We present a simulation study of a single-wire, modular and robust ionisation gas drift chamber designed for muon imaging applications. It offers an active area of 250 mm & times; 250 mm with an interaction layer height of 10 mm. As a result, multiple drift chambers can be stacked very close to each other in order to assemble smart hodoscopes measuring muon tracks. Simultaneously, its high detection efficiency optimises measurement times, given the low flux of cosmic muons, and allows for simple signal electronics. The design optimisation is performed using COMSOL and Garfield++ simulation tools, which provide static electrical field studies and electron drift analysis, respectively. The chamber design has also been optimised with respect to economic aspects, i.e. all required components are commercially available. Finally, an asymmetric, i.e. single-ended, drift chamber design is found that provides moderate dead zones at its edges and is suitable for mass production.

The Gas Flow Modulation technique (GFM) is a recently introduced approach for measuring axial gas dispersion coefficients in bubble columns. This technique overcomes the limitations of the traditional tracer-based approaches, enabling axially resolved measurements. The present work evaluates the effects of column diameter, gas sparger design and gas superficial velocity on the axial gas dispersion coefficient. Applying GFM, this parameter is evaluated compartment-wise along the axial position in the column. The results highlight a strong influence of the gas sparger design and formed gas bubbles on the dispersion phenomena. In addition, the axial gas dispersion coefficient was found to change significantly along the column axial direction. This study highlights the potential role of GFM for developing reliable dispersion correlations and advanced reactor models in the future.

Ultrafast electron beam X-ray computed tomography (UFXCT) is a fast tomographic imaging technique used, e.g., for investigations of highly dynamic multiphase flows. In the last years, UFXCT was enhanced with the capability of real-time image acquisition and reconstruction. Using those capabilities, a new feedback-loop to a positioning unit was realized which allows for real-time repositioning of the scanner based on the images contents. By traversing the scanner, and hence its imaging planes, vertically, an object moving up- and/or downwards in the imaging region can be tracked and visualized. Using a phantom object moving with predetermined trajectories, the tracking latency, trackable object velocities and positioning accuracy was evaluated. Further, a latency compensation approach was developed that enhances the tracking performance.

Engineers, geomorphologists, and ecologists acknowledge the need for temporally and spatially resolved measurements of sediment clogging (also known as colmation) in permeable gravel-bed rivers due to its adverse impacts on water and habitat quality. In this paper, we present a novel method for non-destructive, real-time measurements of pore-scale sediment deposition and monitoring of clogging by using wire-mesh sensors (WMSs) embedded in spheres, forming a smart gravel bed (GravelSens). The measuring principle is based on one-by-one voltage excitation of transmitter electrodes, followed by simultaneous measurements of the resulting current by receiver electrodes at each crossing measuring pores. The currents are then linked to the conductive component of fluid impedance. The measurement performance of the developed sensor is validated by applying the Maxwell Garnett and parallel models to sensor data and comparing the results to data obtained by gamma ray computed tomography (CT). GravelSens is tested and validated under varying filling conditions of different particle sizes ranging from sand to fine gravel. The close agreement between GravelSens and CT measurements indicates the technology’s applicability in sediment–water research while also suggesting its potential for other solid–liquid two-phase flows. This pore-scale measurement and visualization system offers the capability to monitor clogging and de-clogging dynamics within pore spaces up to 10,000 Hz, making it the first laboratory equipment capable of performing such in situ measurements without radiation. Thus, GravelSens is a major improvement over existing methods and holds promise for advancing the understanding of flow–sediment–ecology interactions.

Ultrafast electron beam X-ray computed tomography produces noisy data due to short measurement times, causing reconstruction artifacts and limiting overall image quality. To counteract these issues, two self-supervised deep learning methods for denoising of raw detector data were investigated and compared against a non-learning based denoising method. We found that the application of the deep-learning-based methods was able to enhance signal-to-noise ratios in the detector data and also led to consistent improvements of the reconstructed images, outperforming the non-learning based method.

