Reactor Geometry Research Articles

Optimization of Rotational Hydrodynamic Cavitation Reactor Geometry

A Rotary-Pulsation Apparatus (RPA), also known in the literature as a Rotational Hydrodynamic Cavitation Reactor (RHCR), is a device which typically consists of a rotating mechanism that generates pulsations or vibrations within a fluid. This can be achieved through various means such as mechanical agitation, pneumatic pulses, or hydraulic forces. It is widely used in food, chemical, pharmaceutical, and microbiological industries to improve the mixing of different fluids, dispersion, pasteurization, and sterilization. In the present paper, a CFD study was conducted to develop and optimize the geometry of the RPA’s rotor and stator to induce cavitation in the fluid flow. The effect of cavitation has the potential to improve dispersion and emulsion properties and to significantly reduce operation pressure, in comparison to conventional mixing systems.

Computational Fluid Dynamics Modelling of Hydrogen Production via Water Splitting in Oxygen Membrane Reactors.

The utilization of oxygen transport membranes enables the production of high-purity hydrogen by the thermal decomposition of water below 1000 °C. This process is based on a chemical potential gradient across the membrane, which is usually achieved by introducing a reducing gas. Computational fluid dynamics (CFD) can be used to model reactors based on this concept. In this study, a modelling approach for water splitting is presented in which oxygen transport through the membrane acts as the rate-determining process for the overall reaction. This transport step is implemented in the CFD simulation. Both gas compartments are modelled in the simulations. Hydrogen and methane are used as reducing gases. The model is validated using experimental data from the literature and compared with a simplified perfect mixing modelling approach. Although the main focus of this work is to propose an approach to implement the water splitting in CFD simulations, a simulation study was conducted to exemplify how CFD modelling can be utilized in design optimization. Simplified 2-dimensional and rotational symmetric reactor geometries were compared. This study shows that a parallel overflow of the membrane in an elongated reactor is advantageous, as this reduces the back diffusion of the reaction products, which increases the mean driving force for oxygen transport through the membrane.

An innovative solar reactor with Gaussian-pattern geometry for syngas production from dry reforming of methane

Solar reactors are promising energy storage technologies that convert solar energy into the heating value of passing fluids. This study is focused on a foam-based solar reactor, one of the most common types of solar reactors, supposed to produce syngas from the dry reforming of methane (DRM). The novelty of the present study is that it proposes a new Gaussian-pattern reactor geometry inspired by the Gaussian distribution of the incident solar flux. Local thermal non-equilibrium (LTNE) model and the finite volume method (FVM) numerical approach are employed to assess the performance of the proposed solar reactor design. A comparison between the present design and the benchmark design (the design with cylindrical geometry) shows that the new design leads to better temperature distribution and improves energy storage efficiency by about 3.3%.

Fast simulation strategy for capacitively-coupled plasmas based on fluid model

Fluid simulations are widely used in optimizing the reactor geometry and improving the performance of capacitively coupled plasma (CCP) sources in industry, so high computation speed is very important. In this work, a fast method for CCP fluid simulation based on the framework of Multi-physics Analysis of Plasma Sources (MAPS) is developed, which includes a multi-time-step explicit upwind scheme to solve electron fluid equations, a semi-implicit scheme and an iterative method with in-phase initial value to solve Poisson's equation, an explicit upwind scheme with limited artificial diffusion to solve heavy particle fluid equations, and an acceleration method based on fluid equation modification to reduce the periods required to reach equilibrium. In order to prove the validity and efficiency of the newly developed method, benchmarking against COMSOL and comparison with experimental data have been performed in argon discharges on the Gaseous Electronics Conference (GEC) reactor. Besides, the performance of each acceleration method is tested, and the results indicated that the multi-time-step explicit Euler scheme can effectively decline the computational burden in the bulk plasma and reduce the time cost on the electron fluid equations by half. The in-phase initial value method can greatly decrease the iteration times required to solve linear equations and lower the computational time of Poisson's equation by 77 %. The acceleration method based on equation modification can reduce the periods required to reach equilibrium by two-thirds.

