Control of a Gas-Liquid Inline Swirl Separator Based on Tomographic Measurements

Garcia, Matheus; Sahovic, B.; Sattar, Muhammad Awais; Atmani, Hanane; Schleicher, Eckhard; Hampel, Uwe; Babout, Laurent; Legendre, Dominique; Portela, L.M.

doi:10.1016/j.ifacol.2020.12.588

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…Another option would be to include the wire-mesh measurement in a model predictive controller, which would use it to predict the gas core at the pickup tube and use the prediction to compute the control actions in the valve. The model linking the upstream conditions to the gas core can be either analytic, based on the conservation of mass (e.g., in Appendix B), based on the conservation of mass and momentum (e.g., in [53]), or based on empirical fits (e.g., the power law of Figure 18).…”

Section: Upstream Flow and Predictive Controllersmentioning

confidence: 99%

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

Garcia

Sattar

Atmani

et al. 2022

Sensors

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The performance of multiphase flow processes is often determined by the distribution of phases inside the equipment. However, controllers in the field are typically implemented based on flow variables, which are simpler to measure, but indirectly connected to performance (e.g., pressure). Tomography has been used in the study of the distribution of phases of multiphase flows for decades, but only recently, the temporal resolution of the technique was sufficient for real-time reconstructions of the flow. Due to the strong connection between the performance and distribution of phases, it is expected that the introduction of tomography to the real-time control of multiphase flows will lead to substantial improvements in the system performance in relation to the current controllers in the field. This paper uses a gas–liquid inline swirl separator to analyze the possibilities and limitations of tomography-based real-time control of multiphase flow processes. Experiments were performed in the separator using a wire-mesh sensor (WMS) and a high-speed camera to show that multiphase flows have two components in their dynamics: one intrinsic to its nonlinear physics, occurring independent of external process disturbances, and one due to process disturbances (e.g., changes in the flow rates of the installation). Moreover, it is shown that the intrinsic dynamics propagate from upstream to inside the separator and can be used in predictive and feedforward control strategies. In addition to the WMS experiments, a proportional–integral feedback controller based on electrical resistance tomography (ERT) was implemented in the separator, with successful results in relation to the control of the distribution of phases and impact on the performance of the process: the capture of gas was increased from 76% to 93% of the total gas with the tomography-based controller. The results obtained with the inline swirl separator are extended in the perspective of the tomography-based control of quasi-1D multiphase flows.

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Section: Upstream Flow and Predictive Controllersmentioning

confidence: 99%

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

Garcia

Sattar

Atmani

et al. 2022

Sensors

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“…Within the last two decades, numerous approaches Based on the flow properties upstream the separator, the light-phase core created by the static swirl element varies in size and eccentricity [8]. A potential approach to monitor the performance of inline swirl separators in real time is to measure the geometrical parameters (size and position) of the light-phase core created, which explains if most of the fluid is being captured or not when compared to the position and size of the pick-up tube [7].…”

Section: Introductionmentioning

confidence: 99%

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

Sattar

Garcia

Portela

et al. 2022

Sensors

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Electrical resistance tomography (ERT) has been used in the literature to monitor the gas–liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the relevant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10× less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000× faster than solving the inverse problem non-iteratively via the Gauss–Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 104 times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the average estimation error below 6 mm in the worst-case scenario.

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“…The lighter phase accumulates in the center of the pipeline, creating a continuous core that is extracted by a pick-up tube placed by the end of the equipment [6] as shown in Figure 1. [7] Based on the flow properties upstream the separator, the light-phase core created by the static swirl element varies in size and eccentricity [8]. A potential approach to monitor the performance of Inline Swirl Separators in real-time is to measure the geometrical parameters (size and position) of the light-phase core created, which tells if most of the fluid is being captured or not when compared to the position and size of the pick-up tube [7].…”

Section: Introductionmentioning

confidence: 99%

“…Figure1. Schematics of the Inline Swirl Separator with the sensor and pick-up tube considered in this research[7] …”

mentioning

confidence: 99%

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

Sattar¹,

Garcia²,

Portela³

et al. 2021

Preprint

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Electrical Resistance Tomography (ERT) has been used in the literature to monitor the gas-liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the rele-vant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10x less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000x faster than solving the inverse problem non-iteratively via the Gauss-Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 104 times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the aver-age estimation error below 6 mm in the worst case scenario.

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Control of a Gas-Liquid Inline Swirl Separator Based on Tomographic Measurements

Cited by 8 publications

References 9 publications

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

Towards Tomography-Based Real-Time Control of Multiphase Flows: A Proof of Concept in Inline Fluid Separation

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows

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