Abstract
Hybrid physical-data-driven modeling techniques have steadily been developed to address the multi-scale and multi-physical aspects of dynamic process simulations. The analytical and computational features of a new hybrid-evolving technique for these processes are elaborated herein and its industrial applications are highlighted. The authentication of this multi-physical and multi-scale framework is carried out by developing an integrated simulation environment where multiple solver technologies are employed to create a reliable industrial-oriented simulation framework. The goal of this integrated simulation framework is to increase the predictive power of material and process simulations at the industrial scale.
Highlights
The predictive power of numerical simulations for modeling and optimizing dynamic material processes have rigorously been examined by scientists and engineers to avoid extensive and costly experimental and repeated trial series
To establish this integrated simulation framework, reliable interfacing and coupling procedures are required to implement the multi-solver scheme which is a pillar of the proposed Through Process Simulations (TPS) of materials which might include casting process to the forming of final parts [1]
The hybrid models are categorically grouped into different classes, namely; liquid phase and dispersive gases, the three-phase continuity auxiliary, augmented, full, and dynamic hybrid models where different applications can equation for phase k can be written as [32,33]: be handled using an appropriate type of hybrid model
Summary
The predictive power of numerical simulations for modeling and optimizing dynamic material processes have rigorously been examined by scientists and engineers to avoid extensive and costly experimental and repeated trial series. In recent years, some multi-solver simulation frameworks along with extensive interfacing and bridging technologies were proposed to handle the simulation of material processes at different phases and length scales. To help establish a ground for such an integrated simulation framework, new and innovative hybrid techniques have widely been proposed [2,3,4], which help to improve analytical and numerical aspects of simulations These upgraded and sophisticated analytical and numerical simulations are founded on hybrid physical-data-driven schemes where data processing and handling techniques are used to improve the analytical and numerical modeling. The hybrid-evolving numerical solution proposed is based on a computational concept which institutes the sound physical\mathematical models and does rely on the improved algorithm or solver technology for the material and process simulations. One of the main contributions of this paper is to show how new computational technologies combined with hybrid modeling and suitable AI scheme can transform the traditional material and process simulation techniques
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