Li2FeSi04 is a promising cathode active material for lithium-ion batteries due to its significant theoretical capacity (332 mAhg-1). Nevertheless, its practical electrochemical performance faces significant hurdles due to low electron conductivity. In the research, a simple solid-state technique was used to synthesize the high-purity cathode material Li2FeSi04. Additionally, nitrogen-doped reduced graphene oxide nanosheets were fabricated using a household microwave-assisted process and then selectively deposited to coat the active cathode material to increase conductivity and significantly improve electrocatalysis. The properties of the as-prepared nanosheets and Li2FeSi04/ nitrogen-doped reduced graphene oxide nanocomposites are studied using X-ray diffraction, high-resolution transmission electron microscopy, field emission scanning electron microscopy, RAMAN spectrometry, and Fourier transform infrared spectroscopy techniques. The study investigated the influence of different amounts of as-prepared nanosheet coatings on the electrical conductivity of the Li2FeSi04 by comparing their band gap energy value. Accordingly, a lower band gap, indicates higher and better electronic conductivity in the cathode of lithium-ion batteries. Therefore, diffusion reflectance spectroscopy and electrochemical impedance spectroscopy were used to determine the band gap size and conductivity. Studies show that coating Li2FeSi04 particles with only 5 wt% nitrogen-doped nanosheets reduced the bandgap energy value by about 0.78 eV and increased the electrical conductivity by 54.31%. It is concluded that Li2FeSi04/ nitrogen-doped reduced graphene oxide nanocomposites can be a promising candidate as a high-performance cathode material for lithium-ion batteries.
In this paper, a two-layer stability control system based on output feedback is designed for electric vehicles with four in-wheel motors using super twisting sliding mode control and extended Kalman filter. The joint-extended Kalman filter method is used at the same time for estimating the state of the vehicle and the friction coefficients between the wheels and the road. In the upper layer controller, the control torque required to ensure the lateral stability of the vehicle is calculated. In the second layer, by using torque vectoring, the required traction forces for each wheel are determined so that the control torque calculated in the first layer is provided. Then the corresponding slip rates are calculated for the new adjusted longitudinal forces. Using the obtained slip rates as the desired slip rate for each wheel, the required wheel torques are computed by using appropriate longitudinal controller. Using the Kalman filter largely eliminates the effects of sensor noise and structural uncertainty on estimated parameters. The present algorithm can calculate the control inputs for the lateral and longitudinal control of the vehicle, as well as estimate the state of the system and estimate the friction coefficients between the wheels and the road at the same time. The results show the efficiency of the designed control system which is discussed on different maneuvers.
This research focuses on the impact of Carbon Nanotube geometry and dispersion on fracture behavior within nanocomposite materials. Specifically, straight and sinusoidal configurations were investigated under both ordered and disordered spatial arrangements. The analysis employed finite element methods and micromechanical techniques to explore crack propagation paths and evaluate interactions at the Carbon Nanotube-matrix interface. Fracture toughness across the four configurations was assessed based on the Maximum Tangential Stress criterion and the maximum energy release rate. The study concludes with a comparative evaluation of the findings and previously published results, confirming the reliability of the proposed modeling approach.
This paper presents a new design of a spiral solar air heater with a 90 turning of the air inside the passageway assembled between the absorber and bottom plate for the purposes of mixing process and extending the surface of heat transfer that finally leads to higher performance. To enhance the thermal efficiency, an air gap is considered at the top of the solar collector to reduce heat loss. The proposed solar collector is simulated numerically by the Finite Element Method using the COMSOL software. The set of governing equations for both forced and free convection turbulent air flows are solved based on the RNG k–ε turbulence model. In the energy equation solution, the effect of surface-to-surface radiation as an important phenomenon in solar collectors is considered. Numerical results reveal a high thermal efficiency of 75% for the test case with 100 solar heat flux and air mass flow rate of 0.01 kg/s. Compared to the conventional smooth duct solar air heater with 35% thermal efficiency, the designed solar collector operates with higher performance, and a more than 100% increase in thermal efficiency is achieved due to the applied technique with the limitation of pressure drop which is increases about three times in spiral solar air heater.
