Search

TRACE is developed by U.S. NRC for the nuclear power plants (NPPs) safety analysis. We focus on the establishment and application of TRACE/FRAPTRAN/SNAP models for Chinshan NPP (BWR/4) spent fuel pool in this research. The geometry is 12.17 m × 7.87 m × 11.61 m for the spent fuel pool. In this study, there are three TRACE/SNAP models: one-channel, two-channel, and multi-channel TRACE/SNAP model. Additionally, the cooling system failure of the spent fuel pool was simulated and analyzed by using the above models. According to the analysis results, the peak cladding temperature response was more accurate in the multi-channel TRACE/SNAP model. The results depicted that the uncovered of the fuels occurred at 2.7 day after the cooling system failed. In order to estimate the detailed fuel rods performance, FRAPTRAN code was used in this research. According to the results of FRAPTRAN, the highest cladding temperature located on the node 21 of the fuel rod (the highest node at node 23) and the cladding burst roughly after 3.7 day., {"references":["Taiwan Power Company, \"Final Safety Analysis Report for Chinshan\nNuclear Power Station Units 1&2\", 1999.","U.S. NRC, \"TRACE V5.0 User's Manual\", 2010.","K.J. Geelhood, W.G. Luscher, C.E. Beyer, J.M. Cuta, \"FRAPTRAN 1.4:\nA Computer Code for the Transient Analysis of Oxide Fuel Rods\",\nNUREG/CR-7023, Vol. 1, 2010.","Applied Programming Technology, Inc., \"Symbolic nuclear analysis\npackage (SNAP) user's manual\", 2012.","J.R. Wang, H.T. Lin, Y.S. Tseng, C. Shih, \"Application of TRACE and\nCFD in the spent fuel pool of Chinshan nuclear power plant\", Applied\nMechanics and Materials Vol. 145, pp. 78-82, 2012.","J.R. Wang, H.T. Lin, W.W. Li, H.C. Chen, C. Shih, \"The Spent Fuel Pool\nAnalysis Of Chinshan Nuclear Power Plant By Using\nTRACE/FRAPCON-3.4\", Advanced Materials Research, Vols. 690-693,\npp. 2947-2950, 2013.","J.R. Wang, H.T. Lin, W.W. Li, S.W. Chen, C. Shih, \"Application of\nTRACE and FRAPTRAN in the Spent Fuel Pool of Chinshan Nuclear\nPower Plant\", Applied Mechanics and Materials, Vols. 479-480, pp.\n543-547, 2014.","U.S. NRC, \"Standard Review Plan for the Review of Safety Analysis\nReports for Nuclear Power Plants: LWR Edition-Auxiliary Systems\",\nNUREG-0800, Chapter 9, 2007."]}

In this research, TRACE model of Chinshan BWR/4 nuclear power plant (NPP) has been developed for the simulation and analysis of ultimate response guideline (URG).The main actions of URG are the depressurization and low pressure water injection of reactor and containment venting. This research focuses to verify the URG efficiency under Fukushima-like conditions. TRACE analysis results show that the URG can keep the PCT below the criteria 1088.7 K under Fukushima-like conditions. It indicated that Chinshan NPP was safe., {"references":["K.S. Liang, S.C. Chiang, Y.F. Hsu, H.J. Young, B.S. Pei, L.C. Wang,\n\"The ultimate emergency measures to secure a NPP under an accidental\ncondition with no designed power or water supply,\" Nuclear\nEngineering and Design, 253, pp.259-268,2012.","U.S. NRC, \"TRACE V5.0 User's Manual\", 2010.","J. R. Wang, H. T. Lin, Y. H. Cheng, W. C. Wang, C. Shih, \"TRACE\nmodeling and its verification using Maanshan PWR start-up tests\",\nAnnals of Nuclear Energy, 36, pp. 527-536, 2009.","C. H. Chen, J. R. Wang, H. T. Lin, C. Shih, \"ATWS analysis for\nMaanshan PWR using TRACE/SNAP code\", Annals of Nuclear Energy,\n72, pp. 1-10, 2014.","H. T. Lin, J. R. Wang, C. Shih, \"The development and assessment of\nTRACE model for Lungmen ABWR\", Kerntechnik, 76, pp. 205-215,\n2011.","H. T. Lin, J. R. Wang, H. C. Chen, C. Shih, \"The development and\nassessment of TRACE/PARCS model for Lungmen ABWR\", Nuclear\nEngineering and Design, 273, pp. 241-250, 2014.","C. Y. Chen, C. Shih, J. R. Wang, H. T. Lin, \"Sensitivity study on the\ncounter-current flow limitation in the DEGLBLOCA with the TRACE\ncode\", Annals of Nuclear Energy, 57,pp. 121-129, 2013.","C. Y. Chen, C. Shih, J. R. Wang, \"The alternate mitigation strategies on\nthe extreme event of the LOCA and the SBO with the TRACE Chinshan\nBWR4 model\", Nuclear Engineering and Design, 256, pp. 332-340,\n2013.","J. H. Lee, J. R. Wang, H. T. Lin, S. M. Yang, C. Shih, \"TRACE\nmodeling of Chinshan load rejection startup test\", American Nuclear\nSociety: 2009 Annual Meeting.\n[10] Taiwan Power Company, \"Final Safety Analysis Report for Chinshan\nNuclear Power Station Units 1&2\", 1999.\n[11] W. S. Hsu, J. R. Tang, \"The calculation notes of the startup test\nbenchmark analysis for the Chinshan RETRAN-02 model\", INER\nreport, 1997."]}

