Discrete Approaches for Optimal Routing of High Pressure Pipes
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Beschreibung
This thesis lays a first foundation of an algorithmic engineering aid to help routing a high pressure pipe in a power plant.
The planning of a whole power plant involves diversified specializations in engineering and can take up to several years. Within the planning procedure the routing of the high pressure pipes transporting the hot steam from the main boiler to the steam turbines exerts a strong influence on efficiency of the power plant.
The design of pipe routing is usually done by a specially trained and experienced engineer with the aid of CAE software. The starting point of the problem is given by a rough outline of the design space and specified points where steam is produced and expended. In addition to the routing, the placement of hangers has to be specified to hold the pipe in place and meet technical restrictions. Even with the help of engineering software the planning procedure often involves trial and error, which makes the design phase cumbersome - especially if unforeseen obstacles have to be incorporated in a late stage of the project. This thesis lays a first foundation of an algorithmic engineering aid to help speed up the routing of the pipe and suggest a placing for the hangers.
After deriving a mixed-integer nonlinear model that captures all the problem's combinatorial and nonlinear aspects different approaches to tackle real-world instances are investigated. These include linear and convex reformulations, as well as a decomposition approach which is further improved by cutting planes. Moreover, hardness results are proven and real-world instances show the effectiveness of the different models and algorithms.
Autor*in
Jakob Schelbert
Short Academic CV:
2005-2010: Studies of Mathematics at the Technical University of Darmstadt, Germany.
2015: Ph.D. in Applied Mathematics (Discrete Optimization) at the University of Erlangen-Nürnberg, Germany.
Themen in »Discrete Approaches for Optimal Routing of High Pressure Pipes«
mixed integer programming combinatorial optimization programming involving graphs or networks convex programming nonconvex programming global optimization applications of mathematical programming Timoshenko beam Steiner tree