Sharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Experimental Investigation of the Effect of Pre-evacuation on the Starting Performance of a Vacuum Simulator Diffuser with Conical Nozzles of Different Expansion RatiosExperimental Investigation of the Effect of Pre-evacuation on the Starting Performance of a Vacuum Simulator Diffuser with Conical Nozzles of Different Expansion Ratios3162402410.24200/j40.2024.64065.1703FANematollahFouladi1Space Transportation Research Institute, Iranian Space Research Center, Tehran, Iran.MohammadFarahaniDepartment of Aerospace Engineering, Sharif University of Technology, Tehran, IranAmiraliNojoumiDepartment of Aerospace Engineering, Sharif University of Technology, Tehran, Iran.Journal Article20240218The starting time of a high-altitude exhaust diffuser is a key factor in evaluating an engine’s unsteady performance. One common approach to reduce this time is to pre‑evacuate the vacuum chamber and part or all of the diffuser. This study examines how pre-evacuation influences diffuser performance using four diffuser inlet to nozzle outlet area ratios 1.27, 1.91, 4.1, and 7.81, tested using compressed air and rapid nozzle pressurization. These ratios correspond to four conical nozzles with expansion ratios of 45, 30, 15, and 7.5. Wall pressures were measured at 13 points along the diffuser and vacuum chamber, both with and without pre-evacuation. The pre-evacuation process used a vacuum pump. Results showed that at area ratios of 1.91 and higher, harmonic pressure oscillations develop in the diffuser and vacuum chamber. Pre-evacuation did not eliminate these oscillations but shortened their onset and the diffuser starting time, especially at an area ratio of 1.27, where the narrow annular gap delays starting. Mass flow rate analysis revealed alternating filling and emptying of the vacuum chamber during oscillations. Fourier analysis indicated that oscillation frequency increases with area ratio, while amplitude decreases.The starting time of a high-altitude exhaust diffuser is a key factor in evaluating an engine’s unsteady performance. One common approach to reduce this time is to pre‑evacuate the vacuum chamber and part or all of the diffuser. This study examines how pre-evacuation influences diffuser performance using four diffuser inlet to nozzle outlet area ratios 1.27, 1.91, 4.1, and 7.81, tested using compressed air and rapid nozzle pressurization. These ratios correspond to four conical nozzles with expansion ratios of 45, 30, 15, and 7.5. Wall pressures were measured at 13 points along the diffuser and vacuum chamber, both with and without pre-evacuation. The pre-evacuation process used a vacuum pump. Results showed that at area ratios of 1.91 and higher, harmonic pressure oscillations develop in the diffuser and vacuum chamber. Pre-evacuation did not eliminate these oscillations but shortened their onset and the diffuser starting time, especially at an area ratio of 1.27, where the narrow annular gap delays starting. Mass flow rate analysis revealed alternating filling and emptying of the vacuum chamber during oscillations. Fourier analysis indicated that oscillation frequency increases with area ratio, while amplitude decreases.https://sjme.journals.sharif.edu/article_24024_87dffab2a1c686df8d00042b33a9e5b8.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221A Ring Selection Platform for Treatment of KeratoconusA Ring Selection Platform for Treatment of Keratoconus17312402310.24200/j40.2025.64700.1711FAAmirhosseinKhademiFaculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran.MohsenAsghariFaculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran.Mohammad RezaNaderi EshkaftakiFaculty of Mechanical Engineering, Sharif University of Technology, Tehran, Iran.Journal Article20241002This study presents a fully integrated platform for selecting appropriate intrastromal corneal ring segments (ICRS) for keratoconus treatment using a combination of finite element modeling and machine-learning techniques. A patient-specific corneal geometry was reconstructed using Pentacam-derived elevation maps, followed by meshing and biomechanical simulation of ring implantation at various depths and angular positions. Optical parameters of the cornea were calculated using curvature-based relationships (Eqs. (3)–(4)). A comprehensive database of 288 simulated ring-implantation scenarios was generated by varying Ring radius, Implantation depth, ring implantation zone, and arc length (Fig. 7). To predict keratometric outcomes, a random forest regression model and a deep learning architecture were developed and trained on the simulation-derived dataset. Model validation demonstrated acceptable accuracy using an independent rectangular-groove benchmark (Fig. 8). The trained algorithms were finally tested on a separate patient to evaluate generalization capacity. The results indicate that machine-learning prediction of ring-induced corneal response is feasible and can support treatment planning. This platform provides a foundation for developing preoperative decision-support tools to enhance clinical outcomes in keratoconus ring implantation.This study presents a fully integrated platform for selecting appropriate intrastromal corneal ring