CFD analysis of turbulence non-homogeneity in mixing vessels

Mathematical Modeling of Hydrodynamics in Bioreactor by Means of CFD-Based Compartment Model

This study presents the procedure of deriving a compartmental model (CM) based on an analysis obtained from the computational fluid dynamics (CFD) model of a bioreactor. The CM is composed of two parts, a structural (that takes into account the architecture of the mathematical model), and a parametric part (which contains the extrinsic parameters of the model). The CM is composed of the branches containing the set of perfectly mixed continuous stirred-tank reactors (CSTRs) in a configuration that matches the bioreactor’s flow patterns. Therefore, this work’s main objective was to develop a mathematical model that incorporated the flow field obtained by CFD technique. The proposed mathematical model was validated by means of the experimental data in the form of the residence time distribution (RTD) measurements.

Design of waste stabilization pond systems: A review

A better design instruction for waste stabilization ponds is needed due to their growing application for wastewater purification, increasingly strict environmental regulations, and the fact that most of previous design manuals are outdated. To critically review model-based designs of typical pond treatment systems, this paper analyzed more than 150 articles, books, and reports from 1956 to 2016. The models developed in these publications ranged from simple rules and equations to more complex first-order and mechanistic models. From a case study on all four approaches, it appeared that rules of thumb is no longer a proper tool for pond designs due to its low design specification and very high output variability and uncertainty. On the other hand, at the beginning phase of design process or in case of low pressure over land and moderate water quality required, regression equations can be useful to form an idea for pond dimensions. More importantly, mechanistic models proved their capacity of generating more precise and comprehensive designs but still need to overcome their lack of calibration and validation, and overparameterization. In another case study, an essential but often overlooked role of uncertainty analysis in pond designs was investigated via a comparison between deterministic and uncertainty-based approaches. Unlike applying a safety factor representing all uncertainty sources, probabilistic designs quantify the uncertainty of model outputs by including prior uncertainty of inputs and parameters, which generates more scientifically reliable outcomes for decision makers. Based on these findings, we advise engineers and designers to shift from the conventional approaches to more innovative and economic tools which are suitable for dealing with large variations of natural biological systems.

Visual study of mass transfer characterization in the process of biological catalytic hydration of acrylonitrile using pendant drop method

In this work, a pendant drop method was utilized to observe visually the mass transfer process of an acrylonitrile droplet during bio-hydration.

Advanced Design of Industrial Mixers for Fluid Foods Using Computational Fluid Dynamics

This work focuses on discontinuous (batch) vertical fluid mixing systems for food fluids with particles. A properly designed mixing process has to provide two main results: a satisfactory homogeneity of the product and the preservation of the integrity of the solid particles. The main problem in the design of a mixer for fluid–solid suspensions is to identify the operating levers which act in order to optimize the performance of the process, while preserving the integrity of the pieces. The purpose of this work is to identify some structural and physical parameters that have the strongest influence on the performance of the mixing process, in order to obtain useful indications for the design of mixing systems.

Different mixer designs were thus analyzed thanks to computational fluid dynamics simulations, from which some key performance indicators (KPIs) related to the effectiveness of the mixing process were obtained. An analysis of variance and a residual analysis were then performed in order to assess the significance of the influence of each input parameter (position of the rotor, fluid viscosity, and aspect ratio), on the individual KPIs and on the global performance of the mixer. From these analyses, some conclusions useful to choose an appropriate design solution for fluid mixers were derived.

A compartmental model to describe hydraulics in a full-scale waste stabilization pond

The advancement of experimental and computational resources has facilitated the use of computational fluid dynamics (CFD) models as a predictive tool for mixing behaviour in full-scale waste stabilization pond systems. However, in view of combining hydraulic behaviour with a biokinetic process model, the computational load is still too high for practical use. This contribution presents a method that uses a validated CFD model with tracer experiments as a platform for the development of a simpler compartmental model (CM) to describe the hydraulics in a full-scale maturation pond (7 ha) of a waste stabilization ponds complex in Cuenca (Ecuador). 3D CFD models were validated with experimental data from pulse tracer experiments, showing a sufficient agreement. Based on the CFD model results, a number of compartments were selected considering the turbulence characteristics of the flow, the residence time distribution (RTD) curves and the dominant velocity component at different pond locations. The arrangement of compartments based on the introduction of recirculation flow rate between adjacent compartments, which in turn is dependent on the turbulence diffusion coefficient, is illustrated. Simulated RTD's from a systemic tanks-in-series (TIS) model and the developed CM were compared. The TIS was unable to capture the measured RTD, whereas the CM predicted convincingly the peaks and lags of the tracer experiment using only a minimal fraction of the computational demand of the CFD model. Finally, a biokinetic model was coupled to both approaches demonstrating the impact an insufficient hydraulic model can have on the outcome of a modelling exercise. TIS and CM showed drastic differences in the output loads implying that the CM approach is to be used when modelling the biological performance of the full-scale system.

CFD investigation of turbulence models for mechanical agitation of non-Newtonian fluids in anaerobic digesters

This study evaluates six turbulence models for mechanical agitation of non-Newtonian fluids in a lab-scale anaerobic digestion tank with a pitched blade turbine (PBT) impeller. The models studied are: (1) the standard k-ɛ model, (2) the RNG k-ɛ model, (3) the realizable k-ɛ model, (4) the standard k-ω model, (5) the SST k-ω model, and (6) the Reynolds stress model. Through comparing power and flow numbers for the PBT impeller obtained from computational fluid dynamics (CFD) with those from the lab specifications, the realizable k-ɛ and the standard k-ω models are found to be more appropriate than the other turbulence models. An alternative method to calculate the Reynolds number for the moving zone that characterizes the impeller rotation is proposed to judge the flow regime. To check the effect of the model setup on the predictive accuracy, both discretization scheme and numerical approach are investigated. The model validation is conducted by comparing the simulated velocities with experimental data in a lab-scale digester from literature. Moreover, CFD simulation of mixing in a full-scale digester with two side-entry impellers is performed to optimize the installation.

Compartmental models for continuous flow reactors derived from CFD simulations

Reactor modeling is of major interest in environmental technology. In this context, new contaminants with higher degradation requirements increase the importance of reactor hydraulics. CFD (Computational Fluid Dynamics) may meet this challenge but is expensive for everyday use. In this paper, we provide research and practice with a methodology designed to automatically reduce the complexity of such a high-dimensional flow model to a compartmental model. The derivation is based on the concentration field of a reacting species which is included in the steady state CFD simulation. While still capturing the most important flow features, the compartmental model is fast, easy to use, and open for process modeling with yet unknown compounds. The inherent overestimation of diffusion by compartmental models has been corrected by locally adjusting turbulent fluxes. We successfully applied the methodology to the ozonation process and experimentally verified it with tracer experiments. The loss of information was quantified as a deviation from CFD performance prediction for different reactions. With increasing discretisation of the compartmental model, these deviations diminish. General advice on the necessary discretisation is given.