Centrifugal compressor anti-surge control system modelling

<span>From the middle of XX century, natural gas is an important mineral, widely used in the energy sector. Transportation of natural gas is carried out via gas pipeline networks and compression stations. One of the key features which need to be implemented for any centrifugal gas compressor is a surge protection. This article describes the method and develops software application intended for simulation and study of surge protection system of a centrifugal compressor used in modern gas compression stations. Within the article research method, modelling environment’s block diagram, proposed algorithms and results are described. For surge cases control and prediction, Anti-surge control block implemented which based on practical experience and centrifugal compressor theory. To avoid complicated energy balancing differential equations the volumetric flow calculation algorithm proposed which is used in combination with Redlich-Kwong equation of state. Developed software’s adequacy test performed through modeling of one-stage gas compression scheme at rated speed with comparison of parameters with reference commercial software and verification of the anti-surge control system.</span>

A scenario study on the transition to a closed nuclear fuel cycle using the nuclear energy system modelling application package (NESAPP)

The paper presents the results of a case study on evaluating performance and sustainability metrics for Russian nuclear energy deployment scenarios with thermal and sodium-cooled fast reactors in a closed nuclear fuel cycle. Ten possible scenarios are considered which differ in the shares of thermal and sodium-cooled fast reactors, including options involving the use of mixed uranium-plutonium oxide fuel in thermal reactors. The evolution of the following performance and sustainability metrics is estimated for the period from 2020 to 2100 based on the considered assumptions: annual and cumulative uranium consumption, needs for uranium enrichment capacities, fuel fabrication and reprocessing capacities, spent fuel stocks, radioactive wastes, amounts of plutonium in the nuclear fuel cycle, amounts of accumulated depleted uranium, and the levelised electricity generation cost. The results show that the sustainability of the Russian nuclear energy system can be significantly enhanced through the intensive deployment of sodium-cooled fast reactors and the transition to a closed nuclear fuel cycle. The authors have highlighted some issues for further considerations, which will lead to more rigorous conclusions regarding the preferred options for the development of the national nuclear energy system.

Identification of crowd behaviour patterns using stability analysis

Crowd behaviour analysis and management have become a significant research problem for the last few years because of the substantial growth in the world population and their security requirements. There are numerous unsolved problems like crowd flow modelling and crowd behaviour detection, which are still open in this area, seeking great attention from the research community. Crowd flow modelling is one of such problems, and it is also an integral part of an intelligent surveillance system. Modelling of crowd flow has now become a vital concern in the development of intelligent surveillance systems. Real-time analysis of crowd behavior needs accurate models that represent crowded scenarios. An intelligent surveillance system supporting a good crowd flow model will help identify the risks in a wide range of emergencies and facilitate human safety. Mathematical models of crowd flow developed from real-time video sequences enable further analysis and decision making. A novel method identifying eight possible crowd flow behaviours commonly seen in the crowd video sequences is explained in this paper. The proposed method uses crowd flow localisation using the Gunnar-Farneback optical flow method. The Jacobian and Hessian matrix analysis along with corresponding eigenvalues helps to find stability points identifying the flow patterns. This work is carried out on 80 videos taken from UCF crowd and CUHK video datasets. Comparison with existing works from the literature proves our method yields better results.

Assessing the Asynchrony Event Based on the Ventilation Mode for Mechanically Ventilated Patients in ICU

Respiratory system modelling can assist clinicians in making clinical decisions during mechanical ventilation (MV) management in intensive care. However, there are some cases where the MV patients produce asynchronous breathing (asynchrony events) due to the spontaneous breathing (SB) effort even though they are fully sedated. Currently, most of the developed models are only suitable for fully sedated patients, which means they cannot be implemented for patients who produce asynchrony in their breathing. This leads to an incorrect measurement of the actual underlying mechanics in these patients. As a result, there is a need to develop a model that can detect asynchrony in real-time and at the bedside throughout the ventilated days. This paper demonstrates the asynchronous event detection of MV patients in the ICU of a hospital by applying a developed extended time-varying elastance model. Data from 10 mechanically ventilated respiratory failure patients admitted at the International Islamic University Malaysia (IIUM) Hospital were collected. The results showed that the model-based technique precisely detected asynchrony events (AEs) throughout the ventilation days. The patients showed an increase in AEs during the ventilation period within the same ventilation mode. SIMV mode produced much higher asynchrony compared to SPONT mode (p < 0.05). The link between AEs and the lung elastance (AUC Edrs) was also investigated. It was found that when the AEs increased, the AUC Edrs decreased and vice versa based on the results obtained in this research. The information of AEs and AUC Edrs provides the true underlying lung mechanics of the MV patients. Hence, this model-based method is capable of detecting the AEs in fully sedated MV patients and providing information that can potentially guide clinicians in selecting the optimal ventilation mode of MV, allowing for precise monitoring of respiratory mechanics in MV patients.

Least mean sixth control approach for three-phase three-wire grid-integrated PV system

<p><span lang="EN-US">This work proposes an adaptive filter based on a new least mean sixth control approach with incremental conductance method of MPP for 3-phase grid-incorporated photovoltaic (PV) system. The proposed system comprises a PV array, 3-phase DC to AC converter, maximum power point tracker (MPPT), three-phase electronic load, and a 3-phase grid. The combination of solar PV array and the voltage source converter (VSC) supplies power to the grid. The 3-phase inverter as a distribution static synchronous compensator (D-STATCOM) improves the quality of the system performance in case of zero solar irradiation. D-STATCOM also reduces total harmonic distortion (THD) in grid currents, improves power factor, and maintainsa constant voltage at the point of common coupling (PCC). The system modelling and simulation is achieved on MATLAB/Simulink. The proposed system performance has been found satisfactory and conform to IEEE-519 standards.</span></p>