In this paper, we put forward a classifier to automatically identify the most suitablemechanical behaviour law among two candidates, enabling optimal modelling ofexperimental data from a uniaxial tensile test, represented as elongation–specific stresscurves. An ArtificialNeuralNetwork (ANN) is employed to performthis classificationtask and assist the modeler, even when the resulting curves from different models arevery close. This paper compares two different methods that enable supervised learningof the neural network from a training dataset labelled with specific stress values as afunction of elongation, without requiring any external data. The learning process isthen validated by testing the network’s ability to correctly identify the most suitablemodel from experimental data it has never encountered before. This approach couldpotentially pave the way for adaptations to more complex tasks in a multidimensionalcontext or to feature recognition in imaging, in the frame of various fields of materialsmechanics.
The use of cutting fluids (CF) is regarded as one of the most efficient supplementarymethods to lower production expenses and improve the quality of machined surfaces.In this study, the influence of CF’s flow rate on machining performance of AISI1045 was comparatively investigated in turning operations. The experimental designincluded different cutting velocities, feed rates, cutting depths and three flowing rates(2.5, 4, 6 l/min) of CF. 5% concentration of potassium dichromate (K2Cr2O7) in waterwas used as a CF. The evaluation of machining performance was studied based onthermos-electromotive force (Thermo-EMF), chip shrinkage and formation, and toolwear characterization. The results indicated that high rates of fluid flow into cuttingzone yielded better results in terms of reducing the thermo-EMF, minimizing toolwear and BUE, and improving chip morphology. It was then found that increasing thefluid flow rate during cutting leads to early fracture of the chip and the segmented chipformation. In addition, with an increase in the CF flow rate from 2.5 l/min to 6 l/min,the thermo-EMF generated during turning of AISI 1045 with titanium alloyed carbidetools decreased to 13%, and flange wear to 160%.
The flutter of a shape memory alloy (SMA) fiber-reinforced panel in hypersonicflow is investigated. A nonlinear aerothermoelastic governing equation is formulatedby coupling Von Kármán’s large deflection plate theory with first-order piston theoryaerodynamics. Discretization via the Galerkin method enables the derivation ofanalytical solutions for the critical dynamic pressure and flutter frequency, using theRouth-Hurwitz criterion and Hopf bifurcation theory. Numerical integration confirmsthe predicted stability loss via a supercritical Hopf bifurcation, leading to limit cycleoscillations. The results demonstrate thatSMAfibers raise the flutter boundary throughrecovery stress and a high elastic modulus, which increase the equivalent structuralstiffness –an effect that intensifies with SMA volume fraction. Conversely, aerodynamicheating induces thermal softening, creating a destabilizing thermomechanicalfeedback loop that reduces the stability margin. A nonlinear saturation effect is observed:beyond a critical fiber content, the marginal stability benefit diminishes. Thissuggests that strategically placing localized, high-concentration SMA fibers providesa mass-efficient strategy for significant stability enhancement.
Solar energy is a source of renewable energy and is considered a clean, convenient,sustainable, safe, abundant, and economical source. Solar Air Heaters (SAHs) are oneof the applications of solar energy. SAH has a wide variety of applications but has lowthermal efficiency. This low thermal efficiency is due to the low thermal capacity ofthe air, and the poor process of heat transfer between the absorbing plate channel andair.With the aim to improve thermal efficiencies, the novel dimple/protrusion surfaceshave been incorporated onto the 307 × 212 mm aluminum absorbing plate. A 3 × 3array of 5 mm impinging jets is used to further decrease the temperature of the plate.A set of five different plate configurations, i.e., smooth, dimpled, dimpled-protruded,protruded-dimpled, and protruded configurations are simulated by using the experimentallyvalidated Computational Fluid Dynamics (CFD) model. The values of heattransfer enhancement, pressure drop, and Thermal Performance Factor were evaluatedfrom the CFD study. The protruded plate is selected as the best plate configuration,based on the Thermal Performance Factor. An overall improvement of 33.5% is observedin the current research work, as compared to the smooth configuration. Hencepromising is the augmentation.