Estimation of Turbulent Mixing Factor and Study of Turbulent Flow Structures in Pressurized Water Reactor Sub Channel by Direct Numerical Simulation

Abstract Subchannel analysis codes are presently a requirement for design and safety analysis of nuclear reactors. Among the crucial inputs for these codes, the turbulent mixing factor holds particular significance. However, acquiring this factor through experimental means proves to be a challenging endeavor, primarily due to the necessity for precise pressure equilibrium between subchannels. Consequently, this requirement leads to the undertaking of expensive and intricate experiments for each new reactor or in cases where there are modifications in fuel bundle design. The need for direct numerical simulation (DNS) stems from the challenges and costs involved in experimental techniques, and the uncertainties due to empiricism in computational fluid dynamics (CFD) models. In this study, DNS has been conducted across six Reynolds numbers, ranging from 17,640 to 1.176 × 105, in the geometry of a pressurized water reactor (PWR) subchannel. The resulting turbulent flow structures have been computed and their dynamics are examined. Furthermore, this paper presents a methodology for directly calculating the turbulent mixing factor from the fluctuating velocity field obtained from DNS data. The turbulent mixing process has been scrutinized in-depth, and a correlation for the turbulent mixing factor is developed. It is noted that most of the mixing occurs in the near-wall region. The study suggests different mixing factors for mass and momentum mixing. This paper aims to provide a comprehensive insight into the turbulent mixing phenomenon.

Investigating instabilities in magnetized low-pressure capacitively coupled RF plasma using particle-in-cell (PIC) simulations

The effect of a uniform magnetic field on particle transport in low-pressure radio frequency (RF) capacitively coupled plasma (CCP) has been studied using a particle-in-cell model. Three distinct regimes of plasma behavior can be identified as a function of the magnetic field. In the first regime at low magnetic fields, asymmetric plasma profiles are observed within the CCP chamber due to the effect of E→×B→ drift. As the magnetic field increases, instabilities develop and form self-organized spoke-shaped structures that are distinctly seen within the bulk plasma closer to the sheath. In this second regime, the spoke-shaped coherent structures rotate inside the plasma chamber in the −E→×B→ direction, where E→ and B→ are the DC electric and magnetic field vectors, respectively, and the DC electric field exists in the sheath and pre-sheath regions. The spoke rotation frequency is in the megahertz range. As the magnetic field strength increases further, the rotating coherent spokes continue to exist near the sheath. The coherent structures are, however, accompanied by new small-scale incoherent structures originating and moving within the bulk plasma region away from the sheath. This is the third regime of plasma behavior. The threshold values of the magnetic field between these regimes were found not to vary with changing plasma reactor geometry (e.g., area ratio between ground and powered electrodes) or the use of an external capacitor between the RF-powered electrode and the RF source. The threshold values of the magnetic field between these regimes shift toward higher values with increasing gas pressure. Analysis of the results indicates that the rotating structures are due to the lower hybrid instability driven by density gradients and electron-neutral collisions. This paper provides guidance on the upper limit of the magnetic field for instability-free operation in low-pressure CCP-based semiconductor deposition and etch systems that use the external magnetic field for plasma uniformity control.

Monte Carlo multiphysics simulation on adaptive unstructured mesh geometry

Monte Carlo simulation based on Constructive Solid Geometry (CSG) brings unique challenges for multiphysics simulation, including establishing field transfers with mesh-based physics codes, the combination of stochastic and deterministic solvers, and high computational expense. In this work, an adaptive, on-the-fly mesh-based Monte Carlo geometry algorithm is implemented in Cardinal to reduce the barrier-to-entry for high-fidelity multiphysics by (i) eliminating ambiguity in defining CSG cells for temperature and density feedback, (ii) enabling simple mesh convergence studies, and (iii) more closely integrating Computer Aided Design (CAD) workflows with Monte Carlo methods. During Picard iterations, an OpenMC mesh geometry is adaptively refined or coarsened by contouring temperature and/or density fields from a thermal-fluid solver. This algorithm is applied to a full-core Molten Salt Fast Reactor (MSFR) geometry with NekRS Large Eddy Simulation (LES) coupled to OpenMC neutron transport. A performance study indicates a net speedup of 2.3× in the OpenMC solver when using an adaptive geometry for cell sizes chosen intermediate to the as-built CAD geometry versus 1:1 element tracking, which points to future algorithmic research in accelerated Monte Carlo mesh tracking.

