Spiral plate heat exchangers (SPHEs) are used in industrial applications due to their enhanced thermal performance and tolerance to a soiled stream. The coupling of several SPHEs in series might further improve performance in terms of the effectiveness parameter. In the present study, a compact connection of several SPHE modules is proposed and investigated. For this purpose, a numerical model for the prediction of the effectiveness parameter of a modular SPHE was developed. The model predicted a 2.9% increase in the maximal effectiveness for a two-module SPHE in comparison to a conventional single module SPHE. The temperature profiles of particular streams within the two-module SPHE were predicted. The improved thermal performance and compactness of the modular SPHE configuration observed is advantageous for space-constrained applications.

On the way to reducing emissions released into the atmosphere, there is an obstacle in the form of the emissions of solid pollutants produced by households, namely the burning of solid fuels in small heat sources. In this article, the authors deal with the development of a low-cost electrostatic precipitator, which would be able to significantly reduce the production of particulate matter. This is a tubular precipitator concept, which is enhanced by dividing the precipitation space into four chambers, each of which has an ionization electrode. With the investigated structural arrangement, it is possible to increase the size of the collection area without affecting the external dimensions of the separator. The essence of this article was to focus on the design of an ionization electrode, which, in addition to the function of a negative electrode, would also fulfill the function of a structural element of the proposed geometry. The work contains a technical design for the shape of the ionization electrode, which was subsequently examined using ANSYS Fluent software. The conditions under which a corona discharge will occur on the electrodes and how particulate matter is captured in the separation device were investigated with the help of simulations of the electric field intensity. According to the achieved simulation results, calculations were made for the theoretical efficiency of particle collection, which reached a value of approximately 78%.

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Gas hydrates are considered a global phenomenon that, as an unconventional fossil fuel, can be an alternative energy source for the future. Hydrates form spontaneously in permafrosts and marine sediments, where the conditions for their formation are naturally suitable - low temperature and high pressure. The energy of hydrates could replace or supplement the most commonly used fossil fuels today. Hydrates are also an advantageous solution to the problem of natural gas storage. The main part of the experimental equipment operated is a pump, which generates the pressure energy needed to form hydrates. The article deals with the assessment of the effectiveness of the current state and the estimation of losses in the pipelines of the facility.

Emissions, including CO2 emissions, are generated during the combustion process. Perfect combustion of biomass should not lead to the formation of CO, but all carbon should burn perfectly and change to CO2 by the oxidation process. Under real conditions, complete combustion never occurs and part of the carbon is not burned at all or only imperfectly to form CO. The aim of the work was to create a prediction model of machine learning, which allows to predict in advance the amount of CO2 generated during the combustion of wood pellets. This model uses machine learning regression methods. The most accurate model (Gaussian process) showed a root-mean-square error, RMSE = 0.55. The resulting mathematical model was subsequently verified on independent measurements, where the ability of the model to correctly predict the amount of CO2 generated in % was demonstrated. The average deviation of the measured and predicted amount of CO2 represented a difference of 0.53 %, which is 8.8 % of the total measured range (3.08 - 9.2). Such a model can be modified and used in the prediction of other combustion parameters.