Date of Award
Spring 2013
Access Type
Thesis - ERAU Login Required
Degree Name
Master of Science in Mechanical Engineering
Department
Mechanical Engineering
Committee Chair
Sathya Gangadharan
First Committee Member
James Sudermann
Second Committee Member
Brandon Marsell
Abstract
The use of computational fluid dynamics has risen in the past decade. With major advances in high performance computing, the ability to solve complex flow fields has become much easier. Computational fluid dynamics is now used in many industries including: aerospace, automotive, chemical, medical, and various others. Experimental testing can be very expensive and the ability to predict flow phenomenon for components and systems is essential to the design process. Various computer aided engineering techniques such as finite element analysis and computational fluid dynamics allow engineers to find potential pitfalls in the design and make quicker changes. Because it is important to conduct both simulations and experimental testing, the ability to predict potential problems, allows for more effective testing scenarios. Ultimately, the ability to respond quickly to changes reduces time. Therefore, it is important to implement an optimized method to reduce time and cost. This research will illustrate the basics of product development along with the role of computational fluid dynamics in the process. This research will illustrate the use of computational fluid dynamics in predicting the steady-state pressure coefficient of a launch vehicle under transonic conditions. The results from the computational fluid dynamics simulations are then compared to experimental data from NASA Technical Memorandum X-778. The results indicate a process to implement computational fluid dynamics and obtain results that match experimental data within a reasonable margin.
Scholarly Commons Citation
Desai, Miraj Mukesh, "Effective CFD Integration into Product Development and Validation of Wind Tunnel Data for Transonic Launch Vehicle" (2013). Doctoral Dissertations and Master's Theses. 44.
https://commons.erau.edu/edt/44