segments (ICRS) for keratoconus treatment using a combination of finite element modeling and machine-learning techniques. A patient-specific corneal geometry was reconstructed using Pentacam-derived elevation maps, followed by meshing and biomechanical simulation of ring implantation at various depths and angular positions. Optical parameters of the cornea were calculated using curvature-based relationships (Eqs. (3)–(4)). A comprehensive database of 288 simulated ring-implantation scenarios was generated by varying Ring radius, Implantation depth, ring implantation zone, and arc length (Fig. 7). To predict keratometric outcomes, a random forest regression model and a deep learning architecture were developed and trained on the simulation-derived dataset. Model validation demonstrated acceptable accuracy using an independent rectangular-groove benchmark (Fig. 8). The trained algorithms were finally tested on a separate patient to evaluate generalization capacity. The results indicate that machine-learning prediction of ring-induced corneal response is feasible and can support treatment planning. This platform provides a foundation for developing preoperative decision-support tools to enhance clinical outcomes in keratoconus ring implantation.https://sjme.journals.sharif.edu/article_24023_901867245862bd789b9d68187d53ffc5.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Edge-Computing-Based Anomaly Detection of Rotating Machines Using Artificial Neural NetworksEdge-Computing-Based Anomaly Detection of Rotating Machines Using Artificial Neural Networks33472402110.24200/j40.2025.65863.1730FAAlirezaMostafaviSchool of Mechanical Engineering, University of Tehran, Tehran, IranAysanAlizadehSchool of Mechanical Engineering, University of Tehran, Tehran, IranAliSadighiSchool of Mechanical Engineering, University of Tehran, Tehran, IranJournal Article20241224Manufacturing companies face issues due to demand for high-quality, affordable products. Since maintenance costs account for 60–70% of production costs, real-time fault detection is vital to lower maintenance expenses and extend equipment life. This article introduces a high-performance anomaly detection framework using edge computing for real-time industrial asset monitoring. Hardware and firmware were designed to perform critical tasks such as data acquisition, preprocessing, feature extraction, and algorithm training on the microcontroller unit (MCU), despite limited processing and memory. Using a 3-axis accelerometer for vibration signals, the MCU stores training data in Flash memory. An autoencoder with three hidden layers is trained on the edge device to model normal operating conditions, and reconstruction error of new data detects anomalies. This study is, to the best of our knowledge, the first to train an artificial neural network (ANN) on an MCU for comprehensive edge-based condition monitoring. achieved over 99.9% accuracy when validated on a centrifugal pumpManufacturing companies face issues due to demand for high-quality, affordable products. Since maintenance costs account for 60–70% of production costs, real-time fault detection is vital to lower maintenance expenses and extend equipment life. This article introduces a high-performance anomaly detection framework using edge computing for real-time industrial asset monitoring. Hardware and firmware were designed to perform critical tasks such as data acquisition, preprocessing, feature extraction, and algorithm training on the microcontroller unit (MCU), despite limited processing and memory. Using a 3-axis accelerometer for vibration signals, the MCU stores training data in Flash memory. An autoencoder with three hidden layers is trained on the edge device to model normal operating conditions, and reconstruction error of new data detects anomalies. This study is, to the best of our knowledge, the first to train an artificial neural network (ANN) on an MCU for comprehensive edge-based condition monitoring. achieved over 99.9% accuracy when validated on a centrifugal pumphttps://sjme.journals.sharif.edu/article_24021_5aef3654906d2a8008fb44ba96b4e8c0.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221The Effect of Fixed Blades Installation Angle on the High-Efficiency Operating Range of a Centrifugal Pump asTurbineThe Effect of Fixed Blades Installation Angle on the High-Efficiency Operating Range of a Centrifugal Pump asTurbine49612402210.24200/j40.2025.66460.1735FAMohammad HassanShojaeefardFaculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.SalmanSaremianFaculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.Journal Article20250312Using the pump as turbine (PAT) for energy recovery has received considerable attention in recent years as an efficient and economical approach. This study investigates the performance of a centrifugal PAT both numerically and experimentally within its operational range. For numerical analysis, design and simulation processes were conducted using CFturbo and CFX software. The validity of numerical simulations was confirmed by comparing them with experimental results. Due to the absence of a flow control mechanism at the impeller inlet, a significant reduction in efficiency is observed compared to pumping mode, particularly