https://mme.modares.ac.ir/ Modares Mechanical Engineering en daily 1 Fri, 22 May 2026 00:00:00 +0330 Fri, 22 May 2026 00:00:00 +0330 https://mme.modares.ac.ir/article_28226.html In this study, the aerodynamic performance of a wing equipped with a slotted flap is investigated and compared using three-dimensional computational fluid dynamics simulations. To evaluate the influence of flap configuration on aerodynamic characteristics, three main designs are considered, including a baseline configuration (wing with a simple flap), a double-slotted flap configuration, and a four-bar linkage flap mechanism. Lift, drag, and pitching moment coefficients are computed and analyzed over a range of angles of attack for different flap configurations, and flow patterns are examined to identify flow separation and stagnation phenomena.The results indicate that although the baseline configuration improves lift at low angles of attack and enhances performance during takeoff and landing phases, it suffers from reduced aerodynamic efficiency and increased drag and pitching moment at higher angles of attack due to intensified flow separation. In contrast, the double-slotted flap configuration significantly increases the lift coefficient and delays flow separation by increasing the effective camber and forming a flow channel between the flaps, albeit at the expense of increased drag. The analysis of the four-bar linkage mechanism demonstrates that simultaneous control of the flap gap and overlap plays a crucial role in regulating the aerodynamic behavior of the wing. Among the investigated cases, the G3 configuration provides the best balance between lift enhancement, drag control,, and pitching moment stability. https://mme.modares.ac.ir/article_28274.html Improving the performance of internal combustion engines requires a thorough understanding of the interactions among various engine parameters under dynamic operating conditions. This study investigates the effects of manifold roughness, geometric parameters (compression ratio and bore-to-stroke ratio), spark timing, and catalytic converter characteristics on the performance of a gasoline engine. Simulations were conducted over a speed range of 1000 to 6000 rpm using a parametric analysis framework. The novelty of this research lies in the comprehensive assessment of engine parameters and their combined impact on key performance indicators — torque, power, and brake specific fuel consumption (BSFC). A comprehensive engine model was employed to evaluate parameter variations, and optimal combinations for each performance objective were identified. The results demonstrated that simultaneous optimization of geometric parameters, ignition timing, and exhaust system characteristics enhances gasoline engine performance, such that at zero-degree spark advance, maximum torque and power were achieved at 4000 and 6000 rpm with a 5–8% reduction in BSFC, and in the optimal exhaust configuration with a volume of 40,000 mm³ and catalyst density of 100 CPI, the minimum BSFC of 0.258 kg/kWh was obtained at 3000 rpm. https://mme.modares.ac.ir/article_28246.html Cold formed steel structures, known for their efficiency, cost-effectiveness and environmental benefits, play a pivotal role in meeting the needs of societies for durable, cost-effective and environmentally friendly structures. However, what ensures its stability and safety against lateral forces are steel shear walls. In this paper, a finite element model was developed based on laboratory data, which includes 3D deformable shell elements for columns, beams and steel cladding. In previous studies, the issue of bolts and their spacing, as well as the effect of steel sheet thickness, has not been addressed. The aim of this paper is to investigate the factors affecting steel shear walls through the analysis of data from the finite element analysis of CFS shear walls. Then, using a regression substitution model, the effects of the parameters of plate thickness (t) and edge screw spacing (s) on the maximum shear capacity, displacement, initial stiffness and energy dissipation of the investigated escapement were investigated. The results showed that the maximum shear capacity increases nonlinearly with t and decreases with s. To evaluate the proposed model, the performance metrics R²=0.9816, MAE=12.42, and RMSE=17.28 were used. These values indicate a very good fit between the model predictions and the results obtained from numerical simulations and experimental data. The findings provide practical tools for optimizing CFS shear walls, improving seismic performance and filling gaps in key parameters. Finally, the model output was converted into a design plan that allows for direct estimation of the shear wall capacity in each combination. https://mme.modares.ac.ir/article_28312.html In this study, the transient energy and exergy performance of a novel solar air heater incorporating a phase change material (PCM), a porous matrix and an air recycling system was investigated based on the climatic data of Bojnord city using an analytical–numerical approach. Energy balance equations for the system components were derived analytically, and local temperature distributions along the channel and over time were computed. Three configurations were considered: a reference system without PCM and porous matrix, a system with