https://sjme.journals.sharif.edu/ Sharif Journal of Mechanical Engineering en daily 1 Sun, 21 Dec 2025 00:00:00 +0330 Sun, 21 Dec 2025 00:00:00 +0330 https://sjme.journals.sharif.edu/article_24161.html - https://sjme.journals.sharif.edu/article_24024.html 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_24023.html 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_24021.html Manufacturing 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 pump https://sjme.journals.sharif.edu/article_24022.html 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_24020.html 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_24005.html 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_24078.html 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_24087.html 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_24167.html 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_24092.html 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_24162.html - https://sjme.journals.sharif.edu/article_23980.html Health monitoring of rotating machinery is a critical engineering task that involves the measurement, recording, analysis, and evaluation of key parameters affecting machine behavior and performance over time. This process aims to assess the current condition and predict future behavior of mechanical systems to prevent sudden failures and optimize maintenance schedules. Among rotating components, the structural integrity of wind turbine blades is especially important, as damage can lead to costly downtimes or even catastrophic failures.Since the modal or resonant properties of a mechanical structure are directly influenced by its physical characteristics—such as stiffness, mass, and boundary conditions—any alteration caused by damage, like a crack, can lead to detectable changes in modal parameters. Therefore, by continuously monitoring the system and analyzing changes in these parameters, it becomes possible to detect structural degradation at an early stage.This study focuses on structural health monitoring (SHM) of a composite wind turbine blade using principles from fracture mechanics and vibration-based modal analysis. The numerical investigation is carried out by tracking the variations in natural frequencies as a crack initiates and propagates along the blade. Results indicate that the reduction in natural frequencies becomes more pronounced beyond a certain crack depth, enabling the identification of a critical threshold for maintenance intervention. Furthermore, it is observed that increasing the distance between the crack and the clamped root of the blade leads to a higher critical depth and more stable frequency behavior. For example, a crack located near the root with a depth of 250 mm results in about a 6% decrease in the first mode frequency, while a crack near the tip with a depth of 350 mm leads to over 20% reduction in the fourth mode, which is torsional and structurally critical.If resonance occurs in specific modes, the approximate location of the crack can be estimated based on the observed frequency. These findings confirm the effectiveness of SHM techniques for real-time damage detection and localization in composite blade structures. https://sjme.journals.sharif.edu/article_24154.html Rotating systems such as axial flow fans and wind turbines are essential components in modern engineering applications, serving crucial roles in cooling processes, ventilation, and the production of clean and sustainable energy. Despite their importance, one of the most persistent challenges associated with their operation is the generation of aerodynamic noise. This noise often originates from complex flow instabilities, with tip-leakage vortices and unsteady interactions near the blade tips being among the dominant sources. Such noise not only reduces the efficiency and reliability of these systems but also poses environmental and health concerns, particularly in urban and residential settings where noise exposure is critical. As a result, the development of effective noise-reduction strategies has become a pressing necessity in both industrial and academic research.Recent studies have highlighted the potential of porous casings as a passive and practical solution for mitigating aeroacoustic emissions. In this context, the present study investigates porous structures based on Triply Periodic Minimal Surfaces (TPMS), which are known for their unique geometric features, high surface area, and tunable porosity. Initially, the acoustic performance of several TPMS configurations was examined by calculating their sound absorption coefficients. Among the designs, the Gyroid structure with 50% porosity was identified as the most effective due to its balance of acoustic damping and mechanical integrity.The selected design was subsequently implemented in two representative case studies: the casing of an axial flow fan and the duct surrounding a ducted wind turbine. A comprehensive methodology combining high-fidelity numerical simulations and experimental validation was employed to capture both aerodynamic characteristics and underlying mechanisms of noise generation and suppression.Results