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Gears are one of the the most widespread mechanical components and their design is supported by standard calculation methods. Among all the possible failure modes of gears, tooth root bending is the most critical and could lead to catastrophic failures. In this regard, different surface treatments could be exploited to improve the gear strength. Among them, shot peening is the most common. The aim of this study is to evaluate the effectiveness of shot peening on improving the tooth root bending resistance. This is achieved by exploiting the Finite Element Method (FEM) in combination with advanced multiaxial fatigue criterion based on the critical plane concept. A standard Single Tooth Bending Fatigue test was reproduced numerically via FEM. Beside the wrought gears, shot peened ones were also simulated. The state of stress induced by the shot peening was obtained numerically by simulating the surface treatment itself with non-linear dynamic analyses. The results have shown quantitatively how the residual stresses promote an improvement in the resistance and how the local hardening could lead to different early paths of nucleation and propagation of cracks on the tooth fillet.

Downsizing is a more and more widespread trend in many industrial sectors, and, among the others, the automotive industry is pushing the design of its components towards increasingly compact, lightweight, efficient, and reliable solutions. In the past, the drivetrains for automotive were designed and manufactured with gears having modules in the range 3 to 10. In this respect, the main actual European standards for gear design such as ISO 6336:2019 (based on the DIN 3990:1987) are validated in the 3 to 10 mm range only. Moreover, it is well known that, by increasing the gear size, the gear size factor for tooth bending YX reduces. However, nowadays the advances in terms of materials and design knowledge have made possible the realization of miniaturized gearboxes with gears having normal modules below 3 mm with comparable (or better) reliability. In this scenario, understanding how the size affects (positively) the load-carrying capacity for tooth root bending for small modules below 5 mm is fundamental to maximize the design effectiveness in case of downsizing of the drivetrains. In this paper an experimental study was performed on small gears made of 39NiCrMo3 having a normal module of 2 mm to verify the load-carrying capacity for tooth root bending. Based on the experimental evidences and additional data from literature and past studies by the author, an extended formula for the size factor YX (according to ISO 6336) is proposed.

The lubrication of the mechanical components reduces friction, and increases the efficiency and the reliability. However, the interaction of moving components with the lubricant leads to power losses due to viscous and inertial effects. Nowadays, the study of lubricant behavior can be carried out through computational fluid dynamics (CFD) simulations. Nevertheless, the modeling of the computational domain within complex mechanical systems (e.g., ordinary, planetary and cycloidal gearboxes, roller bearings, and pumps) requires the exploitation of specific CFD techniques. In the last decades, many mesh-based or meshless approaches have been developed to deal with the complex management of the topological changes of the computational domain or the modeling of complex kinematics. This paper aims to collect and to classify the scientific literature where these approaches have been exploited for the study of lubricated mechanical systems. The goal of this research is to shed a light on the current state of the art in performing CFD analysis of these systems. Moreover, the objective of this study is to stress the limits and the capabilities of the main CFD techniques applied in this field of research. Results show the main differences in terms of accuracy achievable and the level of complexity that can be managed with the different CFD approaches.

For decades, journal bearings have been designed based on the half-Sommerfeld equations. The semi-analytical solution of the conservation equations for mass and momentum leads to the pressure distribution along the journal. However, this approach admits negative values for the pressure, phenomenon without experimental evidence. To overcome this, negative values of the pressure are artificially substituted with the vaporization pressure. This hypothesis leads to reasonable results, even if for a deeper understanding of the physics behind the lubrication and the supporting effects, cavitation should be considered and included in the mathematical model. In a previous paper, the author has already shown the capability of computational fluid dynamics to accurately reproduce the experimental evidences including the Kunz cavitation model in the calculations. The computational fluid dynamics (CFD) results were compared in terms of pressure distribution with experimental data coming from different configurations. The CFD model was coupled with an analytical approach in order to calculate the equilibrium position and the trajectory of the journal. Specifically, the approach was used to study a bearing that was designed to operate within tight tolerances and speeds up to almost 30,000 rpm for operation in a gearbox.

The application of Computer-Aided Engineering (CAE) tools in mechanical design has consistently increased over the last decades. The benefits introduced by virtual models in terms of time and cost reductions are the main drivers for their exploitation in industry as well as for research purposes in academia. In this regard, Computational Fluid Dynamics (CFD) can be exploited to study lubrication and efficiency of gears. However, the mesh handling complexities deriving from the boundary motion is still a concern for its application to multi-stage gearboxes. In this work, an innovative multi domain partitioning method for the simulation of a two-stage industrial speed reducer is presented. The implemented solution foresees the combination of two remeshing strategies, namely GRA (Global Remeshing Approach) and GRAMC (GRA with Mesh Clustering), and resulted in a computationally effective performance. The results were compared with experimental data obtained with measurements on the real system, providing a good agreement in the power losses prediction. Considering the complexity of obtaining such results experimentally, the proposed numerical algorithm can offer substantial benefits for an estimation of the transmissions’ efficiency in various operating conditions. The numerical model was built in the open-source environment OpenFOAM®.

