scholarly journals A New Stress Intensity Factor Solution Based on the Response Surface Method for Nozzle Corner Cracks in Nuclear Reactor for Thermal Energy Generation

2021 ◽  
Vol 9 ◽  
Author(s):  
Ting Jin ◽  
Zhibo He ◽  
Pan Liu ◽  
Zihang Wang ◽  
Yuebing Li ◽  
...  

As considered carbon-free, the use of nuclear energy for thermal energy generation may expand in the future, with the guarantee of safe operation of the nuclear reactor. In a nuclear reactor pressure vessel (RPV), the nozzle area is an important part of the safe operation. It bears internal pressure, axial force, and overall moment, and at the same time bears higher stress than the rest of the vessel. To assess the integrity of the nozzle structure with a crack under combined load, an accurate solution of stress intensity factors (SIF) along the crack front is necessary. To obtain the SIF, this paper proposes a solution method that uses the stress on the crack surface and the response surface method to fit the stress under the framework of the linear superposition technique. This method is the first choice to determine a series of influence coefficients under unit pressure load. Then, one can estimate the SIFs by superposition method for an arbitrary stress distribution resulted from combined loads. The proposed solution is verified for a typical RPV with cracks under internal pressure, axial force, and global bending moment. The results reveal that the proposed solution is in good agreement with the existing solutions under internal pressure. Therefore, it can be obtained that this solution can be effectively used for the structural integrity assessment of RPV with nozzle corner cracks.

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3552 ◽  
Author(s):  
Chun-Yi Zhang ◽  
Jing-Shan Wei ◽  
Ze Wang ◽  
Zhe-Shan Yuan ◽  
Cheng-Wei Fei ◽  
...  

To reveal the effect of high-temperature creep on the blade-tip radial running clearance of aeroengine high-pressure turbines, a distributed collaborative generalized regression extremum neural network is proposed by absorbing the heuristic thoughts of distributed collaborative response surface method and the generalized extremum neural network, in order to improve the reliability analysis of blade-tip clearance with creep behavior in terms of modeling precision and simulation efficiency. In this method, the generalized extremum neural network was used to handle the transients by simplifying the response process as one extremum and to address the strong nonlinearity by means of its nonlinear mapping ability. The distributed collaborative response surface method was applied to handle multi-object multi-discipline analysis, by decomposing one “big” model with hyperparameters and high nonlinearity into a series of “small” sub-models with few parameters and low nonlinearity. Based on the developed method, the blade-tip clearance reliability analysis of an aeroengine high-pressure turbine was performed subject to the creep behaviors of structural materials, by considering the randomness of influencing parameters such as gas temperature, rotational speed, material parameters, convective heat transfer coefficient, and so forth. It was found that the reliability degree of the clearance is 0.9909 when the allowable value is 2.2 mm, and the creep deformation of the clearance presents a normal distribution with a mean of 1.9829 mm and a standard deviation of 0.07539 mm. Based on a comparison of the methods, it is demonstrated that the proposed method requires a computing time of 1.201 s and has a computational accuracy of 99.929% over 104 simulations, which are improvements of 70.5% and 1.23%, respectively, relative to the distributed collaborative response surface method. Meanwhile, the high efficiency and high precision of the presented approach become more obvious with the increasing simulations. The efforts of this study provide a promising approach to improve the dynamic reliability analysis of complex structures.


2021 ◽  
Author(s):  
Alfikri Khair ◽  
Haryudini A. Putri ◽  
Suprapto Suprapto ◽  
Yatim L. Ni’mah

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