In this work, it is looked into how adding silicon nitride (Si3N4) particles into Functionally Graded Material (FGM) plates affects their resistance to fracture propagation. A comprehensive numerical study is performed using the extended finite element method (XFEM) implemented in the Abaqus software to investigate the impacts of different Si3N4 particle characteristics, including geometry, size, and volume percentage, on the fatigue behavior of FGM plates. The results indicate that these variables have a significant influence on the fracture formation rate and overall fatigue life of the FGM. Specifically, square Si3N4 particles displayed higher efficiency in arresting crack development compared to alternative shapes, which was attributable to their optimal stress distribution. Results show that adding 10, 20, and 30 weight percent of square Si3N4 particles with a side length of 0.89 μm to the FGM increased the fatigue life by 70.47, 57.69, and 53.79 percent, respectively, compared to the case without reinforcing particles. Furthermore, increasing the volume percentage of Si3N4 particles while concurrently reducing their size resulted in a significant gain in both fatigue life and overall strength of the FGM plates. These findings highlight the potential of Si3N4-reinforced FGMs as a highly effective method for reducing fatigue-induced damage and increasing the service life of engineering components. The findings of this study provide useful insights for the design and optimization of FGM-based structures under cyclic loading conditions.
This research focuses on optimizing the cooling system of a circular-to-rectangular transition duct in a turbine engine nozzle, a critical step in enhancing engine efficiency by enabling higher turbine inlet temperatures and increased thrust through afterburner usage, both of which significantly elevate exhaust gas temperatures. The study employs a combined film and impingement cooling method and utilizes fluent computational fluid dynamics software for analysis and optimization. Experimental design methodology was used to identify key parameters for optimizing the geometry for three blowing ratios (0.5, 1, and 1.5). Simulation results demonstrate that the optimal cooling configuration for all blowing ratios includes three rows of film cooling. The most influential parameters on cooling efficiency were found to be the diameter of the film cooling holes and the number of film cooling rows. For a blowing ratio of 1.5, increasing the hole diameter and the number of cooling rows resulted in a 32% and 33% increase in cooling efficiency, respectively. Regarding the relationship between cooling angle and efficiency, it was observed that efficiency increased up to 20 degrees and then decreased in blowing ratios of 0.5 and 1.5, while in a blowing ratio of 1, efficiency increased up to 30 degrees and then decreased. This research provides valuable insights into optimizing the cooling system of turbine engine nozzles, enabling more efficient and powerful engines.
One of the most commonly used techniques in 3D printing is Fused Deposition Modeling (FDM). Despite its widespread adoption, creating functional parts with suitable mechanical properties remains a significant challenge. Previous studies have often focused on various aspects of FDM. Still, there remains a lack of comprehensive research addressing the flexural properties of 3D-printed ABS plus polymer parts under bending loads. This gap in the literature motivated the current study. The manufacturing parameters in the FDM process, such as infill density (ID) (20, 50, and 80 percent), layer thickness (LT) (0.1, 0.2, and 0.3 mm), and raster angle (RA) (0, 45, and 90 degrees) were investigated to understand their mutual influence on the bending mechanical properties at ambient temperature through experimental design and analysis of variance. Reinforced ABS polymer filament was utilized in this research. The parameters were studied using the response surface method (RSM) based on the central composite design (CCD), employing quadratic regression equations for all responses to determine the model coefficients. Analysis of variance revealed that the raster angle is the most critical factor influencing the bending response, as it directly affects load transfer to the specimen. The optimal parameters identified for maximum bending strength were ID = 78.277%, LT = 0.295 mm, and RA = 1.599 degrees. The bending strength is maximum in thick layers and low raster angles.
This study addresses the prediction of the flutter speed for a double-sweep folding wing in subsonic airflow, an area less explored in past research. Two types of modeling are employed: structural and aerodynamic. The structural model treats the wing as an Euler-Bernoulli beam. For the aerodynamic model, Theodorsen's unsteady aerodynamic theory is used. This theory is initially in the frequency domain but is converted to the time domain using the Kussner function and a new formulation method. Kinetic energy, strain energy, and the work of aerodynamic forces are then calculated. The differential equations governing the wing structure are derived using Hamilton's principle. The wing's motion equation is obtained using assumed modes and the Galerkin method. The instability flutter speed is determined through the p-method, and graphs of frequency versus airflow velocity are plotted. The results indicate that using the Kussner function for variable airflow improves the accuracy of flutter speed prediction. The analysis of sweep angle changes on flutter speed and frequency revealed that sweep angle one has the least positive effect, while sweep angle two has the most positive effect on flutter speed and frequency, respectively.