Flexible manufacturing systems (FMS) are widely used in modern mechanicalengineering and instrumentation due to their adaptability and high productivity. However,their effective operation is strongly dependent on accurate management of cuttingtool (CT) resources, which are subject to wear during machining processes. This studyaims to develop and justify a methodology for evaluating CT resource consumptionwith higher precision to support decision-making in FMS operations. Machining operationsare classified into positional and contour types based on their tool engagementcharacteristics. For each type, appropriate quantitative wear criteria are proposed: thenumber of discrete tool actions for positional machining and the processed volume orpath length for contour machining. A Monte Carlo-based numerical procedure is developedto estimate the actual volume of material removed during contour operations,accounting for overlapping tool trajectories and idle movements. The results confirmthat the proposed approach significantly improves the accuracy of tool workloadestimation compared to traditional time-based methods. The methodology enables more reliable forecasting of CT wear, supports predictive maintenance strategies, andimproves overall system efficiency. The proposed algorithm can be integrated intodigital manufacturing workflows, contributing to the implementation of intelligenttool management in line with Industry 4.0 objectives.
The vibration behavior of an adatom-microresonator featuring a perforated microcoreis examined in this paper. The nonlocal strain gradient theory (NSGT) isincorporated to characterize the microscale response. The system is subjected toa nonlinear thermal field and the adsorption of adatoms. The thermal response ismodeled by solving a nonlinear steady-state heat conduction equation. Atom-surfaceinteractions are characterized using the Buckingham-Coulomb interatomic potential.Furthermore, the model introduces the coupled dynamic behavior between the twofunctionally graded porous sandwich (FGPS) microbeams through a defined couplingstiffness term included in the governing equations. To evaluate the impact of rotaryinertia, both the Rayleigh beam model (RBM) and the Euler-Bernoulli beam model(EBM) are employed, enabling a comparative analysis. The nonlocal frequencies arecalculated using the Navier-type solution method (NTM) and the differential quadraturemethod (DQM). These frequency results are subsequently visualized through3D numerical plots. A detailed analysis is performed to investigate the impact ofphysical parameters such as thermal gradients, porosity distribution, hole number,and adatom density on the nonlocal frequency shift of the system. The findings ofthis research are significant for advancing the fields of thermal monitoring and gasdetection technologies.
Forestry forwarders transport cut logs from the felling site to a landing area or a secondary transport vehicle, a task that is physically and mentally demanding for the operator. Even partial automation of the loading cycle can reduce workload and improve safety. This study extends prior reinforcement-learning (RL) work on grasping to the full pick–lift–transport–deliver sequence. We train an agent with Proximal Policy Optimization (PPO) and a two-stage curriculum in a GPU-accelerated simulator (NVIDIA Isaac Gym), using a trailer-type forwarder model with a hydraulic crane and grapple. The task is simplified to a single log and a fixed target location inside the bunk: the agent must reach a randomly placed log, grasp it, lift it above the bed guards, and deliver it with reduced vertical impact velocity. The reward is decomposed into three components, reaching (r1) lifting/unloading (r2), and stable target delivery (r3), and we compare curriculum compositions. In an evaluation over 1,024 parallel episodes, the best two-stage configuration (r1 + r2, then + r3) reaches a 94% success rate, outperforming flat and fully staged alternatives. Generalization tests on unseen log sizes, elevated ground, and rough terrain show partial transfer with clear degradation under larger shifts. The study is limited to a highly simplified simulation setting (flat ground, fixed forwarder base, single log), and no sim-to-real transfer was attempted.
Kinematic behavior of a 3-PRS parallel manipulator is investigated with particularemphasis on the characterization and analysis of the so-called parasitic motions.These unintended displacements, arising from the mechanism’s inherent geometricand structural constraints, play a critical role in determining the overall accuracy andperformance of parallel manipulators. The displacement analysis is performed usingtwo distinct strategies based on simple closure equations, enabling the derivation ofexpressions for the parasitic displacements of the moving platform. Subsequently,the input-output velocity relationship is obtained by applying the theory of screws.This expression is independent of passive joint rates and can be directly appliedto both inverse and forward velocity analyses. Numerical examples, validated usingspecialized software such as ADAMS,tmare presented to demonstrate that the socalledparasitic motions are both predictable and computable, rather than the result ofunexpected or random behavior in the zero-torsion mechanism.
