New AI method designs better cooling for jet engines at extreme temperatures
Researchers have developed an optimization technique that automatically designs internal cooling channels for high-temperature engines—potentially cutting design time and improving efficiency. The approach could accelerate development of more durable turbines for aerospace and power generation, where thermal performance directly impacts operational lifespan and fuel consumption.
Originaltitel: Flow–heat topology optimization of internally cooled high temperature applications using a voxelization approach for domain initialization
<p>A method is presented for obtaining topology optimized designs for internally cooled high temperature applications, using a flexible geometry description, by means of a voxelization methodology and a novel boundary detection algorithm. A conjugate heat transfer approach is taken; the physics is described by a Stokes-Brinkman model for the flow, weakly coupled with a convection-diffusion model for the heat transfer. A practically relevant optimization formulation, consisting of a maximum temperature objective with a mass flow constraint, is used, and applied to an industrial-relevant non-trivial geometry resembling a guide vane in a gas turbine. Temperatures and velocities from the optimized design are compared with the response from a Stokes flow model with body-fitted mesh and a high-fidelity Reynolds-averaged Navier-Stokes model. A comparison of the performance from a mixed and a penalty approach for solving the flow problem is included. The voxelization approach shows good promise for handling complex design domains.</p>