Dataset Information

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors-AI Models and Their Validations.

ABSTRACT: In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid flow rate is difficult to measure due to the varying flow conditions (e.g., wavy, turbulent and irregular) and the presence of drilling cuttings and gas bubbles. Inclusion of a Venturi section in the open channel and an array of ultrasonic level sensors above it at locations in the vicinity of and above the Venturi constriction gives the varying levels of the drilling fluid in the channel. The time series of the levels from this array of ultrasonic level sensors are used to estimate the drilling fluid flow rate, which is compared with Coriolis meter measurements. Fuzzy logic, neural networks and support vector regression algorithms applied to the data from temporal and spatial ultrasonic level measurements of the drilling fluid in the open channel give estimates of its flow rate with sufficient reliability, repeatability and uncertainty, providing a novel soft sensing of an important process variable. Simulations, cross-validations and experimental results show that feedforward neural networks with the Bayesian regularization learning algorithm provide the best flow rate estimates. Finally, the benefits of using this soft sensing technique combined with Venturi constriction in open channels are discussed.

SUBMITTER: Chhantyal K

PROVIDER: S-EPMC5713661 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors-AI Models and Their Validations.

Chhantyal Khim K Viumdal Håkon H Mylvaganam Saba S

Sensors (Basel, Switzerland) 20171026 11

In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid flow rate is difficult to measure due to the varying flow conditions (e.g., wavy, turbulent and irregular) and the presence of drilling cuttings and gas bubbles. Inclusion of a Venturi section in the open channel and an array of ultrasonic level sensors above it at locations in the vicinity of and above th ...[more]

PMID: 29072595

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Project description:The analytical characterization of a novel ion source for mass spectrometry named array of micromachined ultrasonic electrosprays (AMUSE) is presented here. This is a fundamentally different type of ion generation device, consisting of three major components: (1) a piezoelectric transducer that creates ultrasonic waves at one of the resonant frequencies of the sample-filled device, (2) an array of pyramidally shaped nozzles micromachined on a silicon wafer, and (3) a spacer which prevents contact between the array and transducer ensuring the transfer of acoustic energy to the sample. A high-pressure gradient generated at the apexes of the nozzle pyramids forces the periodic ejection of multiple droplet streams from the device. With this device, the processes of droplet formation and droplet charging are separated; hence, the limitations of conventional electrospray-type ion sources, including the need for high charging potentials and the addition of organic solvent to decrease surface tension, can be avoided. In this work, a Venturi device is coupled with AMUSE in order to increase desolvation, droplet focusing, and signal stability. Results show that ionization of model peptides and small tuning molecules is possible with dc charging potentials of 100 Vdc or less. Ionization in rf-only mode (without dc biasing) was also possible. It was observed that, when combined with AMUSE, the Venturi device provides a 10-fold gain in signal-to-noise ratio for 90% aqueous sample solutions. Further reduction in the diameter of the orifices of the micromachined arrays led to an additional signal gain of at least 3 orders of magnitude, a 2-10-fold gain in the signal-to-noise ratio and an improvement in signal stability from 47% to 8.5% RSD. The effectiveness of this device for the soft ionization of model proteins in aqueous media, such as cytochrome c, was also examined, yielding spectra with an average charge state of 8.8 when analyzed with a 100 Vdc charging potential. Ionization of model proteins was also possible in rf-only mode.

Dataset Information

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors-AI Models and Their Validations.

Publications

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors-AI Models and Their Validations.

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