The removal of unwanted droplets in thermal separation units is often accomplished using knitted wire meshes. Alongside the separation efficiency, the pressure drop plays a crucial role for the design of these demisters. Wire meshes have been subject to limited investigations, and correlations for predicting the pressure drop, both with or without loading (referred to as dry pressure drop), have not yet been validated. To address this gap, experimental analyses of porosity and dry pressure drop were conducted over a wide range of wire mesh parameters and intake gas velocities. An empirical correlation was developed from these experimental results and further data from the literature. This correlation enables prediction of the pressure drop with a mean deviation of +/- 20 %. The removal of unwanted droplets in thermal separation units requires pressure drop prediction during engineering and design of wire mesh demisters. Porosity and dry pressure drops were studied experimentally for a wide range of mesh parameters and gas velocities. A new correlation predicts the pressure drop with a mean deviation of +/- 20 %. image

Ultrafast X-ray computed tomography is an advanced imaging technique for multiphase flows. It has been used with great success for studying gas-liquid as well as gas-solid flows. Here, we apply this technique to analyze density-driven particle segregation in a rotating drum as an exemplary use case for analyzing industrial particle mixing systems. As glass particles are used as the denser of two granular species to be mixed, beam hardening artefacts occur and hamper the data analysis. In the general case of a distribution of arbitrary materials, the inverse problem of image reconstruction with energy-dependent attenuation is often ill-posed. Consequently, commonly known beam hardening correction algorithms are often quite complex. In our case, however, the number of materials is limited. We therefore propose a correction algorithm simplified by taking advantage of the known material properties, and demonstrate its ability to improve image quality and subsequent analyses significantly.

We report on an experimental study of high-pressure (up to 65 bar) steam condensation heat transfer in a slightly inclined tube at the thermal-hydraulic test facility COSMEA. The study is part of an extended experimental program on this topic and focused this time on heat transfer and two-phase flow at low inlet steam qualities (down to 2.8 %). We determined condensation rates respectively total heat transfer, wall heat flux distribution and flow morphology using X-ray imaging and local temperature measurements.

We present a modular and cost-effective gamma ray computed tomography system for multiphase flow investigations in industrial apparatuses. It mainly comprises a 137Cs isotopic source and an in-house-assembled detector arc, with a total of 16 scintillation detectors, offering a quantum efficiency of approximately 75% and an active area of 10 × 10 mm2 each. The detectors are operated in pulse mode to exclude scattered gamma photons from counting by using a dual-energy discrimination stage. Flexible application of the computed tomography system, i.e., for various object sizes and densities, is provided by an elaborated detector arc design, in combination with a scanning procedure that allows for simultaneous parallel beam projection acquisition. This allows the scan time to be scaled down with the number of individual detectors. Eventually, the developed scanner successfully upgrades the existing tomography setup in the industry. Here, single pencil beam gamma ray computed tomography is already used to study hydraulics in gas–liquid contactors, with inner diameters of up to 440 mm. We demonstrate the functionality of the new system for radiographic and computed tomographic scans of DN110 and DN440 columns that are operated at varying iso-hexane/nitrogen liquid–gas flow rates.

Although it is known that a loss in separation performance is caused by liquid maldistribution, there is only marginal knowledge of liquid distribution in rotating packed beds (RPBs). As a result, the exact influence of the liquid distribution on separation performance in RPBs is not fully understood. Therefore, this study focuses on the influence of different liquid distributors on the liquid hold-up distribution of rotating metal foam packing inside RPBs. Liquid hold-ups were measured noninvasively using gamma-ray computed tomography (CT), and water/air was the system under investigation, operated at atmospheric pressure, temperature of 20 degrees C, liquid flow rate of 60 l h(-1), F-factor of 2.3 Pa-0.5, and rotational speeds up to 900 rpm. For the first time, the liquid hold-up distribution in the axial direction of a rotating metal foam of an RPB could be accessed, which allowed the identification and quantification of occurring liquid accumulation at the rotor plates. Furthermore, the liquid hold-up distribution through the entire opaque packing could be visualized for different operating conditions by synchronizing the CT with the rotational speed of the rotor. The use of a single-point full-jet nozzle was more prone to cause liquid accumulation at the rotor plates than that with a rotating baffle distributor with 36 baffles. For comparison, circumferential liquid maldistribution was also observed by using a rotating baffle distributor with 12 baffles.

