This paper investigates the collision of different bearing balls with a massive steel cuboid in order to determine the restitution parameter experimentally. A test bench is constructed to measure the rebound distances of the different balls using slow-motion camera. The numerical analysis of the collision with energy dissipation assumes nonlinear viscoelastic property with Hertzian contact. The hysteresis damping factors are determined from the expression of the Flores model. First, second and fourth order numerical methods are compared to each other as regards the running times and accuracies for finding the most suitable technique.
The thermal performance of jacketed reactors is strongly influenced by the thermophysical properties of the applied heat transfer fluid. While analytical methods provide rapid engineering estimates, they are often unable to describe local flow structures and temperature distributions within the jacket space. In the present study, a three-dimensional computational fluid dynamics (CFD) model was developed in ANSYS CFX to investigate the flow and heat transfer behavior of two commonly used coolant solutions: methanol-water and ethylene glycol-water mixtures. The numerical simulations were performed for two jacketed reactor geometries under identical thermal boundary conditions. The velocity field, temperature distribution, pressure drop, and heat transfer coefficient were evaluated and compared with previously published analytical calculations. The results showed that the methanol-based coolant provided higher heat transfer coefficients in both investigated geometries. The calculated differences between the two coolant solutions reached 23.0% and 20.7%, respectively, which is in good agreement with the trends predicted by the analytical model. The CFD simulations confirmed the main conclusions of the analytical investigation while providing additional insight into the underlying flow and temperature fields. The proposed methodology can support the comparative evaluation of heat transfer fluids and assist engineering decision-making during the thermal design of jacketed reactor systems.
This study investigated the morphology replication and resulting structural and tribological effects of different surface treatment methods on metal injection-molded (MIM) 17-4PH martensitic precipitation-hardenable stainless steel. Three conditions were evaluated: untreated, TiAlN + TiCN PVD-coated, and hybrid-treated samples combining low-temperature plasma nitriding (LTPN) with PVD coating. The specimens were characterized for surface roughness and morphology, phase composition, hardness, adhesion, friction behavior, and wear resistance. The results showed that LTPN significantly modified the substrate surface through crack formation, grain boundary shear offsets, and grain surface uplifts, with the latter two morphological features being subsequently replicated by the deposited coating, leading to increased roughness parameters (Rpk, Rvk, and Rk). The nitrided layer improved coating support and increased the hardness of the PVD-coated system. In addition, the altered surface morphology was associated with changes in the coating's preferred crystalline orientation, including the appearance of the (220) and strengthening of the (222) TiAlN/TiCN reflections. Tribological testing demonstrated that the hybrid-treated samples exhibited improved tribological performance, including lower steady-state friction and enhanced wear resistance, attributed to the combined effects of the modified surface morphology and enhanced load-bearing capacity of the nitrided substrate. The findings highlight the role of substrate grain morphology in governing LTPN-induced surface modifications and their subsequent replication by the PVD coating, suggesting that further optimization of MIM processing parameters could enable control of the surface morphology and, consequently, the tribological properties of hybrid surface-treated MIM components.
With the advancement of technology, cyber-physical systems are increasingly gaining ground. Today, virtual reality is appearing in numerous areas - not only in industrial applications or popular video games but also in education, facilitating a deeper understanding of various processes. The topic of this paper is the implementation of a generalized 3D printer simulation using the 3D virtual software MaxWhere. This simulation can demonstrate the operation of any Cartesian printer by providing its 3D models and URDF description, thereby offering an easily accessible and manageable demonstration tool to support education. For the sake of user-friendliness, an AI-based URDF generation application is also presented.
Vision-language models (VLMs) have shown strong performance on multimodal reasoning tasks, yet their ability to perform quantitative analysis of technical drawings remains largely unexplored. This study evaluates the instruction-guided zero-shot performance of three open-source VLMs, on the task of estimating room areas from color-coded residential floor plan images. Of the three models tested, two produced quantitatively evaluable structure outputs. A dataset of 100 floor plans, comprising 472 plan-level room-type evaluation comparisons derived from 894 ground-truth room instances, was used to compare predicted and ground truth areas. Results show moderate predictive correlation (R2 approximate to 0.71), but substantial estimation errors (MAPE approximate to 43%), with noticeably larger errors for smaller rooms. A classical pixel counting baseline, using color segmentation, achieved MAPE = 5.68% at the room-instance level, and MAPE = 1.58% when evaluated at the floor plan level, highlighting the limitations of the tested VLMs for precise geometric estimation under this controlled setup. These findings suggest that while the evaluated open-source VLMs can approximate spatial proportions in simplified color-coded layouts, their quantitative accuracy remains significantly below that of deterministic image analysis methods.
