Saulo de Tarso Marques Bezerra

Dr. Saulo de Tarso Marques Bezerra

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Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 September 2020 in Water Resources Management
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Journal Article
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JAJosé Matheus Bezerra dos Santos Amorim
José Matheus Bezerra dos Santos Amorim
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
MSMaisa Mendonça Silva
Maisa Mendonça Silva
LSLyanne Cibely Oliveira de Sousa
Lyanne Cibely Oliveira de Sousa

25 May 2021 in Urban Water Journal
Verified
Journal Article
Closed access
JCJosé Almir Cirilo
José Almir Cirilo
ANAlfredo Ribeiro Neto
Alfredo Ribeiro Neto
NRNyadja Menezes Rodrigues Ramos
Nyadja Menezes Rodrigues Ramos
CFCarla Fernanda Fortunato
Carla Fernanda Fortunato
JSJúlia Daniele Silva de Souza
Júlia Daniele Silva de Souza
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
This paper develops a discharge allocation model for public water supply for a set of communities, considering available and planned reservoirs and interbasin transfer projects. Reservoir operation rules were defined for maximum water withdrawals in function of the storage volume over a period of 45 years, and then the discharges to be transported from the different sources to 18 locations were defined, minimizing the costs. Generalized Reduced Gradient and Particle Swarm Optimization algorithms were used in the optimization processes. The model was applied in the Agreste region of the state of Pernambuco, Brazilian semiarid. This region has the worst water balance in the entire country and three interbasin water transfer systems are under construction. Due to the interconnection among the systems, it will be possible to supply the communities from one or another source. The results showed that the optimized operation of the reservoirs can minimize water transfer and costs.

1 March 2023 in Water Supply
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Journal Article
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TETuane Batista Do Egito
Tuane Batista Do Egito
JAJosé Roberto Gonçalves de Azevedo
José Roberto Gonçalves de Azevedo
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
The high costs generated by water supply systems’ pumping stations has generated great concerns regarding concessionaire companies in the sector. Improvements to increase these systems’ efficiency and consequently reduce electricity costs have been the objective of several researchers and technicians responsible for the sector. Given the many elements that compose these systems, finding the best operational rules is frequently a complex activity. In this context, the present work includes an optimization model based on genetic algorithms that combine the efficient use of reservoirs with the best operational rule for activating pumping systems. The results indicate that with better use of the water storage infrastructure, it is possible to reduce costs for the electricity of the system as a whole.

26 September 2017 in Water Supply
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Journal Article
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EFEmânuel Guerra Barros Filho
Emânuel Guerra Barros Filho
LSLaís Régis Salvino
Laís Régis Salvino
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
MSMoisés Menezes Salvino
Moisés Menezes Salvino
HGHeber P. Gomes
Heber P. Gomes
The objective of this research study was the development of an intelligent system based on artificial neural networks for water distribution networks that operate with parallel pumps. The purpose of the system is to automate the process and to define the operating state of the electric motors (on, off or with partial rotation speed). The intelligent system developed is generic, which allows the application of its control structure in similar processes, and it was applied in an experimental setup that simulates a real water supply system. The performance of the network was tested experimentally under different operating conditions, including in the presence of disturbances. The settling time was, in all experiments, less than 30 seconds, the tests did not show overshoot and the maximum error was 2.9%. Results showed excellent performance in terms of pressure regulation, and it is hoped that the controller can be successfully implemented in real water distribution systems, in order to reduce water and electricity consumption, decrease maintenance costs and increase the reliability of operating procedures.

26 March 2015 in IEEE Latin America Transactions
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Journal Article
Closed access
MSMagno Jose Gomes Silva
Magno Jose Gomes Silva
CAClivaldo Silva Araujo
Clivaldo Silva Araujo
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
CSCicero Rocha Souto
Cicero Rocha Souto
SSSimplicio Arnaud Silva
Simplicio Arnaud Silva
HGHeber P. Gomes
Heber P. Gomes
This paper presents the project of an adaptive control system to modeling and controlling, in real time, a water distribution system. The controllers act in determining the turning speed of the motor/pump set and in the opening angle of control valves. An experimental workbench was set aiming at modeling and identifying parametrically a hydraulic network. The control system is a Generalized Minimum Variance self-tuning (GMV), whose parameters where real-time estimated by the recursive least squares (MQR) method according to the imposed inputs to the converter and the valves. The GMV aims at the pressure control in measuring points, which provided the reduction of energy and water in the workbench. Experimental results show the performance of adaptive control system and its ability to control the water distribution process.

4 January 2023 in Water
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Journal Article
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JSJúlia Daniele Souza
Júlia Daniele Souza
JCJosé Almir Cirilo
José Almir Cirilo
SBSaulo de Tarso Marques Bezerra
Saulo de Tarso Marques Bezerra
GOGabriel Araújo de Oliveira
Gabriel Araújo de Oliveira
GFGuilherme Duarte Freire
Guilherme Duarte Freire
JCJaime Joaquim da Silva Pereira Cabral
Jaime Joaquim da Silva Pereira Cabral
To alleviate the impacts of water shortages and ensure the effective allocation of water resources, the integration of multiple sources has been a viable but challenging alternative for water resource managers. A robust decision support system (DSS) reduces the complexity of decision making and allows the user to define operational strategies that reduce costs and address system limitations. Through the Particle Swarm Optimization (PSO) collective intelligence algorithm and the operational zoning of reservoirs, it was possible to identify the monthly flow allocation for the Agreste of Pernambuco in Brazil. The analysis of unit costs allowed us to conclude that high local energy tariffs guide the DSS in the exploration of water-transfer works between basins, such as the Agreste pipeline, which had full use of approximately 2 m3/s in the analyzed scenarios. The study also sought to investigate the influence of rainy and dry periods, with the higher flows into local reservoirs in rainy periods leading the system to operate at a cost 2.6% higher compared to the dry period. The use of DSS was able to provide support and parameters that facilitate decision making, ensuring that the system operates efficiently and sustainably.