under off-design conditions. To enhance PAT performance, a diffuser with fixed blades was designed, and the impact of its blade angles on performance was numerically analyzed by varying angles between 15° and 35°. Turbulent kinetic energy parameter was employed to evaluate performance at different fixed blade angles. Results indicate that the blades' installation angle substantially affects both the distribution and the magnitude turbulent kinetic energy. Higher turbulence intensity was primarily concentrated in the impeller and volute tongue. Comparison of turbulent kinetic energy contours indicates that for a PAT with fixed blades at 25°, the distribution is more uniform, resulting in an efficiency improvement of 2.63% at the design point.Using the pump as turbine (PAT) for energy recovery has received considerable attention in recent years as an efficient and economical approach. This study investigates the performance of a centrifugal PAT both numerically and experimentally within its operational range. For numerical analysis, design and simulation processes were conducted using CFturbo and CFX software. The validity of numerical simulations was confirmed by comparing them with experimental results. Due to the absence of a flow control mechanism at the impeller inlet, a significant reduction in efficiency is observed compared to pumping mode, particularly under off-design conditions. To enhance PAT performance, a diffuser with fixed blades was designed, and the impact of its blade angles on performance was numerically analyzed by varying angles between 15° and 35°. Turbulent kinetic energy parameter was employed to evaluate performance at different fixed blade angles. Results indicate that the blades' installation angle substantially affects both the distribution and the magnitude turbulent kinetic energy. Higher turbulence intensity was primarily concentrated in the impeller and volute tongue. Comparison of turbulent kinetic energy contours indicates that for a PAT with fixed blades at 25°, the distribution is more uniform, resulting in an efficiency improvement of 2.63% at the design point.https://sjme.journals.sharif.edu/article_24022_9eb535d481d107dd79c49ddc2d6e5306.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Numerical Study of the Effect of Flow Control Using Plasma Actuator on the Aerodynamic Performance of a VAWTNumerical Study of the Effect of Flow Control Using Plasma Actuator on the Aerodynamic Performance of a VAWT63752402010.24200/j40.2025.67068.1739FASaeedKarimian AliabadiDept. of Mechanical Engineering, Aerospace Engineering, Tarbiat Modares University, Tehran.Seyed JavadGaskarinezhadDept. of Mechanical Engineering, Aerospace Engineering, Tarbiat Modares University, Tehran.Journal Article20250701In this study, a numerical approach is employed to examine the effects of active flow control using the SDBD (Surface Dielectric Barrier Discharge) plasma actuator model on the aerodynamic performance of a Darrieus vertical-axis wind turbine. The unsteady, pressure-based Navier-Stokes equations are solved in 2D computational domain, using the finite volume method. One of the common challenges for vertical-axis wind turbines is dynamic stall and flow separation. Therefore, before applying plasma control, the flow physics around the Darrieus wind turbine is analyzed, with a focus on the aerodynamic forces and torques affecting the instantaneous torque generated by the blades. Subsequently, plasma actuators are positioned at 3 distinct chord-wise locations on the airfoils, namely at 0.25, 0.5, and 0.75 chord lengths. The plasma dynamics are incorporated using user-defined functions (UDFs) according to the SDBD model. Results indicate that the 0.25 chord position yields the most improvement, increasing the overall power coefficient by up to 20%. Moreover, the plasma actuator mitigates dynamic stall, suppresses vortex formation, and enhances aerodynamic forces and torques. Overall, the primary effect of the plasma actuator is observed in the upstream flow region and during the blade’s downward motion, which leads to improvements in local blade torque and output power.In this study, a numerical approach is employed to examine the effects of active flow control using the SDBD (Surface Dielectric Barrier Discharge) plasma actuator model on the aerodynamic performance of a Darrieus vertical-axis wind turbine. The unsteady, pressure-based Navier-Stokes equations are solved in 2D computational domain, using the finite volume method. One of the common challenges for vertical-axis wind turbines is dynamic stall and flow separation. Therefore, before applying plasma control, the flow physics around the Darrieus wind turbine is analyzed, with a focus on the aerodynamic forces and torques affecting the instantaneous torque generated by the blades. Subsequently, plasma actuators are positioned at 3 distinct chord-wise locations on the airfoils, namely at 0.25, 0.5, and 0.75 chord lengths. The plasma dynamics are incorporated using user-defined functions (UDFs) according to the SDBD model. Results indicate that the 0.25 chord position yields the most improvement, increasing the overall power coefficient by up to 20%. Moreover, the plasma actuator mitigates dynamic stall, suppresses vortex formation, and enhances aerodynamic forces and torques. Overall, the primary effect of the plasma actuator is observed in the upstream flow region and during the blade’s downward motion, which leads to improvements in local blade torque and output power.https://sjme.journals.sharif.edu/article_24020_6a171c9daeed2f38a87f2febe7b274c0.