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RISS 인기검색어
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- 저자 : Fynan, (검색결과 3 건)
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Fynan, Douglas A.,Park, Jin Hee Elsevier 2018 Annals of nuclear energy Vol.118 No.-
<P><B>Abstract</B></P> <P>The study derives the optimal working fluid charge of a closed-circuit intermediate natural circulation heat transport loop based on the passive residual heat removal system (PRHRS) of SMART (System-integrated Modular Advanced ReacTor). The study finds that efficient natural circulation flow and heat transfer regimes can be maintained in a narrow band of working fluid charge mass owing to the small secondary side volume of the once-through helical-coil steam generator design of SMART. Overcharging condition is a severe passive system degradation mode that quickly leads to system failure. Overcharging is characterized by sustained two-phase flow instabilities, mainly liquid slugging in the hot leg of the PRHRS, and an increased operating pressure of the PRHRS coupled with a compensating increase in the operating pressure of the reactor coolant system (RCS). Increased pressures maintain the required temperature differential across the steam generator tubes and heat sink heat exchanger to achieve a prescribed quasi-steady state heat removal rate capacity. Undercharging condition is a benign degradation mode relative to overcharging and is characterized by a slow upward drift of the RCS pressure and temperature of the liquid water entering the primary side of the steam generator. Only the undercharged case of a completely dry steam generator secondary side leads to PRHRS failure-to-start via vapor lock.</P>
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Fynan, Douglas A.,Ahn, Kwang-Il Elsevier 2016 Nuclear engineering and design Vol.310 No.-
<P><B>Abstract</B></P> <P>Characteristic pressure drop-flow rate curves are generated for all row numbers of the OPR1000 steam generators (SGs), representative of Combustion Engineering (CE) type SGs featuring square bend U-tubes. The pressure drop-flow rate curves are applicable to severe accident natural circulations of single-phase superheated steam during high pressure station blackout sequences with failed auxiliary feedwater and dry secondary side which are closely related to the thermally induced steam generator tube rupture event. The pressure drop-flow rate curves which determine the recirculation rate through the SG tubes are dependent on the tube bundle geometry and hydraulic diameter of the tubes. The larger CE type SGs have greater variation of tube length and height as a function of row number with forward flow of steam favored in the longer and taller high row number tubes and reverse flow favored in the short low row number tubes. Friction loss, natural convection heat transfer coefficients, and temperature differentials from the primary to secondary side are dominant parameters affecting the recirculation rate. The need for correlation development for natural convection heat transfer coefficients for external flow over tube bundles currently not modeled in system codes is discussed.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Pressure drop-flow rate curves for superheated steam in U-tubes were generated. </LI> <LI> Forward flow of hot steam is favored in the longer and taller U-tubes. </LI> <LI> Reverse flow of cold steam is favored in short U-tubes. </LI> <LI> Steam generator U-tube bundle geometry and tube diameter are important. </LI> <LI> Need for correlation development for natural convention heat transfer coefficient. </LI> </UL> </P>
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FYNAN DOUGLAS ANDREW,안광일 한국원자력학회 2016 Nuclear Engineering and Technology Vol.48 No.3
The Gaussian process model (GPM) is a flexible surrogate model that can be used fornonparametric regression for multivariate problems. A unique feature of the GPM is that aprediction variance is automatically provided with the regression function. In this paper,we estimate the safety margin of a nuclear power plant by performing regression on theoutput of best-estimate simulations of a large-break loss-of-coolant accident with samplingof safety system configuration, sequence timing, technical specifications, and thermalhydraulic parameter uncertainties. The key aspect of our approach is that the GPMregression is only performed on the dominant input variables, the safety injection flow rateand the delay time for AC powered pumps to start representing sequence timing uncertainty,providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the codeoutput and are implicitly treated in the GPM in the noise variance term, providing localuncertainty bounds for the peak clad temperature. We discuss the applicability of theforegoing method to reduce the use of conservative assumptions in best estimate plusuncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitionswhile dealing with a large number of uncertainties.
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