This study investigates the flow and heat transfer characteristics of copper (Cu) and silver (Ag) nanofluids over a permeable, moving flat plate embedded in a porous medium under the influence of a uniform magnetic field. Key effects such as thermal radiation, viscous dissipation, nanoparticle volume fraction, and suction/injection are incorporated into the model. The governing partial differential equations are reduced to ordinary differential equations using similarity transformations and solved numerically via the Runge-Kutta fourth-order method with a shooting technique. Results reveal that Ag-water nanofluid exhibits a higher temperature profile, whereas Cu-water shows greater skin friction and heat transfer rates. Velocity decreases with increasing magnetic field strength, porosity, volume fraction, and suction/injection parameters. Thermal boundary layer thickness increases with magnetic and porosity parameters but decreases with stronger suction. The Nusselt number increases with nanoparticle concentration, and temperature rises with higher viscous dissipation but decreases with thermal radiation.
This study presents a nonlinear dynamic model of a flexible overhead crane operating in a vertical plane. The model simultaneously considers the flexural deformation of the main girder, the axial elongation of the hoisting cable, and the effects of internal damping. The equations of motion are formulated as a system of nonlinear ordinary differential equations (ODEs), allowing efficient simulation of the system's dynamic response, vibration behavior and stability characteristics. Numerical analyses are conducted for both undamped and damped cases. The results show that the elastic deformation of the cable is the primary source of beam vibration, while the payload sway also contributes to the overall oscillation. Including cable elasticity slightly increases the maximum beam deflection but significantly amplifies elastic oscillations. When damping is introduced, both cable and beam oscillations are reduced, and can be reduced to static deformation with increasing damping. The study provides a compact yet accurate modeling framework and offers useful insights for the integrated control of elastic and sway vibrations in flexible overhead cranes.
This study evaluates the thermal performance of phase change material (PCM) in a triplex tube heat exchanger (TTHE) integrated with flat-plate solar collectors. To enhance the PCM melting rate, the heat exchanger system incorporates newly designed fin geometries and nanoparticle additives. A numerical parametric analysis was conducted to evaluate the effects of fin dimensions (length and thickness) in conjunction with average temperature, liquid fraction, and various nanofluids (Al2O3, CuO, and TiO2). Model validation was performed by comparing the predicted temperature distribution with previously published numerical and experimental data, thereby confirming the model's reliability. The results indicate that adding Al2O3 nanoparticles improves the melting rate by 31.6%, while the optimized fin geometry enhances heat distribution and reduces the melting time by 32.5% compared to conventional configurations. These findings contribute to the development of more efficient latent heat thermal energy storage systems (LTES). Additionally, preliminary integration of a circulation system and learning mechanism is proposed as a promising approach for future performance enhancement.
This study investigates the unsteady rotational motion of a solid spherical particle with slip at its surface, immersed in an incompressible viscous fluid saturating a porous medium, under the influence of an external magnetic field. The flow dynamics are governed by the unsteady Brinkman equation coupled with the Lorentz force. To obtain analytical expressions, the Laplace transform technique is employed, and a slip boundary condition is applied at the surface of the sphere. The torque acting on the sphere is derived in the Laplace domain. The combined influence of the permeability, magnetic field, and slip condition on the torque is examined for three distinct cases: damping oscillatory motion, accelerating velocity, and impulsive motion. Graphical representations are provided to illustrate the variation of torque with time for different values of the Hartmann number, slip parameter, and permeability parameter. The results demonstrate that the Hartmann number and slip parameter enhance the torque in all cases, while the torque decreases with increasing value of the permeability parameter. In the limiting cases, the present results reduce to earlier findings in the absence of magnetic effect and permeability.
