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The emphasis in this paper is also on utilizing the experimental data for validating a model, previously developed by our group, for the study of such reactors.
The simulation model was first validated utilizing the experimental data and was then used to determine the optimal design parameters, viz. the inner, black absorber, and outer, transparent insulator, tube thicknesses.
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In addition, a concise strategy on how to process and utilize the experimental data in tandem with mathematical models is proposed.
The purpose of this article is to utilize the experimental data produced by the incorporation and implementation of the BSC in hospitals and to investigate the effects of the BSC red light tracking warning system on performance improvement.
Overall, in this work we present a methodology to utilize the experimental data to get a better insight of the dynamics of flow structures, and propose a path forward for the deeper understanding of transport phenomena in bubble columns.
We will utilize the experimental data from papers [1], [2] in order to calculate the quantities is, isk and iskm.
In order to test the sensitivity of MUSIC-OMAG to capillary hemodynamic variations, we utilized the experimental data set of UHS-OMAG, which were continuously acquired during active control of the body temperature of the animal, giving an opportunity to observe capillary flow response in the mouse ear pinna.
A control volume approach is utilized on the experimental data for the determination of the total stored/rejected energies.
Then, utilizing some of the experimental data for training, an ANFIS model for the system was developed.
A predictive model for laser turning process parameters is created using a feed-forward artificial neural network (ANN) technique utilized the experimental observation data based on response surface methodology (RS M.
Response surface methodology was used to optimize machining conditions utilizing the relevant experimental data as obtained through experimentation.
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