ECVT imaging of 3D spiral bubble plume structures in gas-liquid bubble columns

Real-Time Monitoring of Powder Mass Flowrates for Plant-Wide Control of a Continuous Direct Compaction Tablet Manufacturing Process

While measurement and monitoring of powder/particulate mass flow rate are not essential to the execution of traditional batch pharmaceutical tablet manufacturing, in continuous operation, it is an important additional critical process parameter. It has a key role both in establishing that the process is in a state of control, and as a controlled variable in process control system design. In current continuous tableting line operations, the pharmaceutical community relies on loss-in-weight feeders to monitor and understand upstream powder flow dynamics. However, due to the absence of established sensing technologies for measuring particulate flow rates, the downstream flow of the feeders is monitored and controlled using various indirect strategies. For example, the hopper level of the tablet press is maintained as a controlled process output by adjusting the turret speed of the tablet press, which indirectly controlling the flow rate. This gap in monitoring and control of the critical process flow motivates our investigation of a novel PAT tool, a capacitance-based sensor (ECVT), and its effective integration into the plant-wide control of a direct compaction process. First, the results of stand-alone experimental studies are reported, which confirm that the ECVT sensor can provide real-time measurements of mass flow rate with measurement error within -1.8 ~ 3.3% and with RMSE of 0.1 kg/h over the range of flow rates from 2 to 10 kg/h. The key caveat is that the powder flowability has to be good enough to avoid powder fouling on the transfer line walls. Next, simulation case studies are carried out using a dynamic flowsheet model of a continuous direct compression line implemented in Matlab/Simulink to demonstrate the potential structural and performance advantages in plant-wide process control enabled by mass flow sensing. Finally, experimental studies are performed on a direct compaction pilot plant in which the ECVT sensor is located at the exit of the blender, to confirm that the powder flow can be monitored instantaneously and controlled effectively at the specified setpoint within a plant-wide feedback controller system.

Electrical Capacitance Volume Tomography (ECVT) for Characterization of Additively Manufactured Lattice Structures (AMLS) in Gas-Liquid Systems

Against the background of current and future global challenges, such as climate change, process engineering requires increasingly specific solutions adapted to the respective problem or application, especially in gas–liquid contact apparatuses. One possibility to adjust the conditions in this kind of apparatuses is an intelligent and customized structuring, which leads to consistent fluid properties and flow characteristics within the reactor. In the course of this, the interfacial area for mass transfer, as well as residence times, have to be adjusted and optimized specifically for the respective application. In order to better understand and advance the research on intelligent customized additively manufactured lattice structures (AMLS), the phase distributions and local gas holdups that are essential for mass transfer are investigated for different structures and flow conditions. For the first time a tomographic measurement technique is used, the Electrical Capacitance Volume Tomography (ECVT), and validated with the volume expansion method and a fiber optical needle probe (A2PS-B-POP) for an air-water system for different modes of operation (with or without co-current liquid flow in empty or packed state). The ECVT proved to be particularly useful for both in the empty tube and the packed state and provided new insights into the phase distributions occurring within structured packings, which would have led to significantly underestimated results based on the visual reference measurements, especially for a densely packed additively manufactured lattice structure (5 mm cubic on the tip). Particularly for the modified structures, which were supposed to show local targeted differences, the ECVT was able to resolve the changes locally. The additional use of a pump for co-current flow operation resulted in slightly higher fluctuations within the ECVT data, although local events could still be resolved sufficiently. The final comparison of the empty tube at rest data with a fiber optical needle probe showed that the results were in good agreement and that the local deviations were due to general differences in the respective measurement techniques.

Machine learning holography for 3D particle field imaging

We propose a new learning-based approach for 3D particle field imaging using holography. Our approach uses a U-net architecture incorporating residual connections, Swish activation, hologram preprocessing, and transfer learning to cope with challenges arising in particle holograms where accurate measurement of individual particles is crucial. Assessments on both synthetic and experimental holograms demonstrate a significant improvement in particle extraction rate, localization accuracy and speed compared to prior methods over a wide range of particle concentrations, including highly dense concentrations where other methods are unsuitable. Our approach can be potentially extended to other types of computational imaging tasks with similar features.