# Analysis of Erosion Minimization for a Slurry Pump Using Discrete Phase Model Simulations
## 1 Introduction  
A slurry pump is a device used to transport slurry, which is a mixture of solids and liquids. It has been used in various industrial fields, such as coal mining, chemical manufacturing, and electricity generation. A slurry pump is subjected to physical erosion, generally resulting from erosion by friction between the solid and liquid particles, referred to as slurry erosion [1, 2]. The erosion damage of the slurry pump is a chronic problem caused by the characteristics of the slurry, geometry of the main components of the pump, and working conditions. The key components of a slurry pump subjected to erosion damage are the impeller, casing, and throat bush. The impeller is subjected to wear owing to its rotation. However, it exhibits relatively uniform erosion characteristics. However, irregular erosion patterns occur in the case of the casing and throat bush owing to the flow path of the slurry. Recently, the surface erosion of the pump and pump cases caused by slurry particles was experimentally investigated. [PERSON] et al. [3], measured the erosion damage caused by particle collisions and expressed the wear coefficient based on the Bitter model. [PERSON] et al. [4], analyzed the amount of erosion based on Bommes' theory using the angle and diameter of the casing and the impeller blade exit angle as parameters. [PERSON] et al. [5], predicted the flow field of a high-density slurry in a centrifugal pump casing under various work and geometric conditions and identified the physical causes of erosion. They demonstrated that the solid concentration of the slurry and the shear stress generated in the casing gradually increased from the upstream tongue region to the downstream naval region. These measurements can be used to calculate the amount of erosion that occurs in the casing wall. [PERSON] and [PERSON], [6], presented a neuralnetwork prediction of slurry erosion of heavy-duty pump impeller casing materials. In their work, a standard multilayer artificial neural network was designed. That research aimed to study the slurry erosion of pump materials for the flow of sand slurry using experimental and predictive methods. A pot tester was employed to conduct the slurry erosion experimentation for the variation of rotational speed, concentration, time, and impact angles. [PERSON] and [PERSON], [7], established the effect of variation in particle size distribution on the centrifugal slurry pump (CSP) performance and particle kinetics. Computational fluid dynamics (CFD) modeling of a CSP with multi-size particulate slurry was performed using the granular Eulerian-Eulerian model. The numerical model was validated with the experimental data of the pump performance for multi-size particulate fly ash slurry. [PERSON] et al., 2020 [8], analyzed solid-liquid two-phase flow and wear in a large-scale centrifugal slurry pump. After that, in 2021 [9], they proposed the optimal hydraulic design to minimize erosive wear in a centrifugal slurry pump impeller. They used an Eulerian-Eulerian mixture model to simulate the solid-liquid two-phase flow of quartz sand and water in a slurry pump. The impeller was optimized statistically. With the development of advanced computing techniques, the computational CFD-based approach is being increasingly applied for analyzing the flows in components handling slurry. The CFD method has the advantages of high efficiency and good economy, and its accuracy has been very reliable. The benefit of the CFD-based approach is that it gives comprehensive information about the local variations of flow parameters where the measurements are either difficult or impractical to conduct. In the case of a low particle concentration, choosing the CFD-DPM method can improve the calculation efficiency while ensuring calculation accuracy [10,11]. [PERSON] et al. [12], showed the design optimization of a hemispherical protrusion for mitigating elbow erosion via CFD-DPM. [PERSON] et al. [13], used the DPM model to accurately predict the erosion distribution of the elbow in a gas-liquid-solid flow.