PCM, and a combined system with both PCM and porous matrix. Results showed that PCM reduced thermal fluctuations and sustained heating during periods without solar radiation, with outlet air temperature approximately 6 °C higher than the reference system. Moreover, the porous matrix enhanced flow turbulence and heat transfer surface area, resulting in a more uniform thermal response. The analysis of mass flow rate effects in the combined system indicated that increasing the flow rate from 0.01 to 0.025 kg/s raised cumulative thermal efficiency from 48.02% to 65.88%, while cumulative exergy efficiency decreased from 3.58% to 1.82%, demonstrating that higher flow rates enhance heat recovery, whereas lower flow rates improve the quality of the output energy. The main novelty of this study lies in the simultaneous investigation of the effects of a phase change material (PCM) and a porous matrix in a solar air heater under Iranian climatic conditions. The findings suggest that the proposed system can be effectively applied for energy-efficient heating of residential and industrial buildings. https://mme.modares.ac.ir/article_28103.html This study aims to experimentally and numerically investigate the energy absorption of square lattice tubes with uniform and functionally geometrically graded distributions of re-entrant auxetic cells. Three stainless steel 304 specimens were fabricated using a rotary laser cutting machine. These specimens included two auxetic tubes with uniform cell distribution and one with a functionally geometrically graded cell distribution. Quasi-static axial compression tests were conducted on the specimens using a 300 kN universal testing machine. Numerical simulations were performed using Abaqus, and the results were validated against experimental data. The influence of cell angle and cell-wall thickness on the energy absorption capacity of uniformly distributed auxetic tubes was evaluated numerically. Additionally, the energy absorption of square auxetic tubes with three types of functionally geometrically graded auxetic cell distributions was investigated using the finite element method. The evaluation parameters for analysis are energy absorption, specific energy absorption, initial peak force, and crushing force efficiency. The functionally geometrically graded distributions of auxetic cells improved the evaluation parameters relative to uniform cell distributions in lattice tubes. Specifically, the optimally performing graded tube (Gt-Re45t1.0t1.6) exhibited 56% higher energy absorption and 65% higher specific energy absorption compared to the best-performing uniform tube (Ut-Re45t1.4t1.4). Furthermore, its crushing force efficiency was 165% higher, while the initial peak force was 41% lower. https://mme.modares.ac.ir/article_28130.html This study presents a robust and intelligent control method for flexible satellites operating under underactuated conditions. When the number of actuators is fewer than the system's degrees of freedom, issues like instability and vibrations arise. To address these problems, a combination of super-twisting sliding mode control and high-order adaptive sliding mode control, along with reinforcement learning, is used. Reinforcement learning helps to adaptively adjust the control gains, improving the system’s performance in the presence of disturbances and actuator failures. Quaternion parameters are utilized to avoid singularity issues when modeling the satellite's angular orientation. In this approach, the control inputs for the first and second axes are adjusted to reduce the error in the third axis without requiring direct control. Various simulations have shown that the proposed method outperforms classical approaches in reducing errors, minimizing chattering, and enhancing system stability. Furthermore, the high-order adaptive sliding mode control demonstrates greater stability against model uncertainties, although with longer settling times. These results indicate the high potential of the proposed methods for use in sensitive space missions. https://mme.modares.ac.ir/article_27872.html Conventional DVA optimization offers little direct control over shaping the frequency response, and weak parameter screening lets unnecessary variables persist, leading to over-parameterized designs. This paper presents a unique criterion (C_s) that integrates normalized, weighted objectives for peak positions, peak amplitudes, bandwidth, and other factors, incorporating a specific sparsity term that mitigates the inclusion of superfluous parameters. The framework is implemented in the DeVana software, which was developed by the authors, and it is utilized for a fully coupled 1DOF–1DOF benchmark that includes a designated avoidance band within the frequency range of 1000 to 2000 Hz for the purpose of conducting a case study. The optimized DVA divides the baseline resonance into two narrow peaks at the band edges and attenuates the in-band response, while the majority of ν parameters approach zero, leaving only a limited set of β, λ, and μ active. Convergence was achieved at an optimal fitness of 0.001206. This fitness is composed of 40.8% from C_s, 34.7% from the sparsity penalty, and 24.5% from the target-accuracy term. Overall, combining the design goals into a single, interpretable objective enables direct FRF targeting and streamlined