Purpose This study aims to examine the wear performance of polyurethane (PU)-coated GFRP composites under onshore and offshore conditions. With the world’s growing reliance on wind energy, leading-edge erosion of turbine blades particularly offshore has become a pressing challenge, directly impacting durability and efficiency. This work evaluates PU coatings protective effectiveness and their potential to extend turbine blade service life. Design/methodology/approach A hybrid methodology was used to evaluate the erosion wear by using design of experiments (Taguchi L25) and artificial neural network (ANN) modelling. To identify the wear mechanisms, SEM microstructural methods were used and the influence of three important parameters including impact velocity, impact angle and the duration of exposure were also investigated systematically. Findings PU coatings provided good protection in both environments as the average S/N ratios were 43.9 and 40.1 under onshore and offshore, respectively. DOE-ANN had a ranking of parameter influence in Impact Velocity > Impact Angle > Exposure Duration and offshore conditions resulted in erosion which was more severe in salty conditions. ANN prediction accuracy was high, achieving R² values of 0.9931 (onshore) and 0.9851 (offshore). Hybrid crow search algorithm and grey wolf optimizer identified optimal parameters that reduced mass loss to 0.00145 g (onshore) and 0.0044 g (offshore). SEM observations revealed plowing, matrix removal, fiber exposure, and deeper grooves. Originality/value The paper integrates experimental design, ANN-based prediction, parameter validation, and hybrid metaheuristic optimization to address wear behavior. This comprehensive approach provides practical insights for reducing wear and enhancing the service life of wind turbine blades, particularly under offshore operating conditions. Peer review The peer review history for this article is available at: Link to the website of publons

Purpose The aim of the present study is to investigate the slurry erosion behavior of uncoated and WC-10Co-4Cr coated SS-317 steel, with a focus on the influence of various parameters on erosion rates. Additionally, it examines the predictive accuracy of the Artificial Neural Network (ANN) model for forecasting erosion behavior and compares its performance with traditional methods such as Multiple Linear Regression (MLR). Design/methodology/approach The research employed Design of Experiments (Taguchi and ANOVA) to systematically analyze the effects of rotational speed, concentration, particle size and time duration, on the erosion rates. Erosion behavior was modeled using ANN, with the model’s predictions being rigorously compared against experimental results to evaluate its accuracy. Additionally, erosion mechanisms were explored to gain insights into the wear processes and material performance. Findings The results showed that WC-coated SS-317 (986 HV) exhibited 22% higher resistance to erosion mass loss than uncoated SS-317, owing to its higher hardness. The particle size was the most influential parameter (confirmed using ANOVA) as it contributed 45.5% to the erosion wear rate for coated SS-317, with time duration contributing the least. The ANN model demonstrated high prediction accuracy, with error rates of 0–4.5% for uncoated and 0–1.2% for coated SS-317, outperforming MLR by 20-fold. Originality/value This study highlights the exceptional erosion resistance of WC-10Co-4Cr coatings, ideal for high-abrasion environments like thermal plants and ash-handling systems. Utilizing Taguchi, ANN and ANOVA approaches, it provides valuable insights into material performance and reliable erosion wear predictions, enhancing durability and efficiency in industrial applications.

Purpose This study aims to enhance the mechanical properties of 3D-printed acrylonitrile butadiene styrene (ABS) by reinforcing it with copper and optimizing key process parameters using Taguchi, artificial neural network (ANN) and metaheuristic optimization techniques. Design/methodology/approach Copper-reinforced ABS filaments were fabricated using a twin-screw extruder and printed via fused deposition modelling. A Taguchi L25 design was used to study the effects of printing temperature and layer height on tensile, compressive and flexural strengths. An ANN was trained on experimental data to model these properties, and a hybrid crow search algorithm–grey wolf optimizer (CSA–GWO) was used for multi-objective parameter optimization. Findings The Taguchi method identified printing temperature as the most influential factor. The ANN model demonstrated high predictive accuracy, achieving R² values exceeding 0.99 and maintaining prediction errors below 2%. The hybrid CSA–GWO algorithm effectively identified optimal parameters for maximizing each mechanical property, with a balanced setting of 245.68°C and 0.100 mm providing strong overall performance (947.97 N tensile, 4,173.61 N compressive and 176.06 N flexural). Originality/value The use of a hybrid CSA–GWO algorithm presents a novel approach within the additive manufacturing domain, offering enhanced exploration and convergence capabilities for optimizing mechanical properties of copper-reinforced ABS composites.