clearly demonstrate that TPMS-based porous casings weaken the strength and scale of tip-leakage vortices and reduce turbulence intensity near the casing wall. Furthermore, they effectively attenuate tonal noise associated with the blade passing frequency as well as broadband noise caused by turbulence interactions. Quantitatively, the approach achieved a 6 dB reduction (≈11%) in the axial fan, alongside a 36% decrease in accumulated acoustic energy. For the ducted wind turbine, an 8% reduction in overall sound pressure level (OASPL) was observed.These findings confirm that TPMS-based porous casings represent a novel and efficient aeroacoustic treatment, offering significant potential for reducing noise in rotating machinery without compromising aerodynamic performance. https://sjme.journals.sharif.edu/article_24170.html In light of the depletion of fossil fuel resources and growing environmental concerns caused by greenhouse gas emissions, the utilization of renewable energy sources, particularly biomass, has garnered increasing attention. This study presents an innovative system for clean energy production using eucalyptus biomass. The proposed system consists of four main components: a gasification reactor, a steam methane reforming reactor, a water-gas shift reactor, and a palladium membrane for hydrogen purification. Thermodynamic modeling and simulation of the system components were conducted using Engineering Equation Solver software, with a particular focus on the effects of process temperature on system performance. The results indicate that increasing the temperature of the gasification reactor from 800 to 1000 K significantly influences the composition of the syngas. The hydrogen content increases from 32.35% to 40.71%, while carbon monoxide content rises from 9.93% to 18.85%. In the steam methane reforming reactor, elevated temperature improves reforming efficiency, reducing the carbon dioxide concentration in the product gas by 4.17%. On the other hand, in the water-gas shift reactor, higher temperature leads to a slight decrease in hydrogen conversion from 61.31% to 60.01%, accompanied by an increase in carbon dioxide content from 10.22% to 12.13%. These findings emphasize the critical role of temperature in directing the equilibrium and reaction kinetics within each subsystem. The hydrogen flux through the palladium membrane shows a substantial enhancement with temperature rise, improving from 0.29 to 1.52 J/m2.s. This reflects the superior performance of palladium membranes at higher temperatures for separating and purifying hydrogen from the gas mixture. The use of eucalyptus biomass as a renewable and widely available feedstock, coupled with advanced hydrogen production and purification technologies, presents a promising approach to addressing energy and environmental challenges. The insights gained from this study highlight the potential for improving overall system efficiency and hydrogen yield through careful thermal management across each reactor unit. https://sjme.journals.sharif.edu/article_24232.html Cyclones play a crucial role in particle separation from fluid streams due to their high efficiency and low cost. In this study, the performance enhancement of a gas cyclone was investigated through step-by-step geometric modifications. These changes were aimed at improving flow guidance, reducing turbulence fluctuations and increasing particle-wall interactions to improve overall cyclone performance a concept referred to in this study as flow control. Initially, the Stairmand cyclone was selected as the baseline model, and its performance was analyzed using numerical simulations with the Reynolds Stress Model (RSM) turbulence model and the Eulerian-Lagrangian approach in ANSYS Fluent software. The mesh generation was structured and adhered to quality criteria to ensure accurate results. The numerical model was validated against published experimental data, demonstrating good agreement with less than 10% error. Geometric modifications were applied to four main sections of the cyclone: the inlet, vortex finder, body, and collection section. The results showed that the 360-degree helical inlet design, by better guiding the flow and increasing particle-wall collisions, enhanced the separation efficiency by 11.52% and reduced the cut-off diameter by 12.14%, though it caused a 22.04% increase in pressure drop. The addition of a curved vortex finder reduced the pressure drop by 7.49% compared to the first modification and had a positive overall effect. Introducing a cylindrical vortex stabilizing rod in the cyclone body reduced flow oscillations and further improved separation efficiency by 1.15% compared to the previous stage. Finally, the implementation of a reverse cone in the collection section enhanced fine particle separation, reducing the cut-off diameter to 1.3 micrometers. In the current work, not only the performance indices have been evaluated, but also the physics of the flow have been tried to be captured. These findings provide a foundation for further cyclone optimizations and highlight the potential for improving their performance in industrial applications.