Mechanic of Advanced and Smart Materials

Abstract In this paper, shape memory polymers (SMPs) are reviewed, as they have demonstrated exceptional properties that make them suitable as advanced materials for current and potential applications, particularly in robotics. However, the thermomechanical properties and traditional shape memory features are somewhat limited due to their ability to recover their original shape solely through the use of a heating source. SMPs not only possess remarkable mechanical and shape memory properties but also their ease of fabrication makes them suitable candidates for numerous applications. In this research, an artificial muscle equipped with a shape memory polymer is introduced, and its mechanical properties are measured and tested in a simple gripping and releasing mechanism. The results showed that the device is capable of performing cyclic loading and provides a force-to-energy ratio of 0.25. In future, the possibility of using this apparatus in robotic application such as surgical operation and crop harvester will be studied and evaluated.

Abstract The aim of this project is to present an approach for developing a real-time hand gesture recognition which uses only a webcam and Computer Vision technology, such as image processing that can recognize several gestures for using in computer interface interaction. The most important goal of this project is to simulate playing a virtual piano using hand gesture recognition and recognizing specific gestures for each piano note. Implementing this virtual piano is done using a Personal Computer in MATLAB and also in Visual Studio C++ by OpenCV library environments and some comparisons is reported. The results show that implementing using OpenCV library is more fast and has higher performance than using MATLAB. Hand gesture distinguish accuracy is about 86.45% in MATLAB environment and about 92.7% using OpenCV library. Comparing the results based on consumed time to correctly distinguish a hand gesture is about 1.39 seconds in MATLAB environment and about 1.19 seconds using OpenCV library.

Abstract Ultra-precision machining refers to the process of manufacturing very high-precision parts that are required in industries such as aerospace, medicine, optics, and electronics, where nanometer tolerances, fine surface coatings, and precise geometries are essential. In this research, the nano-machining process of polycrystalline nickel-iron-chromium alloy has been investigated using the molecular dynamics method. Investigating the effects of cutting speed and cutting depth parameters on this process by the response surface method shows that by reducing the cutting speed from 400 to 10 m/s, the cutting depth from 5 to 0.5 nm, the values of cutting forces, normal forces and the Von Mises stress of the workpiece decreases by 65.9, 23.4 and 25.58 percent, respectively. When the cutting depth was set to 0.5 nm and the cutting speed was 10 m/s, the temperature reached 308.82 K. At this state, the machining forces—including cutting forces and Thrust force —were measured at 152.42 and 221.2 (eV/n), respectively. This configuration minimizes the machining forces, resulting in an optimized state for the machining process. The investigation of structural changes using the radial distribution function shows that increasing the cutting speed from 10 m/s to 400 m/s, while maintaining a cutting depth of 2.75 nm, results in an increase of 10 units in the radial distribution function. This change has contributed to the structural alterations of the workpiece.

Abstract In this research, the effect of manganese content on the microstructure and tensile properties of dual-phase steels was studied. At first, three low-carbon steels with fixed carbon and silicon and variable amount of manganese (0.76-2.3wt.%) were produced by melting and casting method. Then the cast steels were hot rolled in several stages to create sheets with a thickness of 2 mm. To create dual-phase ferritic-martensitic structure in steels, they were subjected to intercritical annealing process at three different temperatures of 750, 775 and 800 ℃ for 20 minutes and then quenched in cold water. According to the variables of intercritical annealing temperature and manganese content, different ratios of volume fraction of ferrite and martensite phases were created in steels. In order to study the role of manganese in dual-phase steels, these steels were subjected to microstructure and tensile properties. The relationship between tensile properties and microstructure was cleared.
Increasing Mn at a constant intercritical annealing temperature significantly increased the martensite volume fraction. Meanwhile, the effect of annealing temperature on the volume fraction of martensite was less. The uniaxial tensile test on steels showed that manganese reduces the ductility of steels due to the increase of martensite volume fraction, while it increases their strength. The effectiveness of tensile strength was more than yield strength.

Abstract In this research, the highly selective heterogeneous cation exchange membrane based on metal-organic frame works (MOFs) was prepared and introduced to electrodialysis system as hopeful material for the removal of heavy metal ions. MIL-101 (Fe) particles were fabricated via a simple chemical technique and suggested into matrix of the ion exchange membranes as additive particles. The membranes were prepared via solution casting technique by applying the desired concentrations of additive particles (0, 0.5, 1, 1.5, 2, 3 (wt%)) and then the effect of the additive particles on the morphology, electrochemical properties, and overall performance in electrodialysis system was studied. the synthesized MOF and homemade membranes were characterized using FTIR, FESEM, EDX and AFM. the images related to morphological studies showed uniform distribution of MIL-101 (Fe) particles in matrix of membranes. Utilizing MIL-101 (Fe) particles in the membrane body led to increase of surface hydrophilicity. The Water content of modified membranes was enhanced considerably compare to pristine. The membrane potential, transport number and permselectivity were increased by applying MIL-101 (Fe) loading ratio up to 1.5 wt% and then decreased. MIL-101 (Fe) membranes also, have considerable performance in removal of lead ions, so that modified sample with 2 wt% of MOF particles displayed a significant increase of 190% compare to pristine. The results are useful for electo-membrane process specially electrodialysis in order to water treatment.