Optimization of Pyrolysis Parameters by Design of Experiment for the Production of Biochar from Sewage Sludge

Sewage sludge management is a key concern in today’s world. Improper disposal can lead to various environmental issues including air, water and soil pollution. Among the available technologies, thermal treatments, particularly pyrolysis, are gaining interest for their ability to reduce sewage sludge volume and to recover materials and energy from it. This study explored the influence of some relevant parameters in the thermal pyrolysis process. The design of experiment, named central composite design, was accounted to optimize temperature, heating rate and residence time in order to maximize the biochar yield and its CO2 adsorption capacity. A two-factor interaction model provided a satisfactory interpretation of the results. Within the studied ranges, maximum values of 47.8 wt% and 0.514 mol CO2/kg were obtained for the yield and CO2 adsorption capacity, respectively. Two significant experiments were repeated in a different pyrolysis system highlighting how other factors (e.g., reactor geometry, granulometry, etc.) can influence the quantity and the quality of produced biochar. The biochar obtained under the best pyrolysis conditions was characterized by a surface area of 124 m2/g and an ash content of 61 wt%. Lastly, the theoretical energy balance showed that the drying process is the main energy-intensive step in the pyrolysis of sewage sludge.

Monomer Transport by Collisions in (Mini) Emulsion Polymerization, a Personal Perspective

AbstractTransport of monomer from droplets to growing latex particles in emulsion polymerization in general is assumed to proceed via diffusion through the aqueous phase. Especially in miniemulsion polymerizations the direct transfer of very hydrophobic species from droplet to droplet is assumed to also proceed via collisions. Amongst the hydrophobic species where this is shown to play a role are monomers, initiators, inhibitors and (catalytic) chain transfer agents. It is well known that the reactor geometry and the stirring speed can have a profound effect on emulsion polymerizations. The 1972 paper of Nomura on the effect of stirring on emulsion polymerization is cited more than 100 times and until today keeps scientists intrigued. Diffusion limitations of monomer going from the droplet into the aqueous phase can occur for very hydrophobic monomers. The alternative route of transport via collisions is often not considered. In this perspective, paper will discuss the evidence for collision based transfer in miniemulsion polymerization and also consider whether collision based monomer transport can play a role in regular emulsion polymerizations.

An Analytical Model for Electrochemical Tubular Flow Reactors

This paper introduces the first analytical model designed for tubular electrochemical flow reactor, enabling a detailed examination of how reactor geometry and material selection impact performance. The model revealed that certain conditions, such as high electrode resistance relative to charge transfer, electrolyte, and separator resistance, can lead to uneven current distributions and reduced electrode utilization. The model highlights a critical electrode radius, dependent on reactor geometry and material properties, that minimizes the Area Specific Resistance (ASR) while minimizing reactor size. Additionally, it was found that the ASR increases with reactor length, but this effect can be mitigated by using highly conductive electrodes, thus allowing for enhanced power output. These insights provide a foundation for future research and the development of more efficient tubular reactor designs.

A parametric study on hydrogen storage in AB5 hydride alloys: Heat and mass transfer, thermodynamics, and design

The design of heat exchangers plays an important role in the performance of solid-state hydrogen storage devices. In this study, three different designs of hydrogen storage devices were investigated, incorporating phase change material (PCM), specifically, RT25HC into their walls in various shapes. A mathematical model, validated using previous experimental data, was employed to calculate heat and mass transfer and determine the reaction time period. The calculations were conducted using ANSYS Fluent, with a constant hydrogen supply pressure of 10 bars and a temperature of 295 K. The absorption properties of the storage reactor were investigated through various parameters such as liquid fraction, hydrogen concentration, and natural convection heat transfer coefficients. Results showed that the geometric structure and PCM distribution significantly impacted the performance of the hydrogen storage devices. Design 1, with a centralized PCM distribution, demonstrated moderate heat transfer rates and a longer reaction time. Design 2, featuring a more distributed PCM layout, improved heat transfer rates and reduced hydrogen kinetics time by 40%. Design 3, which optimized the geometric structure with advanced PCM shapes, achieved the highest heat transfer rates and improved hydrogen kinetics time by 50%. This design also enabled the storage of thermal energy at a high density, ranging from 10.2 J/g to approximately 190.5 J/g. The study provides critical information on the design of efficient solid hydrogen storage processes. The findings suggest significant potential for improved performance in industrial applications such as electric vehicles and domestic energy supply. The high efficiency of the large-scale reactor is due to its well-designed system, which effectively converts chemical energy into thermal energy. Optimizing the reactor geometry and PCM distribution is crucial for achieving superior hydrogen storage and retrieval performance.

