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Item type:Publication, Access status: without files , A new efficient framework for reduced two-dimensional nonlinear aggregation population balance models(Elsevier, 2026-08-18); ; Two-dimensional (2D) nonlinear population balance models are inherently complex due to their high computational demands and sensitivity to the choice of grid type. To address the challenge of tracking multiple properties and to provide an alternative to full 2D population balance models, we consider a reduced model that efficiently captures moisture content (tracer) and size distributions of granule in aggregation population balance equations (PBEs), under the assumption that the aggregation kernel depends solely on granule volume and time, and is independent of tracer volume. This reduced model is formulated as a tracer population balance equation (TPBE), for which we present a new and efficient discretization method that ensures conservation of tracer mass. The proposed formulation is versatile and applicable to any grid type, making it suitable for both continuous and batch particulate systems. We validate its performance using two benchmark applications: (a) batch systems and (b) mixed-suspension mixed-product removal systems. The formulation is tested across various kernels and compared against the cell average technique (CAT) to confirm its effectiveness. Results show that the proposed method achieves accuracy comparable to CAT while requiring approximately 50–60% less computational time. Overall, this approach offers a computationally efficient alternative to standard 2D models, with broad applicability in systems where reduced computational cost is critical for particle process modeling.Publicationtype: Journal Article9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Implementation of multi-level coarse-graining method on GPU using MUSEN(Elsevier, 2026-08-11); ; ; ; GPU-based discrete element method (DEM) simulations have recently gained popularity due to their ability to reduce the computational costs associated with modelling large-scale granular systems. To further enhance the efficiency of these simulations, we implement the multi-level coarse-graining (MCG) method on GPU using the open-source GPU-accelerated DEM software MUSEN. The MCG method significantly improves performance by reducing the number of simulated particles while maintaining accuracy. The key simulation parameters such as the Verlet distance and the interval of performing refinement or coarsening of particles are optimized to maximize computational efficiency. The MCG-GPU method is validated using a hopper discharge system, achieving a speedup of about 3.4× compared to the MCG-CPU simulation. The robustness of this method is further demonstrated through its application to two industrial systems: a tablet-press feeder and a twin-screw feeder, where speedups of approximately 5.5× and 8×, respectively, are achieved relative to MCG-CPU simulations. These results affirm that the MCG-GPU method is a powerful tool for efficiently conducting large-scale particle simulations with complex geometries.Publicationtype: Journal Article45 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A note on the analytical approach and its efficiency for solving multivariate breakage population balance equationsBreakage population balance equations are of significant importance in powder technology, specifically in the processes which involve reduction of particle size, milling, granulation and material refinement. The dynamics of breakage process can be captured well by multivariate formulations but are challenging to solve due to strong non-linearity and contributions from internal and external coordinates. To address these challenges, a semi-analytical technique based on the homotopy of functions is employed to solve linear and collisional breakage equations in a multivariate framework. Accuracy and computational performance of the proposed method are validated with respect to the Adomian decomposition method and finite volume method. Numerical results show that the proposed homotopy-based method outperforms both the existing techniques in terms of computational accuracy. Thus, homotopy analysis method can be considered as a robust and powerful tool to solve intricate multivariate particulate problems arising in scientific research and industrial applications.Publicationtype: Journal Article7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , An accurate approach and its convergence analysis for the multidimensional nonlinear collisional breakage equations(Elsevier, 2026-01-29); ; ; ; Particulate processes such as bubble breakage, granule preparation, and ore extraction are often modeled using population balance equations. While most studies rely on linear fragmentation models, these fail to capture realistic dynamics where breakage occurs due to particle collisions, leading to nonlinear collisional breakage equations. The mathematical complexity of nonlinear kernels and integrals has limited progress in this direction, with very few analytical solutions available. In this work, we develop an accurate approach based on a modified variational iteration method for solving multidimensional collisional breakage equations. The method allows flexible operator selection and efficient determination of the Lagrange multiplier. A rigorous convergence and error analysis is carried out using the fixed-point theorem. The approach is further extended to two- and three-dimensional models, including collisional fragmentation cases. Numerical experiments confirm the accuracy and efficiency of the method compared with existing approaches.Publicationtype: Journal Article11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , An improved meshfree approach for solving nonlinear multivariate models involving aggregation, breakage, growth and source(2026-01); ; The modeling of aggregation and collisional breakage phenomena remains largely unexplored due to nonlinearity and nonlocal nature of the model equation. This article discusses the performance and efficiency of a redefined homotopy-based method and generalized iteration method for solving bivariate aggregation-collision breakage model for several kinetic kernels. Solution for Brownian motion kernel and equi-partition of kinetic energy kernel are obtained to analyze the dynamics of bubble columns as well as the granular flow behavior. The iterative scheme is further extended to solve aggregation-breakage model with simultaneous growth and source terms. This model is also extended for solving bivariate cases.Publicationtype: Journal Article12 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimizing mechanical pretreatment of cotton textile waste to enhance enzymatic hydrolysisEnzymatic recycling processes of cotton from waste materials have gained increasing interest in recent years. Therefore, the aim of this study was to optimize the application of mechanical shear forces to end-of-life cotton-based textile suspensions, followed by an enzymatic hydrolysis to glucose. Mechanical pretreatment in a cutting mill followed by a wet-rotor-milling