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Abstract

One of the parameters characterizing the quality of the gaseous fuel transported in gas pipeline network to consumers and being the basis for the classification of gaseous fuels is the heat of combustion. The main research hypothesis of this paper is the analysis of the possibility of using MLP 18-yi-1 neural network model to forecast the natural gas heat of combustion with a forecast error smaller than in case it calculates the heat of combustion based on the composition of natural gas predicted using the MLP 18-65-5 (Szoplik and Muchel, 2023). The training of the models was carried out on the basis of 8760 real data, presenting the hourly heat of natural gas combustion at one of the measurement points of this parameter in the pipeline network. The model takes into account the influence of calendar factors (month, day of the month, day of the week and hour of the day) and weather factors (ambient temperature) on the amount of heat of natural gas combustion in a given location of the gas network. Many MLP 18-yi-1 models were trained, differing in the number of neurons in the hidden layer and activation functions of neurons in the hidden and output layers.
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Authors and Affiliations

Jolanta Szoplik
1
ORCID: ORCID
Paulina Muchel
1

  1. West Pomeranian University of Technology in Szczecin, Faculty of Chemical Technologyand Engineering, Department of Chemical and Process Engineering, Piastów 42, 71-065Szczecin, Poland
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Abstract

Efficiency of agitation was considered for different physical systems on the basis of our own experimental studies on homogenisation, heat and mass transfer as well as gas hold-up. Measurements were performed for different physical systems: Newtonian liquids of low and higher viscosity, pseudoplastic liquid, gas–liquid and gas–solid–liquid systems agitated in vessels of the working volume from 0.02 m3 to 0.2 m3. Agitated vessels of different design were equipped with a high-speed impeller (10 impellers were tested). Comparative analysis of the experimental results proved that energy inputs (power consumption) should be taken into account as a very important factor when agitation efficiency is evaluated in order to select a proper type of equipment. When this factor is neglected in the analysis, intensification of the process can be estimated only.
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Authors and Affiliations

Joanna Karcz
1
Jolanta Szoplik
1
ORCID: ORCID
Marta Major-Godlewska
1
Magdalena Cudak
1
Anna Kiełbus-Rapała
1

  1. West Pomeranian University of Technology in Szczecin, Faculty of Chemical Technology and Engineering, al. Piastów 42, 71-065 Szczecin, Poland

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