A novel X-ray computed tomography method for fast measurement of multiphase flow

A new approach based on an improved genetic algorithm (GA) was proposed to implement the image reconstruction when using X-ray computed tomography (XCT) for the application of fast measurement of multiphase flow dynamics. Instead of directly using a traditional XCT, we pursued to develop a different discrete tomography (DT) method, aiming to achieve a high resolution in time during the measurements with only limited projection data. The proposed method assumed that the interested multiphase flow can be simplified as having distinct dense and dilute phases so that the local phase concentration can be binary-coded, e.g., 0 or 1 in a gas bubbling system. The mathematical problem under these circumstances is strongly ill-posed, and thus tackled with an optimization approach, i.e., a GA incorporated with the underlying physics as some constraints. The numerical simulations mimicking the physical measurements demonstrated the feasibility of the new approach, namely GA-XCT, especially with high robustness to the noise. Experiments were performed to simulate a transient measurement on the gas bubbles in water, with a portable X-ray tube and a 2D plane detector as the hardware and a static object rotating in between. The results further provided the validation of the GA-XCT being superior to the conventional algorithm, e.g., filtered back-projection (FBP) technique, in dealing with the tomography of multiphase system with binary local density field.