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Shape optimization of a Roots blower rotor profile using CFD model with a coupled Adjoint-Sculpting method.

Number: 1120

Author(s) : BIKRAMADITYA N., RANE S., KOVACEVIC A.

Summary

A Roots Blower operates as a rotary positive displacement machine. Minimizing clearance gaps between the rotors and housing is crucial for enhancing volumetric efficiency. One of the options is optimizing the configurations of the leakage gap over the rotor tip. Utilizing prediction tools for this purpose is preferable to manual numerical simulations. Moreover, shape optimization tools are instrumental in identifying optimal design solutions. In this study, the combination of Fluent-Adjoint solver and RBF-morph technology, known as Adjoint-Sculpting, is employed to explore design conceptualization. Adjoint-Sculpting leverages Fluent-Adjoint's predictive capabilities to estimate the effects of shape changes based on observable targets, complemented by RBF fluid morphing to accommodate these changes without necessitating fluid volume remeshing. Notably, RBF morphing maintains the quality of the base volume mesh. To investigate optimization methods for positive displacement machines, a 2D simplified Roots blower is considered, with the Adjoint methodology compared against conventional CFD results. Subsequently, variations in observables and different rotor tip shapes and combinations are examined using RBF fluid morphing. The findings from this study demonstrate that utilizing Fluent-Adjoint and RBF morph enables more effective and efficient prediction of tip shapes compared to conventional methods. Additionally, the study highlights the limitations of shape optimization using moving wall boundary conditions. These insights hold significance for compressor technology, facilitating the implementation of rotor tip design changes and streamlining resource-intensive conventional CFD calculations.

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  • Original title: Shape optimization of a Roots blower rotor profile using CFD model with a coupled Adjoint-Sculpting method.
  • Record ID : 30033001
  • Languages: English
  • Subject: Technology
  • Source: 2024 Purdue Conferences. 27th International Compressor Engineering Conference at Purdue.
  • Publication date: 2024/07/18

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