In this paper the results of parametric study and multi-objective optimization for the effect of fresh air inlet angle, warehouse height and shelves fullness on the flow and temperature distribution in the pharmaceutical warehouses is presented. The warehouse is simulated in two dimensions and subjected to analysis via CFD using the ANSYS-Fluent software. Parametric study shows that increasing warehouse height in the studied range results in a more acceptable and more uniform temperature. A medium level of shelf occupancy leads to the worst temperature conditions, considering both the average quantity and uniformity. Altogether, shelves that hold a relatively low amount of medicines yield the most favorable temperature environment. When the inlet angle increases relative to the vertical line the temperature rises undesirably and its uniformity decreases. In the horizontal direction, the shelves further away from the symmetry axis, have higher temperatures and less uniformity. In the vertical direction, the middle shelves show better results in temperature and uniformity compared to the upper and lower shelves. As the height increases from 3 to 5 and 7 m, the average temperature decreases by 1.4% and 2.2%, respectively, and the temperature difference has decreased by approximately 32% and 42.2%. As the height of the storage increases, the average velocity in the warehouse decreases. The optimal point has been identified by taking into consideration both temperature and its uniformity.
This research investigates the vibration characteristics of composite shells featuring a cylindrical-hemispherical geometry, fabricated from functionally graded porous materials with varying thicknesses. Two kinds of boundary conditions are assumed: the first assumes both ends are free, while the second involves clamped and free edges for the cylindrical and hemispherical sections, respectively. The analysis employs three-dimensional elasticity principles in conjunction with the Ritz method, utilizing orthogonal polynomials like Legendre polynomials as admissible functions. The natural frequencies' convergence is demonstrated, and results are validated against prior findings from finite element and analytical methods. After confirming the model's accuracy, the influence of porosity is examined. The results indicate that a higher percentage of porosity leads to a decrease in the shell's natural frequencies. The study also investigates how natural frequencies are affected by various geometric parameters. Ultimately, the outcomes highlight the significant impact of porosity and geometric attributes on the frequencies of porous shells. Additionally, torsional and axisymmetric vibration modes are observed to be more influential under clamped-free conditions than under free-free conditions. A general trend of decreasing frequencies with reduced thickness is identified, and higher porosity levels, leading to lower stiffness, consistently reduce frequencies across all modes.
Integrated Guidance and Control (IGC) is a method devised in a framework in which guidance and control are considered integrated within, and unified rather than independent of each other. The advantage of IGCs is their ability to use interactions between guidance and control subsystems. This methodology is employed, intended to increase the performance of the Flying Vehicle by taking advantage of the synergy between the two processes of guidance and control. This article describes the process of designing and simulating the performance of the online model predictive controller, which was devised in order to guide the Flying Vehicle in a three-dimensional scenario to minimize the time to collision as well as the miss distance to the target. As for the controller design, an online predictive model is devised. In general, the controller model can be implemented in two ways: online and offline. In the implementation of the online type, the optimization problem of the control cost function is solved online in each time step, and The solution to this problem will determine the optimal control signal. According to the simulations, it was shown that the use of the proposed controller and the application of the integrated guidance and control model, led to smaller values for the Flying Vehicle-target miss distance and the time to collision as compared to those from the PID and LQR controllers
The objective of the present study was to analyze the cylinder heads' thermo-mechanical fatigue life. This investigation was done by employing the finite element method. Moreover, ANSYS software was also used to achieve temperature and stress predictions. The thermo-mechanical fatigue life was then examined using Sehitoglu theory and FEMFAT software. The cylinder head's elastic and plastic properties were acquired at various temperatures by low-cycle fatigue tests. Low-cycle fatigue tests were simulated by ANSYS software, and excellent agreement was observed between the experimental and simulation results low-cycle fatigue tests. According to the finite element analysis, 208.6°C and 89.475 MPa were the maximum temperatures and stresses in the cylinder head at the valve bridge, which is located betwixt exhaust valves. The thermo-mechanical fatigue life analysis showed 71.16%, 25.04%, and 3.79% for mechanical, oxidation, and creep damages, respectively. The thermo-mechanical fatigue results proved the significant impact of the mechanical damage on the cylinder head's total thermo-mechanical fatigue life. Moreover, the numerical results indicated the negligibility of the creep damage.