DVA synthesis, delivering rapid, criteria-satisfying tuning with only the minimal set of screened parameters https://mme.modares.ac.ir/article_28006.html Accurate state estimation in INS/GNSS integrated navigation is critical, and its most common implementation, the Extended Kalman Filter (EKF), is highly dependent on the tuning of its process noise covariance matrix (Q). Conventional tuning methods, such as those based on stationary Allan-variance (AV) analysis, often fail to capture sensor behavior under real-world dynamic conditions, leading to filter inconsistency, sub-optimal accuracy, and poor dynamic response, such as overshoot upon GNSS re-acquisition. This paper proposes a novel, data-driven offline framework to optimize Q. Our approach parameterizes the continuous-time covariance (Qc) using four physically meaningful scalars and tunes them using a hybrid Particle Swarm Optimization and Genetic Algorithm (PSO-GA). The optimization minimizes a performance-based objective function: the mean trajectory-wide Root Mean Square Error (RMSE) evaluated over a comprehensive set of sliding, pure-INS windows. Experimental validation on a real-world dataset demonstrates that the proposed tuning framework significantly outperforms conventional Allan-variance based tuning. Specifically, it reduces the mean terminal position and attitude errors by 52% and 84%, respectively, while simultaneously tightening the estimated error bounds by 59% and 82%, indicating superior filter consistency and robustness. Critically, in a simulated GNSS outage-and-recovery scenario, the proposed filter exhibited rapid, stable convergence without any overshoot, a significant improvement over the AV-tuned filter which suffered from severe overshoots. By directly linking the Q matrix parameters to observed navigation performance, this work provides a practical and robust methodology for EKF tuning. https://mme.modares.ac.ir/article_28064.html In this study, the evolution of thermophysical and rheological properties of Aeroshell Turbine Oil 500 during its service life was experimentally investigated in two helicopter platforms operating under different conditions: a Military Attack Helicopter (MAH) subjected to severe thermal and mechanical loads, and a Military Utility Helicopter (MUH) operating under comparatively milder conditions. Engine and gearbox oil samples were collected over 200 hours of operation at 25-hour intervals. The experimental analysis included measurements of viscosity, thermal conductivity, density, and specific heat capacity, along with the evaluation of thermal diffusivity and rheological behavior. The results indicated that oil degradation in the engine was significantly more severe than in the gearbox. Kinematic viscosity increased by 34% in the MAH engine and 25% in the MUH, leading to a proportional rise in frictional losses. Thermal conductivity decreased by 23.7% in the MAH and 18.9% in the MUH, reflecting a reduction in oil cooling capability. In both platforms, specific heat decreased while density increased, indicating structural changes associated with thermal aging. Rheological analysis showed Newtonian behavior in the gearboxes of both helicopters. However, engine oil exhibited nearly Newtonian behavior after prolonged operation and transitioned to mild shear-thinning behavior in the MAH engine during the final service stage. These findings highlight the importance of continuous monitoring of oil thermophysical properties in high-load aircraft systems and provide a basis for optimizing maintenance strategies, lubricant selection, and thermal management system design. https://mme.modares.ac.ir/article_28135.html Abstract: This paper introduces a robust adaptive controller tailored for collaborative multiple robots and equipped with elastic joints. It utilizes a simple model of manipulator dynamics, treating all other dynamics as lumped uncertainty. The proposed approach integrates Function Approximation Techniques (FAT), specifically Bernstein-type rational functions, to estimate lumped uncertainty. Recent advancements have utilized FAT-based robust adaptive controllers for uncertainty estimation. However, our innovation distinguishes itself from prior research by minimizing the required regressor matrices. This advantage becomes particularly pronounced as the number of manipulators and their degrees of freedom increase. In addition, the coefficients of the Bernstein-type rational functions are adjusted by the adaptation laws derived from stability analysis, which are not presented in the previous literature. To the best of our knowledge, this paper marks the first engineering application of Bernstein-type rational functions for function approximation in adaptive form. Stability analysis guarantees that all error signals remain uniformly ultimately bounded (UUB). The theoretical advancements are validated by employing two elastic joint manipulators to transport a rigid object. The outcomes are also compared with two advanced approximation techniques to show the precision and effectiveness of the proposed controller design. The results exhibit the usefulness of the proposed control scheme, facing uncertainties and disturbances https://mme.modares.ac.ir/article_28217.html Air curtains are commonly employed in a variety of applications, including industrial ventilation