Pressure loss coefficients for T-pieces at low Reynolds numbers, based on a Neural Network model and experimental data

Philip Ohnewein, AEE INTEC

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Software . 2017

License: CC BY SA

Data sources: Datacite

ZENODO

Software . 2017

License: CC BY SA

Data sources: ZENODO

Pressure loss coefficients for T-pieces at low Reynolds numbers, based on a Neural Network model and experimental data

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 31 Jan 2017Publisher:Zenodo

Authors: Philip Ohnewein, AEE INTEC;

doi: 10.5281/zenodo.383647

Pressure loss coefficients for T-pieces at low Reynolds numbers, based on a Neural Network model and experimental data

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Abstract

For a project description of ParaSol, see http://www.aee-intec.at/index.php?seitenName=projekteDetail&projekteId=207&lang=en The results provided here were developed in an R&D project supported by the Austrian Climate and Energy Fund and carried out as part of the "Energy of the Future" program under contract number FFG 829854. For more information, see https://www.klimafonds.gv.at/foerderungen/gefoerderte-projekte/detail/?plistcall=1&pid=46200

This Matlab toolbox contains 4 Matlab functions that serve to calculate pressure loss coefficients (zeta values) for 4 different cases of T-pieces (one function for each case). The pressure loss coefficients are relevant for T-pieces (junctions) of round pipes, and are especially interesting for low Reynolds numbers where hardly any reliable information can be found in literature (as of 2015).

Keywords

solar thermal, thermal modeling, energy conversion, hydraulics, pressure loss, pressure loss coefficients, minor pressure loss, collector array, hydraulic modeling, solar collector

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