Fuel rod analysis program transient (FRAPTRAN) code was used to study the fuel rod performance during a postulated large break loss of coolant accident (LBLOCA) in Maanshan nuclear power plant (NPP). Previous transient results from thermal hydraulic code, TRACE, with the same LBLOCA scenario, were used as input boundary conditions for FRAPTRAN. The simulation results showed that the peak cladding temperatures and the fuel centerline temperatures were all below the 10CFR50.46 LOCA criteria. In addition, the maximum hoop stress was 18 MPa and the oxide thickness was 0.003mm for the present simulation cases, which are all within the safety operation ranges. The present study confirms that this analysis method, the FRAPTRAN code combined with TRACE, is an appropriate approach to predict the fuel integrity under LBLOCA with operational ECCS. &nbsp

Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the overpressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study., {"references":["NRC,\"TRACE V5.0 User's Manual\", Office of Nuclear Regulatory\nResearch, 2010.","K. J. Geelhood, W. G. Luscher, C. E. Beyer and J. M. Cuta, \"FRAPTRAN\n1.4: A Computer Code for the Transient Analysis of Oxide Fuel Rods\",\nNUREG/CR-7023, Vol. 1, 2011.","Taiwan Power Company, \"Final Safety Analysis Report for Kousheng\nNuclear Power Station Units 1&2 (FSAR),\"2001.","R.Y. Yuann,H.T. Lin, \"Guideline of Generating Parameters for Reload\nLicensing Analyses for Kuosheng Units 1 and 2,\" INER report,\nINER-6529R,2009.","K. Y. Lin, \"Verification of the Kuosheng BWR/6 TRACE Model with\nLoad Rejection Startup Test,\" ASME 2012 V&V, 2012.","J. R. Wang et al, \"Kuosheng Startup Tests Transient Analyses,\" INER\nreport, INER-0965, 1989.","U.S. NRC,\" Standard Review Plan\", NUREG-0800, 2007."]}