systems, commercial buildings, fire safety measures, and smoke control systems. These devices are particularly effective in creating an invisible barrier of high-velocity air that separates indoor and outdoor environments. This barrier significantly reduces the infiltration of external air, thereby limiting the spread of pollutant gases within enclosed spaces. In addition to improving indoor air quality, air curtains contribute to temperature regulation and energy efficiency by minimizing air leakage and reducing heat transfer across the separation boundary. This study focuses on enhancing the performance of air curtains for pollutant containment, specifically the control of CO₂ gas mass fraction under varying air and pressure conditions that act as external disturbances. To achieve this, a sliding mode control (SMC) method is integrated into the regulation mechanism of the air curtain velocity. The SMC approach is known for its robustness and effectiveness in handling systems with high degrees of uncertainty or external perturbations. A wall jet configuration of the air curtain, combined with the SMC strategy, is subjected to comprehensive numerical simulations. These simulations evaluate the system’s ability to maintain effective pollutant separation and control in dynamically changing environments. The results demonstrate that the proposed control system significantly enhances the stability and performance of the air curtain, ensuring consistent pollutant containment. Even under critical pressure fluctuations, the system maintains optimal functionality, offering improved safety, and operational efficiency.   https://mme.modares.ac.ir/article_28243.html The design and maneuvering analysis of Autonomous Underwater Vehicles (AUVs) typically require multiple independent tools, resulting in time-consuming and inefficient workflows. To address this limitation, this research introduces SUT-AUVSIM, a novel graphical user interface that integrates hydrodynamic body design, derivative estimation, and maneuvering simulation within a single framework, significantly reducing the overall analysis time from several months to a few minutes. The software enables users to design C-type AUV hulls based on DARPA classes, Series 58, Myring, and DRDC configurations, which are not simultaneously supported in existing tools. Once the body is designed, SUT-AUVSIM estimates the hydrodynamic derivatives of the main body and appendages using strip theory. The algorithm includes a database of control surface profiles, such as NACA 0009, 0012, 0015, and elliptic sections, to facilitate design flexibility. After computing the derivatives, the software simulates traditional marine maneuvers, including turning, descending, and helical motions. The simulation results are exported as a .txt file, containing data such as position, velocities, Euler angles, and effective angles of attack for the appendages. The maneuver parameters are generated quickly, allowing users to evaluate the impact of hydrodynamic parameters on the maneuverability of AUVs. This capability makes SUT-AUVSIM a valuable tool for optimizing AUV designs and improving their performance in real-world scenarios. https://mme.modares.ac.ir/article_28277.html Scaling high strain-rate phenomena in concrete structures remains challenging due to the nonlinear and strain-rate-dependent behavior of concrete, which prevents full similitude between scaled models and prototypes. This study proposes an analytical framework termed the Finite similitude Method for scaling concrete structures subjected to high-rate impact loading. The formulation is derived from the integral forms of the conservation laws of mass, momentum, and energy, while explicitly incorporating strain-rate-dependent material behavior. Scaling factors are established for both purely dimensional and combined dimensional–material scaling, enabling extrapolation from scaled models to full-scale structures. To assess the method’s accuracy, numerical simulations were conducted for rigid spherical projectile penetration at one-fifth and one-tenth scales, and rigid ogive-nosed projectile penetration at 1.15 and 1.67 scales, impacting concrete targets with varying compressive strengths. Simulations were performed using Autodyn, and concrete behavior was modeled with the RHT constitutive model. Results show that increasing the scaling factor leads to larger deviations in peak force, absorbed energy, crater diameter and depth, and residual velocity. Maximum deviations reached 8% in dimensional scaling and 24% in dimensional–material scaling for spherical projectiles, and 13.2% and 21.1%, respectively, for ogive-nosed projectiles. The findings confirm that the proposed method provides reliable accuracy within limited scaling ranges and offers a practical tool for designing scaled impact experiments in concrete structures. https://mme.modares.ac.ir/article_28289.html Exposure to helicopter vibrations during flight and maneuvers can lead to long-term physical strain on pilots, particularly in the low-frequency range (0–20 Hz). While seat suspensions provide some vibration isolation, the seat cushion plays a critical role in overall ride comfort. This study presents an integrated computational and experimental investigation of nonlinear polyether polyurethane seat cushions and their effect on helicopter