Hardware forgings are important basic parts in the machinery manufacturing industry, and their manufacturing process involves complex physical field interaction. In order to improve product quality, reduce production cost and improve production efficiency, the importance of multi-physical field simulation and optimization design in the manufacturing process of metal forgings has become increasingly prominent.
Metal forgings are widely used in various machinery and equipment, and their quality directly affects the safety and reliability of machinery and equipment. The traditional metal forgings design mainly relies on experience, the design cycle is long, the cost is high, and the optimal performance of the final product cannot be guaranteed. With the development of computer technology and numerical simulation technology, multi-physical field simulation and optimization design have gradually become an important technical support in the manufacturing process of metal forgings.
Before the multi-physics simulation and optimization design, a series of preparations need to be made. First of all, it is necessary to select the appropriate materials according to the product requirements, such as carbon steel, alloy steel, stainless steel, etc., and to test and evaluate its chemical composition, mechanical properties, process properties, etc. Secondly, it is necessary to establish accurate simulation models, including geometric models, material models, boundary conditions, etc., and set parameters according to actual production conditions. In addition, data processing work, including data cleaning, data analysis, data visualization, etc., is needed to provide support for subsequent simulation analysis and optimal design.
Multi-physical field simulation is to simulate the behavior of metal forgings under the action of complex physical field by computer simulation. Among them, it mainly includes the establishment of material model, the division of deformation area, the calculation of thermal stress, strain energy and other parameters. In the simulation process, the model can be iterated and optimized continuously to obtain more accurate results.
On the basis of multi-physics simulation, the optimal design scheme can be proposed. The optimization design is mainly through the optimization and adjustment of material properties, process parameters, etc., in order to improve the performance of metal forgings and reduce production costs. For example, you can change the yield strength, hardness and other properties of the material, or adjust the forging temperature, deformation rate and other process parameters to achieve the purpose of optimal design. In the optimization design, it is necessary to fully consider the limitations of manufacturing process and cost to ensure that the design scheme has strong practicability and operability.
Through the analysis and comparison of the results of optimal design, the best design scheme can be obtained. In the evaluation of the design scheme, it is necessary to consider the performance improvement, production cost reduction and other factors. In addition, the optimization scheme needs to be further discussed and perfected to solve the possible problems and improve the reliability of the scheme.
This paper introduces the multi-physics simulation and optimization design of metal forgings, including preparatory work, simulation analysis, optimization design, results and discussion. Through multi-physical field simulation and optimization design, it can greatly improve the product quality and production efficiency of metal forgings, reduce production costs, and provide strong technical support for the development of machinery manufacturing industry. However, there are still some limitations in the application of this technology, such as the accuracy and stability of the simulation model, which need to be further studied and improved. Future research directions could include the development of more accurate material models and numerical algorithms, the consideration of more physical effects and influencing factors, and the integration of artificial intelligence technology for assisted design.
