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Jin Ho Song

Yonsei University · Engineering

About the Lab

Professor Jin Ho Song's research lab specializes in severe accident phenomena in nuclear power plants, with a focus on molten core behavior, fuel-coolant interactions, and steam explosion dynamics. The lab integrates experimental studies using prototypic materials—such as corium and zirconia melts—with advanced simulation and machine learning models to predict and diagnose accident progression. Key research directions include the development of data-driven models for real-time accident diagnosis, understanding phase equilibrium and morphology of corium, and improving severe accident management guidelines (SAMG) through physics-informed modeling and simulation. The lab also emphasizes the integration of high-fidelity experimental data with AI techniques like LSTM networks for enhanced predictive capability in nuclear safety applications.

severe accident analysiscorium behaviorsteam explosionmachine learning in nuclear safetyaccident diagnosis

Research Overview

Papers
71
Total Citations
498
Papers (5y)
19
Primary Field
Engineering

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
19total
2022
2023
2024
2025
2026
Citations per year (5y)
69total
20222023202420252026

Selected Papers

15
1
Article|49 citations·2016
Low temperature solution processed Mn3O4 nanoparticles: Enhanced performance of electrochemical supercapacitors
Phuong T.M. Bui, Jin‐Ho Song, Zhenyu Li, M. Shaheer Akhtar, O–Bong Yang
SJR Q1Journal of Alloys and Compounds
Electronic, Optical and Magnetic MaterialsMaterials Science
2
Article|23 citations·2022
A simulation and machine learning informed diagnosis of the severe accidents
Jin‐Ho Song, Kwang-Soon Ha
SJR Q1Nuclear Engineering and DesignOA

We propose a simulation and machine learning informed model (SMLIM) for the diagnosis of severe accidents. A machine learning model which consisted of one hidden Long Short Term Memory (LSTM) layer and two dense layers with variations in the number of neurons and regularization parameters and an Adams optimizer was constructed for the multi-time step ahead forecasting analysis and the regression analysis. Using feature variables of lower plenum liquid level, core liquid level, reactor vessel pre

Aerospace EngineeringEngineering
3
Article|17 citations·2024
A machine learning informed prediction of severe accident progressions in nuclear power plants
Jin‐Ho Song, SungJoong Kim
SJR Q2Nuclear Engineering and TechnologyOA

A machine learning platform is proposed for the diagnosis of a severe accident progression in a nuclear power plant. To predict the key parameters for accident management including lost signals, a long short term memory (LSTM) network is proposed, where multiple accident scenarios are used for training. Training and test data were produced by MELCOR simulation of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident at unit 3. Feature variables were selected among plant parameters, where th

Aerospace EngineeringEngineering
4
Article|17 citations·2008
Performance and scaling analysis for a two-phase natural circulation loop
Jin‐Ho Song
SJR Q1International Communications in Heat and Mass Transfer
Aerospace EngineeringEngineering
5
Article|14 citations·2001
The one-dimensional two-fluid model with momentum flux parameters
Jin‐Ho Song, Mamoru Ishii
SJR Q1Nuclear Engineering and Design
Computational MechanicsEngineering
6
Article|12 citations·2016
Effect of melt water interaction configuration on the process of steam explosion
Jin‐Ho Song, YoungSu Na, Seong-Wan Hong, Seong-Ho Hong
SJR Q2Journal of Nuclear Science and Technology

Steam explosion experiments are performed at various modes of melt water interaction configuration using prototypic corium melt. The tests are performed to simulate both melt water interaction in a partially flooded cavity and melt water interaction in a cavity with submerged reactor. The tests are performed using zirconia and corium melts. The behavior of melt jet fragmentation during the flight in the air and fragmentation and mixing of melt jet in water is investigated by a high-speed video v

Materials ChemistryMaterials Science
7
Article|10 citations·2002
Spontaneous Steam Explosions Observed In The Fuel Coolant Interaction Experiments Using Reactor Materials
Jin‐Ho Song, Ikkyu Park, Yongseung Sin, Jonghwan Kim, Seong-Wan Hong, Byung-Tae Min, Hee-Dong Kim
SJR Q2Nuclear Engineering and Technology

The present paper reports spontaneous steam explosions observed in fuel coolant interaction experiments using prototypic reactor materials. Pure ZrO and a mixture of UO and ZrO are used. A high temperature molten material in the form of a jet is poured into a subcooled water pool located in a pressure vessel. An induction skull melting technique is used for the melting of the reactor material. In both tests using pure ZrO and a mixture of UO and ZrO, either a quenching or a spontaneous steam exp