Abstract The failure of the E-637 heat exchanger necessitated repairs and prompted a redesign process. Initially, the non-circular, thick-walled vessel was designed using elasticity theory and evaluated against established standards. Data for analysis and redesign were gathered from the E-637 heat exchanger at the Shazand Oil Refinery. Both analytical and numerical modeling were conducted in accordance with standard requirements and incorporated reasonable simplifications. The simulation results were compared with operational data, which confirmed the accuracy of the analysis and design process.After verifying the design's accuracy, the optimization process commenced. The final model was analyzed based on the actual configuration while considering theoretical thicknesses. Studies showed that the ASME approach tends to adopt a conservative design. Therefore, optimization was achieved through numerical simulations and adherence to standard guidelines. This process led to a reduction in the vessel wall thickness. Ultimately, by referencing the analyses in Chapter 5 of the standard, the initial thicknesses were successfully optimized.

Abstract Ultrasonic levitation, as an advanced non-contact particle manipulation technology, has gained prominence in modern research due to its independence from material physical properties and extensive applications in fields such as pharmaceuticals, microelectronics, and sonochemistry. However, optimal utilization of this technology requires a deep insight into parameters affecting particle stability and dynamics. In this study, the impact of initial particle release position—a less-explored key factor—on the dynamic behavior of particles levitated in an ultrasonic levitation system was investigated. Acoustic pressure at 20 kHz was modeled using Multiphysics simulation in COMSOL software, and the behavior of 20 polypropylene particles (diameter: 3 mm, density: 910 kg/m³) at various initial positions (ranging from 0.23 to 8.01) was analyzed. Drag forces, acoustic pressure forces, and gravitational forces were considered effective forces. Results revealed that particles released near pressure nodes exhibited the lowest oscillation amplitude and shortest stabilization time. As the initial release distance from pressure nodes increased, both oscillation amplitude and stabilization time increased. This factor’s influence on stabilization time was more pronounced near the reflector than near the transducer, indicating that particles released close to the reflector achieve a more stable levitated state compared to those released close to the transducer. Experimental validation showed significant agreement with simulation results.

Abstract Nanoparticles can enhance the thermophysical properties of base fluids, leading to increased efficiency, especially in heat transfer applications. Therefore, achieving optimized thermophysical properties of nanofluids is of particular importance. In this study, two multilayer feedforward artificial neural networks (ANN) were designed and trained to predict the relative viscosity and thermal conductivity ratio of a water-based hybrid nanofluid MWCNT-Y2O3 (with a nanoparticle weight ratio of 80:20). The nanofluid samples studied contained varying volume concentrations of MWCNT-Y2O3 nanoparticles (from 0.01 to 0.2 percent) in the base fluid. Experimental data for relative viscosity and thermal conductivity ratio at different temperatures (from 25°C to 60°C) were available. For each ANN designed to estimate either the relative viscosity or the thermal conductivity ratio outputs, regression plots corresponding to the training, validation, and testing data sets demonstrated the networks' excellent performance. The mean and maximum relative percentage errors obtained for the testing data were as follows: for relative viscosity output, 0.5120% mean error and 2.5450% maximum error; for thermal conductivity ratio output, 0.1733% mean error and 0.2874% maximum error. Moreover, based on the developed model, a multi-objective optimization problem was formulated to simultaneously determine the minimum relative viscosity and maximum thermal conductivity ratio of the nanofluid. This problem was solved using the multi-objective particle swarm optimization (MOPSO) metaheuristic method. Consequently, the optimal objective function values and input parameters were obtained, and the Pareto optimal points were graphically illustrated.

