Engineering is approximations of physics, and many physical systems break down into intractable math quickly. This is most true in places that care about dynamic (time-sensitive) systems, such as Computational Fluid Dynamics (CFD) or Kinematics. Modeling is done by doing discrete time steps and using previous time steps as approximations of derivatives for the differential equations that determine the system, which always loses some detail as you can never discretely calculate an infinitely small time step.
A simple example would be a double pendulum, where the fundamental equations are straightforward, but behaves chaotically. Most physical systems have this chaotic behavior at some level, just due to the complexity of the world.
The bottlenecks would be physics in this case!
Engineering is approximations of physics, and many physical systems break down into intractable math quickly. This is most true in places that care about dynamic (time-sensitive) systems, such as Computational Fluid Dynamics (CFD) or Kinematics. Modeling is done by doing discrete time steps and using previous time steps as approximations of derivatives for the differential equations that determine the system, which always loses some detail as you can never discretely calculate an infinitely small time step.
A simple example would be a double pendulum, where the fundamental equations are straightforward, but behaves chaotically. Most physical systems have this chaotic behavior at some level, just due to the complexity of the world.