Bruno Furtado de Moura
@universidade federal de catalão
Universidade Federal de Catalão
Universidade Federal de Catalão/Professor
EDUCATION
Bruno de Moura received the B.Eng. and M.Sc. degrees in Mechanical Engineering from the Universidade Federal do Espírito Santo (UFES), Vitória, Espirito Santo, Brazil, in 2012 and 2014, respectively, and obtained the D.Sc. degree in Computational Methods in Mechanical Engineering from the same university in 2020. In the same year, joined the Universidade Federal de Catalão (UFCAT), Catalão, Goiás, Brazil, where is currently an Assistant Professor. His research interests include metrology applied to instrumentation development, with a focus on conductance sensors for multiphase processes, as well as data science, together with parameter and state variable estimation applied to thermal and fluid dynamics processes; energy management, with a focus on planning, inspection, monitoring, and modeling of energy and process efficiency in buildings.
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Electrical and Electronic Engineering, Energy
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Marciellyo Ribeiro de Oliveira, Eron Talisson Dias Lourett, Adriana Machado Malafaia da Mata, Marcio Ferreira Martins, Francisco Hernán Sepúlveda Palma, and Bruno Furtado de Moura
Elsevier BV
Adriana Machado Malafaia da Mata, Bruno Furtado de Moura, Marcio Ferreira Martins, Francisco Hernán Sepúlveda Palma, and Rogério Ramos
AIP Publishing
Electrical Resistance Tomography (ERT) has the potentialities of non-intrusive techniques and high temporal resolution which are essential characteristics for multiphase flow measurements. However, high background conductivities, such as saline water in oil extraction, impose a limitation in ERT image reconstruction. Focusing on the operational limits of an ERT tomography system operating in different conductivity backgrounds from 0.010 to 4.584 S/m, the impact on the image reconstruction was assessed via signal-to-noise variance. The signal-to-noise ratio (SNR) variance had a strong correlation ( p-value = 5.40 × 10−15) with the image reconstruction quality at the threshold of 30 dB, reaching a correlation value of r = −0.92 in the range of 0.010–0.246 S/m. Regarding the position error of the phantom, p-value = 1.30 × 10−5 and r = −0.66 were attained. The global results revealed that the correlation of the mean of the SNR ( p-value = 5 × 10−4 and r = 0.55) was kept unaltered through the whole conductivity range, showing that such a statistical index can induce bias in establishing the operational limits of the hardware.
Bruno F. de Moura, Adriana M. M. da Mata, Marcio F. Martins, Francisco H. S. Palma, and Rogério Ramos
Springer International Publishing
Adriana M. M. da Mata, Bruno F. de Moura, Marcio F. Martins, Francisco H. S. Palma, and Rogério Ramos
Springer International Publishing
Bruno Furtado De Moura, Adriana Machado Malafaia Da Mata, Marcio Ferreira Martins, Francisco Hernan Sepulveda Palma, and Rogerio Ramos
Institute of Electrical and Electronics Engineers (IEEE)
Electrical Impedance Tomography (EIT) is a technique that enables the reconstruction of the impedance distributions inside a vessel in a multiphase flow of industrial processes. Such a technique combines a data acquisition (DAQ) system to inject a current and to measure the voltages on the sensors and an inverse problem technique to reconstruct the image properly. This problem is highly ill-conditioned, causing errors to produce instabilities. Therefore, when performing the acquisition, the DAQ system must have adequate accuracy to allow the reconstruction of images with good quality. To avoid these measurement inaccuracies, this paper introduces a methodology that aid in the process of development of low-cost systems. It consists of investigating the errors in the current version of the system. Further, predicting the systematic errors of each subsystem by modeling its frequency response by Simulation Program with Integrated Circuit Emphasis (SPICE). From this information, it is possible to perform critical analysis, aiding design decisions.
B F de Moura, A M M da Mata, M F Martins, F H S Palma, and R Ramos
IOP Publishing
The film thickness of a two-phase flow is a parameter of interest since it is of importance to the heat and mass transfer phenomena. A novel method is proposed based on electrical impedance tomography (EIT) and conductance sensors to measure this quantity. An analytical equation is developed to relate the differential voltage associated with a current injection on the domain and the angular film thickness profile. A characteristic of the measuring procedure is that it presents a high sensitivity when the thickness is small, with the possibility of adjustment using different magnitudes of current. This model is compared experimentally and by the complete electrode model (CEM), solved by finite elements method (FEM). Results presented a good agreement with the FEM simulations, and the experimental results presented systematic error caused by the fringe effect.
Bruno Furtado de Moura, Marcio Ferreira Martins, Francisco Hernán Sepúlveda Palma, Wellington Betencurte da Silva, Jorge Acevedo Cabello, and Rogério Ramos
Elsevier BV
Adriana Machado Malafaia da Mata, Bruno Furtado de Moura, Marcio Ferreira Martins, Francisco Hernán Sepúlveda Palma, and Rogério Ramos
Elsevier BV
Adriana Machado Malafaia da Mata, Bruno Furtado de Moura, Marcio Ferreira Martins, Francisco Hernán Sepúlveda Palma, and Rogério Ramos
Elsevier BV
Bruno Furtado de Moura, Marcio Ferreira Martins, Francisco Hernan Sepulveda Palma, Wellington Betencurte da Silva, Jorge Acevedo Cabello, and Rogerio Ramos
Institute of Electrical and Electronics Engineers (IEEE)
Electrical Resistance Tomography (ERT) is a technique employed in the industrial environment that reconstructs images formed by the impedance distributions inside a vessel. The method relies on measures from a data acquisition system, responsible to inject a current inside the vessel and measures the voltage on the boundaries, and sequentially an inverse problem solution. This paper introduces a low-cost design of an acquisition system that can obtain 30 images/s with a signal-to-noise ratio of 57.47 dB and a maximum error of 3.79%. It utilizes a simple RMS-to-DC converter demodulation scheme to provide good accessibility to researchers aimed at investigating flow patterns of multiphase flow applications.
Bruno Furtado de Moura, Wellington Betencurte da Silva, Marcelo Camargo Severo de Macêdo, and Márcio Ferreira Martins
Informa UK Limited
Abstract Sequential Monte Carlo or Particle Filter Methods have been widely used to deal with sequential Bayesian inference problems in several fields of knowledge. This technique involves approximation of probability sequences distributions of interest, by means of a large set of random samples, i.e. particles that are propagated along time with a simple Sampling Importance distribution, SI. A re-sampling technique is also used to improve the predictive probability. In this study, a methodology is proposed: apply the Bayesian filters to a state estimation problem involving the corrosion amount-time in a contraction–expansion geometry with the aid of Computational Fluid Dynamics to improve the accuracy of the results. The following filters were applied and compared: Sampling Importance Re-sampling filter (SIR filter) and Auxiliary Sampling Importance Re-sampling filter (ASIR filter). The corrosion model adopted is based on a double resistance due to the oxygen diffusion towards the wall through the hydrodynamic boundary layer and the oxide layer. Mass loss data over time are obtained from the literature to compare corrosion rates. Also, the influence of the corrosion products in rates of corrosion is discussed . Best results in corrosion damage estimation were obtained using the ASIR filter.