pilot comfort. Ride comfort is initially analyzed using a 4-DOF biodynamic model and subsequently extended to a 5-DOF model to explicitly include seat cushion dynamics. Experimental measurements of both linear and nonlinear stiffness and damping properties are conducted through modal analysis tests, providing data for model validation. Results demonstrate that considering nonlinear cushion behavior significantly improves predictions of transmissibility, mechanical impedance, and apparent mass, showing strong agreement with experimental observations. The findings highlight the importance of accurate nonlinear modeling for the design of seat cushions that enhance vibration isolation and improve overall pilot ride comfort. https://mme.modares.ac.ir/article_28290.html The main objective of this paper is to present a novel approach for dynamic modeling of manipulators mounted on a flying base. The most significant challenges addressed in this research can be summarized as follows: 1) Determining an appropriate formulation for computing the generalized forces of the system, including both the active forces generated by the actuators and the passive forces arising from the constraints governing the system. 2) Defining a desired trajectory for the flying base that incorporates not only the desired position but also the desired orientation. 3) Developing an automatic and systematic dynamic modeling framework such that increasing the number of links in the robotic manipulator or the flying base does not impose any limitation on the derivation of the system’s equations of motion. 4) Arranging the motors installed on the flying base in a manner that enables arbitrary motion in three-dimensional space. To overcome these challenges, the overall robotic structure—comprising the flying base and the mounted manipulator is first decomposed, through a fully systematic procedure, into a specified number of substructures. The dynamic equations of motion of each substructure (which can be regarded as an open kinematic chain with a moving base) are then derived using the recursive Gibbs–Appell algorithm. Subsequently, by appropriately combining the equations of motion of these robotic chains, the kinetic equations of motion of the complete system are obtained, explicitly accounting for the mutual dynamic interactions between the flying base and the robotic manipulator. https://mme.modares.ac.ir/article_28291.html Autonomous vehicles require a precise control system capable of handling nonlinear vehicle dynamics safely perform agile maneuvers, such as lane changes. However, in real-world operating conditions, factors such as sensor measurement noise, process noise, time delays, and data packet loss can compromise the stability of the control system. In this research, an integrated control framework based on Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) is proposed. In the proposed method, the MHE filters out noise effects and reconstructs the system states during periods of data loss and time delays by incorporating physical constraints and the dynamic model. Subsequently, the NMPC receives the corrected states and calculates optimal commands aimed at minimizing the tracking error and maintaining passenger comfort. Simulation results of a double lane change maneuver at a speed of 108 km/h demonstrate that in a critical scenario (comprising a 100 ms network delay, 20% data packet loss, sensor noise, and uncertainties arising from employing a twin-track model with the Pacejka tire formula in the simulation plant), the proposed approach exhibits superior performance compared to the Extended Kalman Filter (EKF) algorithm. This structure fully maintains the vehicle's stability while preventing undesirable oscillations in the steering angle and traction force. Recording a maximum lateral error of 0.1 m and a Root Mean Square Error (RMSE) of 0.044 m demonstrates the outstanding performance of this system in ensuring safety and stability. https://mme.modares.ac.ir/article_28348.html This paper focuses on designing a controller to regulate the temperature of a horizontal metal bar with varying thermal conductivities by manipulating the heat flux. To this end, the governing partial differential equations of the bar are first discretized using the finite difference method, resulting in a set of ordinary differential equations that establish a state-space representation for the system. The high order of the resulting state-space model leads to a complex final controller, so reduced-order transfer function parameters are determined for different conductivity values using an optimization-based approach. Open-loop simulation results show that the obtained low-order models achieve over 99% accuracy for various conductivity cases. Internal model controllers are then designed for different conductivity scenarios using these reduced-order models and applied to the original system. Simulation results indicate that the designed internal model controller exhibits enhanced performance in tracking the desired reference input and rejecting disturbances compared to other methods. The system output effectively follows the desired temperature profile with appropriate speed, minimal overshoot, and zero steady-state error. https://mme.modares.ac.ir/article_28352.html The aim of this research is to design an intelligent