This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability., {"references":["K. Saravanan and H. Mahalakshmi, \"Brain-computer control of wheelchair concluded mobile robot,\" International Journal of Advanced Research in Robotics and Development, vol. 1, no. 1, pp. 1–5, 2013.","S. Sutton, M. Braren, J. Zubin, and E. R. John, \"Evoked-potential correlates of stimulus uncertainty,\" Science, vol. 150, no. 3700, pp. 1187–1188, 1965.","M. Kutas and S. A. Hillyard, \"Reading senseless sentences: Brain potentials reflect semantic incongruity,\" Science, vol. 207, no.4427, pp. 203–205, 1980.","E. Donchin, K. M. Spencer, and R. Wijesinghe, \"The Mental Prosthesis: Assessing the Speed of a P300-Based Brain–Computer Interface,\" IEEE Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 174–179, 2000.","Y. H. Liu, , H. P. Huang, , T. H. Huang, , Z. H. Kang, and J. T. Teng, \"Controlling a Rehabilitation Robot with Brain-Machine Interface: An approach based on Independent Component Analysis and Multiple Kernel Learning,\" International Journal of Automation and Smart Technology, vol. 3, no. 1, pp. 67–75, 2013.","Y. Su, J. Dai, X. Liu, Q. Xu, Y. Zhuang, W. Chen, and X. Zheng, \"EEG channel evaluation and selection by rough set in P300 BCI,\" Journal of Computational Information Systems, vol. 6, no. 6, pp. 1727–1735, 2010.","D. V. Renterghem, B. Wyns, and D. Devlaminck, \"Shared control between P300 BCI and robotic arm,\" International Journal of Bioelectromagnetism, vol. 13, no. 1, pp. 2–4, 2011.","I. H. Hasan, , A. R. Ramli, , S. A. Ahmad, and R. Osman, \"P300-Based EEG Signal Interpretation System for Robot Navigation Control,\" World Applied Sciences Journal, vol. 26, no. 5, pp. 566–572, 2013.","W. Chen, J. Zhang, Y. Li, Y. Qi, Y. Su, B. Wu, S. Zhang, J. Dai, and X. Zheng, \"A P300 based online brain-computer interface system for virtual hand control,\" Journal of Zhejiang University SCIENCE C, vol. 11, no. 8, pp. 587–597, 2010.\n[10]\tN. Birbaumer, \"Breaking the silence: Brain–computer interfaces (BCI) for communication and motor control,\" Psychophysiology, vol. 43, no. 6, pp. 517–532, 2006.\n[11]\t\tB. Hong, F. Guo, T. Liu, X. Gao, and S. Gao, \"N200-speller using motion-onset visual response,\" Clinical Neurophysiology, vol. 120, no. 9, pp. 1658–1666, 2009.\n[12]\tL. A. Farwell, and E. Donchin, \"Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials,\" Electroencephalogr Clin. Neurophysiol, vol. 70, no. 6, pp. 510–23, 1988.\n[13]\tJ. N. Mak, D. J. McFarland, T. M. Vaughan, L. M. McCane, P. Z. Tsui, D. J. Zeitlin, E. W. Sellers, and J. R. Wolpaw, \"EEG correlates of P300-based brain-computer interface (BCI) performance in people with amyotrophic lateral sclerosis,\" J. Neural Eng., vol. 9, no. 2:026014, 2012.\n[14]\tR. Fazel-Rezai, B. Z. Allison, C. Guger, E. W. Sellers, S. C. Kleih, and A. Kübler, \"P300 brain computer interface: current challenges and emerging trends,\" Front. Neuroeng., vol. 5, doi: 10.3389/fneng.2012.00014, July 2012.\n[15]\tD. Zhang, H. Song, H. Xu, W. Wu, S. Gao, and B. Hong, \"An N200 speller integrating the spatial profile for the detection of the non-control state,\" Journal of Neural Engineering, vol. 9, No. 2, doi:10.1088/1741–2560/9/2/026016, 2012.\n[16]\tB. Hong, F. Guo, T. Liu, X. Gao, S. Gao, \"N200-speller using motion-onset visual response,\" Clin. Neurophysiol, vol. 120, pp. 1658–66, Sep 2009.\n[17]\tL. Tonin, E. Menegatti, M. Cavinato, C. D'Avanzo, M. Pirini, A. Merico, L. Piron, K. Priftis, S. Silvoni, C. Volpato, and F. Piccione, \"Evaluation of a robot as embodied interface for brain computer interface systems,\" International Journal of Bioelectromagnetism, vol. 11, no.2, pp. 97–104, 2009.\n[18]\tP. Belluomo, M. Bucolo, L. Fortuna, and M. Frasca, \"Robot Control through Brain-Computer Interface for Pattern Generation,\" Complex Systems, vol. 20, no. 3, pp. 243–251, 2012.\n[19]\tT. Carlson and J. del R Millan, \"Brain-controlled wheelchairs: a robotic architecture,\" IEEE Robotics and Automation Magazine, vol. 20, no. 1, pp. 65–73, 2013.\n[20]\tR. Singla and B. A. Haseena, \"BCI-based wheelchair control using steady state visual evoked potentials and support vector machines,\" International Journal of Soft Computing and Engineering, vol. 3, no. 3, pp. 46–52, 2013.\n[21]\tK. T. Sun, T. W. Huang, and M. C. Chen, \"Design of Chinese spelling system based on ERPs,\" in Proc. 11th IEEE International Conference on Bioinformatics and Bioengineering, Taichung, Taiwan, 2011, pp. 310–313.\n[22]\tK. T. Sun, T. W. Huang, M. C. Chen, and Y. C. Li, \"Design of Chinese spelling system,\" in Proc. 2nd Annual International Conference on Advanced Topics in Artificial Intelligence, Fort Canning, Singapore, 2011, pp.26–31."]}

