Silt Erosion Research Articles

Numerical investigation of flow around the injector of a Pelton turbine due to eroded needle

Abstract Injectors of Pelton turbines are prone to both sediment erosion and cavitation. This causes degradation of the surface morphology, which aggravates the quality of the jet, lowering the turbine’s performance. The study focuses on CFD analysis of a groove-shaped erosion pattern on the needle and analyses its influence on the quality of the jet at the three stages of erosion. The numerical model comprises of a nozzle with a cylindrical passage for modelling the jet. The research used the SST turbulence model and boundary conditions defined according to the turbine’s data, from which the model was obtained. This study explores the impact of silt erosion on pressure signals around the injector of a Pelton turbine. Needle pressure distribution curves were plotted at various erosion levels and openings, revealing that pressure deviation increases with increase in erosion. The effect turns out to be minimal during high opening levels but becomes substantial as opening levels decrease. Operating in part load conditions leads to a significant pressure drop due to the reduction in flow rate. The pressure distribution tends to become more uniform at full load, achieving optimal flow rates. However, a noticeable pressure drop is observed in the eroded region, reaching a minimum at the deepest eroded area. The pressure drop is further amplified with an increase in the level of erosion, indicating erosion’s disruptive impact on fluid flow. The findings highlight the complex interplay between erosion, needle pressure distribution, and jet diffusion.

Artificial Neural Networks in Spray Coatings for Protection of Hydroturbines in Silt Conditions

Background: Artificial intelligence techniques are able to predict the erosion in various coatings. In recent times, the erosion of the coating was successfully predicted using artificial neural networks (ANN). Aim: This patent aims to present the critical findings in the area of spray coatings used for the protection of hydroturbines. This critical review explores the surface erosion of numerous hydroturbine materials and coatings. Moreover, it covers the evolution of coating techniques used in different industries such as hydropower plants and materials handling industry. Objective: The objective of this patent is to present the critical finding in the field of erosion wear in coatings utilizing an artificial neural networks (ANN) technique. Methods: The effect of influencing factors on silt erosion was assessed. However, the evolution of various coating processes was explored comprehensively. Furthermore, the properties of various coatings, namely WC, Cr2C3, and Ni/Co coatings, were reported. A number of comparative analyses were carried out that can help in the selection of coatings on the basis of their mechanical as well as chemical properties. The applications of ANN in the spray industry were explained extensively. Results: The results show that the HVOF coating is the most widely used deposition method. HVOF is an appropriate technique for both ceramics and pure metals. Ceramics, as well as cermet, are deposited to enhance the wear and tear resistance of hydroturbine materials. As a result, the HVOF, laser cladding, D-Gun, and plasma spray technique are optimal in these circumstances. Coatings based on WC have been employed by several researchers to increase stainless steels' resistance to erosion and wear. Conclusion: With the application of appropriate models and ML methods, it is expected that coatings with specific desired properties can be manufactured with fewer experiments. There is no surprise that WC-10Co-4Cr finds widespread usage in a variety of industrial contexts. Ni- and Cobased coatings show promise for use in tribological settings. Stellite is suggested by several researchers for high-erosion duty conditions in hydroturbines. Co-based coatings are more erosion resistant as compared to No-based coatings. Coatings formulated with chromium (Cr) are resistant to erosion and wear in harsh mining environments.

Influence of operating parameters on the silt erosion performance of bare and coated SS304 steel

Purpose The purpose of this paper is to investigate the silt erosion performance of Bare, 75%Cr2O3 + 25%Al2O3 and 85%Cr2O3 + 15Al2O3-coated SS304 under various control parameters such as rotation speed, concentration of silt and particle size of silt used for making slurry. This can provide insight for using chromia and alumina-based coatings for hydro-turbines. Design/methodology/approach Taguchi approach was used to identify the effect of three input parameters on the bare and coated alloys. L16 orthogonal array is used for determining the signal-to-noise (S/N) ratio for each process parameter. For each level of parameters taken into consideration about the erosion wear, the arithmetic mean of the S/N ratio is calculated. On the essence of the results of S/N ratios, it is possible to determine the effect of the most dominating parameters of the erosion wear. Findings Results show that the erosion increases with an increase in silt concentration (Wt.%). It has been analyzed that the rotational speed has the most significant effect followed by the particle size and concentration on erosion wear for all uncoated and coated SS-304 samples. Maximum resistance to erosion is provided by 85%Cr2O3 + 15%Al2O3. The least erosion wear for process parameters has occurred at the optimal parametric combination of rotational speed (N) = 415 rev/min, concentration (C) = 15 Wt.% and particle size range as <53 µm for uncoated and coated stainless steel. Originality/value The study clearly shows the silt erosion performance of chromia and alumina coatings of different compositions at different input parameters. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0028/

