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In order to address the urgent demand for high-performance materials in the field of automotive lightweighting, there is a need for solutions to the interface instability and performance degradation of traditional reinforcing phases (e.g., SiC, CNT) at elevated temperatures. The present study prepared BNNTs/Al composites via the stirred casting method for automotive connecting rods. The microstructure, interface characteristics, phase evolution, and high-temperature wettability were systematically characterised using a range of analytical techniques, including SEM, TEM, XRD, and DSC. A study was conducted to assess the mechanical properties of the composites in comparison to those of conventional 40Cr steel. This investigation enabled an evaluation of the material’s comprehensive performance for use in automotive connecting rods. The study successfully achieved uniform dispersion of BNNTs within the aluminium matrix, forming tightly bonded, semi-coherent interfaces such as Al/AlN and Al/AlB2. It was found that complete wetting was achieved at 675 °C, with interface reactions generating AlN and AlB2 phases that significantly enhanced performance. The prepared connecting rod demonstrates a specific strength that significantly exceeds that of 40Cr steel. The experimental investigation conducted in a controlled setting yielded notable outcomes. The empirical evidence demonstrated a 6.5% enhancement in braking performance and a 5.8% reduction in fuel consumption. Through the optimisation of interface design and process control, the BNNTs/Al composite achieves a balanced compromise between high strength, low density, and excellent thermal stability. The material’s potential for use in lightweight automotive connecting rods is significant, offering a novel approach to the eco-friendly manufacturing of related components.

In order to accurately calculate the reliability of mechanical components and systems with multiple correlated failure modes and to reduce the computational complexity of these calculations, the Copula function is used to represent related structures among failure modes. Based on a correlation analysis of the failure modes of parts of a system, a life distribution model of components is constructed using the Copula function. The type of Copula model was initially selected using a binary frequency histogram of the life empirical distribution between the two components. The unknown parameters in the Copula model were estimated using the maximum likelihood estimation method and the most suitable Copula model was determined by calculating the square Euclidean distance. The reliability of series, parallel, and series–parallel systems was analyzed based on the Copula function, where life was used as a variable to measure the correlation between components. Thus, a reliability model of a system with life correlations was established. Reliability calculation of a particular diesel crank and connecting rod mechanism was taken as a practical example to illustrate the feasibility of the proposed method.

Residual stress is the main factor that causes the deformation of the connecting rod during its coupled machining process. Thus, it is essential to predict the residual stress and deformation of the connecting rod before its machining. As the traditional independent analysis method is no longer suitable to the coupled machining process, a novel genetic-based method was proposed. Firstly, the genetic mechanism of residual stress field and deformation field was established to realize the effective correlation of multiple machining process simulation models. Secondly, a milling process was established based on the birth and death element method, which converted complex milling processes into dynamic loading of milling forces and the elimination of elements of the FEM model. It realized the coupling of initial residual stress (IRS) and machining induced residual stress (MIRS). Then, a multi-process simulation model of heat treatment, cutting off, and milling of connecting rod was established, which can reveal the evolution law of the residual stress field under multi-process coupling of connecting rod, the coupling mechanism between IRS and MIRS, and the deformation response law of the big hole cylinder of the connecting rod. The proposed method will have great significance to the deformation control of connecting rod.

To improve the surface roughness (Ra) of the connecting rod journals of crankshafts and reduce polishing time for abrasive belt polishing machines, a method for optimizing the polishing process parameters for connecting rod journals is proposed, combining BP neural network and NSGA-II algorithm. Initially, factors affecting the surface roughness are screened, and in consideration of practical production requirements, a five-factor four-level orthogonal experiment is designed. A BP neural network is then used to establish a nonlinear mapping relationship between the polishing process parameters and the surface roughness of the connecting rod journals. The predicted results from the BP neural network are used as fitness values, and the NSGA-II algorithm is employed to obtain the Pareto frontier optimal solution set and the corresponding combination of polishing process parameters.According to the optimization results, the process parameters of the abrasive belt polishing machine model are modified as follows: polishing arm cylinder pressure of 0.8 MPa, rotational axis output speed of 140 rpm, abrasive belt model B with grit size 800#, Coolant type concentration of 9%, and polishing time of 20 s. In comparison to the initial scheme parameters of the abrasive belt polishing machine, this combination of parameters resulted in a 25.2% increase in surface roughness at the connecting rod journal and saved 20% of the polishing time. Through the process parameter optimization method in this paper, it will contribute to improving the production performance of the crankshaft abrasive belt polishing machine, effectively enhancing the surface roughness at the processed connecting rod journal and saving polishing time.

