According to the energy-saving and new energy vehicle technology roadmap released by the Society of Automotive Engineers, the focus for automotive materials is to improve the application system of high-strength steel in the short term, to form a lightweight alloy application system in the medium term, and to form a multi material hybrid application system in the long term. Aluminum alloy, as the most widely used lightweight structural material, is a key material in fields such as automobiles and aviation due to its high specific strength and thermal conductivity. The lightweight advantage of aluminum makes it widely needed in the field of automotive materials, and the amount of aluminum used in bicycles has enormous growth potential. Low pressure casting, as an important forming method for aluminum alloy components, has a casting pressure between gravity casting and high-pressure casting. Due to its high productivity, smooth filling under pressure, controllable filling speed, high dimensional accuracy, ability to form castings with complex structures, resistance to oxidation inclusions, and dense microstructure, low-pressure casting methods are mostly used in the automotive industry to produce wheel hubs and engine cylinder heads. Complex thin-walled castings have the characteristics of thin walls, complex structures, large contour dimensions, high dimensional accuracy, and high internal quality requirements. Especially for thin-walled castings with complex shapes and large differences in wall thickness, the microstructure and mechanical properties of different parts vary greatly, and the mechanical properties of key parts are difficult to meet the service requirements. Therefore, further in-depth research is needed on the precise forming and microstructure control, mechanical property prediction, and other issues of complex thin-walled aluminum alloy castings.
The casting process conditions determine the evolution of microstructures at different scales, and these microstructures at different scales determine the final mechanical properties of castings, such as tensile strength, yield strength, elongation, and fatigue strength. This requires researchers to conduct multi-scale simulations of the microstructural evolution process during low-pressure casting, and to study the coupling calculation of solidification conditions, microstructure, and properties in low-pressure casting, in order to accelerate the research and development of aluminum alloy low-pressure casting technology.
Multi scale modeling and simulation of low-pressure casting process
Low pressure casting is a method of anti gravity casting, which applies a certain pressure on the liquid surface of the liquid alloy in the holding furnace or holding crucible, causing the liquid metal to fill the mold cavity from bottom to top along the riser, and then Solidification and forming under pressure. However, in the actual production process, factors such as pressure level, liquid phase flow rate, and cooling rate during the casting process can still affect the formation and distribution of defects such as porosity and oxide film in castings. In addition, the mechanical properties of castings are also influenced by microstructure such as grain size, secondary dendrite arm spacing, and the morphology and distribution of precipitated phases. Therefore, it is necessary to clarify the influencing factors and formation mechanisms of various defects in the low-pressure casting process of aluminum alloys, optimize the process to reduce casting defects and improve the mechanical properties of low-pressure casting castings. Due to the complexity of the filling and solidification process in low-pressure casting, it is impossible to understand the actual physical changes through experiments and post dissection methods. Although researchers have conducted some experimental studies on the filling and solidification process of low-pressure casting, their understanding of the factors that cause various defects and their formation and development mechanisms is still not deep enough to accurately and effectively predict and eliminate their effects. Therefore, establishing physical and mathematical models related to the low-pressure casting process, and using computer numerical simulation technology to simulate the macroscopic filling flow field, solidification temperature field, and microstructure evolution process to predict the formation of low-pressure casting defects, has important engineering value for optimizing the casting process and obtaining high-quality castings.
The numerical simulation study of low-pressure casting filling process began in the 1980s. There are many methods for calculating flow fields, such as early MAC algorithm and SMAC algorithm, Finite Volume method, etc. The commonly used one now is SuhasV The SIMPLE algorithm proposed and the SOLA-VOF algorithm proposed by LOS Alamos laboratory in the United States The law. A series of commercial software for numerical simulation of casting have been developed, such as
MAGMASOFT, ProCAST, Flow 3D, AnyCasting, etc. can simulate the filling, heat conduction, solidification process, and stress field of casting. In recent years, domestic casting numerical simulation software has also developed rapidly. Tsinghua University is one of the earliest institutions in China to develop numerical simulation software for casting. Its FT Star software, which has independent intellectual property rights, adopts finite difference technology and includes functional modules for low-pressure casting. The Huazhong University of Science and Technology has developed Huazhong Casting CAE software, which can simulate the filling and solidification processes of castings, and also includes functional modules for low-pressure casting. North China Institute of Technology has developed CASTsoft casting process simulation software, which can simulate various casting methods including low-pressure casting.
