Improved Wall Temperature Prediction for the LUMEN Rocket Combustion Chamber with Neural Networks

Aerospace, vol. 10, pp. 450

Abstract

Accurate calculations of the heat transfer and the resulting maximum wall temperature are essential for the optimal design of reliable and efficient regenerative cooling systems. However, predicting the heat transfer of supercritical methane flowing in cooling channels of a regeneratively cooled rocket combustor presents a significant challenge. High-fidelity CFD calculations provide sufficient accuracy but are computationally too expensive to be used within elaborate design optimization routines. In a previous work it has been shown that a surrogate model based on neural networks is able to predict the maximum wall temperature along straight cooling channels with convincing precision when trained with data from CFD simulations for simple cooling channel segments. In this paper, the methodology is extended to cooling channels with curvature. The predictions of the extended model are tested against CFD simulations with different boundary conditions for the representative LUMEN combustor contour with varying geometries and heat flux densities. The high accuracy of the extended model’s predictions, suggests that it will be a valuable tool for designing and analyzing regenerative cooling systems with greater efficiency and effectiveness.

Authors 4

1. Kai Dresia corresponding

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   Institute of Space Propulsion, German Aerospace Center (DLR), 74239 Lampoldshausen, Germany

2. Eldin Kurudzija

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   Institute of Space Propulsion, German Aerospace Center (DLR), 74239 Lampoldshausen, Germany

3. Jan C. Deeken Aachen Institute of Jet Propulsion and Turbomachinery

   RWTH Aachen University · Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   Institute of Jet Propulsion and Turbomachinery, RWTH Aachen University, 52062 Aachen, Germany

   Institute of Space Propulsion, German Aerospace Center (DLR), 74239 Lampoldshausen, Germany

4. Günther Waxenegger-Wilfing

   University of Würzburg · Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   Institute of Computer Science, University of Würzburg, 97070 Würzburg, Germany

   Institute of Space Propulsion, German Aerospace Center (DLR), 74239 Lampoldshausen, Germany