We present an evaluation study on the characterization of bubbles rising in liquid sodium by applying two-plane ultrafast X-ray computed tomography (UFXCT). It includes a new method for determining the three-dimensional shape and velocity vector of each individual bubble. In the experimental part, argon gas was injected through a single nozzle located slightly above the bottom of a cylindrical vessel filled with liquid sodium. The gas flow rate was varied between 10 and 635 cm3/min to obtain a chain of individual bubbles. In this parameter range, collisions of bubbles, coalescence or breakup are not expected. Measurements were carried out in a wide spatial range starting near the nozzle up to a height of about 200 mm above it. It was convincingly demonstrated that two-plane UFXCT imaging, in combination with the data processing presented here, allows a reliable characterization of the size, shape and velocity of bubbles with a size of a few millimeters in a sodium column of 54 mm diameter. Moreover, a reproducible fluctuation of shape, position and velocity has been observed in the experiments in the lower part of the column.

In this article, we introduce a parallel algorithm for connected-component analysis (CCA) on GPUs which drastically reduces the volume of data to transfer from GPU to the host. CCA algorithms targeting GPUs typically store the extracted features in arrays large enough to potentially hold the maximum possible number of objects for the given image size. Transferring these large arrays to the host requires large portions of the overall execution time. Therefore, we propose an algorithm which uses a CUDA kernel to merge trees of connected component feature structs. During the tree merging, various connected-component properties, such as total area, centroid and bounding box, are extracted and accumulated. The tree structure then enables us to only transfer features of valid objects to the host for further processing or storing. Our benchmarks show that this implementation significantly reduces memory transfer volume for processing results on the host whilst maintaining similar performance to state-of-the-art CCA algorithms.

The gas flow modulation technique (GFM) is a recently proposed approach for measuring the axial gas dispersion coefficient in bubble columns. It is based on a time-resolved measurement of the modulated gas holdup at different axial positions in the column and a subsequent calculation of the axial dispersion coefficient from amplitude damping and the phase lag of a gas holdup wave. In recent studies holdup has been measured with gamma-ray densitometry, which is advantageous in terms of measurement accuracy. However, the application of radiative measurement techniques in industrial settings poses several logistical and safety challenges. This study investigates the potential of nonradiative measurement techniques in the context of GFM. In particular, differential pressure sensors, conductivity needle probes and optical probes are considered. The results obtained using these alternative techniques are compared with gamma-ray measurements. The comparison qualifies differential pressure sensors as a particularly viable alternative to gamma-ray densitometry.

Rotating packed beds (RPBs) are increasingly used in academia and industry for separation processes, but a lack of knowledge about fluid dynamics and liquid maldistribution still limits our understanding of the mass transfer inside. Recently, structured Zickzack packings (ZZ packings) were designed that promise to provide a homogeneous liquid distribution throughout the packing volume. In this study, the fluid dynamics of a water-air system in ZZ packings were characterized at atmospheric pressure and 20 degrees C. For decreasing rotational speeds, a strongly increasing wet pressure drop was observed below 500 rpm due to the formation of a liquid wreath in front of the inner packing edge, and flooding of the rotor eye was visually detected at rotational speeds lower than 300 rpm. At rotational speeds greater than the flooding limit, the fluid dynamics of a single ZZ packing were found to be equal to those of a stacked two-level ZZ packing. In addition,.-ray computed tomography (CT) was used to noninvasively investigate the liquid distribution inside the rotating ZZ packing at multiple scanning planes along the packing height for selected operating conditions. The scans revealed that liquid maldistribution occurred at rotational speeds of less than 1200 rpm, while the liquid was perfectly distributed throughout the packing volume at rotational speeds greater than 1200 rpm.