Photocatalytic oxidation of n-decane in a NETmix photoreactor: Insights into the reactor geometry and illumination mechanism

This study focuses on the gas-phase photocatalytic degradation of n-decane using a NETmix photoreactor illuminated by UVA light-emitting diodes. The photoreactor is a static mixer composed of a network of cylindrical chambers interconnected by prismatic channels imprinted in a stainless-steel slab sealed with a borosilicate glass slab (reactor window with 55.7 cm2 of illuminated area). Photocatalytic performance was evaluated as a function of the flow rate (0.67 to 15 L min−1), corresponding to Reynolds number (Re) from 54 to 1209, using NETmix plates with 1 mm (92.3 cm2) and 3 mm depth (165.4 cm2), under back-side (BSI) and front-side (FSI) illumination mechanisms. The TiO2-P25 loading over the borosilicate slab (25–100 mg; BSI optimal: 75 mg) and stainless-steel slabs (100–400 mg; FSI-1/FSI-3 optimal: 200/400 mg) was optimized. Within system constraints, higher Re corresponds to increased reaction rate, apparent quantum yield, and reactivity, with decreased degradation efficiency, due to a reduction in the residence time, regardless of the reactor geometry and illumination. Moreover, operating at the same Re, the NETmix plate with 3 mm depth achieves reaction rates 2.2-/1.9-fold higher than 1 mm, considering FSI/BSI mechanisms. The results were consistent with applied experimental conditions and ray tracing simulations, indicating superior kinetic performance with higher catalyst superficial area. Ray tracing was coupled with Computational Fluid Dynamics (CFD) simulations to evaluate n-decane single-pass oxidation. A 94 % n-decane maximum experimental conversion was attained for a Re of 54, representing an error of ∼ 6.6 % compared to CFD simulation. In these conditions, only 1 % of n-decane was not mineralized, being identified aldehydes, alkanes, carboxylic acids, and ketones as the main reaction by-products. The influence of relative humidity (2 %-40 %) and n-decane inlet concentration (15–114 ppm) were also investigated.

Machine learning-assisted discovery of flow reactor designs

Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current approaches. Furthermore, existing parameterizations of reactor geometries are low dimensional with expensive optimization, limiting more complex solutions. To address this challenge, we have established a machine learning-assisted approach for the design of new chemical reactors, combining the application of high-dimensional parameterizations, computational fluid dynamics and multi-fidelity Bayesian optimization. We associate the development of mixing-enhancing vortical flow structures in coiled reactors with performance and used our approach to identify the key characteristics of optimal designs. By appealing to the principles of fluid dynamics, we rationalized the selection of design features that lead to experimental plug flow performance improvements of ~60% compared with conventional designs. Our results demonstrate that coupling advanced manufacturing techniques with ‘augmented intelligence’ approaches can give rise to reactor designs with enhanced performance.

