A Comparative Study of Fracture Toughness Distribution of Reactor Pressure Vessel Material with Generalized Extreme Value Distribution and Weibull Distribution in the Lower Self of Ductile to Brittle Transition Region

2021 ◽  
Author(s):  
K. Bhattacharyya
Keyword(s):  
Fracture Toughness ◽  
Comparative Study ◽  
Weibull Distribution ◽  
Pressure Vessel ◽  
Extreme Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Brittle Transition ◽  
Ductile To Brittle Transition ◽  
Vessel Material ◽  
Reactor Pressure

Bayesian Uncertainty Evaluation of Charpy Ductile-to-Brittle Transition Temperature for Reactor Pressure Vessel Steels

2020 ◽  
Author(s):  
Hisashi Takamizawa ◽  
Yutaka Nishiyama ◽  
Takashi Hirano
Keyword(s):  
Transition Temperature ◽  
Test Temperature ◽  
Pressure Vessel ◽  
Credible Interval ◽  
Irradiation Embrittlement ◽  
Brittle Transition ◽  
Pressure Vessel Steels ◽  
Brittle Transition Temperature ◽  
Ductile To Brittle Transition ◽  
Reactor Pressure

Abstract The irradiation embrittlement of reactor pressure vessel steels can be predicted using the ductile-to-brittle transition temperature (DBTT) shift obtained from Charpy impact tests. For the structural integrity assessment considering irradiation embrittlement, it is necessary to set margins for various uncertainties. It is important to understand what and how much factors contribute to the uncertainty. In the present study, a 34% credible interval value of Charpy DBTT at a 41J energy level (T41J) was evaluated by estimating the probability distributions of Charpy test data using Bayesian statistics. To fit the Charpy transition curves, a hyperbolic tangent with coefficients whose uncertainties depend on the test temperature was used. The probability distribution of T41J was estimated using Monte Carlo sampling and Bayesian inference. It was clarified that 34% of the credible-interval values of T41J before and after irradiation unchanged for base and weld metals when the number of specimens and test temperature were equivalent under un-irradiated and irradiated conditions. When the Charpy transition curve was determined by 12 specimens loaded in a surveillance test capsule, the estimated uncertainty of T41J was about 5 °C.

Variation of Beremin Model Parameters With Temperature by Monte Carlo Simulation

2019 ◽  
Vol 141 (2) ◽  
Author(s):  
K. Bhattacharyya ◽  
S. Acharyya ◽  
S. Dhar ◽  
J. Chattopadhyay
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Master Curve ◽  
Model Parameters ◽  
Three Point Bending ◽  
Brittle Transition ◽  
Different Temperatures ◽  
Ductile To Brittle Transition ◽  
Vessel Material ◽  
Reactor Pressure

In this work, variation of the Beremin parameters with temperature for reactor pressure vessel material 20MnMoNi55 steel is studied. Beremin model is used, including the effect of plastic strain as originally formulated in the Beremin model. A set of six tests are performed at a temperature of −110 °C in order to determine reference temperature (T0) and master curve for the entire ductile-to-brittle transition (DBT) region as per the ASTM Standard E1921. Monte Carlo simulation is employed to produce a large number of 1 T three-point bending specimen (TPB) fracture toughness data randomly drawn from the scatter band obtained from the master curve, at different temperatures of interest in the brittle dominated portion of DBT region to determine Beremin model parameters variation with temperatures.

Characteristic Values of Fracture Toughness Test Data

2016 ◽  
Author(s):  
Yuebing Li ◽  
Weiya Jin ◽  
Zengliang Gao ◽  
Zhenyu Ding ◽  
Yuebao Lei
Keyword(s):  
Fracture Toughness ◽  
Weibull Distribution ◽  
Pressure Vessel ◽  
Confidence Level ◽  
Fracture Toughness Test ◽  
Real Distribution ◽  
Characteristic Values ◽  
Distribution Type ◽  
Tolerance Factors ◽  
Reactor Pressure

Fracture toughness of reactor pressure vessel materials appears obvious scatter. It is desirable in assessment codes to characterize fracture toughness by a low fractile of its distribution. This low fractile is known as a characteristic value. However, the real distribution type is unknown, and usually assumed to be normal, lognormal or Weibull. In this paper, the characteristic values with given confidence level and probability are obtained by one-sided tolerance factors for normal, lognormal and Weibull distribution. These characteristic values are compared with that obtained with minimum of three equivalent.

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