In this article, a new version of the Real-time Image Stream Algorithms (RISA) data processing suite is introduced. It now features online detector data acquisition, high-throughput data dumping and enhanced real-time data processing capabilities. The achieved low-latency real-time data processing extends the application of ultrafast electron beam X-ray computed tomography (UFXCT) scanners to real-time scanner control and process control. We implemented high performance data packet reception based on data plane development kit (DPDK) and high-throughput data storing using both hierarchical data format version 5 (HDF5) as well as the adaptable input/output system version 2 (ADIOS2). Furthermore, we extended RISA's underlying pipelining framework to support the fork-join paradigm. This allows for more complex workflows as it is necessary, e.g. for online data processing. Also, the pipeline configuration is moved from compile-time to runtime, i.e. processing stages and their interconnections can now be configured using a configuration file. In several benchmarks, RISA is profiled regarding data acquisition performance, data storage throughput and overall processing latency. We found that using direct IO mode significantly improves data writing performance on the local data storage. We could further prove that RISA is now capable of concurrently receiving, processing and storing data from up to 768 detector channels (3072 MB/s) at 8000 fps on a single-GPU computer in real-time. Program summary Program Title: GLADOS/RISA CPC Library link to program files: https://doi .org /10 .17632 /65sx747rvm .2 Developer's repository link: https://codebase .helmholtz .cloud /risa Licensing provisions: Apache-2.0 Programming language: C++ Journal reference of previous version: Comput. Phys. Commun. 219 (2017) 353-360 [1] Does the new version supersede the previous version?: Yes. Reasons for the new version: Extended capabilities for real-time operation with latest UFXCT hardware. Summary of revisions: (i) Add forking and joining of processing pipeline branches (ii) Add runtime (re-)configuration of pipeline stages and connections (iii) Add UDP receiver stage to acquire detector data in real-time (iv) Add high-throughput data dumping Nature of problem: Ultrafast electron beam X-ray computed tomography scanners stream multiple Gigabytes of raw data per second via Ethernet to a control computer. Receiving the data with low latency, real-time image-based control would become possible. For this, data need to be captured from the network, stored on disk, reconstructed and post-processed concurrently. The current total data rate of up to 3072 MB/s requires high-throughput solutions for each of these tasks. Solution method: Using a pipeline scheme, RISA processes incoming raw data in distinct stages (sources, processors, sinks). These are implemented in GPU kernels and are executed concurrently to exploit data parallelism as well as task parallelism. To capture detector data, we implemented a UDP packet capturing stage based on DPDK [2] which acts as a source stage. By allowing the pipeline to fork up into multiple branches, we concurrently acquire, store and process the data. For storing these data, we use the HDF5 format [3]. We achieve the required data rates by writing in direct IO mode onto an SSD array in RAID 0 configuration. Additional comments including restrictions and unusual features: RISA provides a set of general-purpose processing stages which are suitable for generic image stream processing. References [1] Frust T., et al., Comput. Phys. Commun. 219 (2017) 353-360 [2] Data Plane Development Kit, https://www.dpdk.org/ [3] Hierarchical Data Format Version 5, https://www.hdfgroup .org /solutions /hdf5/ (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).

The gas flow modulation technique is a recently proposed approach for measuring the axial gas dispersion coefficient in bubble columns. This study presents a quantitative analysis of the experimental uncertainty associated with gamma-ray densitometry and ensemble-averaging of the data. The considered uncertainty sources are the statistics of the photon counting process, a mismatch between the modelled and the real radiation propagation due to the spatial extent of the detector, and a potential mismatch between modulation and sampling frequencies. The analysis is based on a numerical gamma-ray propagation model and a Monte Carlo approach to account for statistical uncertainty. The proposed algorithm supports the selection of an optimal total scanning time based on detector size, modulation parameters, involved fluids and column and source parameters. The analysis reveals that a mismatch between the modulation and sampling frequencies is most critical while the impact of the other considered uncertainty sources is rather marginal.

