Automatické vyhodnocování úloh vícefázového proudění v prostředí Ansys

Abstract

Multiphase flow plays a critical role in many engineering applications, particularly in the automotive and aviation sectors, where understanding and optimizing complex fluid interactions is essential. However, evaluating the results of multiphase flow simulations manually is a time-intensive process prone to errors, which can hinder efficiency and accuracy. This research aims these problems by developing an automated evaluation framework within the Ansys Fluent environment. By focusing on tasks such as oil surface coating and simulating various boundary conditions, the study establishes a robust methodology for universal multiphase flow evaluation. A custom script was created to standardize post-processing tasks, enabling the accurate assessment of simulation performance across different scenarios. The proposed solution reduces the reliance on manual evaluation, ensuring consistency and saving significant time. While the scripts limitations are explored, the methodology provides a foundation for integrating automation into CFD workflows. In the future, advancements in artificial intelligence and automation will further enhance the efficiency and applicability of such tools, enabling engineers to optimize multiphase flow systems with greater precision.Multiphase flow plays a critical role in many engineering applications, particularly in the automotive and aviation sectors, where understanding and optimizing complex fluid interactions is essential. However, evaluating the results of multiphase flow simulations manually is a time-intensive process prone to errors, which can hinder efficiency and accuracy. This research aims these problems by developing an automated evaluation framework within the Ansys Fluent environment. By focusing on tasks such as oil surface coating and simulating various boundary conditions, the study establishes a robust methodology for universal multiphase flow evaluation. A custom script was created to standardize post-processing tasks, enabling the accurate assessment of simulation performance across different scenarios. The proposed solution reduces the reliance on manual evaluation, ensuring consistency and saving significant time. While the scripts limitations are explored, the methodology provides a foundation for integrating automation into CFD workflows. In the future, advancements in artificial intelligence and automation will further enhance the efficiency and applicability of such tools, enabling engineers to optimize multiphase flow systems with greater precision.