Correlation development of erosive wear and silt erosion failure mechanisms for pump as turbine

One of the factors contributing to the gradual decline in the performance as well as the failure of hydropower plants over the years is silt erosion. Several researchers have developed empirical correlations for the prediction of erosive wear of hydro turbines, but these correlations are not directly applicable in practice as the materials examined for the impeller blades were different from the actual impeller material. In this study, an effort has been made to experimentally evaluate the silt erosion of the Pump as Turbine (PAT). The novelty of the study is to use the same material (SS304) for the specimens used for the analysis as well as for the impeller. The experiments were performed with three silt sizes of 100–350 μm, 350–700 μm, and 700–1000 μm; with three different silt concentrations of 0.75 %, 1 %, and 1.25 % for the duration of 18 hrs, 36 hrs, and 54 hrs. An empirical correlation is established for the assessment of normalized wear of the PAT impeller in terms of silt size, concentration, and operating time based on the experimental data. This correlation can be utilized to estimate normalized erosive wear of PAT impeller made up of SS304 material with an inaccuracy of ±15 %. According to the analysis, silt concentration was found to be a more significant parameter in causing erosion than silt size. Additionally, scanning electron microscopy was used to conduct a thorough analysis of the erosive failure mechanism of SS304 specimens. According to the analysis, silt size was observed to be an important factor in producing various types of erosive failures. The material removal from the substrate’s surface was found to be caused by plastic deformation and surface ploughing.

Trend study on COVID-19 pandemic lockdown impact on rivers in Selangor, Malaysia

According to the Department of Environment, numerous rivers, and streams in Selangor, and practically all rivers, are in the 'polluted' and ‘slightly polluted' category even before the COVID-19 outbreak (DOE, 2022). Due to a lack of anthropogenic activities such as industrial discharge, agricultural, poultry, sediment, and silt erosion, the trend of pandemic lockdown on water quality parameters in Selangor is expected to decline. The goal of this research is to see if contamination of water resources and rivers increases or decreases during a pandemic by examining the trajectory of water quality parameters in relation to the COVID-19 pandemic, to figure out which parameters are affecting pollution in Selangor rivers, and to emphasize the water quality in each river for DOE (2022), utilizing data from 2016 to 2020. The results of the investigation revealed significant variations in water and wastewater quality over time. Finally, it showed positive changes during the pre-pandemic and pandemic lockdown periods. DO, TSS, ammoniacal nitrogen, and turbidity exhibited positive effects on water quality metrics during the pandemic lockdown period, however, BOD, COD, and pH levels had negative effects.

SUPPORT VECTOR MACHINE LEARNING ON SLURRY EROSION CHARACTERISTICS ANALYSIS OF Ni- AND Co-ALLOY COATINGS

In this paper, a novel support vector machine (SVM) learning approach has been used to predict the silt erosion of coatings sprayed by the high-velocity oxy-fuel (HVOF) process. The silt erosion resistance of HVOF-coated Co- and Ni-alloys is studied using an erosion tester. Both of these spraying powders were deposited on the 18Cr-12Ni-2Mo austenitic steel substrate. For the erosion experiments, the fixtures were developed to test the erosion characteristics at different impingement conditions (i.e. [Formula: see text], [Formula: see text], and [Formula: see text]). The image processing technique enables an understanding of the erosion mechanisms of coatings. The support vector regression is more effective than the traditional regression models. The proposed model employs support vector regression with parameter tuning. The ideal parameters are selected with the help of the grid search method. The model is trained by supplying 70% data and validated with 15% data. Afterward, the remaining 15% is given to the prepared model as testing data. The dataset obtained is employed for building an effective support vector regression model. The predicted results are compared against the original experimental values. The developed model is also compared with other state-of-the-art machine learning techniques for showing the preciseness of the proposed model. The Ni-based HVOF coating showed superior performance ([Formula: see text]) better than the Co-based HVOF coating under similar experimental conditions. An SVM model was successfully developed to predict the erosion of coated and uncoated 18Cr-12Ni-2Mo austenitic steel. The precision performance of the SVM model was calculated in terms of [Formula: see text], RMSE, [Formula: see text], and MAE as 0.99, [Formula: see text], 0.99, and [Formula: see text], respectively.

