Classification of experimental data and evaluation with empirical correlations and ANN

Institut

Lehrstuhl für Energiesysteme

Typ

Semesterarbeit /

Inhalt

 

Beschreibung

A good knowledge of the heat transfer coefficient is of the utmost importance to ensure safe and efficient operation of modern steam generators whenever convection is involved in the heat transfer process. In the near-critical pressure range, experimental data are essential for the development of prediction methods. Currently, several experiments are conducted at the high pressure test section at the Chair of Energy systems. In the first step, a database is to be created for this data as part of this thesis. In this context, a classification of the experimental data regarding heat transfer phenomena is to be implemented. In the second step, a literature research is to be carried out with regard to empirical correlations and ANN for the prediction of heat transfer phenomena. These methods are then to be applied to the previously created database and thus evaluated.

 

Work packages:

• Familiarizing with the topic and literature research.
• Development of a database based on existing measurement data.
• Adaptation of an existing evaluation tool to classify the experimental data.
• Evaluation of experimental data with empirical correlations and ANN.
• Highlighting optimization potential.

Voraussetzungen

• Autonomous work.
• Good knowledge in MATLAB.
• Knowledge in thermodynamics.

Möglicher Beginn

sofort

Kontakt

Jan Oettig, M.Sc.
Raum: MW 3708
Tel.: 089 289 15758
jan.oettigtum.de

Ausschreibung