Abstract In this study, the time-dependent behavior and stress relaxation of API-X42 seamless steel pipes reinforced with glass fiber composites were investigated to assess the effects of time on system stability and load-bearing capacity. A composite layer of E-glass fibers embedded in epoxy resin was applied to the pipe joint regions. Tensile tests were conducted in single-step and multi-step modes, with a 10minute hold at each stage, and the stress–time data were recorded in normalized form. The results indicated that lower loading rates promoted gradual stress relaxation and extended system stability, whereas higher rates led to faster stress release and attainment of a stable state in the early stages. Moreover, increasing the number of loading steps resulted in cumulative stress reduction and brought the system behavior closer to a quasi-stable state. At loading rates of 50, 100, and 200 mm/min, the final stress relaxation values were recorded as 8.9%, 7.7%, and 9.4%, respectively. These findings highlight the key role of resin viscoelasticity and stress distribution between fibers and steel in the mechanical stability of the system and underscore the importance of evaluating time-dependent behavior in the design and long-term performance prediction of reinforced steel pipes. The results of this study provide clear guidance for future research aimed at comprehensively investigating the effects of multi-step loading and ultimate failure mechanisms in steel–composite hybrid systems.

Abstract The challenge of designing and implementing optimal data fusion methods that are both robust to uncertainties and simple enough for practical deployment has become a significant topic of interest in a wide range of navigation and positioning systems. In this study, inspired by the principles of Proportional-Integral-Derivative (PID) control theory and integrating them with the conventional structure of the standard Kalman filter, we propose a novel data fusion approach. This method is specifically designed to improve robustness against measurement uncertainties from the Doppler Velocity Log (DVL) sensor in an integrated marine navigation system based on INS/DVL. The proposed approach aims to enhance the system’s resilience without introducing excessive computational complexity. Simulation results demonstrate that the integrated navigation system using the proposed algorithm outperforms traditional Kalman filter-based systems in terms of accuracy and response time, particularly under conditions involving sensor errors or uncertainty. These findings highlight the potential of the method for real-world applications in marine navigation scenarios.

Abstract Recent advances in nanotechnology have highlighted the need for precise and stable methods for manipulating both biological and non-biological particles. Among the available tools, atomic force microscopy (AFM) is considered a key instrument due to its high capability for controlled contact and measurement of extremely small displacements. However, maintaining stable contact between the probe tip and the particle and preventing undesired slippage, especially when dealing with complex geometries, remains a significant challenge. In this study, a dynamic modeling framework combined with sliding mode control (SMC) was proposed to enhance AFM performance during particle manipulation. Simulation results demonstrated that the designed controller could maintain the probe’s position and angle with high accuracy. Examination of three particle geometries—spherical, cylindrical, and chamfered cylindrical—revealed that slippage increased with surface complexity, with spherical particles exhibiting the least sliding (3.4%) and chamfered cylindrical particles the most (4.8%). Furthermore, a comparison of three cantilever types showed that the V-shaped cantilever achieved the best performance, with only 2.1% sliding and a significant reduction in angular fluctuations.These findings indicate that combining accurate dynamic modeling with sliding mode control provides an effective approach for developing advanced AFM systems and expanding their applications in biological studies and tissue engineering.

Abstract The perturbation friction process is a solid state method used to modify the surface, improve mechanical properties, and produce composites. In this research, the effect of effective parameters on the surface compositing of AZ31B / CNT alloy with carbon nanotubes has been investigated by the frictional perturbation process method and Sobel sensitivity analysis. Input parameters in this study were advance speed, rotation speed, weight percentage of carbon nanotubes and number of welding passes, as well as considered outputs including hardness and weight loss. In order to analyze the results, Sobel sensitivity analysis has been used to investigate the qualitative and quantitative impact of inputs on outputs. The results of this study showed that the weight percentage of carbon nanotubes, rotation speed, number of welding passes and advancement speed affect hardness, respectively. The weight percentage of carbon nanotubes, the rotation speed, the number of welding passes and the advancing speed also affect the weight loss.

Abstract In this paper, the optimization of effective parameters on the process of severe plastic extrusion deformation in the torsional angular channels of the plate is investigated. Initially, the process test was designed using the response procedure method, and four main and influential input variables on the process, torsion angle, radius, channel angle, and coefficient of friction, were extracted, and the regression equations of each for the mechanical properties of the samples produced by this method. Using sensitivity analysis, which is very useful in the production of parts and industry today, and by using it, the quality of manufactured parts can be greatly improved and production costs can be reduced to a large extent, the effect of input variables on plastic strain Parts checked. In this paper, the mean and maximum strain and maximum force, which are defined under the influence of these input variables, have been investigated and analyzed using the e-Fast statistical sensitivity analysis method. The results of the analysis show that the mean strain is affected only by the values of torsional and channel angles, but the maximum strain is affected by the coefficient of friction and has a direct linear relationship with its changes. The maximum force is also in a balanced state from the effect of the variables. Also, the quantitative effect of torsion angle of 52% and channel angle of 48% on mean strain and coefficient of friction with 86% and torsion angle with 42% had the greatest effect on the strain and maximum force.