This paper presents a comprehensive model for the inertia force field acting on a moving connecting rod. The derived formulas enable the accurate calculation of resultant inertia forces and their distribution on individual components for finite element analysis (FEA). The method applies to symmetrical and complex-shaped connecting rods, addressing challenges in modeling forces for asymmetrical designs. This work advances the precision of stress and vibration modeling in connecting rods, crucial for tribology and reliability studies. By improving the understanding of wear and failure mechanisms in reciprocating systems, it supports design optimization. The article presents the application of the proposed computational methods using three materials typically used for connecting rod construction: 42CrMo4, aluminum 2618, and Ti6Al4V. The presented results demonstrate how the material selection influences the total inertia force and the resulting stresses within the material. The numerical results are presented based on simulations conducted for two connecting rods of different sizes, operating at extremely different rotational speeds. The conducted analyses show that in the examined cases, rotational speed is the key factor influencing inertia stresses. The implementation, based on Open Source tools, allows a numerical analysis of inertia forces and stresses, with all the methods and models available in an open repository.

This article presents a new technology for forming automotive connecting rod forgings by means of die forging from cast performs from EN AB-71100 (EN AB-AlZn10Si8Mg) aluminum alloy. A premise was made that the production process would be carried out on forging presses. The process of forming connecting rod forgings was analyzed considering different deformation rates related to the type of machine used: a crank press and a screw press. The billet in the form of in-house designed, shaped preforms cast into sand molds with two variants of geometry was used in the process. The numerical analysis of the new process was carried out on the basis of the finite element method using Deform 3D, the simulation software for metal forming. The simulations were conducted in the spatial deformation conditions, considering the full thermomechanical analysis. Based on the simulations, certain important findings concerning the novel process were acquired, including the distribution of stress, deformation, temperatures, cracking criterion and energy parameters. The results of numerical tests confirmed the possibility of producing defect-free forgings of connecting rods from EN AB-71100 aluminum alloy on forging presses by means of the proposed technology. The proposed process of forging using crank and screw presses was verified in the course of tests conducted in industrial conditions. The properly formed connecting rod forgings were subjected to quality tests in terms of their structure and mechanical properties.

Forging is a widely used manufacturing process, and its design and modeling are important to reducing production costs, increasing die lifespan, and improving the mechanical properties of the final product. In this study, the forging process of a connecting rod was modeled using 3D coupled Eulerian Lagrangian (CEL) analysis by FEM. The methodology adopted achieved to determine a preform geometry that reduces final flash and forging load, while ensuring complete filling of the stamp. Starting from the final geometry, the final die was designed. After the first result for an approximately 27% of flash, the material distribution was adjusted decreasing it at the regions where the flash was too large. After an iterative method was applied to determine better preform, a proposal was found that reduced forging force by approximately 42% and the percentage of flash volume by 64% in comparison with the first one. A final flash of about 10% is considered a good objective to reach. Lower values may cause many iterations, not a significant difference in forging loads, the risk of an unfilled die, and complex preform geometries.

This article compares elastohydrodynamic lubrication (EHL) and mobility-based solution methods for the determination of cyclic minimum film thickness hmin * encountered in four-stroke, big-end connecting rod bearings. Mobility-based solution methods are substantially faster than the EHL method for such bearings, so quantifying the accuracy of mobility-based methods is an obvious benefit to the engine designer. Production-level connecting rods are modeled and analyzed using an established mass-conserving mode-based EHL formulation, accounting for realistic oil feed arrangements and realistic housing deformation associated with structural inertia and surface pressures. From a large set of dimensional studies, it is observed that hmin * calculated using mass-conserving EHL can be bounded by results obtained from finite-bearing mobility formulations, provided that a non-dimensional bearing number Λ falls below a critical value Λ crit ≈ 4. A set of five independent validation dimensional studies supports this observation.

The differences of 0.032% and 0.066% sulfur content on the splitting fracture and machining properties of microalloyed medium-carbon steel 36MnVS4 were studied. The splitting fracture and machining properties were examined by the analysis of MnS inclusions and microstructure, the test of mechanical properties and cutting properties. The results showed that as the number of MnS inclusions increased from 127.3 to 349.8 piece/mm 2 , the product of strength and elongation of 0.066%S steel increased by 12.3%. The functions of MnS as the core of the intragranular ferritic and refining of the austenite grains resulted in the increase in ferrite content by 2.0%, the decrease in ferrite size by 0.5 μm and the decrease in proto-austenite size by 6.0 μm. A higher ferrite content and lower ferrite and proto-austenite size enhanced the plasticity and toughness, which decreased the splitting fracture performance. The tool back surface wear width of 0.066%S steel decreased by 21.0% for 0.032% S steel. The roughness of 0.066%S steel decreased by 10.4% for 0.032%S steel. More and longer MnS inclusions broke the continuity of the matrix and improved the machining performance. For connecting rod manufacturing, to ensure the splitting fracture performance and enhance the machining performance, the sulfur content should be increased.

Aiming at the difficulty of quantitatively evaluating the critical processes in the manufacturing process of complex mechanical products, a critical process identification method based on the PageRank algorithm is proposed with the goal of identifying key processes in the machining process. Based on the complex network theory, the error transfer network model of the machining process is established in this paper. Adopting the actual machining process as the data set of the complex network, the weights of the machining feature nodes are calculated by the PageRank ranking algorithm, and the nodes are ranked according to the weight values to assess the influence and importance of the nodes in the network model. Finally, taking the connecting rod machining process of a medium-speed marine diesel engine as an example, the results show that the method can quickly and effectively identify the key processes in the machining process.