Meccanica最新文献

This research deals with a numerical study of a drop impacting a moving film as a transient three-dimensional and its comparison with static film. For the modeling, the CLSVOF (Coupled Level Set and Volume of Fluid) method has been used for drop impact analysis. The parametric effects of film Reynolds number (830 < Re_f < 4478), non-dimensional film thickness (0.25 < h^* < 0.75), drop Weber number (249 < We < 1762), non-dimensional time (0.5 < τ < 4.0), and impact angle (0°, 30°, and 60°), on the interface evolution, was investigated. Further, the results have been compared to drop-impacting static film obtained by previous researchers, whereby in most cases consists of the results with drop-impacting static film have been observed. However, the drop impacting the moving film indicated a different behavior in some cases because of the unique effect of the moving film movement. Doubling the film velocity as well as a 57% reduction in the drop velocity, caused an 8.3% and 6.66% increase in the crown asymmetry and suppression of the downstream crown. The crown slip toward the downstream flow was observed in all cases. Doubling the fluid film velocity, on average, reduced the crown height by 18.5% and increased its diameter by 10.48%. However, its effect on the crater diameter was negligible (1%). An increase in the film thickness from 0.5 mm to 1 mm (h^* from 0.25 to 0.5), fed the upstream crown, and on average, increased its height by 10.57%. At a low impact velocity of 3 m/s (We = 249), the crown diameter was, on average, 26.7% larger than its diameter at the velocity of 7 m/s (We = 1358). By increasing the drop impact angle to 60 degrees and overcoming the effect of the fluid film velocity, the crown behavior was the same as its behavior with the drop impact on the static film. Finally, to predict the upstream crown height, downstream crown height, crown diameter, and crater diameter, four novel five-variable correlations (depending on τ, θ, Re_f, We, and h^*) are developed. It is concluded that a good agreement exists between the numerical data, and correlation results.

This study provides a reliability improvement control method for robotic arms with clearance joints. Firstly, the dynamical model of a six-DOF robotic arm with joint clearance is established, and the Archard model is utilized to describe joint wear, considering its effect on clearance evolution. The kinematic and dynamic characteristics of the robotic arm with clearances are analyzed concerning the contact and operation state variations. Then, the influence of clearance wear on the operational reliability of the robotic arm is studied as joint wear in the robotic arm contains interval uncertainty. To provide the uncertainty factors caused by the interval, we introduce Chebyshev functions to describe the dynamic response uncertainty and reliability. The non-probabilistic reliability index is given to evaluate the reliability of the robotic arm based on the stress intensity interference theory. Lastly, to improve operational accuracy and reliability, a novel compound control strategy containing collision force feedforward and PD feedback is carried out. It is compared with the traditional PD control strategy. Also, the sensitivity and robustness of the proposed compound control strategies are discussed. The results show that the proposed control strategy can effectively enhance the dynamics precision and reliability of the robotic arm, with satisfactory robustness. This study provides the control method for joint-worn robotic arms with undesired joint clearance, having significant potential applications for guaranteeing mission reliability in the fields of aerospace and industrial robotics.

A multiscale topology optimization model of anisotropic multilayer periodic structures (MPS) is proposed using the isogeometric analysis (IGA) method. The integrative design of multiscale structures was realized in two stages: the distribution optimization of multilayer periodic materials, which determines the types, distribution, and volume fraction of microstructures, and parallel topology optimization, which optimizes the macrostructure and various microstructures simultaneously. To implement the multilayer periodic constraint, the relative density and sensitivity of the IGA control points were equally redistributed. The correctness and advantages of the proposed model were confirmed by comparing its results with those obtained using finite element methods, and the optimal IGA microstructures displayed smoother boundaries. In addition, the multiscale MPS of the cantilever was 3D printed, confirming the practicality of the proposed model. The influences of the regularization scheme, multilayer periodic constraints, and Poisson's ratio factor on the results of the multiscale multilayer periodic optimization were explored, and recommendations for proper values of these parameters were provided to enhance the structural stiffness.

Blown powder laser metal deposition (p-LMD) is an advanced additive manufacturing technique that creates metal components by fusing metal powder particles with a substrate using a high-power laser source. This study explores the interactions between laser energy, powder flow, and gas dynamics within a three-channel nozzle configuration for a p-LMD processes, using an innovative three-step CFD–ray tracing model. Experimental techniques, including scanning electron microscopy for powder characterisation, radiometry for emissivity calibration, Pitot tube anemometry for gas flow velocity, and particle image velocimetry for particle velocity measurements, calibrate and validate the model. Employing ray tracing, the study evaluates the consequences of reflected and scattered light on the effective laser field seen by the powder cloud during the LMD process. Significant findings include the identification of optimal gas flow rates for effective shielding of the interaction volume and the impact of varying mass flow rates on laser beam attenuation and particle heating.

Controlling a cable-driven parallel robot (CDPR) when a cable breaks is challenging. In this paper, a sliding mode adaptive PID control is designed to ensure a safe guidance of the load when a cable fails. Indeed, regardless when a cable breaks, this control makes it possible enchanting the guidance of the load inside the remaining wrench feasible workspace. In other words, it allows reducing the load oscillation and then increasing the safety of the recovery manoeuvre. Performances are evaluated through simulations by considering a spatial CDPR and comparing the results with a PID control.