Effective monitoring of Pelton turbine based hydropower plants using data-driven approach

Hydropower is a renewable and reliable energy source that can be utilized to fulfil energy demands and promote energy sustainability. In hydropower plants, Pelton turbines are installed at high-head and low-discharge sites. In Pelton turbines, needle, nozzle, buckets, and splitter are most exposed to silt erosion. An eroded turbine takes more discharge than rated for generating the same amount of power. Therefore, to minimize the losses due to silt erosion, real-time condition-based monitoring of a hydropower plant is necessary. In this paper, correlations are developed using the historical data collected from the Urgam hydropower plant to predict the generated power. The artificial Neural Network (ANN) technique has been used to develop correlation, and the performance of this model has been compared with the model developed using the Curve Fitting technique. Based on the comparison, it has been found that the ANN model performs better than the curve-fitting model in forecasting the generated power with an R2-value of 0.9522 and Mean Absolute Percentage Error (MAPE) of 2.40% at 3.1515% Root Mean Square Percentage Error (RMSPE). The developed model can be utilized to plan a maintenance schedule of machines based on real-time conditions. It can also help to decide which machine should be taken in maintenance first.

A treatise on retrofitting of hydro-turbine materials

Hydro-turbine materials endure frequently the detrimental losses on account of slurry or silt erosion, cavitation erosion, corrosion or the collaborative effects of any of their combinations. Rivers emanating from Himalayan region or other hilly areas generally flow with enormous quantity of silt of different sizes and shapes. The shape of slurry particles possesses its wide ranges from sharp angular having very high erosion potential to spherical ones of relatively less erosion capacity. These particles sometimes create very severe damage in the form of huge mass loss and development of cracks within the short span of time in the components or parts of turbines in hydropower plants, situated in these regions for electricity generation. To avoid the extensive monetary loss in replacing the harshly eroded or cracked turbine parts, retrofitting (repair & maintenance) of hydro-turbine materials is mostly preferred for enhancing the service life and the smooth and efficient functioning of the concerned industries, responsible for power genesis. Common practice of retrofitting has been elaborated and discussed on the basis of a local cum private industry visit and subsequently, apt and proper optimized parameters related to different retrofitting operations; preheating, welding and post weld heat treatment (PWHT) have been suggested to meet the intended outcomes. Challenges found in execution of retrofitting the turbine parts also have been discussed. Retrofitting of eroded turbine parts has been advised rather to exhaust unnecessary monetary investment in their substitutions. In this brief study and in view of paucity of research availability as being an unorganized sector, retrofitting of hydro-turbine parts are focused, reviewed and discussed alongwith its underlying process. Some reviews in retrofitting prospect of components or parts of turbines other than hydro-turbines also have been considered for representing its approach for repair & maintenance. Additionally, smart retrofitting in accordance to the Industry 4.0 line has been suggested for further reduction in cost to money and time.

Data-driven internet of things and cloud computing enabled hydropower plant monitoring system

Hydropower is one of the renewable energy sources that can play a crucial role to fulfil the global energy demand. However, the performance of the hydro turbine is severely affected by silt erosion and cavitation problems which causes a reduction in the overall efficiency of the plant. Various studies have been carried out and are available in the literature to investigate silt erosion and cavitation issues in hydro turbines. It has been reported that cavitation and silt erosion varies with the variation in discharge under part load and overload operating conditions of the machine. However, very few studies are available to predict the performance of the machine under variable operating conditions. Hence, there is a scope of study for monitoring the performance under these conditions in real-time, as it is difficult to predict the behavior of the machine using the existing models. In view of the above, an architecture of a data-driven IoT-based cloud computing-enabled hydropower plant monitoring system has been proposed under the present study. In order to develop this system, historical plant data has been collected and correlations are developed, which are validated with real-time data on the ThingSpeak cloud. It has been found that the developed model can accurately predict the condition of the hydro turbine with an R2-value of 0.9693 having a mean absolute percentage error (MAPE) of 0.67% at 0.89% of root mean square percentage error (RMSPE), and the power factor with an R2-value of 0.9503, having a MAPE of 0.798% at 0.91% of RMSPE.

