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Improving the Calibration of Surface Time Domain Reflectometry Sensors for Moisture Evaluation of Building Materials Using the Analysis of Covariance Method

Futa Anna, Jastrzębska Magdalena, Paśnikowska-Łukaszuk Magdalena, Wośko Elżbieta, Suchorab Zbigniew

Advances in Science and Technology. Research Journal

2023

Vol. 17, no 5

328--336

The paper presents the models for moisture evaluation using a set of the reflectometric sensors in some types of building materials. The readouts reveal the relationship between the building material moisture, being assessed gravimetrically and the apparent permittivity values obtained by the TDR (Time Domain Reflectometry) method and surface sensors. Based on the readouts, equations describing this relationship were derived. These types of equations function as calibration equations and are used to calibrate the sensors. Most of the equations used to describe the examined relationships are linear regression. These equations very often refer to specific materials and cannot be applied to others that differ in density or chemical composition, which is the cause of many incorrect measurements. In this article, we propose the use of the analysis of covariance method (ANCOVA) for the analysis of reflectometric data. Using this method, it will be possible to determine the moisture content of materials, regardless of their type and construction of the sensor, which can significantly improve moisture measurements using the reflectometric method. For comparative aims data achieved in conducted research were analyzed using both traditional linear regression models and using the analysis of covariance method (ANCOVA). Both types of fitting models are discussed and their quality was compared in terms of accuracy expressed by the Residual Standard Error (RSE), the Root Mean Square Error (RMSE) and the determination coefficient (R2) values. The paper showed that the use of the ANCOVA method allows for improvement the fit of the model in terms of the determination coefficient by 0.0174. Moreover, the average RSE and RMSE value in the ANCOVA models are smaller about 1.24 vol.% and 1.25 vol.% than the ones in the regression model, respectively, which means that the models obtained using ANCOVA more accurately describe the examined relationship.

The Applications of Graph Algorithms to Modeling of Integrated Urban Water Management System

Łazuka Ewa, Futa Anna, Jastrzębska Magdalena, Łagód Grzegorz, Szeląg Bartosz, Fatone Francesco

Advances in Science and Technology. Research Journal

2022

Vol. 16, no 5

277--289

The application of methods using graphs to model a variety of engineering issues has been known for several decades, but the application of graph algorithms to model the urban water management issues is a completely new approach. The article reviews the scientific literature on integrated urban water management systems in terms of the use of graph theory algorithms in this topic. Such a review has not been done before and constitutes a completely novel study. Some of the algorithms presented are directly derived from graph theory, while others were developed from other sciences, including environmental engineering or genetics, to solve specific engineering problems. The paper presents a general scheme and a brief description of the most important components of an integrated urban water management system. The necessary concepts of graphs were defined, the origin and the principle of graph algorithms used in modeling water management issues (Loop-By-Loop Cutting Algorithm, Hanging Gardens Algorithm, Tree Growth Algorithm, Dijkstra’s Algorithm, Genetic Algorithm, and Bayesian Networks Algorithm) were described. Their use in modeling the issues in stormwater, sanitary sewage and water distribution system was described. A complete list of scientific literature in this field was provided.