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Experimental and Numerical Analysis of Hydrostatic Pressure in Ductile Fracture of AL-6061T6Experimental and Numerical Analysis of Hydrostatic Pressure in Ductile Fracture of AL-6061T677922400510.24200/j40.2025.67305.1742FAMohsenMansouriFaculty of Mechanical Engineering, University of Tehran, Iran.MehdiGanjianiFaculty of Mechanical Engineering, University of Tehran, Iran.0000-0001-9839-7795Journal Article20250720This study investigates the effects of stress triaxiality and the Lode angle parameter on the ductile fracture behavior of aluminum alloy 6061-T6 using experimental tests and numerical simulations. To analyze negative triaxiality conditions, compression tests were performed on specially designed specimens, including a standard dog-bone and rectangular samples with elliptical holes of varying curvature. The obtained negative triaxiality values ranged from −0.355 to −0.555. A good agreement between experimental and numerical results confirms the reliability of the adopted approach. The fracture initiation zones coincide with regions of maximum plastic strain, strongly influenced by triaxiality and Lode angle. The results indicate that fracture strain depends nonlinearly on triaxiality: for positive triaxiality it first increases then decreases, while the reverse trend is observed under negative triaxiality. These findings enhance the understanding of how stress-state parameters influence ductile fracture mechanisms and can be applied to improve the design and durability of metallic components in engineering applications.This study investigates the effects of stress triaxiality and the Lode angle parameter on the ductile fracture behavior of aluminum alloy 6061-T6 using experimental tests and numerical simulations. To analyze negative triaxiality conditions, compression tests were performed on specially designed specimens, including a standard dog-bone and rectangular samples with elliptical holes of varying curvature. The obtained negative triaxiality values ranged from −0.355 to −0.555. A good agreement between experimental and numerical results confirms the reliability of the adopted approach. The fracture initiation zones coincide with regions of maximum plastic strain, strongly influenced by triaxiality and Lode angle. The results indicate that fracture strain depends nonlinearly on triaxiality: for positive triaxiality it first increases then decreases, while the reverse trend is observed under negative triaxiality. These findings enhance the understanding of how stress-state parameters influence ductile fracture mechanisms and can be applied to improve the design and durability of metallic components in engineering applications.https://sjme.journals.sharif.edu/article_24005_739a82e565076008d0e12c2a5029fe5e.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Investigating the Effectiveness of the Population Balance Model for Predicting Thermal Transfer Characteristics of Ice Slurry Flow within a PipeInvestigating the Effectiveness of the Population Balance Model for Predicting Thermal Transfer Characteristics of Ice Slurry Flow within a Pipe931052407810.24200/j40.2025.67578.1749FAMohammad AminAlavi NobandeganiSchool of Mechanical Engineering, Shiraz University, Shiraz, Iran.Hossein AliPakravanSchool of Mechanical Engineering, Shiraz University, Shiraz, Iran.Journal Article20250916In this research, we performed a detailed numerical investigation into the effectiveness of the Population Balance Model (PBM) for simulating the complex phenomena of particle aggregation and breakage. The results demonstrated a substantial improvement in prediction accuracy when the PBM is integrated into the simulation framework. Specifically, for turbulent flows with a volume fraction below 10%, the PBM was shown to reduce calculation errors to less than 5%. Our findings also reveal a direct correlation between increased volume fraction and flow velocity, and an increase in the average particle diameter within the flow. Further analysis evaluated different aggregation and breakage mechanisms. These were tested within the PBM framework. The combination proposed by Luo proved to be the most effective, yielding more reliable results than other models. This was consistent across both laminar and turbulent flow regimes and was consistently validated against experimental data. We also examined how the predefined range of allowable particle diameters within the PBM influences the results. Our investigation highlighted a strong dependency between this parameter and the distribution of the average particle diameter across the pipe's cross-section.In this research, we performed a detailed numerical investigation into the effectiveness of the Population Balance Model (PBM) for simulating the complex phenomena of particle aggregation and breakage. The results demonstrated a substantial improvement in