Simulation of Low Pressure Casting Solidification Process
The solidification process of low-pressure casting is a complex physical and chemical process, accompanied by processes such as heat transfer, solute transfer, momentum transfer, and phase transformation. In the entire simulation process of low-pressure casting castings, including filling, solidification, and stress simulation, there is a simulation of temperature field. Due to the fact that the solidification process involves three basic heat transfer modes: heat conduction, heat convection, and heat radiation, the heat exchange during the solidification process of low-pressure casting is simulated using a heat transfer equation.
Like other casting solidification processes, solidification phase transformation occurs during low-pressure casting, releasing latent heat of solidification. Common latent heat treatment methods include equivalent specific heat method, temperature rise method, and enthalpy method. The cooling process of low-pressure casting wheel hub molds was studied using PAM-CAST software. The multi type interface heat transfer characteristics of low-pressure casting were classified and calculations were performed on actual aluminum alloy wheel hub castings. The temperature and stress fields of the ZL114A casing casting were simulated and analyzed using ProCast software, and the process was optimized. Using View Cast software, temperature field simulation was conducted on aluminum alloy wheels produced by low-pressure casting, and the defect forming machine was analyzed Reason. Using ProCast software, the low pressure casting aluminum alloy wheel hub was analyzed by coupling the filling and solidification temperature fields. Based on the simulation results, the mold structure and process parameters were optimized. Numerical simulations were conducted on the filling and solidification behavior of A356 aluminum alloy wheels produced by low-pressure casting, and the solidification time estimated by SDAS was compared with the calculated solidification time.
Summary and Outlook
Numerical simulation technology has a significant guiding role in the process optimization and quality control of low-pressure casting of aluminum alloys. In recent decades, many algorithms and commercial numerical simulation software have been developed to simulate macroscopic processes such as filling and solidification
Numerical simulation of physical phenomena helps optimize low-pressure casting processes, reduce casting defects, lower production costs, improve production efficiency and product quality. In addition, numerical simulations were conducted on the evolution of dendritic and eutectic microstructures during low-pressure casting of aluminum alloys, and the relationship between microstructure and mechanical properties was established. However, the numerical simulation of low-pressure casting of aluminum alloys still faces some challenges, such as the accuracy of numerical simulation calculations, the improvement of numerical calculation efficiency, and the deep coupling of multi-scale simulations. We hope to deepen the development of numerical simulation for low-pressure casting of aluminum alloys in the following areas.
(1) In existing multiscale numerical simulations, macroscopic and microscopic simulations are often uncoupled or weakly coupled. Future research should further develop the application of ICME in low-pressure casting and deeply couple macroscopic simulations Through micro simulation, information transmission between macro and micro levels can be achieved, and a full process simulation system for low-pressure casting technology can be constructed to improve the consistency and accuracy of simulation results.
(2) In the field of numerical simulation of low-pressure casting of aluminum alloys, with the support of high-performance computing and parallel computing technology, the calculation speed of numerical simulation will be accelerated, the computational domain of low-pressure casting numerical simulation will be expanded, and the realization of large-scale Rapid multi-scale simulation of complex thin-walled low-pressure castings.
(3) Rapid design of new casting processes for low-pressure castings with target mechanical properties, combining big data and machine learning methods into numerical simulation technology, mining patterns from large-scale simulation data, and establishing By establishing the correspondence between composition, process, organization, and performance, we can quickly obtain the process corresponding to the target performance casting and accelerate the development of low-pressure casting technology.