Big data and Python

conference paper

English

The end of the 20th and beginning of the 21st century are both characterized by rapid development in information technologies, that have also significant impact on mechanical engineering. There have been many advances in numerical simulations such as finite element method (FEM) and computational fluid dynamics (CFD). These methods allow more precise equipment analyses than traditional analytical and empirical approaches and therefore also better design. Main disadvantages of the numerical simulations are need for expensive software and hardware equipment and also for a qualified designer. There are many problems, that could be simulated using FEM or CFD, but it is not feasible. For such cases, it is possible to create a database of inputs and outputs of simulation for range of parameters. This approach was investigated for a particular case of assessment of cross flow induced vibrations of a tube bundle with final goal to improve tube fatigue prediction. Presented paper deals with issues of big data assessment, which is significant task in development of the new database-based assessment method. This may be done in professional software, but there are also freely available alternatives. One of them is Python programming language, that includes many libraries for data storage and processing and it will be used in work described in this paper.

python, big data, flow-induced vibration

BUZÍK, J.; LÉTAL, T.; LOŠÁK, P.

31. 8. 2016

9781510859623

22nd International Congress of Chemical and Process Engineering, CHISA 2016 and 19th Conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction, PRES 2016

Volume 2

1243

1246

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