Cavitation–Silt Erosion Behavior and Failure Mechanism of an HVOF-Sprayed WC-Cr3C2-Ni Coating for Offshore Hydraulic Machinery

WC-Cr3C2-Ni coatings are a vital class of hard ceramic/cermet coatings with potential applications as wear-resistant materials. However, their erosion wear behavior in 3.5 wt.% sodium chloride medium (SCM) remains largely unexplored. The present study investigated the cavitation–silt erosion (CSE) behavior in 3.5 wt.% SCM of WC-Cr3C2-Ni coatings sprayed with high-velocity oxygen–fuel (HVOF) under different flow velocities (FVs) and sand concentrations (SCs). Comparing the WC-Cr3C2-Ni coating with the 1Cr18Ni9Ti stainless steel, the first possessed superior CSE resistance in 3.5 wt.% SCM in a full range of FV and SC. Meanwhile, the coating appeared more influenced by FV and less influenced by SC, which was indicated by the fact that the amplification of VLR value (377.1%) when the FV ranged from 23.4 to 41.9 m·s−1 was larger than that (129.8%) when the SC increased from 10 kg·m−3 to 35 kg·m−3. With increasing FV and SC, the CSE process of the WC-Cr3C2-Ni coating in 3.5 wt.% SCM mainly included the discontinuous corrosion product films, erosion pits, fracturing of hard-phase grains, and micro-cutting of soft binder matrix, as well as crater formation and coating spalling.

A Comprehensive Review on Investigation of Sediment Erosion of Pelton Wheel Turbine

Hydro turbines installed at different hydropower plants face the issue of sediment erosion. Sediment erosion is an ambiguous phenomenon influenced by several parameters, including silt concentration, size, jet velocity, diameter, and fluid viscosity. Silt erosion imposes severe issues for hydropower plants, like shutdown and maintenance costs. The hydro turbine efficiency decreases with the increase in sediment erosion and eventually the breakdown of turbine components. Various researchers conducted small-scale experimental bench studies and numerical simulations to analyze the influence of the above-mentioned parameters on silt erosion, but the actual flow conditions are too complex to simulate. Therefore, no such erosion model has been developed to predict exact erosive wear. This paper presents an extensive review of the literature survey on sediment erosive wear of hydro turbines, both the adopted methodology by previous studies and parameters affecting sediment erosion in Pelton turbine are summarized. Based on literature studies, various aspects of erosive wear, parameters influencing it, and its severe effects on efficiency are thoroughly discussed. Appropriate remedial measurements for erosive wear made by multiple researchers, erosion models developed so far, and their measuring accuracy and the future scope of this research study are articulated in detail.

Economic analysis of operation and maintenance costs of hydropower plants

The world is experiencing deep climate changes caused by increased population and rapid urbanization. Hydropower is one of the renewable energy sources that can be used to meet energy demands, but most of the hydropower plants suffer from silt erosion and cavitation problems. Therefore, it is important to decide which parts to be repair or replace, as it affects the Operation and Maintenance (O&M) costs. Presently O&M costs are speculated based on the previous years O&M costs data. Various studies are available for forecasting O&M costs, but they are plant specific. This paper deals with the assessment of the O&M costs of hydropower plants, considering the parameters and conditions involved in the O&M costs of hydropower plants. The correlations are developed to predict the O&M costs of hydropower plants and found that the developed correlation models can predict the O&M costs with an accuracy having an R2-value of 0.89, Mean Absolute Percentage Error (MAPE) of 3.53% and Root Mean Square Percentage Error (RMSPE) of 4.45% for Francis turbine-based hydropower plants, and with an R2-value of 0.97, having a MAPE of 0.17% at 1.30% RMSPE for Kaplan turbine-based hydropower plants. This study may be useful for developers, plant operators, and researchers.

