THERMAL EXPANSION AND STRUCTURAL BEHAVIOR OF A CLOSED LOOP THERMAL WIND TUNNEL FOR ORC FLUIDS

asme-orc2015 Tracking Number 69

The Organic Rankine Cycle (ORC) offers great potential for recovering waste heat and using low–temperature sources for power generation. However, the ORC thermal efficiency is limited by the relatively low temperature level, and therefore, designing ORC components with high efficiencies and minimized losses is of major importance. The use of organic fluids creates new challenges for turbine and component design, due to dense gas behavior and the low speed of sound leading to high Mach numbers. Computational fluid dynamics (CFD) offers great potential for design and optimization of ORC components. But the employment of CFD methods requires careful validation by means of experimental data. For ORC components, such an experimental approach requires the use of specially designed wind tunnels for organic vapors. The closed wind tunnel, presented in this contribution, is designed as a pressure vessel system to allow for pressure levels up to p = 10 bars and temperatures up to θ = 180°C. The investigation of heavy weight organic fluid flows at superheated state also needs for higher temperature levels. Heating and cooling units are therefore used to achieve steady state conditions inside of the test section. In this poster contribution the design process of a closed cascade wind tunnel is presented, focusing on the thermal expansion of the system. Thermal finite element method (FEM) analysis is applied to calculate temperature distributions, considering thermal loads and heat losses of the facility. Based on these data, linear FEM analysis is used to investigate thermal stress in the closed loop vessel system. Supporting points and critical zones are assessed in a more detailed analysis. A method to analyse the structure’s transient behavior and to determine allowable heating rates during heat–up phase is presented. The testing facility is part of a large research project aiming at obtaining loss correlations for performance predictions of ORC turbines and processes, which is supported by the German Ministry for Education and Research (BMBF).