In this research, the energy absorption and plastic deformation of circular polyethylene tubes under lateral compression were investigated, comparing empty tubes with those filled with polyurethane foam. The effects of tube length, diameter, wall thickness, and filler density on load-bearing capacity and energy absorption were evaluated. Absorbed energy and lateral load were found to increase with tube length, although the ductile response of polyethylene produced pronounced fluctuations in the load–displacement curve. Diameter influenced the two configurations differently: in empty tubes, smaller diameters yielded greater energy absorption, whereas in foam-filled tubes, larger diameters increased the flattening load and total absorbed energy, underscoring the critical role of diameter in foam-filled systems. Increasing wall thickness enhanced energy absorption, but polyurethane-foam filling was more effective and yielded a more consistent, predictable load–displacement response. Foam-filled tubes outperformed empty tubes overall; dominant damage mechanisms were identified as foam fracture, crushing, and densification. For applications prioritizing structural efficiency and specific absorbed energy (SAE), the use of higher-density polyurethane foam is recommended. Adhesion between the foam and the tube’s inner surface significantly increased peak load capacity. After relaxation, a uniform diameter reduction of approximately 12.7% was observed across specimens, indicating consistency in the final morphology. These findings provide guidance for the design of load-bearing systems employing polyethylene tubes and polyurethane foam.

Road transport plays a significant role in the economic growth of a country. Conventional internal combustion engines (ICEs) are widely used in automobiles, with an efficiency range of 25% to 35%, while the remaining energy is lost through cooling and exhaust gases. Additionally, two parasitic loads—the alternator and the air conditioning (AC) compressor—are driven by the ICE via a belt, further reducing efficiency. In this paper, energy and exergy analysis of the waste heat of exhaust gases has been performed for automobiles equipped with ICEs, i.e., R06A, F8B, K10B, 2NZ-FE, and 2ZR-FE, to evaluate their potential to drive these parasitic loads. The working cycles of these ICE models were simulated using a zero-dimensional MATLAB model based on fundamental governing equations. The results indicate that approximately 10–40 kW of energy is lost through exhaust gases under varying operating conditions for the examined ICEs. The average exhaust gas temperature and mass flow rate for these ICEs are approximately 900 K and 0.016 kg/s, respectively. Based on these findings, an E-turbine retrofit system is proposed to operate under these conditions, recovering exhaust energy to power the alternator and AC compressor. The results showed that the E-turbine generated 6.8 kW of mechanical power, which was converted into 4 kW of electrical power by the generator. This electrical power was used to supply the parasitic loads, thereby enhancing the overall efficiency of ICE.

In the shipbuilding, construction, automotive, and aerospace industries, welding is still a crucial manufacturing process because it can be utilized to create massive, intricate structures with exact dimensional specifications. These kinds of structures are essential for urbanization considering they are used in applications such as tanks, ships, and bridges. However, one of the most important types of structural damage in welding continues to be fatigue. Therefore, it is necessary to take this phenomenon into account when designing and to assess it while a structure is in use. Although traditional methodologies including strain life, linear elastic fracture mechanics, and stress-based procedures are useful for diagnosing fatigue failures, these techniques are typically geometry restricted, require a lot of computing time, are not self-improving, and have limited automation capabilities. Meanwhile, following the conception of machine learning, which can swiftly discover failure trends, cut costs, and time while also paving the way for automation, many damage problems have shown promise in receiving exceptional solutions. This study seeks to provide a thorough overview of how algorithms of machine learning are utilized to forecast the life span of structures joined with welding. It will also go through their drawbacks and advantages. Specifically, the perspectives examined are from the views of the material type, application, welding method, input parameters, and output parameters. It is seen that input parameters such as arc voltage, welding speed, stress intensity factor range, crack growth parameters, stress histories, thickness, and nugget size influence output parameters in the manner of residual stress, number of cycles to failure, impact strength, and stress concentration factors, amongst others. Steel (including high strength steel and stainless steel) accounted for the highest frequency of material usage, while bridges were the most desired area of application. Meanwhile, the predominant taxonomy of machine learning was the random/hybrid-based type. Thus, the selection of the most appropriate and reliable algorithm for any requisite matter in this area could ultimately be determined, opening new research and development opportunities for automation, testing, structural integrity, structural health monitoring, and damage-tolerant design of welded structures.

The concept of “Industry 4.0” encourages the use of automated manufacturing processes and the use of advanced technological systems. Some of the most fundamental needs of the Fourth Industrial Revolution can only be met with the help of additive manufacturing. However, the mechanical behavior and reliability of additive-manufactured components are hardly recognized. This paper provides a systematic review of metal additive manufacturing technologies, materials, lattice structures, and fatigue properties as well as the development of numerical simulations. The current state of development in metal alloys and the optimization of cellular structures were presented. In addition, this paper discussed the main challenges in numerical simulation methods, their validation with experimental results, and the limitations of commercial software used. Overall, this paper provides an overview of metal additive manufacturing as well as a survey of its simulation software development to optimize several parameters in industrial and academic research fields. The results were critically analyzed and provided a benchmark for future research and development.

Developing accurate design data to enable the effective use of new materials is undoubtedly an essential goal in the gear industry. To speed up this process, Single Tooth Bending Fatigue (STBF) tests can be conducted. However, STBF tests tend to overestimate the material properties with respect to tests conducted on Running Gears (RG). Therefore, it is common practice to use a constant correction factor fkorr, of value 0.9 to exploit STBF results to design actual gears, e.g., through ISO 6336. In this paper, the assumption that this coefficient can be considered independent from the gear material, geometry, and loading condition was questioned, and through the combination of numerical simulations with a multiaxial fatigue criterion, a method for the calculation of fkorr was proposed. The implementation of this method using different gear geometries and material properties shows that fkorr varies with the gears geometrical characteristics, the material fatigue strength, and the load ratio (R) set in STBF tests. In particular, by applying the Findley criterion, it was found that, for the same gear geometry, fkorr depends on the material as well. Specifically, fkorr increases with the ratio between the bending and torsional fatigue limits. Moreover, through this method it was shown that the characteristics related to the material and the geometry have a relevant effect in determining the critical point (at the tooth root) where the fracture nucleates.