Adaptive neuro-fuzzy interface system based performance monitoring technique for hydropower plants

ABSTRACT Energy has played a significant role in developing civilization, but the continuous use of fossil fuels has hampered the environment. Hydropower is the alternative to fossil fuels. But most of the hydropower plants in hilly areas suffer from silt erosion problems. Erosion of underwater parts creates vibration and noise and reduces machine efficiency. Therefore, online monitoring of turbines and other equipment is necessary to minimize losses due to erosion and part-load operation. Various studies are reported in the literature and found that correlation-based machine efficiency monitoring is one of the popular techniques. ANN method is useful for system modeling with a wide range of applications. However, despite the excellent classification capacities, its development can be time-consuming, computer-intensive, and prone to overfitting. In this paper, an Adaptive Neuro-Fuzzy Interface System (ANFIS) has been utilized to develop a correlation that removes the drawbacks of ANN and can predict the efficiency of the machine with an R2-value of 0. 99,976 having a Mean Absolute Percentage Error (MAPE) of 0.0108% at 0.06482% Root Mean Square Percentage Error (RMSPE).

Silt erosion performance of high velocity oxy fuel- (HVOF) sprayed Al2O3–Cr2O3 composite coatings on turbine steel

PurposeThe purpose of this paper is to investigate the erosion performance of high velocity oxy fuel- (HVOF) sprayed Al2O3–Cr2O3 composite coatings under silt slurry conditions.Design/methodology/approachThe requisite HVOF composite coatings has been deposited on the stainless steel substrate (SS-304). The slurry erosion pot tester of make Ducom was used for conducting the silt slurry erosion tests on the required substrates. The comprehensive experiments were conducted at different particle size of silt in the range 212–250, 150–212, 53–106 µm, and the concentration of the silt ranged from 10%–40% by weight. The rotational speed of the pot tester has been varied between 500 and 1,500 revolutions per minute, and the test duration has been kept to 4 h.FindingsThe erosion wear resistance of the uncoated SS-304 has been greatly enhanced by the application of HVOF-sprayed Al2O3–Cr2O3 composite coatings. The addition of CeO2 has a significant impact in reducing the erosive wear caused by silt slurry. The composite coating powder composition of 65%Cr2O3 + 34.5%Al2O3 + 0.5%CeO2 has shown the highest erosion resistance.Practical implicationsThe developed coatings have the potential to be used for hydro turbines as subjected to silt slurry conditions.Originality/valueThe erosion wear experiments are conducted comprehensively for coated and uncoated samples and the scanning electron micrographs supports the findings.

Surface and bulk modification techniques to mitigate silt erosion in hydro turbines: a review of techniques and parameters

ABSTRACT Silt erosion causes big efficiency and economic losses to hydro turbines and other industries involving the relative motion of the slurry/silt. This article reviews various techniques employed in the literature to mitigate the silt erosion. The main prominence is given to the latest technologies rather than the number of articles on the same technology. The available techniques are classified into two broad categories namely, surface modification techniques, and bulk material modification techniques; then reviewed systematically. The parameters (properties) which largely influence the material loss, for corresponding techniques, are also familiarized. In addition to this, how these parameters were improved and why these parameters enhanced the slurry erosion performance are discussed. Surface coating increases the surface hardness, is found to be the most addressed and most successful technique for the said purpose. The hardness of the substrate was found to be the most addressed property which can largely control the silt erosion.

Development of correlation to predict the efficiency of a hydro machine under different operating conditions

The global energy demand is increasing due to an increase in economic growth and urbanization which is set to rise by 4.6% in 2021. A major part of this increasing energy demand is accomplished by fossil fuels which create environmental pollution. Hydropower is the most mature, reliable, and cost-effective source of energy. However, the operation and maintenance (O&M) of hydro turbines is the main concern. The flowing water carries the sediment which passes through the underwater parts and creates silt erosion problems. A number of correlations are available in the literature to predict the silt erosion in hydro turbines considering very few parameters. However, no study has been reported on the complete scenario on O&M of hydropower plants. Under the present study, an attempt has been made to develop correlations for the efficiency factor using Curve fitting, ANN, and Support Vector Machine (SVM) methods. It is found that the developed correlation for efficiency using the ANN method is more reliable than other techniques. It is found to predict the efficiency with R2-value as 0.999986 having an average absolute percentage error of 0.0124% at RMSE of 0.0874%. The developed correlation may be used for developing efficient O&M strategies for hydropower plants.

