Advances in Transitional Flow Modeling: Applications to Helicopter Rotors

ISBN-13: 9783319325750 / Angielski / Miękka / 2016 / 130 str.

Chunhua Sheng; Jingyu Wang

Opis

This book provides a comprehensive description of numerical methods and validation processes for predicting transitional flows based on the Langtry Menter local correlation-based transition model, integrated with both one-equation Spalart Allmaras (S A) and two-equation Shear Stress Transport (SST) turbulence models. A comparative study is presented to combine the respective merits of the two coupling methods in the context of predicting the boundary-layer transition phenomenon from fundamental benchmark flows to realistic helicopter rotors.The book will of interest to industrial practitioners working in aerodynamic design and the analysis of fixed-wing or rotary wing aircraft, while also offering advanced reading material for graduate students in the research areas of Computational Fluid Dynamics (CFD), turbulence modeling and related fields.
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Spis treści

Introduction.- Related Works.- Computational Fluid Dynamic Method.- Turbulence Modeling Method.- Validation of Transition Models.- Applications to Helicopter Rotors.- Recommendations.

O autorze

As an Associate Professor in the Department of Mechanical, Industrial, and Manufacturing Engineering at the University of Toledo, Dr. Chunhua Sheng has over twenty years of research experience in Computational Fluid Dynamics (CFD) in the areas of fixed-wing and rotary-wing aircraft, wind turbines, and jet propulsion systems. Over the last decade, he has received nearly three million dollars of research funding from various U.S. federal agencies and designated industries. His recent works included the Bell-Boeing quad tiltrotor aeroelastic study and Bell Helicopter M427, M429, and M525 series of civil helicopters. Currently he is working with U.S. aerospace industries to conduct computational design and optimization for Future Vertical Lift (FVL) rotorcraft.  He is also working on innovative design concepts for offshore wind turbines using computational simulations to support the project funded by the U.S. Department of Energy Wind Energy program