Materials ChemistryMaterials Science
8
Article|9 citations·2020
Morphology and phase distributions of molten core in a reactor vessel
Jin‐Ho Song, Sangmo An, Jong‐Yun Kim, M. Barrachin, Bruno Piar, B. Michel
SJR Q1Journal of Nuclear MaterialsOA

Investigations on the morphology and phase equilibrium characteristics of corium were performed by a series of experiments in parallel with thermodynamic phase equilibrium analyses. Melting and solidification experiments were performed using corium consists of U, Zr, ZrO2, SS, and B4C. TROI-49 and TROI-50 experiments with corium compositions representing Pressurized Water Reactor (PWR), whose compositions are similar to those of MA-3 and MA-4 of OECD MASCA (Material Scaling) Program while amount

Materials ChemistryMaterials Science
9
Article|6 citations·2019
An analysis on the consequences of a severe accident initiated steam generator tube rupture
Jin‐Ho Song, ByungHee Lee, SungIl Kim, G. S. Ha
SJR Q1Nuclear Engineering and Design
Statistics, Probability and UncertaintyDecision Sciences
10
Article|6 citations·2023
A machine learning diagnosis of the severe accident progression
Jin‐Ho Song, Sungjoong Kim
SJR Q1Nuclear Engineering and Design
Materials ChemistryMaterials Science
11
Article|5 citations·2020
An analysis on the steam generator tube rupture events with core damage
Jin‐Ho Song, ByungHee Lee, SungIl Kim, Kwang-Soon Ha
SJR Q1Annals of Nuclear Energy
Statistics, Probability and UncertaintyDecision Sciences
12
Article|4 citations·2018
An analysis of radiological releases during a station black out accident for the APR1400
Thi Huong Vo, Dong Ha Kim, Jin‐Ho Song
SJR Q1Nuclear Engineering and Design
Safety, Risk, Reliability and QualityEngineering
13
Article|4 citations·2012
Improvement of Molten Core Cooling Strategy in a Severe Accident Management Guideline
Jin‐Ho Song, Changwook Huh, Namduk Suh
SJR Q2Nuclear Technology

Weaknesses of the current Severe Accident Management Guideline (SAMG) in handling the cooling of a molten core are discussed, and three improvements for the SAMG are presented. It is suggested that instrumentation to detect either a breach of the reactor vessel or a discharge of corium into the reactor cavity is essential to effectively perform the SAMG. A detailed analysis for a specific plant is necessary to make a decision as to whether preflooding or postflooding should be initiated for effe

Materials ChemistryMaterials Science
14
Article|3 citations·2020
Post-Fukushima challenges for the mitigation of severe accident consequences
Jin‐Ho Song, Sangmo An, Taewoon Kim, Kwang-Soon Ha
SJR Q2Nuclear Engineering and TechnologyOA

The Fukushima accident is characterized by the fact that three reactors at the same site experienced reactor vessel failure and the accident resulted in significant radiological release to the environment, which was about 1/10 of the Chernobyl releases. The safe removal of fuel debris in the reactor vessel and Primary Containment Vessel (PCV) and treatment of huge amount of contaminated water are the major issues for the decommissioning in coming decades. Discussions on the new researches effort

Safety, Risk, Reliability and QualityEngineering
15
Article|2 citations·2023
A comparative simulation of severe accident progressions by CINEMA and MAAP5
Jin‐Ho Song, Donggun Son, Jaehyun Ham, Junho Bae, Sung-Won Bae, Kwang-Soon Ha, Byungjo Kim, Sun Yoon, Bub-Dong Chung, SoonHo Park, Chang‐Hwan Park, JaeHwan Park
SJR Q1Nuclear Engineering and DesignOA

A newly developed code CINEMA is exercised for simulations of severe accident progressions in OPR1000 nuclear power plant. A Large Break Loss of Coolant (LBLOCA) and Station Black Out (SBO) initiated severe accidents are selected to cover a wide range of accident progression in terms of the system pressure, amount of core damage, and fission product release. The effects of mitigation actions by the operator are also considered. In parallel, independent simulations by the MAAP5 are carried out an

Materials ChemistryMaterials Science

Research Areas

Materials ChemistryAerospace EngineeringSafety, Risk, Reliability and QualityComputational MechanicsPulmonary and Respiratory MedicineStatistics, Probability and Uncertainty

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