Meccanica最新文献

This contribution presents a homogenization approach for the computationally efficient modeling of two-dimensional solid bodies that interact through structured surfaces. Instead of resolving the detailed microscale geometry, the method introduces a finite-thickness surrogate layer that captures the essential mechanical response of the structured contact zone. The proposed formulation is based on the description of microscale quantities, such as (normal) gap and relative sliding velocity, which are transferred to the macroscale using internal volumetric variables. The elastic behavior of the surrogate layer is identified through a mean-field homogenization approach that accounts for the non-linear dependency of stress response on the relative slip. As a result, the anisotropic and history-dependent behavior of the interface can be captured within the model. The proposed method is validated using two benchmark problems: a vertical stack of two structured blocks and a knurled interference fit. In both cases, the finite-thickness layer accurately reproduces the mechanical response of the fully resolved model, i.e., stick–slip transitions, hysteresis, and partial interface separation. The good agreement with the reference solutions, combined with a significant reduction in computational cost, demonstrates the potential of the method for efficient multi-scale interface modeling.

A significant challenge in the operation of coaxial magnetic gears is slippage during acceleration, which can introduce vibration due to oscillatory dynamics. These vibrations can threaten the structural integrity of CMGs, highlighting the need to minimize oscillations for effective performance. However, despite its importance, the reduction of transient oscillations has not been investigated in the literature. In this work, a new control method combining PID control and the Lyapunov control function is proposed to provide an efficient and robust response in CMGs during acceleration and deceleration. The governing equations were non-dimensionalized, allowing the control method to adapt to various CMG configurations, loads, and acceleration profiles. Realistic conditions are simulated by incorporating discrete control, external load fluctuations, and measurement errors. Extensive simulations confirm that the proposed control method enables CMGs to quickly reach desired states while reducing oscillations effectively. Furthermore, the impact of sampling time on control response is evaluated to establish conditions that ensure robust CMG operation. As a result, this research introduces a non-dimensional control strategy that could significantly enhance CMG design by mitigating operational drawbacks associated with oscillatory behaviour, improving reliability and stability in practical applications.

Acquiring mechanical information about the state and the mechanical conditions of wheels, rollers or tyres in real-time working conditions is still a significant challenge in transportation and industrial applications. Non-real-time tests represent the most prevalent method for gathering data about rolling element conditions such as applied load, internal strain and stresses. This study proposes a novel solution to sensorize solid wheels, introducing the use of an innovative piezoelectric elastomer already developed and tested by the authors. Its main characteristics, such as softness and intrinsic sensing capability, make it a good candidate for this type of application. We adapted the fabrication process of the elastomer to the realization of a solid wheel coating, through an ambient temperature over moulding process. A custom dedicated testbench was designed and fabricated to test the prototype wheel under rolling at constant vertical load conditions, in a matrix of different test configurations. Results show that output signals are strongly dependent on load, but also on the velocity due to the system design. A juxtaposed FE analysis integrates test results relating the output voltage signals obtained to the mechanical stress condition of the studied wheel.

Metamaterials, artificial lattices with uncommon dynamical properties, have received growing attention due to their wave manipulation capacities. In particular, engineering their dispersion curves allows for obtaining targeted, band-specific responses, with applications in a broad range of subjects. Roton-like dispersion relations, which feature local minima and maxima that invert the direction of energy propagation, have broadened the reach of these devices, with one way to achieve them being the inclusion of beyond-next-nearest neighbours. The mass-spring models usually employed to simulate metamaterial behaviour traditionally assume massless springs. However, in nonlocal cases, this hypothesis may not be always reasonable, and to ensure physical soundness, a mass conservation law for spring mass becomes crucial to prevent their total mass from significantly affecting system dynamics. With the aim of gaining insights into two-dimensional nonlocal systems, this work extends the previous model by the present authors from one-dimensional monoatomic chains to two-dimensional lattices. Building on the mass conservation principle proposed in the above-mentioned work, a mechanical consistency condition is applied to two-dimensional discrete periodic lattices. Two dimensionless parameters are introduced into the analysis: (alpha), to adjust stiffness distribution, and the nonlocality level P, established through homothety. Analytical dispersion relations as functions of (alpha) and P are derived for the five Bravais lattices, and the effects of these parameters on dynamical behaviour are discussed. The potential for applications in waveguiding and lensing of two-dimensional metamaterials is undoubted, and through tuneable nonlocal models, new possibilities for advanced devices may be unlocked.

This article explores certain limitations of some well-known methods employed in machine learning when applied for regression of mechanical models that might exhibit multiple solutions. Using the buckling of a beam as a prototypical example of a mechanical problem with multiple solutions, we show that neural networks, Bayesian methods, random forest, and similar forward techniques are ill-suited for approximating the solution to such problems. Instead, data-driven methods based on set projections are intrinsically capable of coping with multiple solution paths satisfactorily, incorporating in addition the stochasticity of the response.

