Multiobjective evolutionary algorithm based on decomposition (MOEA/D) is the seminal framework of multiobjective evolutionary algorithms (MOEAs). To alleviate the nonuniformly distributed solutions generated by a fixed set of evenly distributed weight vectors in the presence of nonconvex and disconnected problems, an adaptive vector generation mechanism is proposed. A coevolution strategy and a vector generator are synergistically cooperated to remedy the weight vectors. Optimal weight vectors are generated to replace the useless weight vectors to assure that optimal solutions are distributed evenly. Experiment results indicate that this mechanism is efficient in improving the diversity of MOEA/D.

Fretting wear significantly limits the service life of metal O-rings operating under harsh conditions. To address this limitation, this study investigates the wear behavior of metal O-rings under equivalent accelerated reciprocating motion and establishes an accelerated life prediction model based on similarity theory. Fretting wear experiments were conducted using Inconel 718 alloy and 304 stainless steel to replicate service conditions in a controlled laboratory environment. Wear morphology was characterized using laser scanning confocal microscopy, revealing a progressive transition from mild abrasive and adhesive wear to severe abrasive wear accompanied by material spalling. Based on the experimental results, regression analysis was performed to estimate the acceleration model coefficients, leading to the formulation of an equivalent acceleration equation capable of predicting seal wear life under practical service conditions. The resulting equivalent acceleration model can establish a quantitative connection between the acceleration test and the operating conditions. This model can shorten the testing time and can be used to predict parameters related to the surface morphology of static seals, providing a theoretical and experimental basis for reliable life assessment. This provides a practical basis for improving the reliability and safe operation of metal O-ring seals in critical applications, including nuclear energy and chemical processing systems.

The control rod driving mechanism (CRDM) is one of the important equipments in the nuclear reactor, and its sealing shell is part of the pressure boundary of the nuclear reactor. The sealing shell is a pressure vessel made of two different material (austenitic stainless steel and nickel base alloy) cylinders welded by dissimilar metal welds. Product production process, in this dissimilar metal weld ray detection found suspected defects show. In this paper, the mechanism and process of the suspected defects are expounded through experimental verification, and it is proved that the suspected defects do not affect the quality of the weld.

The first step in the analysis of the contact mechanics and leakage prediction of metallic seals applied to nuclear reactor pressure vessels is the proper characterization of the surface topography. At present, two approaches are used for this characterization. On the one hand, there are non-parametric techniques such as HPD and PSD, which retain all the characteristics of the surfaces that have been measured, but the results are high dimensional; hence, they cannot be analyzed analytically. The other type is parametric fractal methods, where the parameters used are fractal dimension D and characteristic scale G, where the analytical derivations can be made; however, this leads to systematic deviations in the mechanical response due to some idealized assumptions, like isotropy, Gaussian distribution, and infinite self-similarity. In this article, we propose an equivalent fractal parameter inversion model (EFPIM) that does not rely on geometric fitting; instead, it fits the mechanical contact behavior of a physical surface. This inversion procedure reduces three errors simultaneously. Thus, the EFPIM does not use D and G as the geometrical fitting variables but rather redefines them as mechanically equivalent ones, the purpose of which is to minimize the difference between the W-M fractal surface and the real measured surface. To address the problem of constrained inversion, we adopt a genetic algorithm with BFGS. To prove its effectiveness, we carried out experiments on C-ring seal surfaces and found that the deviation in the contact area was reduced by an order of magnitude in comparison to traditional structure-function extraction, and the deviation in the approach and the maximum pressure were less than 2%. Moreover, the equivalent parameters shift systematically away from their geometric counterparts in the direction that compensates for the dominant non-ideal deficit of the W-M surface; when both parameters are free, the equivalent fractal dimension decreases, while the equivalent characteristic scale increases, compensating for the absent non-Gaussian deep valleys of ideal W-M surfaces. Existing models of analytical contact and leakage may be directly implemented using equivalent parameters and with accuracy comparable to that of FFT-based simulations, with the modest cost of the offline computations.