Abstract: Accurate and efficient numerical prediction model is the kernel about the digitization and intellectualization of plastic forming. To study advanced plastic forming of large-scale complex components in real time, there exists three fast simulation method: massive model simplifying or dimensionality reducing, solver algorithm modifying and high-performance parallel computing. And these methods are introduced in terms of reducing model scale, accelerating or avoiding time-consuming steps and improving device efficiency. The two major approaches about model scale reducing are introduced: mesh density dynamic controlling technique and shell element model. Subsequently, a review of some innovative numerical algorithms for improving calculation process is provided, such as machine learning, material point method and virtual element method. Then, the research progress of parallel techniques on homogeneous and heterogeneous computing platforms is discussed. Finally, the application prospect and development of these numerical simulation methods for plastic forming are also presented.

Key words: mesh density controlling, shell element, machine learning, material point method, virtual element method, parallel computing, GPU