The ability to design linear systems exhibiting non-reciprocal wave propagation would enable precise control of mechanical signals for filtering and vibration control. This study presents a macroscopic mechanical metamaterial with a time-varying radius based on crank-slider mechanisms. A hierarchical framework is established, formed by supercells, with each supercell comprising multiple subcells. Among configurations with varying numbers of subcells, the investigation focuses on a phase-modulated triatomic configuration designed to break time inversion symmetry to achieve non-reciprocity, which generates asymmetric bandgaps to selectively suppress wave propagation in positive wavenumber domains while permitting propagation in negative domains. The spatiotemporal field patterns with different modulation parameters are provided. Numerical simulations are also conducted to verify non-reciprocal wave propagation behavior. Furthermore, the influences of modulation amplitude, frequency, and initial phase on the bandgap structure are systematically examined, revealing their potential for precise asymmetric bandgap tuning wave propagation characteristics.

In this paper, a novel linear-driven parallel manipulator (PM) which has four identical PRPaR limbs and a simple moving platform is designed for high-speed pick-and-place motion. After proving that the robot can achieve Schönflies motion through Lie group theory, the kinematic model of it was established using the closed-loop vector method. By combining finite element analysis and the substructure method, the elastodynamic model was established, and the shape functions as well as the mass and stiffness matrices of the spatial beam element were derived. Then, the correctness and accuracy of the established elastodynamic model were verified using Ansys Workbench^®. Subsequently, the dynamic response analysis carried out using the Newmark method indicates that when the moving platform moves along a circular trajectory with a radius of 0.3m, its displacement error is sufficiently small. By analyzing the position error curves under different damping conditions, the optimal damping ratio of the mechanism was determined. To achieve the desired pick-and-place trajectory, the improved trapezoidal motion law was applied to ensure that the elastic displacement and angular displacement errors of the moving platform meet the practical requirements. Furthermore, dynamic stress analysis based on the fourth strength theory identifies the weakest components of the mechanism, providing a foundation for the optimization of the physical prototype. This paper offers new perspectives on the study of refined elastodynamic and dynamic response in parallel robots.

This work presents a finite-element (FE) framework for predicting the mechanical response of polymeric powders subjected to confined compaction. A contact-based FE formulation captures the deformation of individual microspheres, their evolving contact network, and the accompanying reduction in bulk porosity inside the mold. Two nonlinear constitutive descriptions, namely, an elastoplastic model with multilinear hardening and a Perzyna-type viscoplastic model, are implemented to assess both rate-independent and rate-dependent particle behavior. Representative-volume simulations of an epoxy-resin powder are carried out under multiple loading-unloading cycles to quantify how the mold-constrained effective Young’s modulus and porosity evolve with the compaction history. Because this effective modulus reflects both the intrinsic particle stiffness and the increasing confinement and densification of the packing, it can exceed the single-particle modulus as the contact network develops. The results show that the cumulative loading history, number of cycles, peak pressure, and loading rate, strongly influences densification and the apparent macroscopic stiffness of the compact. By providing a predictive tool for effective property estimation without costly trial manufacturing, the proposed approach can guide optimization of compression-molding parameters for polymer-based composites and other powder-processed components.

The onset of cavitation in hydraulic devices is caused by rapid pressure variations leading to the formation and collapse of vapor bubbles which can occasionally provoke severe damage. Shape optimizations for cavitation reduction, based on single-phase flow models, prevent static pressure from dropping below the vaporization pressure, but they do not account for the influence of vapor in the flow. In this article, a continuous adjoint-based optimization method for two-phase turbulent cavitating flows, using the Volume of Fluid method, is developed within an in-house GPU-enabled CFD solver. The adjoint accommodates new terms arising from the differentiation of the source terms modeling cavitation, the liquid–vapor mixture properties, as well as the turbulence model. The sensitivity derivatives are expressed in terms of surface integrals, using an adjoint formulation which, prior to this work, has been applied only to single-phase flows. The comparison of the sensitivity derivatives computed by the continuous adjoint method and finite differences shows that the differentiation of the turbulence model equations, frequently omitted in two-phase flows, is necessary to predict accurate gradients. After the validation of both the primal and adjoint solvers, gradient-based constrained shape optimizations are performed in three cavitation-dominated flows around a 2D isolated hydrofoil and a 3D hemispherical head body, as well as inside a 2D hydraulic poppet valve.

A novel method, energy method, for solving bearing stiffness in rotor system supported by multiple bearings is proposed. Energy method has no restrictions on bearing type, bearing arrangement, bearing number and load type in rotor bearing system and can significantly simplify the solution procedures involved in determining bearing displacements and bearing stiffness. The potential energy model of flexible rotor bearing system is derived by combining finite element method and bearing load–displacement relationship and can be expressed as the function of rotor shaft nodes’ displacements. Based on the principle of minimum potential energy, the true displacements of all nodes in the system are calculated by optimization algorithm, and then the stiffness for each bearing is obtained. The effectiveness of the proposed energy method is verified by comparing with the results of bearing displacements, loads and stiffness coefficients in published literatures. Based on the proposed energy method, the effects of the rotor shaft flexibility, bearing arrangement, load position, bearing radial clearance and initial angular misalignment of outer ring caused by installation error on bearing stiffness in the rotor bearing system are investigated.