PurposeThe paper aims to investigate the effects of slurry erosion on hydro turbine components, focusing on the experimental analysis of SS-304 using sand as the erodent material. The study was conducted on a tester under varying parameters to assess the material's erosion behavior. In this work, the experimental investigation of SS-304 with sand was done with sand as the erodent material on a tester with various parameters. Further, the materials were made more resistant to wear by a WC-10Co-4Cr coating, done by the high-velocity oxygen fuel method. The mass loss of the specimens with and without coating was calculated. SEM was carried out on the specimens. The specimens with coating showed greater erosion resistance than the base material; however, wear mechanisms such as craters, lip formation, pores, etc. were discovered on the specimens.Design/methodology/approachThe wear tests were carried out on the specimens with parameters of rotating speeds of 1,000, 1,150, 1,300 and 1,450 rpm; time duration 80, 130 and 180 min with sand concentrations of 30% and 50% in water. The base material was coated with WC-10Co-4Cr by the HVOF method of thermal spray.FindingsIn the results, it was observed that the wear resistance of the coated specimen increased significantly as compared to the uncoated material. Concentration proved to be the major factor influencing the wear erosion followed by rotational speed and time period. Various surface defects such as ploughing, crater formation, lip formation and micro-cutting were also found.Originality/valueSlurry concentration was found to be the more dominant factor in increasing the wear of the specimens. The tests proved that the coating proved to be highly wear-resistant as compared to the uncoated base material and increased the wear resistance up to 3 times.

The longevity of wind turbine components, especially blades, is greatly affected by erosion wear by raindrops. Additionally, the climate, impact velocity, rain duration and the angle at which rain falls have a significant effect on erosion wear. This study aims to examine the impact of coatings and other erosion factors on the raindrop erosion performance of Glass Fiber Reinforced Polymers (GFRP), often used in the manufacture of wind turbine blades. The whirling arm rig tester was constructed, and three key parameters were selected for experimentation: impact velocity (ranging from 30 to 70 m/s), impact angle (ranging from 0 degrees to 90 degrees), and run time (ranging from 30 to 90 minutes). These parameters were systematically varied across five stages to study their effects on erosion wear. To optimize the erosion wear, Taguchi's L25 experimental design array was employed for parameter adjustment. Moreover, the experimentation was conducted on bare and coated (polyurethane based coating) samples and to simulate the onshore conditions simple tap water drops were used as erodent. The erosion was calculated with respect to mass loss of samples and then obtained results further converted into signal to noise (S/N) ratio. The outcomes demonstrated that the coated surface experiences less erosion than the bare surface. Impact velocity was found to be the most significant component when compared to other parameters, whereas run time was the least significant. Furthermore, the material used in GFRP wind turbine blades shows a ductile erosion behavior. Also, the mass loss was 33% less in coated samples as comparison to uncoated samples. This study addresses the limited research on optimizing erosion wear performance of uncoated GFRP and polyurethane-coated materials using Design of Experiments (DOE) approaches. Advanced tools like Minitab software were employed for statistical analysis, while XRD identified crystalline structures and phases, and EDXS analyzed elemental composition. SEM provided detailed surface imaging, revealing erosion features like micro-cutting and craters. Additionally, the shore D hardness test assessed the surface hardness of polyurethane-coated samples, a key factor in erosion resistance. These combined methods offer a comprehensive evaluation of erosion mechanisms and the physical characteristics of both coated and uncoated surfaces.