prediction accuracy when the PBM is integrated into the simulation framework. Specifically, for turbulent flows with a volume fraction below 10%, the PBM was shown to reduce calculation errors to less than 5%. Our findings also reveal a direct correlation between increased volume fraction and flow velocity, and an increase in the average particle diameter within the flow. Further analysis evaluated different aggregation and breakage mechanisms. These were tested within the PBM framework. The combination proposed by Luo proved to be the most effective, yielding more reliable results than other models. This was consistent across both laminar and turbulent flow regimes and was consistently validated against experimental data. We also examined how the predefined range of allowable particle diameters within the PBM influences the results. Our investigation highlighted a strong dependency between this parameter and the distribution of the average particle diameter across the pipe's cross-section.https://sjme.journals.sharif.edu/article_24078_67c374931066b18df3a34ece46b29ccc.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Modeling and Simulation of 18-Degree-of-Freedom Flight Dynamics of a Dragonfly-Inspired Micro Aerial Vehicle Considering Quasi-Steady AerodynamicsModeling and Simulation of 18-Degree-of-Freedom Flight Dynamics of a Dragonfly-Inspired Micro Aerial Vehicle Considering Quasi-Steady Aerodynamics1071252408710.24200/j40.2025.67607.1750FASobhanToulabiDepartment of Aerospace Engineering, Sharif University of TechnologyAfshinBanazadehDepartment of Aerospace Engineering, Sharif University of TechnologyJournal Article20250825In this study, a comprehensive dynamic and aerodynamic model of a dragonfly-inspired flapping-wing system was developed to analyze the mechanisms of unsteady flight. Using a nonlinear 18-degree-of-freedom formulation based on the Newton–Euler equations, the coupled motion of the body and four independently actuated wings was simulated. Key unsteady aerodynamic effects—delayed stall, rotational lift, and added-mass inertia—were modeled and incorporated into the dynamics, while wake capture was omitted for simplicity. Simulation results showed strong agreement with experimental data, reproducing lift and drag characteristics across diverse flight conditions. The model also demonstrated stable hovering and agile turning maneuvers, confirming its capability to capture essential flight characteristics. Overall, the validated framework provides a reliable basis for future research on stability, control, and performance optimization of bio-inspired flapping-wing micro aerial vehicles.In this study, a comprehensive dynamic and aerodynamic model of a dragonfly-inspired flapping-wing system was developed to analyze the mechanisms of unsteady flight. Using a nonlinear 18-degree-of-freedom formulation based on the Newton–Euler equations, the coupled motion of the body and four independently actuated wings was simulated. Key unsteady aerodynamic effects—delayed stall, rotational lift, and added-mass inertia—were modeled and incorporated into the dynamics, while wake capture was omitted for simplicity. Simulation results showed strong agreement with experimental data, reproducing lift and drag characteristics across diverse flight conditions. The model also demonstrated stable hovering and agile turning maneuvers, confirming its capability to capture essential flight characteristics. Overall, the validated framework provides a reliable basis for future research on stability, control, and performance optimization of bio-inspired flapping-wing micro aerial vehicles.https://sjme.journals.sharif.edu/article_24087_46b20069390a096c2ad6d604e7392f99.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Performance and Emission Analysis of an Energy System Based on a Thermochemical Process and a Proton-Conducting Electrolyte Fuel CellPerformance and Emission Analysis of an Energy System Based on a Thermochemical Process and a Proton-Conducting Electrolyte Fuel Cell1271352416710.24200/j40.2025.67629.1751FAParisaMojaverDepartment of Mechanical Engineering, Kermanshah University of Technology, Kermanshah, IranJournal Article20250825The growing need for clean energy and effective waste management highlights the importance of integrated systems like waste gasification combined with fuel cells, offering a sustainable solution to reduce emissions and convert waste into useful energy. This study presents a sustainable energy system based on a proton-conducting solid oxide fuel cell, in which the required fuel is supplied by gasifying municipal solid waste. The main goals are to maximize the net power output and minimize carbon dioxide emissions. The performance of the system was evaluated under varying operating conditions, including current density, inlet temperature, and fuel utilization ratio. A thermodynamic model of the system was developed using an engineering equation solver, and its accuracy was validated by comparing the results with data from previous studies. The comparison showed good agreement, confirming the reliability of the model. To further analyze the system, machine learning techniques were used to create regression models that predict the outputs based on the