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Turbulence and Gust

NASAUnited StatesOn-siteInternshipListed 3 hours ago

DisciplineAEAerospace
TypeInternship
LocationUnited States
Work modelOn-site
DegreesBS · MS · PhD
Listed

About this role

The challenge of navigating Urban Air Mobility (UAM) vehicles through complex urban environments is expected to present significant difficulties for pilots. To verify the flight quality and handling capability of UAM aircraft, it is essential to evaluate their control responses within complex turbulent and high wind gust conditions. The current state of the art for the development of UAM vehicles from conceptual design stage to mature commercial application is time-consuming and expensive. As a first step in validating the flight-handling qualities of such a vehicle, mid-fidelity simulation tools can be leveraged to provide performance predictions, which can then be used as input for real-time simulation. In addition, to validate a mid-fidelity tool and its ability to capture the unsteady aerodynamic interaction between the vehicle and the flow environment, a reliable dataset is required.

Turbulence and Gust project aims to improve the NASA RotLED model, a Lattice Boltzmann Method (LBM) based simulation tool and capable of scaling to multiple GPUs, thus allowing for rapid predictions for rotorcraft prediction developed by Dr. Nicholas Peters, Aeromechanics Branch. RotLED made for investigate low-altitude turbulence and rotor-wake interactions for UAM vehicles in turbulent environments. This effort will generate a robust dataset across various environmental and atmospheric conditions, including but not limited to emergency response scenarios such as hurricanes and wildfires. This data will aid in understanding vehicle behavior and providing valuable insight into (1) pilot handling quality (2) passenger ride comfort (3) mission planning, as well as help to validate numerical models.

The overarching goal of this project is to use the dataset to validate numerical models, improve piloted flight dynamics simulations, and develop flight-test identification methods for UAM vehicles.

**Eligible Applicants:** All
**Academic Level:** Undergraduate Senior, Graduate Master's, Graduate Doctoral, Post Doctoral
**Activity Type:** In-person
**Citizenship:** US Citizen Only
**Type:** Internships