process was investigated by varying solids load and mill parameter settings. The results indicated that both a smaller gap width and higher solids load during mechanical pretreatment resulted in enhanced enzymatic hydrolysis. Additionally, it was found that a minimum amount of energy input while milling was necessary to enable a higher glucose yield. The relationship between energy input, enzymatic hydrolysis, and crystallinity facilitates the assessment of the effect of energy input within the milling process. Furthermore, a decrease in enzyme activity was observed with increasing solids load during enzymatic hydrolysis. Overall, the findings of this research suggest that wet milling presents a promising technology to improve the enzymatic hydrolysis of end-of-life cotton textiles.Publicationtype: Journal Article39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimization of efficiency of lactose drying process in an industrial continuous fluidized bed dryer using dynamic flowsheet simulation(Elsevier, 2025-06-01); ; 27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Real-time magnetic resonance imaging and numerical modelling of gas-solid hydrodynamics in vibrated bubbling fluidized bedsGas-solid fluidized beds are used in a variety of chemical engineering applications, such as food processing, or energy conversion. Vibrating the beds helps to further enhance process efficiency [1]. Studying the hydrodynamics of fluidized beds is challenging due to their opaque nature. Therefore, three-dimensional (3D) tomographic techniques, such as Magnetic Resonance Imaging (MRI) [2], are necessary to study the hydrodynamics within these systems. This work investigates the gas-solid hydrodynamics of 3D vibrated fluidized beds using real-time MRI with a world-wide unique vertical 3T MRI scanner. In contrast to conventional clinical systems, this MRI features an open radiofrequency (RF) shielding, allowing to place the electrodynamic shaker and other RF-noise emitting peripherals in axis with the fluidized bed. A tailored RF receiver array for signal detection is used allowing real-time imaging with high temporal resolution enabling the observation of dynamics such as bubble growth and coalescence. The size distribution and rise velocity of gas bubbles in the bed are investigated for Geldart group A, B, and C particles. Additionally, MRI data is compared with CFD-DEM numerical simulations to validate drag force models and coarse-graining approaches. The project is financially supported by the German Research Foundation (DFG) under project number 471615686. References: [1] Guo, Q. et al., Current Opinion in Chemical Engineering, (2023), 22113398, 100977 [2] Penn, A. et al., Science Advances, (2017), 117-123Publicationtype: Conference Presentation14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Real time magnetic resonance imaging and numerical modelling of gas-solid hydrodynamics in vibrated bubbling fluidized bedsVibrated gas-solid fluidized beds offer improved performance over non-vibrated fluidized beds by preventing particle agglomeration and channeling, facilitating fluidization in systems with high cohesive forces, and enhancing heat transfer, making them a favorable choice for various applications [1]. Studying the hydrodynamics is challenging due to their opaque nature. Intrusive probes like pressure and capacitance sensors measure hydrodynamics in three dimensional (3D) beds but are limited to specific locations and can alter the flow. Therefore, 3D tomographic techniques, such as Magnetic Resonance Imaging (MRI) [2], are favored to study the hydrodynamics within these systems. This work investigates the gas-solid hydrodynamics of 3D vibrated fluidized beds using real time MRI with a world-wide unique vertical 3T MRI scanner located at TUHH. In contrast to conventional clinical systems, this MRI offers a vertical bore allowing the study of columnar samples with outer diameters up to 40 cm and several meters in height. Real-time imaging with high temporal resolution enables the observation of dynamics such as bubble growth and coalescence. The size distribution and rise velocity of gas bubbles in the bed are investigated for Geldart group A, B, C and D particles. Additionally, MRI data is compared with Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) numerical simulations to validate drag force models and coarse-graining approaches. The project is financially supported by the German Research Foundation (DFG) under project number 471615686. [1] Guo, Q. et al., Advances in vibrated gas-fluidized beds, Current Opinion in Chemical Engineering, (2023), 22113398, 100977 [2] Penn, A. et al., Real-time probing of granular dynamics with magnetic resonance, Science Advances, (2017), 117-123Publicationtype: Conference Poster7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Real time magnetic resonance imaging and numerical modelling of gas-solid hydrodynamics in vibrated bubbling fluidized bedsGas-solid fluidized beds are widely utilized in various process engineering applications for their enhanced heat and mass transfer rates. Vibration can improve the performance of fluidized beds by enhancing fluidization of cohesive particles, breaking agglomerates, improving mixing, and enhancing heat transfer in drying [1]. Studying hydrodynamics is challenging due to the chaotic nature of fluidized beds. The addition of vibration makes the dynamics even more complex, and our understanding of their hydrodynamics remains limited, especially in three-dimensional (3D) systems. Tomographic techniques, such as Magnetic Resonance Imaging (MRI) [2], have emerged as indispensable tools for the non-invasive and spatially resolved analysis of 3D beds. This work investigates the hydrodynamics of 3D beds, with and without vibration, using real-time MRI with a unique 3T vertical MRI scanner. The vertical orientation of the magnet enables the measurement of samples up to 400 mm in diameter and several meters in height. An electrodynamic shaker generates vertical sinusoidal acceleration, with vibrations transmitted to the bed via glass fiber-reinforced tubes. The MRI system is elevated from the ground and offers a unique radiofrequency shielding, making it possible to place the electrodynamic shaker in axis. Properties such as bubble size, rise velocity and the influence of particle properties are investigated. Furthermore, complex phenomena, such as dynamically structured bubbling [3], can be studied in 3D systems. Numerical simulations, such as CFD-DEM, which combines computational fluid dynamics and the discrete element method, offer valuable insights into hydrodynamics. In collaboration with the Institute of Solids Process Engineering and Particle Technology, MRI data is compared with CFD-DEM results to validate drag force models and coarse-graining approaches. The project is financially supported by the German Research Foundation (DFG) under project number 471615686. [1] Guo, Q. et al., Current Opinion in Chemical Engineering, 2023, 100977 [2] Penn, A. et al., Science Advances, 2017, 117-123 [3] Guo, Q. et al., PNAS, 2021, 35, e2108647118Publicationtype: Conference Presentation49