

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Application 2

Comparison of Cooling Performance Based on Thermal Fluids and Cell Arrangements

Thermal Flow Analysis Based on Coolant and Angles Between Cells Using Ansys Fluent

- Related works

§ Jaewon Moon et al., Enhancing immersion cooling performance: Focusing on cooling fluid properties and battery cell arrangement angle., Thermal Science and Engineering Progress, 2026​​

Research Field 3.
Process safety
with Machine Learning

Hydrogen Dispersion Prediction Model

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Application 1

Development of a QPCR Model for Hydrogen Dispersion Prediction

Development of a Model for Hydrogen Dispersion Analysis Using an ANN and a Dataset with PHAST

- Related works

§ Junseo Lee et al., Development of the Quantitative Property-Consequence Relationship Model ..., ACS Omega, 2024

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Application 2

Comparison Between Machine Learning Models

Performance Comparison of Hydrogen Dispersion Prediction Models Optimized for Hyperparameters Using GA

- Related works

§ Junseo Lee et al., Performance analysis of optimized machine learning models for hydrogen..., Int. J. Hydrogen Energy, 2024

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