Thin-wall shells (steel plates, steel cylindrical shells, steel spherical shells, etc.) are widely used in many engineering fields such as construction, machinery, chemical industry, navigation, and aviation because of their light weight and high strength. Their failure modes under static pressure or impact dynamic load are mostly buckling instability, and the failure is very sudden, often causing structural failure or even catastrophic accidents without obvious symptoms. In this framework, the significance of this paper is that it considers the influence of external environment corrosion on steel shells' bearing capacity using plate and shell classical stability theory, and investigates the stable bearing capacity of thin-wall steel shells in view of corrosion impact. By this approach, a theoretical calculating method for the time-varying stable bearing capacity of plate and shell thin-walled steel members under the simultaneous action of corrosion and temperature changes is obtained, providing a useful theory for complex engineering practices such as corrosion and temperature changes, including fire actions. Noted that for this method with no analytical solution found, its numerical solutions are given in the appendixes.

To investigate the effect of gradient direction on mechanical properties and energy absorption capability of Gyroid lattice structures (GLSs), network-based and sheet-based lattice structures (G1-N768, G2-N768, G1-S768, G2-S768) of different gradient directions with an average porosity of 70% were established. The Al-Si10-Mg samples were manufactured through selective laser melting (SLM). Through compression tests and finite element analysis (FEA), the energy absorption, deformation behavior, and mechanical properties of the GLSs were evaluated. The data exhibited good consistency, and the deviations of yield strength, elastic modulus, plateau stress, densification strain and energy absorption could be controlled at about 10%. The results indicated that whether it is network-based or sheet-based GLSs, by changing the gradient direction, the deformation behavior could be transformed from layer-by-layer deformation (G1-GLSs) to uniform deformation (G2-GLSs), and thus realize the regulation of mechanical properties. At the same time, due to different topological configurations, stretch-dominated sheet-based GLSs (G1-S768, G2-S768) exhibited higher energy absorption capability and mechanical properties than bending-dominated network-based GLSs (G1-N768, G2-N768), and the energy absorption, yield strength and elastic modulus increased by 93.7%, 80.8% and 66.7%, respectively. In addition, the introduction of the Johnson–Cook model has effectively simulated the failure behavior of GLSs. This paper can offer theoretical guidance for the subsequent performance regulation and application of functionally graded GLSs.

Muscle injuries are the most common sports injuries in eccentric contraction. There are many factors that could influence the severity of muscle injuries, including strain, strain rate and stimulation. This study evaluated the interaction of these factors on the biomechanical properties of the muscle–tendon bundle and their role in injuries. A Hopkinson bar system, an MTS machine and an electrical pulse generator were utilized to collect eccentric contraction response data of over 150 frog muscle–tendon samples at strain rates ranging from 0.01 to 300 s⁻¹. The results have shown that the maximum eccentric stress has increased and peaked at the strain rate of about 150 s⁻¹. That peak value has then maintained at the following strain rates. In contrast, Young’s modulus reduced as the strain rate changed from 50 to 300 s⁻¹. That trend was in contrast to unstimulated muscle bundles. In addition, strain rate has significantly influenced stimulated tendon–muscle bundle fracture. Samples tend to rupture at a minor strain of about 3.5% with strain rates over 200 s⁻¹. Because of the increasing stiffness of the muscle area at high strain rates, increased strain in the tendon region resulted in frequent injuries in the tendon area. On the other hand, a maximum stress reduction was detected when the muscle bundles were stimulated at muscle strain greater than 0.2. The results showed that improper timing of stimulation could increase muscle injury. The study shows that the stimulation and strain rate dramatically impact muscle–tendon properties and the risk of injury.

In this paper, a multi-failure continuum model for in-plane analysis of masonry structures is introduced. The model is based on a recently-proposed single-surface multi-failure strength domain, and is here implemented in an elasto-plastic framework to perform nonlinear incremental static analyses on masonry walls. As a key feature of the model, the activated failure mechanism(s) can be identified and the corresponding plastic strains evolution computed. In particular, the distinction between crushing failure, joint failure (horizontal, vertical, and diagonal) and mixed joint-block failure is guaranteed by means of specific weights assigned to each failure mode. This amounts to a classification procedure which selects the active failure modes based on the information provided by the stress state. As a further novelty of this work, ad hoc nonassociated flow rules are then chosen to characterize each failure mode independently, so allowing a straightforward tracking of their nonlinear evolution. Well-known numerical examples are used to show the capability of the approach. From these, the proposed continuum model appears accurate and the tracking of the plastic strains related to the considered failure modes allows a straightforward interpretation of the results.

This paper introduces a novel approach aimed at addressing persistent challenges inherent in conventional multiphysics modeling methodologies. Existing techniques, such as numerical modeling and analytical calculations, often suffer from time-consuming and computationally intensive processes, leading to inefficiencies, particularly in intricate simulations. The proposed methodology employs regression machine learning algorithms as a black-box solution to anticipate errors and execution times in multiphysics simulations. Diverging from conventional methods, this approach streamlines the exploration of simulation options, providing discernible choices for balancing speed and precision. The efficacy of the methodology is exemplified through successful applications to heat transfer and fluid–structure interaction problems, illustrating its adaptability across diverse scenarios. Notably, the approach upholds the integrity of physics equations and simulation convergence while markedly reducing the trial-and-error efforts and computational burdens associated with traditional methodologies. In summary, the proposed approach emerges as an innovative and promising solution to augment the accuracy, efficiency, and dependability of multiphysics simulations.