Assessment of the TRACE Code Using Transient Data from Maanshan PWR Nuclear Power Plant (NUREG/IA-0241)

On this page:

• Publication Information
• Abstract

Download complete document

• NUREG/IA-0241 (PDF - 1.84 MB)

Publication Information

Manuscript Completed: May 2010
Date Published: June 2010

Prepared by:
¹Jong-Rong Wang, ¹Hao-Tzu Lin, ²Chunkuan Shih

¹Institute of Nuclear Energy Research
Atomic Energy Council, R.O.C.
1000, Wenhua Rd., Chiaan Village, Lungtan, Taoyuan, 325
TAIWAN

²Institute of Nuclear Engineering and Science
National Tsing Hua University
101 Section 2, Kuang Fu Rd., HsinChu
TAIWAN

Antony Calvo, NRC Project Manager

Prepared as part of:
The Agreement on Research Participation and Technical Exchange
Under the International Code Assessment and Maintenance Program (CAMP)

Prepared for:
Division of Systems Analysis
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

Availability Notice

Abstract

This study consists of two steps. The first step is the establishment of TRACE (TRAC/RELAP Advanced Computational Engine) models for important components, such as pressurizers, steam generators, the feedwater control system, the steam dump control system, and so on, in Maanshan Nuclear Power Plant (NPP) using SNAP (Symbolic Nuclear Analysis Program)/TRACE. These component models were tested and compared with Maanshan startup test data to verify their accuracy. Key parameters were identified to refine the models further. The next step is the incorporation of the above component models into the Maanshan NPP TRACE model. TRACE transient analyses of scenarios such as load reduction and turbine trip were performed and their results were compared with the corresponding plant data from Maanshan startup tests. The TRACE model of Maanshan NPP is also used to analyze Loss of Flow transient as defined in FSAR Chapter 15 which includes Partial Loss of Flow (PLOF), Complete Loss of Flow-Under Voltage (CLOF-UV), and Complete Loss of Flow-Under Frequency (CLOF-UF). Analysis results indicate that the Maanshan NPP TRACE model predicts not only the behaviors of important plant parameters consistent with the plant data, but also their associated numerical values with respectable accuracy.