Biomass gasification tar removal using dielectric barrier discharge reactor: Effect of reactor geometry and carrier gases

This study investigates the impact of reactor geometry (varying external electrode length) of Dielectric Barrier Discharge (DBD) reactors on the decomposition of toluene, a model compound for biomass gasification tar, using different carrier gases and various power levels. Results reveal that toluene decomposition is higher at longer electrode lengths (30 mm) at all power levels tested. Specifically, the toluene decomposition in H2 carrier gas at 30 mm electrode length increased from 67.2 % to 97.5 % with rising power from 5 to 40 W, while it ranged from 52 % to 97.4 % at 15 mm electrode length. The decomposition of toluene was found to be higher in N2 carrier gas than in H2 carrier gas at both discharge lengths. At 30 mm external electrode and with rising power from 5 to 40 W, toluene decomposition ranged from 90.5 % to 98.7 %. Similarly, when the electrode length was reduced from 30 to 15 mm for N2 carrier gas, the decomposition of toluene ranged from 74 % to 97.9 %. Thus, the results indicate that the decomposition of toluene is affected by both the electrode length and the nature of the carrier gas. The effect of electrode length was significant at lower power levels, and the difference between the conversion at both electrode lengths nearly disappeared at higher power levels.

Human-algorithm collaborative Bayesian optimization for engineering systems

Bayesian optimization has proven effective for optimizing expensive-to-evaluate functions in Chemical Engineering. However, valuable physical insights from domain experts are often overlooked. This article introduces a collaborative Bayesian optimization approach that re-integrates human input into the data-driven decision-making process. By combining high-throughput Bayesian optimization with discrete decision theory, experts can influence the selection of experiments via a discrete choice. We propose a multi-objective approach togenerate a set of high-utility and distinct solutions, from which the expert selects the desired solution for evaluation at each iteration. Our methodology maintains the advantages of Bayesian optimization while incorporating expert knowledge and improving accountability. The approach is demonstrated across various case studies, including bioprocess optimization and reactor geometry design, demonstrating that even with an uninformed practitioner, the algorithm recovers the regret of standard Bayesian optimization. By including continuous expert opinion, the proposed method enables faster convergence and improved accountability for Bayesian optimization in engineering systems.

Effect of Radial Neutron Reflector on the Characteristics of Nuclear Fuel Burn-Up Wave in a Fast Neutron Energy Spectrum Multiplying Medium: A Consistent Parametric Approach

Abstract The influence of radial neutron reflector on the build-up and propagation of a nuclear fuel burn-up wave in a fast multiplying medium is investigated using a consistent parametric approach. Coupled multigroup neutron diffusion equations with a burn-up evolution model are simulated on the two-dimensional cylindrical reactor geometry with azimuthal symmetry. Uranium–plutonium transmutation model is considered, and the simulation is performed by using the finite element multiphysics software package comsol. Transient characteristics of the burn-up wave are represented by two new parameters, namely, transient time (TT) and transient length (TL). TT and TL are defined as the time and distance required for the burn-up wave to attain its steady-state nature. Steady-state phases are characterized in terms of wave velocity, full width half maximum (FWHM), and full width 10% of maximum (FW10M). A sensitivity study of steady-state and transient parameters is conducted for the different values of radial reflector thickness. The potential relevance of these characterization parameters on the development of optimal geometrical configuration of radial neutron reflector in breed and burn (B&B)-based reactor design is addressed based on the sensitivity study.

Verification of Adjoint Solution Commutativity with the New OpenNode Nodal Diffusion Code

This paper presents in-depth exploration and verification of the OpenNode nodal diffusion code, a robust tool designed for multigroup neutron diffusion simulations under steady-state conditions. Leveraging the Nodal Expansion Method with a quartic polynomial and moments weighting method, OpenNode demonstrates exceptional accuracy in approximating nodal surface fluxes, further enhanced by the Quadratic Transverse Leakage approximation. The critical concept of commutativity between adjoint and forward solutions is thoroughly investigated, serving as a benchmark for the code’s reliability in predicting system responses, determining single-point reactor kinetics parameters, and facilitating perturbation analyses. The paper meticulously details OpenNode’s methodology for adjoint neutron flux computation, unraveling its rigorous approach through transposition operations and intricate mathematical transformations. Noteworthy features, including support for second and fourth polynomial orders; versatile computation modes; different mesh points; and seamless integration with Python, PyQt5, and Blender, underscore OpenNode’s adaptability. Results from comprehensive analysis of the two-dimensional and three-dimensional International Atomic Energy Agency core benchmark problem showcase OpenNode’s prowess. The code excels in reactor geometry visualizations, benchmark parameters, and neutronic analysis, with a particular emphasis on commutativity verification against various benchmarked codes. The precision of OpenNode is further demonstrated in power distribution analyses, revealing remarkable proximity to reference values and symmetrical power distribution patterns.