Purpose This study aims to investigate the erosion wear rate of a stainless steel automobile exhaust manifold, both computationally and physically. Design/methodology/approach The experiment was performed on a motorcycle exhaust manifold as well as on a 3D model, created using SolidWorks 2022 CAD software. The analysis was later achieved using ANSYS 19.2 simulation software using Fluent – code. Findings The analysis of solid particle erosion in the exhaust manifold revealed that erosion wear is concentrated predominantly at the extrados of the manifold, with the most significant wear occurring at the lowermost bend. The erosion wear rate increases with larger particulate sizes and varies among bends, with negligible wear observed in straight pipes. The SEM analysis further confirmed surface degradation, with rugged textures, pits and grooves indicating abrasive wear. Spine-like structures and fractured soot particles suggest erosive and abrasive forces caused by high-speed contact of exhaust gas compounds. Energy dispersive X-ray spectroscopy revealed significant carbon abundance, indicating carbonaceous compounds from fuel combustion, along with notable amounts of oxygen and iron, typical of oxidized metallic constituents. The discrete phase modeling (DPM) analysis highlighted peak particulate matter deposition at the first bend exit, with maximum concentrations observed at specific angles. This deposition is influenced by centrifugal force, leading to increased PM concentration at outer bend walls. Velocity magnitude contours showed asymmetrical flow profiles, with high turbulence levels and secondary flow induced by centrifugal effects in bend areas. Dynamic pressure contours revealed varying pressures at intrados and extrados, with maximum pressure observed at the intrados of the manifold’s bends. These findings provide valuable insights into erosion wear, particulate dispersion and flow dynamics within the exhaust manifold. Originality/value The study investigated an automobile exhaust manifold model using ANSYS Fluent code and DPM to analyze erosion wear rate phenomena and its various constituents. This analysis was conducted in comparison with a physically eroded sample. The study offers insights into the mechanism underlying the exhaust manifold of an automobile.

Purpose - The process of conveyance of solid-liquid mixtures poses a significant challenge due to the considerable wear and tear experienced by critical components. This issue not only affects the lifespan of the system but also jeopardizes its safe operation. The purpose of this study is to numerically and experimentally investigate the erosion wear behavior of impeller steels (SS-410 and S-317) using Computational Fluid Dynamics (CFD) and Design of Experiments (DOE) techniques, aiming to address the significant challenges posed by wear in slurry transportation systems. Design/methodology/approach - In this study, a robust two-phase solid-liquid model combining CFD with Discrete Phase Modeling (DPM) was applied to simulate the effects of coal-ash slurries on impeller steel. Additionally, an experimental evaluation was conducted using the DOE approach to analyze the impact of various parameters on impeller steel. This integrated methodology enabled a comprehensive analysis of erosion wear behavior and the influence of multiple factors on impeller durability by leveraging CFD for fl uid fl ow dynamics and DPM to model particle interactions with the steel surface. Findings - Simulation results highlight a strong link between particle size and the wear life of impeller steel. Through simulations and experiments on SS-410 and SS-317 under varied conditions, it's evident that SS-410 outperforms SS-317 due to its higher hardness and density. This is supported by Taguchi's method, with SS-410 showing a higher Signal-to-Noise ratio. Notably, particle size emerges as the most influential parameter compared to others. Originality/value - Current research primarily focuses on either CFD or experimentation to predict pump impeller steel erosion wear, lacking relevant erosion mechanism insights and experimental data. This study bridges this gap by employing both CFD and DPM methods to comprehensively investigate particle effects on pump impeller steel and elucidate erosion mechanisms.

PurposeThe purpose of this paper is to demonstrate the erosion performance of coated and uncoated surfaces of glass fibre-reinforced polymers (GFRP) wind turbine blade material using Taguchi's approach. Taguchi's array (L25) optimized erosion wear by varying three parameters: impact velocity, impact angle and run time across five levels.Design/methodology/approachThe studies were carried out using a whirling arm rig tester with an impact velocity range of 30-70 m/s (metre per second), an impact angle of 0-90 degree and a run time of 30-90 min. Salt water is used as an erosion agent to replicate the offshore environment. Taguchi's method was used to optimize the process parameters.FindingsThe results showed that erosion is less on the coated surface than on the uncoated surface. When compared to other factors, impact velocity was determined to be the most dominant, whereas run time was the least dominant. In addition, GFRP wind turbine blade material exhibits a ductile erosion process. Furthermore, in all experimental trials less erosion was observed on coated surfaces as compared to uncoated surfaces.Originality/valueFew researches have been done using different design of experiment techniques to optimize the erosion wear response of uncoated GFRP materials and coatings based on polyurethane. Furthermore, mechanism of the erosion and morphology of both surface conditions was investigated using scanning electron microscopy, X-ray diffraction, energy dispersive X-ray spectroscopy testing and Minitab software.

