Automated pipe design in 3D using a multi-objective toolchain for efficient decision-making

Abstract

Abstract Pipe design in 3D is typically characterized by competing objectives, since the different design objectives, such as the reduction of length, weight, number of bends, manufacturing cost, and overall angle sum, are examples for such competing design goals, where one goal is often at the expense of the other. The origin of these competing design goals lies in the highly coupled problems of finding a permissible and collision-free pipe path in a complex 3D geometry and the physical properties of the path found. Because of the complex physics and geometry, these couplings are highly non-linear and mostly accessible via simulation only. The underlying pipe design optimization problem can thus not be solved explicitly and is tackled instead with a multi-disciplinary search procedure. Since the trade-offs between different competing evaluation objectives are often not known in advance, an automated design space exploration can be performed to generate different pipe designs, leading to well-informed design decisions by human experts. Such a design space exploration is shown and discussed using the pipework in a mounting rack in an Airbus A320 main landing gear bay. A total of 144 valid designs are generated, out of which the best in each criteria and the pareto-optimal solutions are automatically selected. Compared to the manually created Airbus A320 series solution, up to $10.4\%$ of the pipe length or up to $16.9\%$ of the bends can be saved using the same fixings and connection points, demonstrating both the feasibility and the industrial applicability of the automated toolchain.