Radioactive Particle Tracking Technique Research Articles

A comparative study of a traditional localization algorithm and a deep learning model for radioactive particle tracking application

Radioactive particle tracking is a nuclear technique that tracks a sealed radioactive particle inside a volume through a mathematical location algorithm, which is widely applied in many fields such as chemical and civil engineering in hydrodynamics flows. It is possible to reconstruct the trajectory of the radioactive particle using a traditional mathematical algorithm or artificial intelligence methods. In this paper, the traditional algorithm is based on solving a minimization problem between the simulated events and a calibration dataset, and it was written using C++ language. The artificial intelligence method is represented by a deep neural network, in which hyperparameters were defined using a Python optimization library called Optuna. This paper aims to compare the potentiality of both methods to evaluate the accuracy of the radioactive particle tracking technique. This study proposes a simplified model of a concrete mixer, six NaI(Tl) detectors, and a137Cs sealed radioactive particle. The simulated measurement geometry and the dataset (3615 patterns) were developed using the MCNPX code, which is a mathematical code based on the Monte Carlo Method. The results show a mean absolute percentage error (MAPE) of 20.81%, 10.33%, and 16.84% for x, y and z coordinates, respectively, for the traditional algorithm. For the deep neural network, MAPE is 6.87%, 2.70%, and 22.79% respectively for x, y and z coordinates. In addition, an investigation is carried out to analyze whether the size of the calibration dataset influences the performance of both methods.

Single-photon emission radioactive particle tracking method for hydrodynamic evaluation of multi-phase flows

Evaluation of the hydrodynamics of opaque multi-phase flows remains a challenging task, with implications for various industrial processes such as chemical processing, pharmaceutical, and mineral processing. Understanding how design and operational variables affect the complex behavior of multi-phase flow systems is essential for optimizing processing conditions and improving efficiency. Radioactive particle tracking (RPT) has been a proven measurement technique to evaluate hydrodynamics in multi-phase flow systems. However, a limitation of the classical RPT technique exists in the assumptions made in the simulation of the count rate received by the detectors in correcting for varying flow-induced fluctuations in the volume fraction of the dispersed phase, often encountered in industrial multi-phase flow systems.In this paper, we introduce a fundamentally novel experimental RPT method that directly uses detected incident photon hit locations for the reconstruction of the three-dimensional radioactive tracer particle position. We argue that this approach is inherently more robust as varying attenuation does not affect the reconstruction. The RPT setup consists of three identical γ-radiation slit collimator detectors that are placed equidistantly at 120° intervals. A subsequent calibration-experimentation procedure is established that allows reconstruction of the tracer particle position with spatial accuracy and precision in the order of 1 mm. We demonstrate the applications of this technique in evaluating hydrodynamics in multi-phase systems by characterizing the flow field of industrial-grade polypropylene reactor powder in a laboratory-scale horizontal stirred bed reactor.

Development, validation and implementation of multiple radioactive particle tracking technique

Computer Automated Radioactive Particle Tracking (CARPT) technique has been successfully utilized to measure the velocity profiles and mixing parameters in different multiphase flow systems where a single radioactive tracer is used to track the tagged phase. However, many industrial processes use a wide range of particles with different physical properties where solid particles could vary in size, shape and density. For application in such systems, the capability of current single tracer CARPT can be advanced to track more than one particle simultaneously. Tracking multiple particles will thus enable to track the motion of particles of different size shape and density, determine segregation of particles and probing particle interactions. In this work, a newly developed Multiple Radioactive Particle Tracking technique (M-RPT) used to track two different radioactive tracers is demonstrated. The M-RPT electronics was developed that can differentiate between gamma counts obtained from the different radioactive tracers on the basis of their gamma energy peak. The M-RPT technique was validated by tracking two stationary and moving particles (Sc-46 and Co-60) simultaneously. Finally, M-RPT was successfully implemented to track two phases, solid and liquid, simultaneously in three phase slurry bubble column reactors.