A comprehensive comparative study of ultrasound-alkaline and thermal-alkaline hydrolysis of duck feather

Feathers, as a byproduct of the poultry industry, present a significant source of keratinous waste. Conventional methods have been widely used to extract keratin from feathers; however, they are associated with limitations such as high operational costs and environmental concerns. It is, therefore, crucial to develop cost-effective and time-efficient methods for extracting keratin on a large scale. In recent years, ultrasound-assisted alkaline hydrolysis has emerged as a promising and sustainable approach for efficient keratin recovery. This study compares the hydrolysis time, yield, and chemical properties of keratin extracted from feathers using ultrasound-assisted alkaline hydrolysis and thermal alkaline hydrolysis (hot plate method). The influence of factors such as particle size, alkali concentration, liquid-to-solid ratio, reactor geometry, temperature of keratin colloid upon precipitation, precipitation pH, and precipitating acid was investigated. Favorable conditions for ultrasound-assisted alkaline hydrolysis were found to be 3% NaOH, a 10:100 (w/v) solid-to-liquid ratio, using a cylindrical vessel, and an ultrasonic energy density of 360 kJ/L, with pH adjustment to 4.5 using citric acid after cooling to room temperature. This method outperformed the thermal approach, yielding 70% keratin in 25 min, compared to 23% in 90 min using a hot plate, due to the exothermic effect of cavitation. The results provide valuable insights into the potential of ultrasound-assisted alkaline hydrolysis as an eco-friendly and cost-effective approach to address the management of keratinous waste and enhance the overall recovery of keratin.

Enabling MOCVD production on next generation 150 mm Indium Phosphide wafer size

150 mm Indium Phosphide wafers are now commercially available with crystal quality comparable to wafer of smaller radius. This may pave the way for scaling up the production of a multitude of photonic devices for Datacoms operating in the 1.30-1.55μm infrared range with a gain in wafer surface of factor 4 and a reduction of roughly 50% in die cost. To achieve this goal, it is of utmost importance to prove that both AlGaInAs and InGaAsP quaternary compound semiconductors can be grown by metal–organic chemical vapor deposition (MOCVD) on wafers of larger sizes with both thickness and composition uniformities comparable to those achievable on 75 mm. In this article, we report pioneering production technology developments based on the Planetary Reactor® design. Both reactor and related inlet geometry have been deeply revisited with the introduction of a novel 4-fold injector, which in combination with Cl2 In-situ chamber clean, prove to enable such transition in wafer size. Sub-nanometric photoluminescence in-wafer uniformities are demonstrated and historic challenges, such as drift in material composition of highly sensitive InGaAsP alloys during a production campaign, are addressed thanks to this unique combination. Uniformity, tunability and reproducibility results are thus presented for two prototypical case scenarios: a highly strained AlGaInAs multiple quantum well (MQW) and a bulk InGaAsP layer with wavelength emission of 1550 nm and 1100 nm respectively to corroborate reactor flexibility in meeting industry requirements for next device generation.

Modeling heat and mass transfer in metal hydride hydrogen storage systems: Impact of operating parameters and reactor geometry

This work introduces a transient 2D axis-symmetrical model for hydrogen absorption in a cylindrical LaNi5 reactor employing finite volume method with a fully implicit Euler's time integration scheme, coupling equations for heat, mass, and momentum transport. The validated model is used to investigate the impacts of pressure, cooling fluid temperature, and variations in reactor geometry and size on temperature and reacted fraction profiles. The findings reveal that the charging pressure affects both peak temperature and reaction kinetics, whereas cooling fluid temperature predominantly impacts the absorption kinetics. A comparative analysis of two models, one incorporating Darcy's velocity and one without, demonstrates that while Darcy's law introduces numerical instability in the coupled equations, its impact on the model outcomes is negligible. The effect of changing the non-homogeneous Neumann to Dirichlet boundary condition is also demonstrated to anticipate the utilization of phase change materials (PCM) instead of the cooling fluid.