input parameters. These models helped examine the combined influence of the operational variables and supported a multi-objective optimization approach. The optimization results showed that higher current densities generally lead to increased power output. At high current densities, increasing the inlet temperature significantly raises carbon dioxide emissions, which may rise from about 1085 kg/MWh to nearly 4468 kg/MWh. In contrast, when the system operates at current densities below 3500 A/m2, carbon dioxide emissions remain in a lower and more stable range (between 500 and 800 kg/MWh), regardless of the fuel utilization ratio. The optimal operating point for the system was found at a current density of 5798 A/m2, an inlet temperature of 800 °C, and a fuel utilization ratio of 0.80. Under these conditions, the system generates a net power output of 315.3 kW, while emitting 1001 kg of carbon dioxide per megawatt-hour of electricity produced.The growing need for clean energy and effective waste management highlights the importance of integrated systems like waste gasification combined with fuel cells, offering a sustainable solution to reduce emissions and convert waste into useful energy. This study presents a sustainable energy system based on a proton-conducting solid oxide fuel cell, in which the required fuel is supplied by gasifying municipal solid waste. The main goals are to maximize the net power output and minimize carbon dioxide emissions. The performance of the system was evaluated under varying operating conditions, including current density, inlet temperature, and fuel utilization ratio. A thermodynamic model of the system was developed using an engineering equation solver, and its accuracy was validated by comparing the results with data from previous studies. The comparison showed good agreement, confirming the reliability of the model. To further analyze the system, machine learning techniques were used to create regression models that predict the outputs based on the input parameters. These models helped examine the combined influence of the operational variables and supported a multi-objective optimization approach. The optimization results showed that higher current densities generally lead to increased power output. At high current densities, increasing the inlet temperature significantly raises carbon dioxide emissions, which may rise from about 1085 kg/MWh to nearly 4468 kg/MWh. In contrast, when the system operates at current densities below 3500 A/m2, carbon dioxide emissions remain in a lower and more stable range (between 500 and 800 kg/MWh), regardless of the fuel utilization ratio. The optimal operating point for the system was found at a current density of 5798 A/m2, an inlet temperature of 800 °C, and a fuel utilization ratio of 0.80. Under these conditions, the system generates a net power output of 315.3 kW, while emitting 1001 kg of carbon dioxide per megawatt-hour of electricity produced.https://sjme.journals.sharif.edu/article_24167_766d169cbaa5c2e2c446686057396224.pdfSharif University of TechnologySharif Journal of Mechanical Engineering2676-472541220251221Optimal Vibration Control of Bladeless Wind Power GeneratorsOptimal Vibration Control of Bladeless Wind Power Generators1371502409210.24200/j40.2025.67390.1743FAMahsaPahlevanzadeDepartment of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan, Kashan, Iran.MohsenIrani RahaghiDepartment of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan, Kashan, Iran.MahdiMohammadimehrDepartment of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan, Kashan, Iran.Journal Article20250831The global energy crisis has drawn growing attention to bladeless wind power generators (BWPGs), which convert wind-induced vibrations into electricity. Their efficiency depends on keeping the natural frequency within resonance. This study presents an optimal control strategy for BWPGs using variable structural stiffness governed by the rod’s effective length. Continuous tuning keeps the natural frequency aligned with the vortex-shedding frequency, maximizing harvested power. The influence of stiffness, mass, and damping is analyzed, and design parameters such as geometry are optimized to maintain resonance under changing wind speeds. Numerical simulations agree with experiments, confirming the accuracy and effectiveness of the proposed model and optimization method.The global energy crisis has drawn growing attention to bladeless wind power generators (BWPGs), which convert wind-induced vibrations into electricity. Their efficiency depends on keeping the natural frequency within resonance. This study presents an optimal control strategy for BWPGs using variable structural stiffness governed by the rod’s effective length. Continuous tuning keeps the natural frequency aligned with the vortex-shedding frequency, maximizing harvested power. The influence of stiffness, mass, and damping is analyzed, and design parameters such as geometry are optimized to maintain resonance under changing wind speeds. Numerical simulations agree with experiments, confirming the accuracy and effectiveness of the proposed model and optimization method.https://sjme.journals.sharif.edu/article_24092_94201ed7fc518c4064ade9dd2d4c773f.pdf