Neural network-supported study on erosive wear performance analysis of Y2O3/WC-10Co4Cr HVOF coating

In this work, a study was carried out by modifying the conventional Tungsten Carbide Cobalt Chrome (WC–10Co4Cr) powder with a small addition of yttrium-oxide (Y2O3). Reinforcement was done by adding yttria (Y2O3) ceramics in WC–10Co4Cr powder by using a jar ball mill process. The surface microstructure, chemical composition, and phase compositions of coating powder and coatings were examined by using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffractometry. Silt erosion was evaluated through a pot tester by preparing equi- and multi-sized slurries at different velocities, impact angles, concentrations, and rates. Results show that the WC–10Co4Cr powder coating reinforced by Y2O3 ceramics possesses low porosity, providing higher erosive performance as compared to conventional WC–10Co4Cr coating. The present study reveals that the deposition of conventional WC–10Co4Cr coating helps improve the wear resistance of AISI 316L stainless steel (UNS S31600) by 9.98% for the variation in rotational speed. However, the erosive wear performance of conventional WC–10Co4Cr coating was improved by 45.9% by blending it with the Y2O3 ceramics.

Investigation of erosion influence in distribution system and nozzle structure of pelton turbine

Pelton turbine, with its unique advantages in high mountainous region especially in the southwest of China, has received more and more attention. This paper focuses on the erosion influence to the hydraulic characteristics by Euler particle tracking model. Two-phase numerical simulation results are compared with the model experiment results and are proved to be accurate. Solid particle is then added in the flow and three-phase flow is solved. Particle parameters (silt particle size, concentration) were considered to investigate the mechanism of silt erosion on Pelton turbine distribution system including distributor, bifurcation tubes, and nozzle structure. It proves that erosion destroys the vortex structure in bifurcation tubes. As the particle's diameter increases, discharge in different bifurcations appear more uniform. With the particle flow, a strong collision phenomenon appears at nozzle seat. As the particle's diameter increases, the erosion strengthens accordingly. This study reveals that the particle influence induces erosion which is important to be considered during the design and operating procedures in the whole life of Pelton turbine.

STRUCTURAL ANALYSIS OF PELTON BUCKET WITH AISI 1020 STEEL AND STRUCTURAL STEEL MATERIAL BY USING SOLID WORKS AND ANSYS

Pelton Turbine is the hydraulic turbine, type of impulse turbine. An Impulse turbine generally suitable for the low flow rate and high head. The discharge water from the nozzle impacts the bucket of the Pelton wheel to produce the hydropower. There are some reasons behind the failure of the Pelton bucket like as: silt erosion, cavitation, fatigue etc. The main reason behind the fatigue failure is the material property and stress concentrations. A high concentration of stresses occurs at the root of the bucket due to its cantilever structure each time a bucket experiences the impact of the water jet. In this work, there are two materials AISI 1020 Steel and Structural Steel have been considered for analyzing the Pelton bucket. For the 3D CAD model of Pelton bucket Solid works 14.0 and for simulation work ANSYS 15.0 software has been used. In simulation work analysis types were static structural. This paper focuses on von-mises stress, total deformation of von-mises strain to analyze the suitable material for the Pelton bucket. From the obtained results it has been observed that among both materials Structural Steel is suitable for bucket due to low-stress concentration, total deformation and strain.

Measurement and analysis of sediment erosion of a high head Francis turbine: A field study of Bhilangana-III hydropower plant, India

The problem of silt erosion is prevalent in hydropower plants of the Himalayan region. In the present study, a measurement methodology is undertaken to investigate the erosion damages of the Francis turbine components of unit-2 of Bhilangana-III Hydro Electric Plant. For the operation of 6993.12 h, a total sediment load of 29,291 MT was passed through the turbine. Around 90% of suspended silt particles were less than 300 μm size, with a modified shape factor of 0.75. The maximum overall weight loss is found as 29 kg for the tungsten carbide coated runner. The initial clearance gap of the guide vanes was increased from 0.04 to 0.55 mm to 0.65 mm and 0.69 mm at leading and trailing edges, respectively. In the runner, the average thickness loss at the blade trailing edge was found as 3 mm, 1.25 mm, and 1.56 mm from shroud to hub for three different templates as per IEC-62364. The maximum erosion depth of 13 mm is measured for the curved part of the runner. The ripple pattern of erosion is observed to be responsible for the material loss from the runner. The observed erosion-prone zones of turbine components are further investigated through CFD analysis at the best efficiency point.