(searched for: doi:10.4236/wjnst.2022.121001)
Computational Intelligence and Neuroscience, Volume 2022, pp 1-10; https://doi.org/10.1155/2022/4125833
Texture has strong expressiveness in picture art, and color texture features play an important role in composition. Together with texture, they can convey the artistic connotation of portrait, especially in oil painting. Therefore, in order to make the picture form oil painting style and oil painting schema, we need to study the texture and color texture in combination with the previous oil painting art images. But now, there are few samples of good oil paintings, so it is difficult to study the texture and color texture in oil paintings. Therefore, in order to form a unique artistic style of modern oil painting and promote the development of modern oil painting art, this paper studies the texture and color texture characteristics in the environment of few oil painting works. This paper establishes a model through deep neural network to extract the image incentive and color texture of oil painting art works, which provides guidance for promoting the development of oil painting art. The experiments in this paper show that the depth neural network has high definition for the extraction of texture and color texture of small sample oil painting images, which can reach more than 85%. It has high guiding significance for the research and creation of oil painting art.
Published: 1 January 2022
World Journal of Nuclear Science and Technology, Volume 12, pp 101-112; https://doi.org/10.4236/wjnst.2022.123009
It has been known that FAC, LDIE, cavitation and flashing are the damage mechanisms that can cause the pipe thickness of the secondary system of nuclear power plants thinner. Severe wall thinning was found in the MSR drain pipes at a Korean nuclear power plant a decade ago, and all the affected pipes were replaced with low alloy steel with higher chromium contents. Therefore, this study was conducted to reduce the possibility of similar thinning cases that may occur in the future by identifying the exact cause of thinning. ToSPACE and FLUENT codes and theoretical evaluation method were applied to analyze the causes of thinning. ToSPACE and FLUENT analyses and theoretical evaluation including all the operating conditions show a relatively large pressure drop and a pressure lower than the saturated vapor pressure in common at the end of the pipe entering the condenser. This means that flashing occurs at the end of the pipe under all operating conditions, and the effect can be greater than that of other parts. As a result, since severe wall thinning occurred at the end of the pipeline entering the condenser, it was evaluated that flashing by the high-velocity two-phase fluid was the direct cause of the wall thinning in the MSR drain pipes. The results of this study will contribute to establishing appropriate countermeasures in the event of pipe wall thinning in the future.