Towards the validation of a CFD solver for non-ideal compressible flows

AJ Head, S Iyer, C De Servi, M Pini - Energy Procedia, 2017 - Elsevier
Energy Procedia, 2017Elsevier
Mini ORC power systems with the capability to deliver 3-50 kWe are receiving increased
recognition for applications such as heat recovery from automotive engines, or distributed
power generation from geothermal reservoirs and solar irradiation. Efficient and reliable
expanders are the enabling components of such power systems, and all the related
developments are currently at the research stage [1]. In the open literature experimental gas
dynamic data is limited concerning the fluids and the flow conditions of interest for ORC …
Abstract
Mini ORC power systems with the capability to deliver 3-50 kWe are receiving increased recognition for applications such as heat recovery from automotive engines, or distributed power generation from geothermal reservoirs and solar irradiation. Efficient and reliable expanders are the enabling components of such power systems, and all the related developments are currently at the research stage [1]. In the open literature experimental gas dynamic data is limited concerning the fluids and the flow conditions of interest for ORC expanders [2]. Therefore, CFD tools used for the fluid dynamic design of these components cannot be validated against reliable test cases. To bridge this gap, new experimental facilities are currently being built, such as the ORCHID setup [3]. The availability of proper experimental datasets is not, however, the sole requirement for validating a CFD code. Another precondition, equivalently important, is to define an appropriate validation methodology. This paper introduces the first steps towards the validation of a CFD solver for non-ideal compressible flows. Notably, a numerical procedure based on uncertainty quantification analysis has been conceived to assess the accuracy of the thermophysical sub-model of the code, i.e. the equation of state (EoS). Due to the lack of suitable experimental data, a synthetic dataset is generated and used to investigate the validity of the procedure. The associated validation exercise confirms the applicability of the proposed procedure, but also points out that the adopted validation metrics should be complemented with additional statistical indicators.
Elsevier
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