On the Possibility of Universal Chemometric Calibration in X-ray Fluorescence Spectrometry: Case Study with Ore and Steel Samples

The accuracy of X-ray fluorescence spectrometry in quantitative element analysis depends on the particular sample composition (so-called matrix effects). Counteracting these effects requires a large number of calibration samples similar in composition to those under analysis. Application of the model constructed for a particular type of samples is not possible for the analysis of samples having a different matrix composition. A possible solution for this problem can be found in the construction of universal calibration models. We propose the development of these universal models using chemometric tools: influence coefficients—partial least squares regression (IC-PLS) and nonlinear kernel regularized least squares regression. We hypothesize that the application of these methods for constructing calibration models would allow embracing the samples of different types in the framework of a single model. We explored this approach for the case of two substantially different types of samples: ores and steels. The performance of these methods was compared with the fundamental parameters (FP) method, which takes into account matrix effects using theoretical equations and allows handling samples of different elemental composition. IC-PLS significantly outperforms traditional FP in terms of accuracy for predicting the content of Al (root mean squared error of prediction 0.96% vs. 3.87%) and Ti (0.05% vs. 0.09%) and yields comparable results for Si and Mn quantification in ores and steels

Research of Woody Biomass Drying Process in Pellet Production

This paper presents results of experimental research on wood chips and sawdust drying in a rotary dryer. Empirical models for the assessment of two dependent parameters of the drying process were created based on the results of experimental data. The mathematical description of the relationship between the independent variable – reduced sawdust moisture content – and dependent variable – specific fuel consumption – is represented by a linear equation

Empirical Model of Cost Reduction in Local DH Systems. Low Temperature Approach

Improving the efficiency of heating systems can give a tremendous contribution towards the EU energy efficiency target for 2030. Significant heat losses are one of the main disadvantages of the dominating high temperature district heating (DH). Even in summer, the high retention time of water in the network leads to thermal losses from domestic hot water reaching up to about 30 %. An empirical model based on experimental data of heat energy consumption in multi-apartment buildings is created for economical optimization of the operation of DH systems. A methodology has been developed that allows estimating the total energy cost savings (including losses) of buildings associated with the reduction of heat loss in the system, by reducing the supply flow temperature, and increasing electricity consumption by increasing the mass flow rate of water in the network