Desenvolvimento de um método para correção de curvas de desempenho em bombas centrífugas submersas operando com fluidos viscosos

Electrical Submersible Pump (ESP) is used as an artificial lift technique. However, pumping viscous oil is generally associated with low Reynolds number flows. This condition leads to a performance degradation respect to the performance expected from the regular operation with water that most of the centrifugal pumps are originally designed for. These issues are considered in this investigation through a numerical study of the flow in two different multistage, semi-axial type ESPs. This investigation is carried out numerically using a Computational Fluid Dynamics (CFD) package, where the transient RANS equations are solved numerically. The turbulence is modeled using the SST model. Head curves for several operating conditions are compared with manufacturer’s curves and experimental data for a three-stage ESP, showing good agreement for a wide range of fluid viscosities and rotational speeds. Dimensionless numbers (n, n, n e Re) are used to investigate performance degradation of the ESPs. In addition, flow phenomena through the impellers of the ESPs are investigated using flow field from numerical results. Results show that performance degradation is directly related to rotational Reynolds number, Re. In addition, it was verified that performance degradation occurs for constant normalized specific speedn, which shows that performance degradation occurs similarly for different centrifugal pumps. Moreover, experimental data and numerical results agreed with a correlation from literature between head and flow correction factors proposed by Stepanoff (1967). A definition of modified Reynolds number was proposed and relates the head correction factor to viscosity. A correlation between head correction factor and the modified Reynolds number was proposed, which agreed well with numerical and experimental data. Then, a method to predict performance degradation based on the previous correlations was proposed. This method was compared with others from literature. In general, results and conclusions from this work can also be useful to bring more information about the flow of highly viscous fluids in pumps, especially in semi-axial, multistage ESPs.

Implante neural controlado em malha fechada

One of the challenges to biomedical engineers proposed by researchers in neuroscience is brain machine interaction. The nervous system communicates by interpreting electrochemical signals, and implantable circuits make decisions in order to interact with the biological environment. It is well known that Parkinson’s disease is related to a deficit of dopamine (DA). Different methods has been employed to control dopamine concentration like magnetic or electrical stimulators or drugs. In this work was automatically controlled the neurotransmitter concentration since this is not currently employed. To do that, four systems were designed and developed: deep brain stimulation (DBS), transmagnetic stimulation (TMS), Infusion Pump Control (IPC) for drug delivery, and fast scan cyclic voltammetry (FSCV) (sensing circuits which detect varying concentrations of neurotransmitters like dopamine caused by these stimulations). Some softwares also were developed for data display and analysis in synchronously with current events in the experiments. This allowed the use of infusion pumps and their flexibility is such that DBS or TMS can be used in single mode and other stimulation techniques and combinations like lights, sounds, etc. The developed system allows to control automatically the concentration of DA. The resolution of the system is around 0.4 µmol/L with time correction of concentration adjustable between 1 and 90 seconds. The system allows controlling DA concentrations between 1 and 10 µmol/L, with an error about +/- 0.8 µmol/L. Although designed to control DA concentration, the system can be used to control, the concentration of other substances. It is proposed to continue the closed loop development with FSCV and DBS (or TMS, or infusion) using parkinsonian animals models.