controller capable of achieving accurate trajectory tracking of a quadrotor in environments with varying wind conditions. To this end, the dynamic modeling of the quadrotor was first carried out. Wind modeling was also implemented by adding horizontal wind acceleration to the translational dynamic equations of the vehicle. Next, to ensure precise position and attitude control of the quadrotor in the presence of wind disturbances, a hybrid control framework was designed, consisting of a baseline proportional–integral–derivative (PID) controller, a reinforcement learning–based gain tuner, and a disturbance observer along with its compensator. For adaptive tuning of the PID gains during trajectory tracking, the DDPG and TD3 reinforcement learning algorithms were utilized. Finally, to evaluate the performance of the control framework, various experiments were conducted under no-wind conditions and under different wind intensities across multiple trajectories. The simulation results indicated that in environments with varying wind, adding the observer and compensator to a fixed-gain PID controller reduced the tracking error by 15% compared to the standalone PID controller. Additionally, PID control with reinforcement learning–based gain tuning, combined with the observer and compensator, reduced tracking error by 25% compared to the fixed-gain case. In the lemniscate trajectory, the DDPG algorithm performed 10% better than TD3; in the circular trajectory, the TD3 algorithm performed 5% better than DDPG; and in spiral trajectories, DDPG outperformed TD3 by 20%. https://mme.modares.ac.ir/article_28445.html This research experimentally evaluated the mechanical performance of UPVC door and window profiles produced using three industrial formulations designated TF-01, TF-02, and TF-03, which contain varying amounts of "ACR" and "CPE" impact modifiers, as well as Calcium Carbonate (〖"CaCO" 〗_3). A comprehensive series of standard tests, including flexural modulus, tensile impact strength, material and profile Charpy impact strength, falling-weight impact test, and compression and tensile stress tests on welded corner joints, were conducted in accordance with the Iranian National Standard INSO 12291-1 and corresponding international standards, at the Plastics Technology Institute of the Roozwin Industrial Complex. The results clearly demonstrate that the TF-03 formulation, characterized by the optimized balance of "ACR" and a reduced 〖"CaCO" 〗_3content from “36Phr” (in TF-01) to “29Phr”, yielded significant performance improvements. Specifically, TF-03 achieved a maximum tensile impact strength of “683 kJ/m2”, substantially higher than the “297 kJ/m2” recorded for TF-01. Furthermore, its profile Charpy impact strength reached “51 kJ/m2”, surpassing the minimum standard requirement (≥〖"\"45 kJ/m" 〗^2"), while TF-01 only reached “30.8 kJ/m2 kJ/m2”. Additionally, the falling-weight impact tests indicated that all three formulations exhibited satisfactory performance (zero failures in ten applied impacts). It can be stated that the reduction of Calcium Carbonate concentration to “29Phr”, by mitigating stress concentration, was a key factor enabling TF-03 to attain the highest toughness and achieve full compliance with the standard’s impact requirements. https://mme.modares.ac.ir/article_28446.html In recent years, significant advances in materials science and engineering have enabled the development and application of novel materials in engineered structures. Among these materials, composites have attracted increasing attention due to their high strength-to-weight ratio, favorable mechanical properties, and design flexibility. One important application of these materials is the fabrication of sandwich panels with lightweight cores and stiff skins, which can serve as suitable alternatives to conventional materials in sectors such as construction and transportation. In the present study, the fabrication and mechanical characterization of bio-based wood-core composite sandwich panels were investigated. Thermoplastic samples were fabricated using the hot-press method, while thermoset samples were produced by the vacuum-assisted resin infusion process. The face sheets of the thermoplastic panels consisted of glass fiber–reinforced polyamide 6, whereas glass fiber–reinforced epoxy resin was used as the face sheet in thermoset samples. Mechanical performance was assessed by three-point bending tests, and parameters such as face bending stress, core bending stress, and overall flexural strength were obtained experimentally. Furthermore, indices of strength-to-weight ratio and energy absorption were calculated and compared across the different systems. Finally, the results were benchmarked against findings from previous studies to highlight performance improvements and potential advantages of the proposed configurations. https://mme.modares.ac.ir/article_28586.html This paper investigates and analyzes an advanced multi-generation combined system that utilizes liquefied natural gas (LNG) as the primary energy source. The proposed system consists of a main Brayton cycle, a supercritical carbon dioxide (sCO₂) cycle, and two organic Rankine cycles (ORCs) as heat recovery subsystems. In addition, a water electrolysis unit for hydrogen production and a reverse osmosis (RO) desalination unit are integrated