Electrical Capacitance Volume Tomography (ECVT) has emerged as an attractive technology for addressing instrumentation requirements in various energy-related multiphase flow systems. ECVT can monitor multiple flow conditions and reconstruct real-time 3D images from capacitance measurements using a large set of electrode plates placed around the processes column enclosing the sensed flow system. ECVT is non-intrusive and allows the measurement of changes in mutual capacitance between all possible plate pair combinations. The objective of this paper is to provide a comprehensive review of recent advances in ECVT, enabling robust monitoring of multiphase flows, especially water-containing multiphase flows.

Velocity profiling of a flow involves the task of determining the velocity vector at every point in a given flow volume. A new method is proposed for velocity profiling of multiphase flows based on electrical capacitance volume tomography (ECVT) sensors. The proposed method utilizes a mapping between the change in measured capacitances and the displacement of flow that is effected by the spatial gradient of the sensitivity distribution. This novel mapping not only avoids the need for costly image cross correlations but also is fully compatible with existing ECVT sensor and image reconstruction algorithms. Simulation and measurement results are provided to demonstrate the proposed method.

Displacement-current phase tomography (DCPT) is a process tomographic technique originally proposed to overcome the limitations of electrical capacitance tomography (ECT) for two-phase flows where one phase is electrically conductive, such as water. Both DCPT and ECT are two-dimensional crosssectional imaging techniques. In this paper, two new developments based on DCPT are described. First, we describe the extension of DCPT to perform direct volumetric imaging. Second, a new method for fluid flow velocimetry (three-dimensional velocity profiling) based on volumetric DCPT is proposed. Simulation and experimental results are provided to demonstrate the proposed techniques for imaging of water-dominated vertical flows.

Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive electrical capacitance volume tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imaging and an improved resolution. Construction of the sensitivity matrix is a necessary step to obtain flow images. This step requires the computation of the electric field inside the sensing domain, which is done via a typical field solver, such as the finite-element method. In this work, we present an efficient and flexible method to construct the sensitivity matrix for AECVT based on individual electrode segment excitations and their judicious combination to form desired matrix elements. We illustrate how the proposed method yields the same sensitivity matrix as the traditional method but at a much lower computational cost. Once all segment contributions are obtained, we also indicate how the proposed method, unlike the traditional approach, can generate the sensitivity matrix on demand for an arbitrary combination of synthetic electrodes and obviating the need for any additional field computations. Finally, we present image reconstruction results for two different experimental scenarios where the mutual capacitance data and the corresponding sensitivity vectors are obtained through the proposed measurement combination scheme.

Electrical Capacitance Volume Tomography (ECVT) has been applied for imaging of multiphase flows found in industrial applications. The ill-posed nature of the image reconstruction problem in ECVT and the consequent low resolution can be alleviated by employing electronic scanning enabled by electrode segmentation and reconfiguration during data acquisition. Here we study electronic scanning strategies that mimic physical rotation and shifting of the sensor along its symmetry axis. First, we study the feasibility of electronic scanning by analyzing the capacitance transducer circuit in SPICE. Then, we simulate electronic scanning using the finite element method for different electrode shapes, for which we compare the image reconstruction results and acquisition time. We find a noticeable improvement in image resolution for the scanning cases over conventional ECVT. Finally, among the scanning cases, we emphasize a particular electrode shape that provides the best image resolution along with the minimal amount of acquisition time.

Propellant mass gauging under micro-gravity conditions is a challenging task due to the unpredictable position and shape of the fuel body inside the tank. Micro-gravity conditions are common for orbiting satellites and rockets that operate on limited fuel supplies. Capacitance sensors have been investigated for this task in recent years; however, the effect of various positions and shapes of the fuel body is not analyzed in detail. In this paper, we investigate this with various fill types, such as annular, core-annular, and stratified fills at different positions. We compare the performance among several curve-fitting-based approaches and a machine-learning-based approach, the latter of which offers superior performance in estimating the fuel content.