The mechanical ventilation smoke management system involves the use of supply fans, jet fans, and exhaust fans, which are activated at different times after a fire is extinguished. This paper numerically investigates the effect of the priority and delay of smoke management systems on smoke distribution and visibility in a car park after a fire, using Fire Dynamic Simulation Code 6.7.6. The flow rates of the exhaust fan, supply fan, and jet fan are 1.9 m³/s, 1.43 m³/s, and 1.67 m³/s, respectively. The fire, located near the supply fans, is modeled as a rectangle with dimensions of 2.0 × 0.8 m² and a power of 1.6 MW, lasting for one minute from ignition to extinguishment. Polyurethane is assumed as a flammable material. The priority and delay of the smoke management systems are evaluated through four scenarios over a period of 420 seconds. The results show that visibility reaches acceptable levels in all scenarios at all locations after 420 seconds. Additionally, the results indicate that the visibility of the upper half is highest for scenario a, at around 15 m. However, the visibility of the lower half is highest for scenario d, ranging between 20 and 30 m. It can be concluded that delaying the activation of smoke management systems is an effective strategy for facilitating smoke removal and fresh air intake.
This paper presents an improved framework for deep reinforcement learning algorithms integrating online system identification, based on the Dyna-Q architecture. The proposed framework is designed to tackle the challenges of both Multi Input Multi Output (MIMO) and Multi Input Single Output (MISO) systems in complex, industry relevant environments, thereby significantly enhancing adaptability and reliability in industrial control systems. It should be noted that in the suggested novel framework, the system identification and model control processes run in parallel with the control process, ensuring a reliable backup in case of faults or disruptions. To verify the efficiency of the aforementioned approach, comparative evaluations in the presence of three of the most common deep reinforcement learning algorithms, i.e. Deep Q Network (DQN), Deep Deterministic Policy Gradient (DDPG), and Twin Delayed Deep Deterministic Policy Gradient (TD3), are conducted on industry-relevant environments simulations available in OpenAI Gym, including the Cart Pole, Pendulum, and Bipedal Walker, each chosen to reflect specific aspects of the novel framework. Results demonstrate that the proposed method for leveraging both real and simulated experiences in this framework improves sample efficiency, stability, and robustness.
Carbon fiber-reinforced polymers are widely used in advanced applications due to their superb specifications. One of the principal problems in drilling such polymers is delamination which deteriorates the composite strength and can lead to part rejection during assembly. Ultrasonic vibration-assisted drilling is a newly developed machining method that induces higher workpiece quality. In this study, a comprehensive experimental examination was conducted with both mechanical and materialistic views. The materialistic parameters include graphene nanoparticles and lay-up arrangement. Furthermore, the mechanical parameters include drilling feed rate, tool type, and ultrasonic vibration. To follow this aim, different carbon fiber-reinforced polymer specimens were fabricated with various lay-up arrangements and graphene nanoparticle amounts. Besides, an analysis of variance was utilized to indicate the significant parameters. The results showed that the feed rate has the most effect on thrust force and delamination damage. Besides, graphene nanoparticles% and tool type were the significant parameters of delamination. To find the optimal settings, grey relational analysis was used. That was suggested to produce carbon fiber-reinforced polymer segments with symmetrical lay-up arrangements to reduce delamination damage. Furthermore, a lower feed rate value with 5% cobalt high-speed steel tool was suggested. Exerting ultrasonic vibration on the tool was also beneficial to improve the hole quality.
This paper numerically investigates the solidification performance improvement of phase change material in a triplex tube latent heat thermal energy storage unit by introducing an innovative longitudinal-parabolic fin. A numerical model based on the enthalpy-porosity approach is employed to simulate the discharging process. Simulation results reveal that the longitudinal-parabolic fins outperform the conventional straight fins in effectually increasing the phase change performance of the latent heat thermal energy storage unit. The complete discharging time of the triplex tube latent heat thermal energy storage unit with the proposed fin was reduced by up to 38.5% compared to that of the unit with straight fins. The study also investigates the influence of geometric parameters of the designed fin to achieve superior phase change material discharging efficiency. Effects of radial pitch and angular pitch of the longitudinal-parabolic fins on energy discharge time are studied by examining various cases under the constant total fins volume. Results infer that the radial pitch of parabolic fins has a moderate impact on solidification time improvement, while the angular pitch has a remarkable impact on reducing energy discharging time. Decreasing the angular pitch from 120° to 60° reduces the solidification time by 52.3%. The maximum of saving discharge time for the most efficient fin design is 61.8% in comparison with straight fins.