Purpose This empirical study aims to investigate the erosion wear performance of two different 3D-printed materials (acrylonitrile butadiene styrene [ABS] and polylactic acid [PLA]) with various micro textures. The two different textures (prism and square) were created over the surfaces of both materials by using the 3D-printed technique. Design/methodology/approach The erosion experiments on both materials were performed by using Ducom Erosion Jet Tester. Erosion tests were performed at four different impacting velocities (15, 30, 45 and 60 m/s) with the four different particle sizes (17, 39, 63 97 µm) at the impact angles (30°–90°) for the time duration of 5, 10, 15 and 20 min. The two different textures prism and cone were used for performing the erosion experiments. Taguchi’s orthogonal L16 (mixed level) was used to reduce the number of experiments and to determine the impact of these parameters on erosion wear performance of both 3D-printed materials. Findings The PLA with cone texture was found to be best (against erosion) than the ABS cone and prism textures due to their high hardness (68 HV). Also, the average signal to noise (S/N) ratio for PLA and ABS was measured as 56.4 and 44.4 dB, respectively. As the value of the S/N ratio is inversely proportional to the erosion rate, the PLA has the least erosion rate as compared to the ABS. The sequence of erosion wear influencing parameters for both materials was in the following order: velocity > erodent size > texture > impact angle > time interval. Originality/value Both PLA and ABS with different micro textures for erosion testing were studied with Taguchi’s optimization method, and the erosion mechanisms are well analyzed by using scanning electron microscopy and Image J techniques.

The inhibition efficiency of an aqueous extract of apple juice in controlling corrosion of mild steel immersed in simulated concrete pore solution (SCPS) prepared in sea water, has been evaluated by weight loss method. Langmuir adsorption isotherm has been investigated. The mechanistic aspect of corrosion inhibition has been investigated by Electrochemical impedance spectra (AC impedance spectra). The protective film has been analysed by Fluorescence spectroscopy, FTIR spectroscopy and AFM. The SCPS system offers 60% inhibition efficiency to mild steel immersed in sea water. In presence of apple juice extract the inhibition efficiency increases as the concentration of the extract increases. When 10 ml of extract is added, 85% inhibition efficiency is obtained. Electrochemical impedance spectra (AC impedance spectra) reveal that a protective film is formed on the metal surface. In the presence of inhibitor system, charge transfer resistance value increases, impedance value increases, phase angle value increases whereas double layer capacitance value decreases as expected. The FTIR spectral study reveals that the protective film consists of complexes consisting of iron-active principles of the apple juice extract. AFM study reveals that when the inhibition efficiency increases the roughness of the surface decreases or in other words the smoothness of the system increases.

This study introduces a novel object recognition algorithm employing the CNN-BiLSTM technique. Through the integration of advanced sensory technologies and deep reinforcement learning approaches, the proposed system dynamically adjusts its detection parameters to accommodate diverse object geometries, sizes, and surface properties. The approach entails training a neural network agent to discern, from an image window, which objects within a predetermined region warrant focused attention. To effectively handle high-dimensional and time-series data, a Double DQN framework is utilized. The proposed approach amalgamates object recognition algorithms with sophisticated reinforcement learning techniques, notably Double DQN, enabling robots to dynamically perceive and grasp items in varied environments. The outcomes were obtained by conducting comparative research to evaluate the effectiveness of current approaches in comparison to the proposed method. The Q-network is trained to execute two distinct motions, namely "twist" and "push," with the intended motion provided as an assigned parameter (+1 for "push" and-1 for "twist"). Moreover, the network can generate intermediate movements between the learned motions when the task parameter falls between-1 and +1. The findings reveal notable enhancements in grasping success rates and adaptability across diverse item sizes, shapes, and conditions. Notably, the study reports a significant increase in the task completion rate for grasping, achieving a success rate of 90%.

