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Coupling of Fluid Field and Electrostatic Field for Electrical Capacitance Tomography

机译:电容层析成像的流场和静电场耦合

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摘要

The performance of an electrical capacitance tomography (ECT) sensor is usually evaluated by static experiment with solid material(s) for some typical distributions encountered in two-phase flows. Considering the soft-field effect of an ECT sensor, the existing evaluation method is not appropriate for evaluating the performance of ECT for the real complex two-phase flows. In this paper, a new simulation model is proposed by coupling two physical fields: fluid field and electrostatic field, based on a mixture model and an electrostatic model. The mixture model is based on the diffusive flux model, which is suitable for liquid–solid mixtures with high concentration of solid particles. An ECT sensor with 12 electrodes is modeled based on an electrostatic model with a periodic excitation signal. The two models are coupled by an additional electric force in the momentum conservation equation in the mixture model. The time-varying permittivity distributions and capacitance data are obtained from the computational simulation based on the coupling model to investigate the performance of the ECT sensor and image reconstruction. Linear backprojection and Landweber iteration with different parameters are used to reconstruct images. Experiment was carried out using a rotation device with a 12-electrode ECT sensor to validate the simulation results. Both simulation and experimental results verify that the proposed coupling model is valid for evaluating the performance of ECT sensors and image reconstruction algorithms.
机译:电容层析成像(ECT)传感器的性能通常是通过使用固态材料进行静态实验来评估两相流中遇到的一些典型分布来评估的。考虑到ECT传感器的软场效应,现有的评估方法不适用于评估实际复相两相流中ECT的性能。本文基于混合模型和静电模型,通过耦合两个物理场:流体场和静电场,提出了一种新的仿真模型。混合物模型基于扩散通量模型,适用于具有高浓度固体颗粒的液固混合物。基于带有周期性激励信号的静电模型对具有12个电极的ECT传感器进行建模。在混合模型的动量守恒方程中,两个模型通过附加的电力耦合。基于耦合模型,通过计算仿真得到了时变介电常数分布和电容数据,以研究ECT传感器的性能和图像重建。使用不同参数的线性反投影和Landweber迭代来重建图像。使用带有12电极ECT传感器的旋转设备进行实验以验证仿真结果。仿真和实验结果均证明所提出的耦合模型对于评估ECT传感器和图像重建算法的性能是有效的。

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