This study focuses on simulating bio-nanocomposite structures using polycaprolactone as the polymer matrix, reinforced with hydroxyapatite and titanium dioxide nanoparticles, both of which are biocompatible and biodegradable. To predict key mechanical and physical properties and reduce experimental costs and time, molecular dynamics simulations were employed. The validation process began by evaluating the mechanical properties, including Young’s modulus and Poisson’s ratio, and physical properties such as density, for the pure components: polycaprolactone, hydroxyapatite, and titanium dioxide. The results were compared with available experimental data. Following this, the study analyzed the nanocomposites containing different amounts of titanium dioxide (0%, 5%, 10%, 15%, and 20% by weight), while maintaining a constant total weight of 25% for hydroxyapatite and titanium dioxide, and 75% for polycaprolactone. In the simulation, the total composite weight was set at 8 grams, with 6 grams allocated to polycaprolactone. The findings show that increasing the titanium dioxide content significantly improves the nanocomposite’s mechanical properties due to the high stiffness of titanium. Specifically, compared to the sample without titanium dioxide, the addition of 20% titanium dioxide increased Young’s modulus, Poisson’s ratio, shear modulus, bulk modulus, and density by approximately 1.14, 3.01, 1.17, 5.99, and 14.85 times, respectively. To further verify these results, the stiffness matrix of the nanocomposites was computed using Materials Studio software.
A novel and unified approach is presented for analyzing the free vibration of rectangular nanoplates with elastic boundary conditions (BCs). The theoretical modeling is achieved using the nonlocal Mindlin plate theory, which accounts for the size-dependent behavior of nanoplates, while the artificial spring technique is employed to accommodate a wide range of BCs, including classical BCs, elastic BCs, and their combinations. The governing equations of motion are derived using the virtual displacement principle, followed by the application of the weighted residual method to obtain the nonlocal quadratic functional. The Rayleigh-Ritz method, employing Gram-Schmidt polynomial series as the admissible displacement functions, is then utilized to solve the eigenvalue problems associated with the free vibration of nanoplates. The present approach is validated through a series of comparison and convergence studies, which demonstrate its high accuracy and low computational cost. Finally, parametric numerical investigations are conducted to elucidate the effects of variations in spring stiffness on the natural frequencies of nanoplates. It is shown that the proposed method can easily compute the natural frequencies of nanoplates with elastic BCs.
This paper proposes a compliant amplifying mechanism for micro-positioning applications by piezoelectric actuators. This mechanism has the advantage of being supported by both input and output ports, enhancing its out-of-plane stiffness, and making it more applicable for positioning devices. However, this property makes the mechanism more complicated for kinetostatic analyses. In this paper, analytical methods are presented to model the kinetostatic and dynamic behaviors. In addition, to take the nonlinear behavior into account, the hysteresis behavior of the mechanism and piezoelectric has been identified by the Prandtl-Ishlinski model. The results are validated by the finite element method (FEM) and experiments. The analytical method can estimate the amplification ratio, output stiffness and input stiffness of the mechanism with a deviation of approximately 9.5%, 20%, and 2%, respectively. Additionally, the resonant frequency obtained from the dynamic stiffness model is 394 Hz, which closely aligns with the results obtained from FEM simulation and experiments, i.e., 371 Hz and 365 Hz, respectively. Based on the conducted analyses, it can be concluded that the dynamic stiffness modeling results indicate a satisfactory correlation between the analytical and FEM method in terms of the amplification ratio and resonance frequency. Furthermore, the hysteresis identification model is appropriately linked with the experimental hysteresis loop with an RSME of less than 2 for input signals with 1,2, and 4 second periods.
This article presents a Fuzzy Trajectory Tracking Controller for a Linear graph model of Four four-wheel skid-steer mobile robots by leveraging a state space model derived from McCormick's work focusing on navigation and obstacle avoidance. The study commences with designing The fuzzy logic controller which is meticulously detailed, focusing on its input parameters, which include metrics like distance to the target, proximity to obstacles, target relative angle, and obstacle relative angle. These inputs guide the controller in making decisions that directly influence the velocities of the Mobile Robot's left and right wheels by adjusting their voltages. Fuzzy controller outputs are voltages of the left and right wheels of the mobile robot. The research methodology encompasses three distinct scenarios, each one challenges the Mobile Robot to navigate towards a target while encountering static and dynamic obstacles with disturbance. The results of these simulations, complete with trajectory plots, angles, velocity profiles, and the distance of the robot to the obstacles and the target, clearly demonstrate the proficiency and robustness of the developed fuzzy logic controller in orchestrating a safe, adaptive, and efficient mobile robot movement.
