Riassunto analitico
This thesis presents a portion of the research conducted at NablaFlow regarding the implementation and validation of a Computational Fluid Dynamics (CFD) code called Aerocoud. The focus of this work is to develop an automated CFD simulation tool specifically for the automotive industry by adding all the features needed to capture accurately the flow around a vehicle. Then the optimized code will be used to conduct an aerodynamic analysis of the electric Italian hypercar, Fulminea, manufactured by Auto-mobile Estrema to assess the optimum configuration for the Nürburgring track.
The primary objective of this thesis is to establish an efficient and accurate CFD simulation framework for the automotive industry, using a cloud-based, generic CFD code that is suitable for various external flows and models. The thesis outlines the step-by-step process of implementing and validating Aero-coud, ensuring its reliability and precision in capturing complex aerodynamic phenomena. The valida-tion procedure involves benchmarking the code against experimental data and comparing the results with well-established CFD tools currently in use. Once the code is validated, it is utilized to conduct an aerodynamic optimization of the Fulminea electric car by iteratively modifying the vehicle's design pa-rameters. The ultimate goal is to enhance the overall performance of the Fulminea and achieve a new electric vehicle (EV) Nürburgring record. The optimization process primarily focuses on improving aer-odynamic efficiency, generating downforce, and achieving a favourable aerodynamic balance, consider-ing the unique requirements and limitations of the Fulminea.
The research primarily centres around leveraging the capabilities of Aerocoud to automate and stream-line the simulation process. By utilizing cloud computing resources, the code enables efficient parallel processing and scalability, resulting in fast turnaround times for large-scale simulations. This automat-ed approach minimizes human intervention, reduces computational costs, and allows for the evaluation of numerous design variations to achieve optimal aerodynamic performance.
In conclusion, this thesis presents the outcomes of the aerodynamic optimization efforts, demonstrating the effectiveness of the developed code and its impact on the performance of the Fulminea. The results highlight the significance of automated CFD simulations in the cloud for efficient and effective aerody-namic design, enabling rapid iteration and exploration of a wide design space, showcasing the potential of this approach to push the boundaries of electric vehicle performance and to set new records.
|
Abstract
This thesis presents a portion of the research conducted at NablaFlow regarding the implementation and validation of a Computational Fluid Dynamics (CFD) code called Aerocoud. The focus of this work is to develop an automated CFD simulation tool specifically for the automotive industry by adding all the features needed to capture accurately the flow around a vehicle. Then the optimized code will be used to conduct an aerodynamic analysis of the electric Italian hypercar, Fulminea, manufactured by Auto-mobile Estrema to assess the optimum configuration for the Nürburgring track.
The primary objective of this thesis is to establish an efficient and accurate CFD simulation framework for the automotive industry, using a cloud-based, generic CFD code that is suitable for various external flows and models. The thesis outlines the step-by-step process of implementing and validating Aero-coud, ensuring its reliability and precision in capturing complex aerodynamic phenomena. The valida-tion procedure involves benchmarking the code against experimental data and comparing the results with well-established CFD tools currently in use. Once the code is validated, it is utilized to conduct an aerodynamic optimization of the Fulminea electric car by iteratively modifying the vehicle's design pa-rameters. The ultimate goal is to enhance the overall performance of the Fulminea and achieve a new electric vehicle (EV) Nürburgring record. The optimization process primarily focuses on improving aer-odynamic efficiency, generating downforce, and achieving a favourable aerodynamic balance, consider-ing the unique requirements and limitations of the Fulminea.
The research primarily centres around leveraging the capabilities of Aerocoud to automate and stream-line the simulation process. By utilizing cloud computing resources, the code enables efficient parallel processing and scalability, resulting in fast turnaround times for large-scale simulations. This automat-ed approach minimizes human intervention, reduces computational costs, and allows for the evaluation of numerous design variations to achieve optimal aerodynamic performance.
In conclusion, this thesis presents the outcomes of the aerodynamic optimization efforts, demonstrating the effectiveness of the developed code and its impact on the performance of the Fulminea. The results highlight the significance of automated CFD simulations in the cloud for efficient and effective aerody-namic design, enabling rapid iteration and exploration of a wide design space, showcasing the potential of this approach to push the boundaries of electric vehicle performance and to set new records.
|