Solid Flow Mapping at the Bottom Section of a Pilot-Plant Scale Riser with the Help of a Radioactive Particle Tracking Technique

Solid phase velocity measurements are performed at the bottom section of a pilot plant scale cold-flow circulating fluidized bed riser with Geldart group B solids using a radioactive particle tracking technique. Experiments are performed at different gas velocities and solid fluxes to evaluate the effect of gas velocity and solid flux on solid phase velocity in the bottom section of the riser. Different flow quantities such as mean velocity, root-mean-square velocities, and granular temperature are calculated and presented at different heights. Solid motion is seen to occur in the axial direction primarily. It is observed that axial velocity fluctuation increases with the height where radial solid velocity fluctuation decreases. Both gas–solid and solid–solid interactions are vital in determining the solid flow field. Gas–solid interaction is critical in the axial direction, while solid–solid interaction is important in the radial direction.

Characterisation of solid hydrodynamics in a three-phase stirred tank reactor with positron emission particle tracking (PEPT)

It is challenging to measure the hydrodynamics of stirred tank reactors when they contain multiphase flows comprising liquid, gas bubbles and particles. Radioactive particle tracking techniques such as positron emission particle tracking (PEPT) are the only established techniques to determine internal flow behaviour due to the inherent opacity and density of fluid and the vessel walls. The profiles of solids flow are an important tool for robust reactor design and optimisation and offer insight into underlying transport processes and particle–fluid–bubble interactions for applications such as froth flotation. In this work, measurements with PEPT were performed with two tracer particles differing in surface hydrophobicity to characterise the solids hydrodynamics in a baffled vessel agitated with a Rushton turbine. The location data from PEPT were averaged with time to estimate the probability density function (PDF) of particle velocity in individual voxels. The peaks of these voxel distributions were used to produce profiles of solids flow in different azimuthal and horizontal slices. Bimodal vertical velocity distributions were observed in the impeller radial jet which suggest the particles experienced trajectory crossing effects due to inertia. Statistical tests were performed to compare the velocity distributions of the hydrophilic and hydrophobic tracer particles, which indicated similar average flow behaviour in the liquid or pulp phase of the vessel and differences near the air inlet, in the impeller discharge stream and pulp–froth interface. With tracers designed to represent gangue and valuable mineral species, the differences in velocity reveal interactions such as bubble–particle attachment and entrainment. • Positron emission particle tracking (PEPT) measurements of multiphase flow. • Solid hydrodynamics in a three-phase stirred tank reactor of gas, liquid and solids. • Comparison of hydrophilic and hydrophobic particle flow behaviour. • Observations of particle interaction with the gas bubble flow field.

New Benchmarking Hydrodynamics Using Newly Developed Methodology for Implements Radioactive Particle Tracking (Rpt) Technique in Bubble Column with Intense Internals

New Benchmarking Hydrodynamics Using Newly Developed Methodology for Implements Radioactive Particle Tracking (Rpt) Technique in Bubble Column with Intense Internals

Integration of dynamic growth modeling and hydrodynamics in an internal‐loop split photobioreactor

AbstractIn this study, new high‐quality experimental data for culturing green microalgae Scenedesmus in tubular and cylindrical split airlift photobioreactors were obtained under different operating conditions. The obtained experimental data of culturing microalgae Scenedesmus in a tubular photobioreactor were used for determining the kinetic parameters of the photosynthetic reaction. On the other hand, the culturing of green microalgae in a split airlift photobioreactor was used to measure the microalgae cell trajectory using an advanced radioactive particle tracking (RPT) technique. The obtained results in terms of kinetic parameters of the photosynthetic reaction and microalgae cell trajectory were integrated for the first time to obtain the three‐state dynamic growth model. This integration between dynamic growth and cell trajectories will provide a direct and comprehensive tool for photobioreactor analysis, which is essential for proper and efficient reactor design and scale‐up for large‐scale biomass production. © 2021 Society of Chemical Industry (SCI).

