scholarly journals Water Droplet Erosion Resistance of Aluminizing Diffusion Coatings on Steel Tubes

2018 ◽  
Vol 59 (2) ◽  
pp. 237-243 ◽  
Author(s):  
Yoshinori I. Oka ◽  
Keiji Ishikawa ◽  
Hideshi Tezuka
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Dingjun Li ◽  
Peng Jiang ◽  
Fan Sun ◽  
Xiaohu Yuan ◽  
Jianpu Zhang ◽  
...  

Abstract The water-droplet erosion of low-pressure steam turbine blades under wet steam environments can alter the vibration characteristics of the blade, and lead to its premature failure. Using high-velocity oxygen-fuel (HVOF) sprayed water-droplet erosion resistant coating is beneficial in preventing the erosion failure, while the erosion behavior of such coatings is still not revealed so far. Here, we examined the water-droplet erosion resistance of Cr3C2–25NiCr and WC–10Co–4Cr HVOF sprayed coatings using a pulsed water jet device with different impingement angles. Combined with microscopic characterization, indentation, and adhesion tests, we found that: (1) both of the coatings exhibited a similar three-stage erosion behavior, from the formation of discrete erosion surface cavities and continuous grooves to the broadening and deepening of the groove, (2) the erosion rate accelerates with the increasing impingement angle of the water jet; besides, the impingement angle had a nonlinear effect on the cumulative mass loss, and 30° sample exhibited the smallest mass loss per unit area (3) an improvement in the interfacial adhesion strength, fracture toughness, and hardness of the coating enhanced the water-droplet erosion resistance. These results provide guidance pertaining to the engineering application of water erosion protective coatings on steam turbine blades.


Author(s):  
Zheyuan Zhang ◽  
Tianyuan Liu ◽  
Di Zhang ◽  
Yonghui Xie

Abstract In this paper, a method for predicting remaining useful life (RUL) of turbine blade under water droplet erosion (WDE) based on image recognition and machine learning is presented. Using the experimental rig for testing the WDE characteristics of materials, the morphology pictures of specimen surface at different times in the process of WDE are collected. According to the data processing method of ASTM-G73 and the cumulative erosion-time curves, the WDE stages of materials is quantitatively divided and the WDE life coefficient (ζ) is defined. The life coefficient (ζ) could be used to calculate the RUL of turbine blades. One convolutional neural network model and three machine learning models are adopted to train and predict the image dataset. Then the training process and feature maps of the Resnet model are studied in detail. It is found that the highest prediction accuracy of the method proposed in this paper can be 0.949, which is considered acceptable to provide reference for turbine overhaul period and blade replacement time.


Author(s):  
Fang Li ◽  
Shunsen Wang ◽  
Juan Di ◽  
Zhenping Feng

Abstract In order to study the effect of initial surface roughness on water droplet erosion resistance of last stage blade substrate of steam turbine, eight 17-4PH samples were grounded and velvet polished by different mesh metallographic sandpaper to establish sample with different initial surface roughness. The water droplet erosion experiments were carried out in the highspeed jet water erosion experiment system, and the mass and micro-morphology of each sample were measured by using precision electronic balance and ultra-depth of field microscope respectively at each experimental stage, and the measurement of water erosion trace width and maximum water erosion depth were also completed at the same time. On the basis of experiments, LS-DYNA was used for numerical simulation to verify the reliability of experimental results again. Results show that the smoother the initial surface of sample, then the smaller the mass loss, the stronger its water erosion resistance. On the contrary, the rougher the initial surface of sample, the more severe the surface irregularity, the more times the water droplets concentrated at the lowest point of pit when water droplets flow laterally after impact is completed, thus accelerating the formation of initial crack and lateral expansion, the poorer the water erosion resistance of sample. At same water erosion time, the smoother the sample surface, the later the complete erosion trace appear, the narrower the water erosion trace width. However, the maximum water erosion depth of sample is not affected by the initial surface roughness. The numerical simulation results are in good agreement with the experimental results.


2021 ◽  
Author(s):  
Rizwan Ahmed Shaik ◽  
Abdullahi K Gujba ◽  
Martin D. Pugh ◽  
Mamoun Medraj

Wear ◽  
2019 ◽  
Vol 426-427 ◽  
pp. 507-517 ◽  
Author(s):  
Charles B. Burson-Thomas ◽  
Richard Wellman ◽  
Terry J. Harvey ◽  
Robert J.K. Wood

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