PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Young Ho Chae Co-author(s): Hyeonmin Kim, hyeonmin@kaeri.re.kr
Poong Hyun Seong, phseong1@kaist.ac.kr
| Development of a physics informed neural network based simulation methodology for DPSA |
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| A nuclear power plant is a safety-critical system with large size and high complexity. Therefore, various methods were developed to identify possible accidents and deal with them. To broadly classify the methods, there are experiment-based methods and simulation-based methods. However, the experiment-based method, in reality, has several limitations. Therefore, various simulation-based analysis methods were developed. Most of the simulation-based analysis methods were highly dependent on numerical methods. Therefore, if the number of nodes and time units are divided to increase the analysis resolution, the time required for calculation tends to increase exponentially as the number of nodes is divided. Therefore, in this paper, to accelerate the simulation we developed artificial intelligence based simulation acceleration method. As an algorithm for AI-based simulation, physics informed neural network algorithm is implemented for convergence speed and extrapolation robustness. By using the suggested method, dynamic event tree based dynamic probabilistic safety assessment can be conducted which is almost impossible due to the calculation speed of the physical process model. |
Paper CY266 Preview
Author and Presentation Info
Lead Author Name: Young Ho Chae (cyhproto@kaist.ac.kr)
Bio:
Country: South Korea
Company: KAIST
Job Title: Researcher (Ph.D Candidate)
Bio:
Country: South Korea
Company: KAIST
Job Title: Researcher (Ph.D Candidate)