Abstract Nanoparticle manipulation is a process in which particles are moved on a micro/ nanoscale scale using an atomic force microscope and has a wide range of applications from component production to the medical world. In this study, using the theories of contact mechanics of Hertz, JKR, DMT and BSP, as well as using the structure of the DNA biological cell using the Elman method using ABAQUS software to study the amount of displacement, acceleration, force, stress and velocity in time The DNA molecule is discussed on a base sheet and the factors that affect them. The results show that in the deformation between the target particles and the spherical tip of the needle, the Hertz model showed the least and the JKR model showed the highest deformation and penetration depth. By increasing the angle of the needle tip with the z-axis, the amount of penetration depth and deformation created between the particle and the base plate is reduced. Also, the graph of changes in each of the studied parameters of the effective factors per 20 μm of displacement and 20 milliseconds of time for the DNA manipulation process has been calculated.

Abstract Metamaterials are materials that exhibit unusual properties. Auxetic materials, as a class of metamaterials, are structures with a negative Poisson ratio. These materials become thicker when applied under tensile stress, unlike conventional materials, in the perpendicular direction to the applied force, and become thinner when applied under compressive stress. Auxetic behavior is an independent property that can be obtained from microscopic or macroscopic levels and even molecular or cellular levels. Many structures and materials are known of this feature. This unique feature has created potential applications in the military, aerospace, medical and intelligent sensors, and many other industries. However, there are still many problems with the widespread use of these structures. This paper provides a comprehensive review of these structures that have unique properties and applications of auxetic materials. In addition, some of the latest developments in these materials are described. Materials with a negative Poisson ratio have great potential in various applications such as lightweight structures or biomaterial applications.

Abstract In recent years, gecko-like dry adhesives have been used in robotic grippers and climbing robots. The adhesive has been introduced as a new approach for manipulating flat objects in production lines. The method has several advantages over other, more traditional, gripping methods such as lower power consumption compared to suction-based systems or the ability to handle non-magnetic materials. Directional Gecko-like adhesives are based on the frictional adhesion and employ asymmetric feature, mostly wedge shape, and perform only in one direction. In this paper, design and fabrication process of a new pyramid shape Gecko-like adhesive using silgard 184 has been described. The new microstructures has the ability of adhesion in several directions, and the contact surface between the adhesive and substrate increases and the possibility of self-sticking between adjacent stalks decreases. Chemical machining and microlithography were used for manufacturing molds in this research and the details were described. The performance of proposed adhesive was evaluated using an experimental set-up and adhesion force was measured on different substrate. During experiments, adhesion was controlled via applied shear force to adhesive. The experimental results showed 30% increase in adhesion using proposed adhesive in comparison with the existing similar adhesive.

Abstract Composite shells are widely used in various industries due to their low weight and high strength. Designing these structures involves various engineering analyses, and one of the most important studies is the investigation of the buckling of shells under axial load. The aim of this research is to investigate the vibrational correlation method on composite cylinders with delamination defects. Delamination defects can occur in structures under different conditions and have a significant impact on the strength of the cylinder. Therefore, in this study, different dimensions and quantities of delamination defects in various specimens were examined using the vibrational correlation method. Carbon fibers of type T300 were used as the reinforcement material, and the epoxy resin LY556 was used as the matrix. The hardener and accelerator combined with the resin in this research are HY917 and DY70, respectively. The layer stacking in the specimens was done with angles [55 90 90 55] using the filament winding method, and artificial delamination defects were created between layers 2 and 3 using Teflon sheets. The manufactured specimens were subjected to modal testing under various compressive forces, and then the critical buckling load of the specimens was obtained using the modal testing method. Using numerical modeling software, critical buckling loads and natural frequencies were calculated for various axial compressive loads through linear and nonlinear analysis. These numerical results were compared with experimental results. The vibrational correlation method accurately predicted the critical buckling load in defect-free specimens with a 3% error, but its accuracy was significantly

Abstract The wheeled mobile robots have many applications due to their advantages such as wide workspace, mobility and maneuverability. Intelligence of mobile robots to perform autonomous movements is also one of the favorite fields of robotics researches. In this paper, the trajectory tracking of an intelligent mobile robot on a sloping surface is studied using a nonlinear sliding mode control. First, the nonlinear dynamic equations of a wheeled mobile robot are derived on a sloping surface using the Newton-Euler method. A multistage nonlinear control block is then proposed for trajectory tracking. First, the controller calculates the linear and angular velocity of the robot to find the position of the robot, and then, assuming uncertainties in the dynamic model, a sliding model controller is used to track the robot's specific path. Various simulations are presented to validate the control method, which the results show the capability and efficiency of the proposed method.