scholarly journals Optimization of solid particle erosion of 2205 duplex stainless steel under air jet using Taguchi method

2021 ◽  
Vol 1057 (1) ◽  
pp. 012073
Author(s):  
Roshan Kuruvila ◽  
S Thirumalai Kumaran ◽  
M Adam Khan ◽  
M Uthayakumar
Author(s):  
Risa Okita ◽  
Yongli Zhang ◽  
Brenton S. McLaury ◽  
Siamack A. Shirazi ◽  
Edmund F. Rybicki

Although solid particle erosion has been examined extensively in the literature for dry gas and vacuum conditions, several parameters affecting solid particle erosion in liquids are not fully understood and need additional investigation. In this investigation, erosion ratios of two materials have been measured in gas and also in liquids with various liquid viscosities and abrasive particle sizes and shapes. Solid particle erosion ratios for aluminum 6061-T6 and 316 stainless steel have been measured for a direct impingement flow condition using a submerged jet geometry, with liquid viscosities of 1, 10, 25, and 50 cP. Sharp and rounded sand particles with average sizes of 20, 150, and 300 μm, as well as spherical glass beads with average sizes of 50, 150 and 350 μm, were used as abrasives. To make comparisons of erosion in gas and liquids, erosion ratios of the same materials in air were measured for sands and glass beads with the particle sizes of 150 and 300 μm. Based on these erosion measurements in gas and liquids, several important observations were made: (1) Particle size did not affect the erosion magnitude for gas while it did for viscous liquids. (2) Although aluminum and stainless steel have significant differences in hardness and material characteristics, the mass losses of these materials were nearly the same for the same mass of impacting particles in both liquid and gas. (3) The most important observation from these erosion tests is that the shape of the particles did not significantly affect the trend of erosion results as liquid viscosity varied. This has an important implication on particle trajectory modeling where it is generally assumed that particles are spherical in shape. Additionally, the particle velocities measured with the Laser Doppler Velocimetry (LDV) near the wall were incorporated into the erosion equations to predict the erosion ratio in liquid for each test condition. The calculated erosion ratios are compared to the measured erosion ratios for the liquid case. The calculated results agree with the trend of the experimental data.


2020 ◽  
Vol 277 ◽  
pp. 128381
Author(s):  
A. Ruiz-Rios ◽  
C. López-García ◽  
I. Campos-Silva

2020 ◽  
Vol 8 (5) ◽  
pp. 1605-1610 ◽  

In this present research work the solid particle erosion test carried on uncoated samples (Ti-31), and HVOF sprayed 10%Al2O3 -CoCrAlTaY on Ti-31 are made. Erosion test are done with impact angles of 30º, 60º and 90º. Solid particle erosion studies were carried out using air jet erosion test rig as per ASTM G76-02 standard.All the three angles of uncoated alloys exhibit erosion damage under ductile mode and less amount of erosive loss compared HVOF coated samples. The HVOF sprayed coated Ti-31 at various impact angles is brittle mode. The mechanism of material removal during erosion of brittle materials is explained by using SEM micrographs.


2020 ◽  
Vol 20 (7) ◽  
pp. 4513-4516
Author(s):  
Kwang-Hu Jung ◽  
Seong-Jong Kim

This study evaluated the solid particle erosion characteristics of 2.25Cr–1Mo steel with aging time. Aging was performed at 750 °C until 100 h. Specimens aged at each time were characterized by microstructure analysis and Micro-Vickers hardness. An erosion experiment was conducted using 100~200 μm of stainless steel shot at a flow velocity of 20 m/s for 4 h. A consequently, a microstructure degradation phenomenon in which Cr-rich carbide was coarsened occurred, and the surface hardness decreased by 45%. With a decrease in the hardness, the solid particle erosion damage increased and the erosion damage type changed.


Author(s):  
Ankit Singh ◽  
Sudhanshu Kumar Pandey ◽  
Ram Mishra ◽  
Dr. Uday Krishna Ravella ◽  

2015 ◽  
Vol 55 (5) ◽  
pp. 1123-1130 ◽  
Author(s):  
Ashish Selokar ◽  
Ujjwal Prakash ◽  
Desh Bandhu Goel ◽  
Balabhadrapatruni Venkata Manoj Kumar

Wear ◽  
2006 ◽  
Vol 261 (7-8) ◽  
pp. 773-778 ◽  
Author(s):  
R.G. Rateick ◽  
K.R. Karasek ◽  
A.J. Cunningham ◽  
K.C. Goretta ◽  
J.L. Routbort

2012 ◽  
Vol 585 ◽  
pp. 549-553 ◽  
Author(s):  
Prasanta Kumar Padhi ◽  
Alok Satapathy

Solid particle erosion (SPE) wear characteristics of particulate filled polymer matrix composites have been widely explored by different investigators. Through judicious control of reinforcing solid particulate phase, selection of matrix and suitable processing technique, composites can be prepared to tailor the properties needed for any specific application. Due to high cost of conventional ceramic fillers, it has become important to explore the potential of cheap materials like mineral ores and industrial wastes for utilization in preparing particle-reinforced polymer composites. Previous researchers have reported the use of industrial wastes such as fly ash and red mud as filler materials in polymeric matrices. But the reinforcing potential of blast furnace slag (BFS) particle, a solid waste generated from pig iron production route, has not been explored so far in polymeric materials. In this work, composite samples are prepared by reinforcing micro-sized blast furnace slag as the particulate filler in epoxy resin reinforced with bi-directional glass fibre. Different specimens with varied BFS content (0, 10, 20 and 30 wt %) are fabricated by simple hand lay-up technique. They are subjected to solid particle erosion using an air jet type erosion test rig. Erosion tests are carried out by following a well designed experimental schedule based on Taguchi’s orthogonal array. Here, factors like BFS content, impact velocity, erodent temperature and impingement angle in declining sequence are found to be significant to minimize the erosion rate. A prediction model based on artificial neural network is proposed to predict the erosion performance of the composites under a wide range of erosive wear conditions. This model is based on the database obtained from the experiments and involves training, testing and prediction protocols. This work shows that an ANN model helps in saving time and resources that are required for a large number of experimental trials and successfully predicts the erosion rate of composites both within and beyond the experimental domain.


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