Multi-rotor RPBs (MR-RPBs) are a promising way to intensify mass transfer by exploiting the centrifugal field while achieving high separation performance. Reaching the full potential of the separation performance of MR-RPBs requires a uniform liquid distribution in each rotor. As conventional liquid distributors like nozzles can only be used at the pressurized inlet of the liquid, a new concept is needed for distribution on additional rotors. For this r eason, a novel liquid distribution concept named rotating baffle distributor (RBD) was developed. It has a compact design and exploits the rotational speed nrot of the rotor. High-speed camera analyses showed that a minimum nrot of 600 r min-1 was required for axial liquid distribution with water at ambient conditions. CT scans revealed a uniform liquid distribution in the circumferential direction using RBD with 36 baffles. Furthermore, RBDs with 12, 24, and 36 baffles were applied to the distillation of ethanol-water at atmospheric pressure under total reflux using a one-rotor RPB (1R-RPB). The F-factor (FG) was set up to 2.3 Pa0.5 and nrot up to 1200 r min-1. The results were compared to the same distillation experiment in the 1R-RPB using the conventional liquid distribution, i.e., spraying the liquid on the packing via a full-jet nozzle. The distillation study revealed that the RBD with 36 baffles showed one theoretical stage higher separation performance at nrot >= 900 r min-1 compared to the conventional liquid distribution. Those results suggest that the RBD is not only multi-rotor-compatible but also provides uniform liquid distribution while being easier to adjust and operate than the conventional nozzle setup.

In this paper, a flexibly applicable gamma ray computed tomography scanner for multi-phase flow investigations in industrial apparatuses is presented. It mainly comprises a Cs-137 source and an in-house developed detector arc with overall 16 scintillation detectors offering a quantum efficiency of approximately 75% and an active area of 10×10 mm2 each. The detectors are operated in pulse-counting mode to enable gamma photon energy discrimination. Highest flexible application of the CT scanner, i.e. for various object sizes, is provided by an elaborated detector design in combination with a sophisticated scanning procedure that allows for multi beam projection acquisition.The developed radiation detector arc upgrades, finally, an already existing single pencil beam gamma ray computed tomography setup that is industrially used to discover hydraulics in chemical columns with inner diameters of up to 440 mm filled with structured aluminum packings. As illustrative examples, radiographic as well as computed tomography scans are successfully performed at DN110 and DN440 columns operated with various iso-hexane/nitrogen liquid-gas flow rates.

In this work, the capabilities of state-of-the-art turbulence models are compared for a three-dimensional flow (3D) field within a constricted vertical pipe. The considered flow domain is a vertical pipe section with a baffle -shaped flow constriction which leads to the development of a jet flow through and a recirculation flow region behind the constriction. Different Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) models were tested for single-and two-phase flow simulations. In the two-phase simulations, bubble-induced turbulence (BIT) was also considered by adding source terms in the k and epsilon/omega equations. The results are vali-dated against experimental data. We employed hot-film anemometry (HFA) for liquid velocity measurement and combined it with ultrafast X-ray computed tomography (UFXCT), which provides gas phase data. Based on the local phase-indicator function obtained from the tomographic image data, we can correct HFA signals, which become corrupted by bubble contacts. We found that for single-phase flow all RANS models predict axial velocity well while radial velocity prediction is inadequate. LES models, however, achieve a better prediction of the latter. For two-phase flow, the axial component of the liquid velocity is well captured by all RANS models and the radial component of the liquid velocity is predicted better than for single-phase flow. In general, the compu-tationally less costly RNG k-epsilon model performs similar to the SSG RSM model and can therefore be recommended for simulation of complex flow scenarios.

In this paper an enhanced signal processing electronics for an existing multi-channel detector module for gamma ray computed tomography is presented. The detector electronics is able to evaluate gamma photon energies by measuring pulse duration times, which makes it perfectly suitable for attenuation measurements with multi-energy and/or multiple isotopic sources. The duration time of each voltage pulse generated by a gamma photon within the radiation detector is measured using a complex programmable logic device. A sophisticated logic circuit for eight detector channels is designed to acquire the pulse duration time spectra in a total of 256 channels per detector channel in parallel. This paper introduces the basic concept, describes the general and a specific CPLD design, provides an analysis of the accuracy and presents measured pulse duration time spectra.