Tool-path smoothing is essential for ensuring continuous motion at transition corners between linear segments, since kinematic discontinuities degrade both machining efficiency and surface quality. Most existing spline-based methods achieve only G(2) or C-2 continuity and therefore produce discontinuous jerk, which can excite high-order structural resonances. Achieving true C-3 continuity remains challenging, particularly because synchronizing tool-tip position and orientation is complicated by the nonlinear relationship between arc length and spline parameterization. This study presents an analytical Catmull-Rom (CR) spline-based method for C-3-continuous tool-path smoothing in five-axis CNC milling. Transition corners are replaced by adjustable Catmull-Rom (ACR) splines, whose control points and tuning parameters are designed or optimized to constrain the deviation from the original path. The remaining linear segments are also substituted with ACR splines to enforce position-orientation synchronization, with control points that can be chosen analytically to guarantee zero synchronization error. The proposed method is fully analytical and non-iterative. Numerical simulations demonstrate that the generated tool paths satisfy prescribed geometric tolerances, produce smooth and continuous jerk profiles, and achieve exact synchronization between tool-tip position and orientation.
This paper presents the design of an optimal robust algorithm for performance control of an automotive electric power steering system. The proposed controller is formulated based on a Sliding Mode Control (SMC) framework. A Genetic Algorithm (GA) with six stages determines the sliding surface parameters of the control mechanism. The Lyapunov criterion evaluates the stability of the system. The novelty of this study lies in integrating the robustness of SMC with the optimization capability of the GA to automatically tune the sliding surface parameters. Unlike conventional SMC designs that rely on manual parameter adjustment, the proposed framework achieves fast convergence and reduced tracking error without complex gain tuning. Furthermore, it simplifies the controller structure and improves energy efficiency while mitigating the chattering phenomenon that typically affects SMC-based systems. The performance of the proposed controller is validated by numerical simulation. The computational results show that tracking errors are significantly reduced (only about 0.101% for v1 = 30 km/h and 0.132% for v2 = 60 km/h) compared to conventional PID control. Furthermore, power consumption is also significantly reduced. In addition, the influence of the chattering phenomenon is largely eliminated. This combination can be applied to the control of automotive mechatronic systems.
The purpose of this research was to develop and investigate a method for real-time lifestyle assessment, with the long-term goal of associating detected behaviours with-menstrual cycle phases, eating habits and hydration. This was achieved by designing a system for detecting health-related activities-eating, drinking and smoking-using a custom ear-worn device equipped with an accelerometer. To account for confounding behaviours, speaking and a generic "other activities" category were also included. Fifteen prototype devices were built and tested in the laboratory, and nine were worn by healthy volunteers for data collection. Raw accelerometer signals were segmented into overlapping windows and processed using topological data analysis (TDA) to extract shape-aware features. Time-delay embeddings were applied to transform signals into point clouds, from which persistence diagrams were computed using Vietoris-Rips and lower-star filtrations. Statistical descriptors derived from these representations included entropy measures, lifetime distributions, and topological complexity metrics. On a dataset of 47 658 labelled windows collected from participants, a random forest classifier achieved 89% balanced accuracy on a held-out test split. Results demonstrate that TDA enables effective discrimination of mandibular and head movements captured by an ear-worn sensor. The source code and feature definitions are publicly available to support reproducibility.
Welded steel body components are commonly employed in special-purpose machine tools due to their high stiffness. However, this design approach typically results in low damping capacity. To enhance the dynamic performance of such structures, the use of polymer concrete as a filler material in closed profiles has been proposed. This paper presents the results of an experimental investigation on steel beams filled with polymer concrete. Three different polymer concrete mixtures were selected for testing. The study includes fatigue testing to evaluate whether long-term variable loading, representative of operational conditions, induces structural changes in the polymer concrete. The study analyzed the natural frequencies corresponding to the first three resonance modes, as well as the damping coefficients. Based on the measurement results, it was found that throughout the entire fatigue testing range, the variation in the sample's natural frequency ranged from 1.5 to 29.5 Hz. In contrast, the damping coefficient varied between 0.023 and 0.161 for the tested sample. Dynamic parameters were analyzed, and the most effective indicator for assessing structural alterations is proposed by the author.