Coal ash slurries hold paramount importance in the service life of the coal and mining industries, significantly impacting their operational efficiency and durability. The literature reveals that the prominent dominating parameters such as rotational speed, concentration, time duration, and particle shape and size have a major impact on erosion wear. This research aims to explore the effects of coal ash slurries on Colmonoy-88-coated pump impeller steel, employing a combination of design of experiments (DOE) and digital image analysis (DIA). Through slurry experiments, it is observed that erosion wear increases non-linearly with an increase in influencing parameters. The particle size emerges as the most significant factor, followed by concentration, speed, and time. Additionally, DIA is leveraged to validate the influence of various erodent particle sizes on the erosion wear of the pump impeller steel. Results indicate that coal particles possess irregular shapes and sizes compared to fly ash and bottom ash, consequently resulting in larger erosion wear due to their lowest circularity factor (0.72). Furthermore, smaller particles exhibit lower erosion wear-rates compared to larger ones. This study sheds light on the intricate dynamics of erosion wear in the context of coal ash slurries, offering insights crucial for optimizing pump impeller steel durability in similar operational environments.

A series of Pd doped heptazine-graphitic carbon nitride (h-g-C3N4) as Pd/h-g-CN (PC composite) was fabricated by varying the amount of PdCl2 with an optimized amount of g-C3N4 (keeping static). The samples were investigated through advance and genuine characterization techniques. DFT computation was used as a strengthening tool for composite performance. The composite material showed remarkable energy storing capacity, particularly, PC9 composite exhibited a specific capacitance of 401.1F/g at a scan rate of 10 mV/s in 1 M H2SO4 with appealing cyclic stability (93.9 %) after 10,000 cycles. At 1 A/g, energy density and power density were 45.7 Wh/kg and 500.3 W/kg respectively. The Rs and Rctof PC9 were 1.10 Omega and 2.74 Omega respectively with n factor as 0.85. Meanwhile, photocatalytic activity was investigated, where PC9 has significant degradation efficiency (69.8 %) and the recyclability and reusability experiments were performed that showed 40 % as sustained composite even after 5 runs.

In concrete technology, rebars are used to strengthen the structure of concrete. The corrosion resistance of mild steel rebars in simulated concrete pore solution has be evaluated by electrochemical studies such as polarization study and AC impedance spectroscopy. The mild steel rebars have been coated with Nippon paint, SUMO XTRA, Durable exterior emulsion. Corrosion parameters such as linear polarization resistance (LPR), corrosion current density, corrosion potential, Tafel slopes, charge transfer resistance (Rt), double layer capacitance (Cdl), phase angle and impedance value have been derived from electrochemical studies. In the presence of emulsion coating, it was observed that, LPR increases, corrosion current density decreases, Rt increases, Cdl decreases, phase angle increases and impedance value increases. When Durable exterior emulsion coated mild steel was immersed in simulated concrete pore solution, the LPR value increases from 283 Ohm center dot cm2 to 1.37x105 Ohm center dot cm2; the corrosion current density decreases from 1.50 x10-4 A/cm2 to 3.323x10-7 A/cm2; charge transfer resistance increases from 50.25 Ohm center dot cm2 to 64351 Ohm center dot cm2; double layer capacitance decreases from 1.01x10-7 F/cm2 to 7.93x10-11 F/cm2; the impedance increases from 1.81 [log(Z/Ohm)] to 4.82 [log(Z/Ohm)] and the phase angle increases from 36.27 degrees to 51.54 degrees. These observations confirm that the emulsion coating is stable in the presence of simulated concrete pore solution. This has controlled the corrosion of the rebars in the concrete. There will be augment in the life time of the mild steel rebars. The corrosion inhibition efficiency calculated from electrochemical studies is greater than 99%.