into the system. By exploiting the energy released from methane combustion in the combustion chamber, the system not only generates 145471 kW of net power, but also performs LNG regasification for injection into the urban natural gas network. Simultaneously, part of the generated power is used to produce 43.1 kg/h of hydrogen in the electrolyzer and to desalinate 30 kg/s of freshwater in the RO unit. A comprehensive energy, exergy, and exergo-economic analysis of the system is carried out using the Engineering Equation Solver (EES) software. The results indicate that the integrated system achieves high energy and exergy efficiencies while simultaneously delivering four valuable outputs, namely electricity, natural gas, hydrogen, and freshwater, at a considerable scale. https://mme.modares.ac.ir/article_28594.html This study investigates the propagation behavior of Lamb waves in a steel beam at varying inter-sensor distances, employing CWT, FFT, and STFT to evaluate their effectiveness for time–frequency and energy-based signal characterization. Results show that the Lamb-wave time-of-flight exhibits minimal variation despite changes in sensor spacing, yielding a nearly constant group velocity of approximately 4540 m/s, which confirms the stable propagation of the S₀ mode. Multiscale wavelet analysis reveals that nearly 90% of the total energy is concentrated in Scale‑1, while the combined contribution of Scales 2–5 remains below 10%, indicating a dominant, low-dispersion single-mode response. Quantitative CWT-based indicators also show consistent trends with increasing distance. Wavelet energy increases by about 20%, whereas entropy decreases from 0.4908 to 0.4651, reflecting stronger energy localization in Scale‑1 and improved separation of the S₀ mode from background noise and secondary modes. The RMS value increases from 0.2199 to 0.239, suggesting reduced attenuation and lower dispersion along the propagation path. The reduction in kurtosis further indicates diminished impulsive peaks, increased waveform smoothness, and an enhanced signal-to-noise ratio. Overall, the findings demonstrate that CWT provides superior capability over FFT and STFT in analyzing energy evolution, attenuation characteristics, and time–frequency dynamics of guided waves. These advantages establish CWT as a robust quantitative tool for structural health monitoring and guided-wave analysis. https://mme.modares.ac.ir/article_28597.html Compressive strength is one of the most critical performance indicators of high-performance concrete (HPC), playing a key role in the safety, durability, and load-bearing capacity of structures. Due to the time-consuming and costly nature of conventional laboratory testing methods for determining this parameter, the application of intelligent data-driven approaches has gained increasing attention as an efficient and accurate alternative. In this study, to predict the compressive strength of high-performance concrete, two models—Gradient Boosting Regression and Ada Boost Regression—were employed as advanced machine learning algorithms. The dataset used in this research consists of 1,030 experimental HPC samples collected from the University of California, Irvine database, including various mix design parameters such as cement content, water, blast furnace slag, fly ash, superplasticizer, aggregates, and specimen age. Initially, correlation analysis was conducted to examine the relationships between input variables and compressive strength, revealing that cement content, concrete age, and superplasticizer dosage have the strongest positive correlations, while water content exhibits the most significant negative correlation with compressive strength. Subsequently, the proposed model was trained and evaluated using a ten-fold cross-validation strategy. Subsequently, the two proposed models were trained and evaluated using 10-fold cross-validation. The results demonstrated that the Gradient Boosting Regression model possesses higher accuracy and reliability in predicting the compressive strength of high-performance concrete across all evaluation metrics. The findings of this study highlight the strong potential of boosting-based machine learning algorithms as reliable and cost-effective alternatives to traditional experimental methods for the design and performance assessment of advanced concrete materials. https://mme.modares.ac.ir/article_28604.html This study experimentally investigates the effect of projectile nose shape on the low-velocity impact response of sandwich panels with 3D-printed lattice and corrugated cores. The face sheets were manufactured from glass-fiber-reinforced polymer composites, and the cores were fabricated from polylactic acid (PLA) using the fused deposition modeling (FDM) process. Drop-weight impact tests were conducted at different energy levels using blunt, hemispherical, and conical projectiles. Force–time and displacement–time histories were recorded, the absorbed energy was obtained from the corresponding force–displacement curves, and post-impact inspections were performed to identify damage mechanisms. The results show that projectile nose geometry significantly influences contact conditions, stress concentration, and failure modes: blunt projectiles generally produce higher peak forces, whereas conical projectiles promote localized penetration