Guided missiles are a key weapon in modern warfare, where designers aim to enhance their accuracy and lethality. In the conceptual design phase, the problem of missile trajectory tailoring to hit a specified target emerges. Nonetheless, focusing solely on this design goal may cause degradation in other design aspects such as structural integrity and flight control demands. Therefore, it is highly recommended to integrate flight, control, and structural aspects in the early phases of design. This study focuses on the conceptual phase of a guided surface-to-surface tactical missile trajectory toward a set of predefined targets with constraints. A comprehensive analysis is implemented to solve the trajectory optimization problem of a generic tactical missile. Based on a point-mass three-degree-of-freedom flight model, the optimal-control solver GPOPS is employed to solve this trajectory optimization problem. To ensure realistic and visible trajectory problem solutions, several physical constraints are considered, including minimum and maximum allowable dynamic pressure and maximum allowable rate for flight path angle. The control budget needed for each trajectory problem is discussed. Optimal trajectories ensuring maximum impact velocity via free and constrained flights are evaluated. Furthermore, trajectory problems that balance between minimum control budget and maximum lethality are analyzed.
The Inverted Pendulum Cart (IPC) system is a significant challenge in control theory, is used as a benchmark for evaluating advanced actuator control techniques, and has critical applications in robotics and autonomous systems. This paper proposes a new control strategy based on a Hierarchical Non-Singular Fast Terminal Sliding Mode (HNFTSM) controller technique enhanced by an Extreme Learning Machine (ELM) neural network to achieve system stability. HNFTSM provides finite time convergence and resistance to disturbances and uncertainty, while the ELM contributes to estimating these disturbances to improve performance. The stability of this strategy is proven using the Lyapunov stability theory, which ensures that all system states reach the desired equilibrium in finite time. Furthermore, the proposed hierarchical control scheme guarantees finite-time convergence of all closed loop IPC states under bounded uncertainties. A comprehensive comparative analysis is conducted against other advanced control techniques, including HSMC, HNTSM, ELM-HNTSM, and conventional NFTSM controllers. Simulation results show that the proposed approach outperforms other methods in tracking accuracy, convergence speed, singularity avoidance, and chattering reduction, which enhances the effectiveness of system control and makes it promising for practical applications.
The automatic conveying line is the key equipment of material flow system in logistics distribution centers. However, conventional automatic conveying line would take up a relatively large place, yet it could only perform simple tasks such as moving packages along a straight line. It is also difficult and costly to add/change an existing conveying line, which makes the distribution center rigid, inflexible, and unfriendly to maintain. To improve the automatic conveying line, this paper proposed a roller array-based package transport and sorting platform, which can be used for logistics distribution centers for advanced automatic conveying purposes. The roller unit is the key component of the platform. It consists of a swiveling roller and a swiveling motor which give the packages the required direction and velocity. Package detection technique is also integrated in the platform to detect the geometry center of the moving package for transport feedback control. The proposed control algorithm enables the platform to perform package translation, rotation, turning and a normal transport. The experiment results show that the transport velocity error is about 6% and the rotation angular velocity error is 5%. The package could move along the designed 'S' shape trajectory. The proposed roller array-based package transport and sorting platform could control the package movement as required.
This paper presents a numerical investigation of unsteady, two-dimensional magnetohydrodynamic (MHD) mixed convection flow and heat transfer over a permeable stretching cylinder embedded in a porous medium. The governing conservation equations of mass, momentum, and energy are formulated by incorporating the effects of viscous dissipation, temperature-dependent thermal conductivity, Joule heating, thermal radiation, and a uniform transverse magnetic field (with negligible induced effects). Additionally, slip velocity and variable surface heat flux are also considered to enhance the model's applicability to engineering systems. Through appropriate similarity transformations, the governing partial differential equations are reduced to a set of nonlinear ordinary differential equations, which are solved using MATLAB's bvp4c scheme. The influence of key dimensionless parameters on velocity and temperature distributions, skin friction coefficient, and Nusselt number is thoroughly examined. Comparative analysis between the stretching cylinder and the flat sheet configurations reveals that the cylinder's curvature significantly thickens the momentum and thermal boundary layers, while enhancing the surface shear stress and heat transfer rate. These findings offer useful implications for the design of thermal systems involving curved geometries, such as cylindrical heat exchangers and pipes.