Comparison of the Fluidized State Stability from Radioactive Particle Tracking Results

Currently, various industrial processes are carried out in fluidized bed reactors. Knowing its internal dynamics is fundamental for the intensification of these processes. This work assesses the motion of fluidized calcium alginate spheres under the influence of an upward fluid flow within a 1.2 m high and 0.1 m inner diameter acrylic column. The liquid–solid fluidized bed was compared with a gas–liquid–solid fluidized bed operation mode in terms of mixing behavior. The radioactive particle tracking technique is a proper methodology to study the internal dynamics of these kinds of equipment. Data gathered were analyzed with Shannon entropy as a dynamic mixing measure. Mixing times were found to be between 1 and 2.5 seconds for both fluidization modes. The liquid–solid fluidized bed presents a rather smooth mixing time profile along the column. On the other hand, the gas–liquid–solid fluidized bed showed high sensitivity of entropy production with height, reaching a sharp tendency break at the second quartile of the column. The Glansdorff–Prigogine stability measure can accurately capture flow regime transitions of the gas–liquid–solid fluidized bed, allowing it to be used to construct reliable operative windows for fluidization equipment.

Study of radioactive particle tracking using MCNP-X code and artificial neural network

Agitators or mixers are highly used in the chemical, food, pharmaceutical and cosmetic industries. During the fabrication process, the equipment may fail and compromise the appropriate stirring or mixing procedure. Besides that, it is also important to determine the right point of homogeneity of the mixture. Thus, it is very important to have a diagnosis tool for these industrial units to assure the quality of the product and to keep the market competitiveness. The radioactive particle tracking (RPT) technique is widely used in the nuclear field. In this paper, a method based on the principles of RPT is presented. Counts obtained by an array of detectors properly positioned around the unit will be correlated to predict the instantaneous positions occupied by the radioactive particle by means of an appropriate mathematical search location algorithm. Detection geometry developed employs eight NaI(Tl) scintillator detectors and a Cs-137 (662 keV) source with isotropic emission of gamma-rays. The modeling of the detection system is performed using the Monte Carlo Method, by means of the MCNP-X code. In this work, a methodology is presented to predict the position of a radioactive particle to evaluate the performance of agitators in industrial units by means of an Artificial Neural Network.

Liquid and solids phase backmixing in a bubble and slurry bubble column using a virtual tracer response methodology based on the trajectory data of the radioactive particle tracking (RPT) technique

AbstractVirtual tracer response methodology developed based on the trajectory data of the computer aided radioactive particle tracking (CARPT) technique was demonstrated. The demonstrated virtual tracer technique has advantages of non‐invasiveness, near perfect injection/sampling, and flexibility in choosing the sampling/injection boundaries in a specific spatial pattern. With the developed virtual tracer technique, liquid and solids backmixing were investigated at the conditions mimicking Fischer‐Tropsch synthesis. Experiments were conducted at different pressure, solids loading, and superficial gas velocity. The axial dispersion model (ADM) and recirculation and cross flow dispersion (RCFD) models were used to model the liquid mixing. Transient sedimentation dispersion model (SDM) was used to model the solids mixing. It was found that the measured axial dispersion coefficient (Dl) in the ADM model increases with increase in the pressure. The increase of dispersion coefficient was explained with the experimental values of mean axial diffusivity and mean recirculation velocity. Axial dispersion coefficients (Dz,uDz,d) in the RCFD model (compartment model) were apparently lower than the Dl, due to the decoupling of global recirculation from the dispersion coefficients in the RCFD. Further, it was found that the dispersion coefficients in the RCFD model follow the trend of the axial eddy diffusivity with change in the operating conditions revealing the dominance of the turbulence in the upflow and downflow compartments. From the solids backmixing study, axial dispersion coefficient (Ds) of solids was found to increase with increase in the solids loading, pressure, and superficial gas velocity at the studied conditions.

Study of the detailed catalyst hydrodynamics using radioactive particle tracking technique in a mimicked Fischer-Tropsch slurry bubble column

Slurry bubble column reactor (SBCR) is the preferred choice of reactor for Fischer – Tropsch (FT) synthesis. However, the understanding of the catalyst flow dynamics in FT-SBCR is still lacking. In this work, hydrodynamics of the FT catalyst were studied using computer aided radioactive particle tracking (CARPT) technique at the mimicked conditions of FT synthesis for the first time. Solids ensemble averaged velocity, turbulent kinetic energy, Reynolds normal and shear stresses were experimentally obtained. Effect of operating conditions on the velocity flow field were investigated. Further, studies were conducted to quantify the difference in flow field due to the change in the liquid and solid phases. It was found that the change of solids turbulence is insignificant with pressure and solids loading at the studied operating conditions. Further, it was found that the surface tension of the fluid and the solid properties plays a dominant role on the turbulence.

