CUDA Spotlight: Monica Syal
By Calisa Cole, posted Feb. 4, 2013
GPU-Accelerated Brownout Simulations
This week's Spotlight is on Monica Syal, an aerospace engineer at Sunnyvale, Calif.-based Advanced Rotorcraft Technology (ART).
Q & A with Monical Syal
NVIDIA: Monica, what is your role at Advanced Rotorcraft Technology (ART)?
This is a very interesting and challenging problem, and we are working on it in collaboration with the University of Maryland (UMD) at College Park. This project is being funded by the Air Force Office of Scientific Research (AFOSR) under a Multidisciplinary University Research Initiative (MURI) grant.
NVIDIA: Who are the end-users of your research?
NVIDIA: What is brownout and what is its significance?
These dust clouds develop because of the rotor downwash flow, which impinges upon the ground. The fluid dynamic effects produced there can mobilize and uplift a very large quantity of dust particles. The underlying physics is basically a dual-phase fluids problem, one fluid phase being the air and the other being the dust.
Helicopter landing in brownout conditions. Source: OADS
As a consequence of the formation of these dense dust clouds, the pilot may lose visibility of the takeoff or landing zones, and may also experience spurious sensory cues and, in some cases, spatial disorientation or even vertigo.
The onset of brownout conditions has led to many accidents with military helicopters when they are operating in desert environments. The uplifted dust can also cause abrasion of the rotor blades and to the compressor blades in the engine, resulting in costly maintenance issues. Therefore, the brownout problem is one of great significance in rotorcraft flight operations, and it is critical to explore ways to mitigate this very serious problem.
NVIDIA: What is your approach to tackling this problem?
The approach being used is to integrate the flight simulation methodology (FLIGHTLAB), which was developed at ART, with the comprehensive rotorcraft brownout simulation model that was developed at UMD. This is an extremely challenging project with ambitious goals because eventually we want to achieve high-fidelity brownout dust cloud simulations in real-time.
Simulation showing development of brownout dust cloud during an approach maneuver
This simulation capability will be used to understand the effects of different rotor design parameters (e.g., rotorcraft), soil parameters (e.g., particle size and mineralogy), and flight conditions (e.g., landing and takeoff maneuvers) on the development of the dust clouds. Different approaches will be explored to mitigate brownout conditions, e.g., by means of flight path management, or by modifying certain aspects of the rotor design, or even the flight control system.
The brownout flight simulation capability that we are developing can also be used to train pilots to recognize the onset of brownout conditions, and to develop piloting strategies that could be used to mitigate the effects of brownout and thus minimize the impact on flight operations.
NVIDIA: Why is it important to accelerate the simulations?
The fact that we want this methodology to be coupled to a flight simulation code (FLIGHTLAB) and used in a piloted simulator, requires the code to run in real-time, which is a great computational challenge. Therefore, it is important to accelerate the simulations as much as possible to achieve the needed fidelity.
An obvious way to achieve the needed computational accelerations by using parallel computing is to conduct the simulations using as many computing resources as possible. The number of cores used in a CPU is relatively few and the CPUs are optimized for serial processing.
On the other hand, a GPU consists of hundreds of cores, which can be used to parallelize the computationally intensive parts of the simulations. Therefore, we decided to use high-end Tesla GPUs to conduct these simulations. This has provided us with about two orders of magnitude speedup in the computational time compared to the serial execution of the code.
NVIDIA: What role does CUDA play in your work?
Regarding GPU programming, I was first introduced to it in a course offered by Dr. Ramani Duraiswami from the Computer Science department at UMD, whose team specializes in this area. We collaborated with his team, and one of his graduate students, Qi Hu, helped us to implement our methodology on GPUs. Our current goal at ART is to achieve such brownout simulations in real-time, and so we are integrating a multi-GPU system to achieve that goal.
This research will benefit the rotorcraft industry in several ways. Incorporating these simulations into flight simulators will be extremely helpful in training pilots to recognize the onset of brownout conditions and to learn the correct piloting tactics, techniques, and procedures to avoid the undesirable consequences of brownout.
Eventually, this research may also help improve the handling qualities of rotorcraft by incorporating certain design changes into the flight control system, such as helping to reduce the workload imposed on the pilot while landing or taking off in conditions where brownout may be unavoidable.
Overall, this research will help enhance flight safety and reduce the large number of brownout related accidents that occur in both military and civil rotorcraft flight operations.
Bio for Monica Syal
Monica Syal is an Aerospace Engineer at Advanced Rotorcraft Technology (ART), and is working on the development of a real-time rotorcraft brownout simulation facility for flight simulator applications. Monica completed her Ph.D. and M.S. from the University of Maryland College Park in 2012 and 2008, respectively.