and more severe localized damage. Regarding core architecture, corrugated cores exhibited higher initial stiffness under a considerable portion of the tested conditions, while lattice cores provided superior specific energy absorption at certain impact energy levels. Overall, the findings indicate that the relative advantages of each core type depend on impact energy and nose geometry, emphasizing that core selection should be guided by the intended performance criteria (initial stiffness versus energy absorption) and loading conditions. https://mme.modares.ac.ir/article_28635.html This study introduces a novel and integrated configuration aimed at the complete and maximum utilization of waste heat in order to enhance exergy efficiency. In the proposed system, which is capable of simultaneous power and hydrogen production, a high-temperature supercritical carbon dioxide (sCO2) cycle is directly integrated with a lower-temperature Rankine cycle. The primary innovation of this system lies in its advanced internal heat management structure, whereby the heat rejection process of the sCO2 cycle is replaced by the evaporation process in the Rankine cycle. This approach enables effective recovery of internal heat and its conversion into additional power output. A portion of the net power generated by this high-efficiency thermodynamic system is fully allocated to a proton exchange membrane (PEM) electrolyzer for green hydrogen production. To comprehensively evaluate the thermodynamic performance and economic potential of the system, detailed exergy and exergoeconomic analyses are conducted. The results demonstrate that the proposed integrated configuration significantly reduces total exergy destruction while achieving a substantial increase in power output and elevating the hydrogen production rate to optimal levels. Overall, this cogeneration system is presented as an efficient and effective solution for clean energy production from low-grade thermal resources. https://mme.modares.ac.ir/article_28641.html The cylinder head is one of the most important and complex parts of the engine that withstands thermal and mechanical loads. Thermomechanical stresses applied to the cylinder head can lead to fatigue damage. The aim of this research is to evaluate the effect of local plasticity on the low-cycle fatigue (LCF) life of the cylinder head. For this purpose, in the first step, thermo-mechanical analysis of the cylinder head was performed using ANSYS software to predict temperature and stress. Then, the effect of local plasticity on the low-cycle fatigue life was evaluated using the Neuber method using ANSYS nCode Design Life software. Constants of the Chaboche hardening model of the aluminum alloy were calculated using low-cycle fatigue tests at different temperatures. LCF tests were simulated by ANSYS software, showing a very good fit between the experimental and simulation results of LCF tests.The results of thermo-mechanical analysis showed that the maximum temperature and stress in the cylinder head were 212.8°C and 87.211 MPa, respectively. The minimum LCF life of the cylinder head with and without considering local plasticity was predicted to be 1486 and 3058 cycles, respectively. Based on the results of the low-cycle fatigue life, not considering the effect of local plasticity causes the LCF life of the cylinder head to be estimated significantly higher than the allowable limit. Therefore, it is necessary to consider the effect of local plasticity in the analysis of the LCF life of the cylinder head. https://mme.modares.ac.ir/article_28655.html This study aims to develop an intelligent and integrated framework for the predictive monitoring of the performance of air-cooled heat exchangers in refinery applications. The main innovation lies in the simultaneous and systematic investigation of the impact of fluid molecular structure (focusing on hydrocarbon branching) and dynamic operating parameters within a data-driven approach. To this end, a real heat exchanger was configured using simulation software and technical data. Ten hydrocarbon compounds with linear, two-branched, and three-branched structures were selected, and for each compound, one hundred operational scenarios were executed by varying key parameters, including inlet temperature, inlet flow rate, and fouling coefficient. Quantitative findings revealed that altering the molecular structure to longer branched forms significantly increased pressure drop by 2.25 to 3 times under a constant fouling coefficient, resulting in a decrease in heat exchanger performance. This indicates that changes in fluid structure (e.g., branching) have a substantial impact on exchanger performance. Additionally, sensitivity analysis using the Sobol method identified the inlet flow rate as the most influential parameter on exchanger performance, with an index of 0.8086. Accordingly, the operational output of the research is a predictive monitoring framework based on machine learning models, which, by defining three levels of performance indicators (optimal, requiring monitoring, and critical), facilitates early detection of fouling and optimal maintenance planning. The implementation of this system could enhance the reliability of heat exchangers and achieve significant cost savings in operational expenses by reducing unplanned shutdowns.