Validation of the new mechanistic scale‐up of gas‐solid fluidized beds using advanced non‐invasive measurement techniques

AbstractThis study focuses on the validation of a new mechanistic of scale‐up for hydrodynamics similarity of gas‐solid fluidized bed reactors that was developed in our Multiphase Reactors Engineering and Applications Laboratory (mReal). It is based on maintaining identical or relatively similar time‐averaged radial profiles of gas holdups in two differently sizes gas‐solid fluidized beds to achieve local and global similarities of the dimensionless hydrodynamic parameters. This is because the gas‐dynamic dictates the hydrodynamics of gas‐solid fluidized beds. The new scale‐up method has been successfully validated by assessing for the first time the local hydrodynamic parameters, such as time‐averaged cross‐sectional distributions and radial‐profiles of gas and solids holdups at different axial levels, which were measured by gamma‐ray computed tomography technique. In addition, the particle velocity field and turbulent parameters (shear stress, normal stresses, and turbulent kinetic energy) were measured by radioactive particle tracking technique. The experimental results showed that achieving similarity in the radial profiles of the gas holdup in the geometrically similar beds is essential for ensuring identical or relatively similar local and global hydrodynamics similarity. As the differences increase in terms of magnitude and trend in the gas holdup radial profiles between two beds, the differences increase in the detailed hydrodynamics.

A novel radioactive particle tracking algorithm based on deep rectifier neural network

Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a137Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.

Validation of the Glicksman Scaling Law for Gas–Solid Conical Fluidized Beds Using the Radioactive Particle Tracking Technique

In the current work, the scale-up study was performed for gas–solid conical fluidized beds using the radioactive particle tracking technique. Two sets of Glicksman scaling laws were used: the inert...

Numerical modelling of stirred tank and its validation by Radioactive Particle Tracking (RPT) technique

ABSTRACT Computational Fluid Dynamics (CFD) model for Rushton Turbine (RT) stirred tanks has been developed. The CFD model has been validated with experimental (RPT) data. The RPT data were calibrated with Laser Doppler Anemometry (LDA) data from literature. The calibration of RPT setup was done in two conditions: (a) stationary rotor and (b) rotor rotating at 200 rpm. The radiation intensity data recorded from measurement was analysed by Analysis of Variance (ANOVA) test and found that intensity counts have statistically equal mean. Also, the percentage error between mean counts is less than 1.72. So calibration step in RPT setup can be done in rotor stationary condition which is useful for estimating fluid dynamical conditions inside the impeller region, which is not possible with any other instruments like PIV, LDA etc. Further, RPT experiments and CFD simulations were conducted and results were in good agreement with LDA data from literature. The classical flow pattern of a jet-like stream coming from impeller tip was observed from RPT and well predicted by the CFD model. CFD model predicted the mean velocities and the turbulent quantities in reasonably good manner in comparison with literature data.

The Predictors of Peri-Procedural and Sub-Acute Cerebrovascular Events Following TAVR

In Brazil, concrete and cement are highly used in construction, therefore mixers are widely used in this industry. During the fabrication process of concrete/cement, the equipment may fail and compromise the appropriate mixing procedure. Besides that, it is also important to determine the right point of homogeneity of the mixture. It is important to have a methodology to monitor the mixing process to ensure the quality of the product. This study presents a methodology based on the principles of the radioactive particle tracking technique to predict the instantaneous positions occupied by the radioactive particle inside an industrial mixer by means of a mathematical location algorithm. The detection geometry modeled by means of MCNPX code employs an array of eight NaI(Tl) scintillator detectors, a 198Au spherical gamma-rays source with isotropic emission and a test section filled with concrete that represents an industrial mixer. The choice of the radionuclide is due its well-characterized peak of 411 keV, its half-life of 2.7 days and the possibility to obtain 198Au by neutron activation in reactors. The purpose of this study is to use an artificial neural network as a location algorithm of the 198Au radioactive particle inside an industrial mixer. Results showed that over 56% of the cases were below 5% of relative error for all coordinates of the radioactive particle, which indicates that it is possible to track the radioactive particle trajectory inside the industrial mixer using the artificial neural network algorithm.

