The design of an indirect method for the human presence monitoring in the intelligent building

This article describes the design and verification of the indirect method of predicting the course of CO2 concentration (ppm) from the measured temperature variables Tindoor (degrees C) and the relative humidity rH(indoor) (%) and the temperature T-outdoor (degrees C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the individual premises in the Intelligent Administrative Building (IAB) using the PI System SW Tool (PI-Plant Information enterprise information system). The CA (Correlation Analysis), the MSE (Root Mean Squared Error) and the DTW (Dynamic Time Warping) criteria were used to verify and classify the results obtained. Within the proposed method, the LMS adaptive filter algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, specifically from February 1 to February 28, 2015, from June 1 to June 28, 2015 and from February 8 to February 14, 2015. For the best results of the trained ANN BRM within the prediction of CO2, the correlation coefficient R for the proposed method was up to 92%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored IAB premises for monitoring. The designed indirect method of CO2 prediction has potential for reducing the investment and operating costs of the IAB in relation to the reduction of the number of implemented sensors in the IAB within the process of management of operational and technical functions in the IAB. The article also describes the design and implementation of the FEIVISUAL visualization application for mobile devices, which monitors the technological processes in the IAB. This application is optimized for Android devices and is platform independent. The application requires implementation of an application server that communicates with the data server and the application developed. The data of the application developed is obtained from the data storage of the PI System via a PI Web REST API (Application Programming Integration) client.Web of Science8art. no. 2

Wall effects on a single spherical particle moving through a Carreau model fluid

The steady slow motion of solid spheres through a Carreau model fluid contained in a cylindrical tube has been solved numerically using a finite element method by means of the COMSOL Multiphysics software package for steady non-Newtonian flows. From the resulting stress fields, the drag force on the sphere, drag coefficient, drag coefficient corrective factor, and wall correction factor have been evaluated in dependence on the Carreau model parameters and the sphere to tube diameter ratio. The results of the wall correction factor calculations are presented herein and compared with our new experimental data

Wall effects on a single spherical particle moving through a power-law fluid

The steady motion of solid spheres through a power-law fluid contained in a cylindrical tube has been solved numerically using a finite element method by means of the COMSOL software package for the steady non-Newtonian flows. From the resulting stress fields, the drag force on the sphere, drag coefficient, drag coefficient corrective factor, and wall correction factor have been evaluated in dependence on the fluid power law index and the sphere-to-tube diameter ratio. The results of numerical computation are in very good agreement with previous theoretical and experimental literature data, which documents suitability of the computational method used