In this work a new image reconstruction technique for imaging two- and three-phase flows using electrical capacitance tomography (ECT) has been developed. A brief review on reconstruction techniques developed recently for ECT is also given. The reconstruction technique proposed here is based on multi-criterion optimization using an analogue neural network, hereafter referred to as neural network multi-criteria optimization image reconstruction (NN-MOIRT). The reconstruction technique is a combination between a multi-criterion optimization image reconstruction technique for linear tomography, and the so-called linear back projection (LBP) technique commonly used for capacitance tomography. The multi-criterion optimization image reconstruction problem is solved using Hopfield model dynamic neural network computing. For three-component imaging, the single-step sigmoid function in the Hopfield networks is replaced by a double-step sigmoid function, allowing the neural computation to converge to three distinct stable regions in the output space corresponding to the three components, enabling differentiation among the single phases. The technique has been tested on a capacitance data set obtained from simulated measurement as well as experiment using a 12-electrode sensor. The performance of the technique has been compared with other commonly used iterative techniques, i.e. iterative linear back projection technique (ILBP) and the simultaneous image reconstruction technique (SIRT) for two-phase system imaging, and has shown great improvements in the accuracy and the consistency as compared with those techniques. The technique has also shown the capability of three-phase image reconstruction with high accuracy.

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The objectives set for this cooperative project between Washington University (WU), Ohio State University (OSU), and Air Products and Chemicals, Inc. (APCI) to advance the understanding of the Fischer-Tropsch (FT) slurry bubble column reactor hydrodynamics for proper design and scale-up via advanced diagnostic techniques have been accomplished successfully despite the unexpected challenging technical difficulties in implementing the advanced techniques in high pressure stainless steel slurry bubble column.In this work, a detailed review of the aspects of high pressure phenomena of bubbles in liquids and liquid-solids suspension was performed. All the challenging technical problems mentioned above were resolved and the advanced measurement techniques were successfully used in this project. The effects of reactor pressure, superficial gas velocity, solids loading, and liquid physical properties on the overall gas holdup, holdups distribution, recirculation velocity, turbulent parameters, bubble dynamics (size and rise velocity) were investigated via advanced measurement techniques that includes optical probe, Laser Doppler Anemometry (LDA), Computed Tomography (CT), Computer Automated Radioactive Particle Tracking (CARPT). The findings are discussed and analyzed in this report. In attempt to advance the design and scale-up of bubble columns, new correlations have been developed based on a large bank of data collected at a wide range of operating and design conditions. These correlations are for prediction of radial gas holdup profile, axial liquid velocity profile, overall gas holdup based on Neural Network and gas-liquid mass transfer coefficient.Despite the noticeable advances made on FT SBCR as a part of this project, there are still many parameters and challenging issues that need to be further and properly investigated and understood before this technology will be readily used for alternative fuel development technology. iv ADVANCED DIAGNOSTIC TECHNIQUES FOR THREE-PHASE SLURRY BUBBLE COLUMN REACTORS (SBCR)Final Technical Report DE-FG-26-99FT40594 Bubble column reactor of 6" without ports used for CARPT/CT measurements. CT1, CT2, CT3 represents the scan levels used in this investigation 30 Figure 3. 4 Bubble column reactor of 6" with ports used for overall gas holdup and DP measurements. CT1, CT2, CT3 represents the scan levels used in this investigation. 31 Effect of superficial gas velocity on gas holdup profile (airwater-glass beads 150 (µm) in 6" column with 9.1 % vol. solids loading at 0.1 MPa 50 Figure 4.10 Effect of superficial gas velocity on solids axial velocity profile (air-water-glass beads 150 µm) in 6" column with 9.1 % vol. solids loading at 0.1 MPa 50 Figure 4.11 Effect of superficial gas velocity on solids shear stress profile (air-water-glass beads 150 µm) in 6" column with 9.1 % vol. solids loading at 0.1 MPa 50 Figure 4.12 Effect of superficial gas velocity on TKE (air-water-glass beads 150 µm) in 6" column with 9.1 % vol. solids loading at 0.1 MPa 51 Figure 4.13 Effect of superf...

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