Reprint of "Radioactive particle tracking methodology to evaluate concrete mixer using MCNPX code"

In Brazil, concrete and cement are highly used in construction, therefore mixers are widely used in this industry. During the fabrication process of concrete/cement, the equipment may fail and compromise the appropriate mixing procedure. Besides that, it is also important to determine the right point of homogeneity of the mixture. It is important to have a methodology to monitor the mixing process to ensure the quality of the product. This study presents a methodology based on the principles of the radioactive particle tracking technique to predict the instantaneous positions occupied by the radioactive particle inside an industrial mixer by means of a mathematical location algorithm. The detection geometry modeled by means of MCNPX code employs an array of eight NaI(Tl) scintillator detectors, a 198Au spherical gamma-rays source with isotropic emission and a test section filled with concrete that represents an industrial mixer. The choice of the radionuclide is due its well-characterized peak of 411 keV, its half-life of 2.7 days and the possibility to obtain 198Au by neutron activation in reactors. The purpose of this study is to use an artificial neural network as a location algorithm of the 198Au radioactive particle inside an industrial mixer. Results showed that over 56% of the cases were below 5% of relative error for all coordinates of the radioactive particle, which indicates that it is possible to track the radioactive particle trajectory inside the industrial mixer using the artificial neural network algorithm.

Velocity measurements in convective boiling flow using radioactive particle tracking technique

AbstractThe design, performance, and safety analysis of nuclear reactors, in particular boiling water reactors, requires information about the vapor–liquid flow dynamics. Such data are necessary for stand‐alone analysis of the thermal hydraulics, as well as to serve as a database for validation of computational fluid dynamics models. Challenges in collecting such data are magnified in the context of flow boiling, which is known to be a complex, multi‐scale problem. The present work focuses on investigating the two‐phase flow dynamics of convective boiling flows on a test section equipped with different heater rods arrangements. Noninvasive radioactive particle tracking (RPT) has been used for measuring liquid velocity field, mean flow patterns, and turbulent kinetic energy of the liquid phase. A novel tracer particle reconstruction algorithm based on support vector regression has been applied in this study. This is the first application of RPT for measuring liquid velocity fields in convective boiling flows.

Study on visualization of water mixing flows in a digester equipped with a vertical impeller by using radiotracers

Abstract A mixer with a new concept design has been adapted into water treatment plants. It reportedly cuts down the energy consumption of the mixer by the new mixer, which moves vertically and creates internal flows toward its bottom. However, no experimental observations have been made on the internal flow caused by a vertical impeller. In this study, a radiotracer experiment, radioactive particle tracking (RPT) technique, and particle image velocimetry (PIV) were carried out to visualize the flow in the mixer, and compared to each other. The results show that the flow patterns from these techniques are very similar to each other, and the performance of the mixer was good enough to mix the inner materials.

Experimental validation of design and performance parameters of radioactive particle tracking (RPT) experimentation

In recent years, radioactive particle tracking (RPT) has emerged as a powerful noninvasive technique for characterization and visualization of flow in opaque multiphase flow reactors. This technique has been applied to a variety of multiphase flow reactors largely based on the theoretical framework for optimal design and performance parameters. No systematic evaluation and validation of the design and performance parameters of the RPT technique has been reported in the literature thus far. Consequently, the theoretical framework for the design of RPT experiments has had limited scalability and application to a wide variety of flow systems. Thus far, design of a “good” RPT experiment continues to be an art, no matter how much the richness of flow of information that the experimental method brings. The present work reports systematic experimental evaluation of design parameters for an optimal RPT experiment and validation of the theoretical results reported in literature. The experiments were performed in a carefully designed setup in which precise positioning of the tracer particle was made possible. The experiments assess the effect of various parameters on the performance of the RPT experiment, such as the choice of radioactive isotope, activity, gamma-ray energy, size of the detector, and relative positioning of detectors. Finally, a set of recommendations based on experimental work are provided to “optimally” perform the RPT experiment in any single or multiphase reactor.