Erosion in elbows is a critical factor affecting the safety and service life of heat-exchange pipelines. To elucidate the erosion patterns of 90° elbows in heat-exchanger tubes under solid–liquid two-phase flow, this study conducts a systematic investigation combining experimental measurements with numerical simulations. An erosion test rig was first designed and constructed, and specimens were arranged at different positions on the inner wall of the elbow to investigate the effects of flow velocity, particle diameter, erosion duration, and specimen orientation on the erosion rate. These tests identified the primary influencing factors and their roles. Due to experimental limitations in capturing minor erosion and evaluating structural parameters, a Fluent-EDEM coupled model based on the Eulerian-Lagrangian approach was further established to simulate the erosion characteristics in the elbow. The numerical results were validated against experimental data, demonstrating the reliability of the model. The simulations provide flow-field and erosion information difficult to obtain experimentally and systematically reveal the effects of flow velocity, particle properties, and geometric parameters on erosion distribution and local erosion intensity. This study enhances the understanding of elbow erosion mechanisms and offers a theoretical basis for the structural optimization of heat-exchange tubes under particle-laden flow conditions.
This paper investigates the tribological behavior of microwave-sintered Ti-0.8Ni–0.3Mo/X wt.% TiB composites using an integrated Multi-Criteria Decision-Making (MCDM) and Machine Learning (ML) approach. It explores the relationship between composition and tribological properties. Criteria Importance Through Intercriteria Correlation (CRITIC) and entropy methods were used to determine criteria weights, revealing wear rate as more influential than friction. Weighted Aggregated Sum Product Assessment (WASPAS) ranked alternatives based on input factors, and various ML algorithms—Decision Tree, Random Forest, Linear Regression, and AdaBoost—were trained to predict the MCDM-derived closeness coefficient. Among these, AdaBoost showed superior performance. The study confirms the accuracy of ML models in predicting wear and friction under varying conditions, highlighting their reliability in optimizing composite performance. This approach effectively supports tribological evaluation and materials design for engineering applications.
Accurate prediction of buckling in telescopic hydraulic cylinders remains a major challenge as with the increase in the number of stages, variations in stiffness become significant. Traditional analytical approaches often fail to capture these variations, leading to erroneous predictions. Although in some studies recursive formulas have been proposed for the buckling load, however, they typically assume equal-slopes at the stage interfaces. This assumption neglects the actual variation in bending stiffness across stages. To address this limitation in the present study, a generalised formula has been developed for the buckling load of n-stage hydraulic cylinders by incorporating variations in bending stiffness and slope discontinuities into the moment boundary conditions. Bending stiffness is evaluated through two distinct approaches. In the first approach, stiffness is determined at each connection by assuming that the rod within the cylinder behaves as a supported beam. While this method simplifies the formulation and supports a generalised solution, it assumes constant stiffness and may not fully capture the deformed behaviour at the interface. To improve accuracy, the second approach evaluates bending stiffness at the actual buckling point, where the deformed segment is modelled as fixed-free with a bending moment acting at the free end. This method redefines boundary conditions at the buckling location using the Successive Approximation Method (SAM), thus better representing the physical response. Both approaches lead to a generalised stiffness matrix applicable to any n-stage hydraulic cylinder configuration. To validate the proposed methods, single-stage, two-stage, and three-stage hydraulic cylinders of varying lengths are analysed. Finite Element Analysis (FEA) is conducted to compare predicted buckling loads and buckling points. While both methods provide consistent predictions, the second approach is better suited for complex, real-world applications.
Mechanical damage is one of the main causes of quality deterioration during mechanized apple harvesting. In this study, a multilayer finite element model of apple tissue was developed using ABAQUS to investigate microscale failure behavior under localized contact loading. The model included wax, peel, and flesh layers, while zero-thickness cohesive elements were inserted at the interfaces to simulate delamination behavior. Different elastoplastic properties were assigned to each layer, whereas creep and permeability effects were incorporated into the flesh to reproduce its time-dependent mechanical response. Three indenter geometries, including Berkovich, Flat, and Spherical indenters, were used to analyze their effects on deformation, stress distribution, damage evolution, and energy dissipation. The Berkovich indenter generated the strongest local stress concentration, with an influence depth of 180 μm, and produced a maximum principal stress that was 60% higher than that of the Spherical indenter, indicating greater a tendency for peel cracking. The Flat indenter caused the largest permanent deformation and pronounced edge stress concentration, whereas the Spherical indenter distributed stress more uniformly and resulted in the lowest residual stress after unloading. Micro-indentation experiments showed trends consistent with the simulation results, thereby validating the proposed model. Interfacial damage initiated first at the wax-peel interface at indentation depths of 50–120 μm, while more severe failure occurred at the peel-flesh interface at depths of 150–250 μm, where complete separation and increased energy dissipation were observed. These results reveal a hierarchical damage mechanism in apple tissue and provide theoretical guidance for reducing mechanical damage during mechanized harvesting.
This paper presents a design method for a harmonic drive (HD) with the full conjugate tooth profiles and dual-eccentric circular-arcs (DECA) external wave generator (WG). First, the conjugate combined cycloid tooth profile (CCTP) equations for the circular spline (CS) and flexspline (FS) is established to analyze the meshing characteristics of the tooth profiles, such as the line of action and meshing angle, etc. Then a multi-tooth contact model considering assembly preload force and internal component interaction is established to systematically study the influence of the parameters on the bearing characteristics and friction losses of the whole machine. Finally, the finite element model of the whole machine is developed to verify the effectiveness of the theoretical model. The simulation results show that the distribution of assembly deformation force and load contact force of FS is basically consistent with the theoretical model, and the radial resultant force on WG during the assembly agrees with the theoretical value to within 2.3%. The research outcomes provide a new way to study high bearing and impact resistant HD.