This analysis of Kuosheng nuclear power plant (NPP) was performed mainly by TRACE, assisted with FRAPTRAN and FRAPCON. SNAP v2.2.1 and TRACE v5.0p3 are used to develop the Kuosheng NPP SPU TRACE model which can simulate the turbine trip without bypass transient. From the analysis of TRACE, the important parameters such as dome pressure, coolant temperature and pressure can be determined. Through these parameters, comparing with the criteria which were formulated by United States Nuclear Regulatory Commission (U.S. NRC), we can determine whether the Kuoshengnuclear power plant failed or not in the accident analysis. However, from the data of TRACE, the fuel rods status cannot be determined. With the information from TRACE and burn-up analysis obtained from FRAPCON, FRAPTRAN analyzes more details about the fuel rods in this transient. Besides, through the SNAP interface, the data results can be presented as an animation. From the animation, the TRACE and FRAPTRAN data can be merged together that may be realized by the readers more easily. In this research, TRACE showed that the maximum dome pressure of the reactor reaches to 8.32 MPa, which is lower than the acceptance limit 9.58 MPa. Furthermore, FRAPTRAN revels that the maximum strain is about 0.00165, which is below the criteria 0.01. In addition, cladding enthalpy is 52.44 cal/g which is lower than 170 cal/g specified by the USNRC NUREG-0800 Standard Review Plan., {"references":["Taiwan Power Company, \"Final Safety Analysis Report for Kuosheng\nNuclear Power Station Units 1&2 (FSAR)\", 2001.","U.S. NRC, \"TRACE V5.0 user's manual\", Division of Safety Analysis\nOffice of Nuclear Regulatory Research U.S. Nuclear Regulatory\nCommission Washington, DC 20555-0001, 2010.","K.J. Geelhood, W.G. Luscher, C.E. Beyer, \"FRAPTRAN 1.4: Integral\nAssessment\", Pacific Northwest National LaboratoryP.O. Box 999\nRichland, WA 99352.","U.S. NRC, \"Symbolic Nuclear Analysis Package (SNAP) User's\nManual\", Applied Programming Technology, Inc. 2007","INER, \"Guideline of Generating Parameters for Reload Licensing\nAnalyses for Kuosheng Units 1 and 2\", INER-6529R, 2009.","Taiwan Power Company, \"Technical Specifications Revision 0,\nKuosheng Nuclear Power Station Units 1 & 2\", January 2008."]}

The dry-storage systems of nuclear power plants (NPPs) in Taiwan have become one of the major safety concerns. There are two steps considered in this study. The first step is the verification of the TRACE by using VSC-17 experimental data. The results of TRACE were similar to the VSC-17 data. It indicates that TRACE has the respectable accuracy in the simulation and analysis of the dry-storage systems. The next step is the application of TRACE in the dry-storage system of Kuosheng NPP (BWR/6). Kuosheng NPP is the second BWR NPP of Taiwan Power Company. In order to solve the storage of the spent fuels, Taiwan Power Company developed the new dry-storage system for Kuosheng NPP. In this step, the dry-storage system model of Kuosheng NPP was established by TRACE. Then, the steady state simulation of this model was performed and the results of TRACE were compared with the Kuosheng NPP data. Finally, this model was used to perform the safety analysis of Kuosheng NPP dry-storage system. Besides, FRAPTRAN was used tocalculate the transient performance of fuel rods., {"references":["C. Shih, Y. S. Tseng,\"The final report of parallel validation study for KSDSS,\"2013.","NRC, \"TRACE V5.0 User's Manual\", Office of Nuclear Regulatory Research, 2010.","F.Mascari, A. M.Colletti, B. G. Woods, A. M. Costa, K. Welter, M. L. Richiusa, F. D. Rosa, F.D'Auria, G.Vella, \"Analyses of Natural Circulation Phenomena Typical of the MASLWR by Using The TRACE V5 Code,\" 2013.","Pacific Northwest Laboratory, \"Performance testing and Analyses of the VSC-17 Ventilated Concrete Cask,\" 1992.","Taipower Co., \"FSAR of Kuosheng NPP Dry Storage System,\"2013."]}