Compartmental models for continuous flow reactors derived from CFD simulations

Oxidation of 51 micropollutants during drinking water ozonation: Formation of transformation products and their fate during biological post-filtration

Micropollutants (MP) with varying ozone-reactive moieties were spiked to lake water in the influent of a drinking water pilot plant consisting of an ozonation followed by a biological sand filtration. During ozonation, 227 transformation products (OTPs) from 39 of the spiked 51 MPs were detected after solid phase extraction by liquid chromatography high-resolution mass spectrometry (LC-HRMS/MS). Based on the MS/MS data, tentative molecular structures are proposed. Reaction mechanisms for the formation of a large number of OTPs are suggested by combination of the kinetics of formation and abatement and state-of-the-art knowledge on ozone and hydroxyl radical chemistry. OTPs forming as primary or higher generation products from the oxidation of MPs could be differentiated. However, some expected products from the reactions of ozone with activated aromatic compounds and olefins were not detected with the applied analytical procedure. 187 OTPs were present in the sand filtration in sufficiently high concentrations to elucidate their fate in this treatment step. 35 of these OTPs (19%) were abated in the sand filtration step, most likely due to biodegradation. Only 24 (13%) of the OTPs were abated more efficiently than the parent compounds, with a dependency on the functional group of the parent MPs and OTPs. Overall, this study provides evidence, that the common assumption that OTPs are easily abated in biological post-treatment is not generally valid. Nevertheless, it is unknown how the OTPs, which escaped detection, would have behaved in the biological post-treatment.

Linking CFD and Kinetic Models in Anaerobic Digestion Using a Compartmental Model Approach

Understanding mixing behavior and its impact on conversion processes is essential for the operational stability and conversion efficiency of anaerobic digestion (AD). Mathematical modelling is a powerful tool to achieve this. Direct linkage of Computational Fluid Dynamics (CFD) and the kinetic model is, however, computationally expensive, given the stiffness of the kinetic model. Therefore, this paper proposes a compartmental model (CM) approach, which is derived from a converged CFD solution to understand the performance of AD under non-ideal mixing conditions and with spatial variation of substrates, biomass, pH, and specific biogas and methane production. To quantify the effect of non-uniformity on the reactor performance, the CM implements the Anaerobic Digestion Model 1 (ADM1) in each compartment. It is demonstrated that the performance and spatial variation of the biochemical process in a CM are significantly different from a continuously stirred tank reactor (CSTR) assumption. Hence, the assumption of complete mixed conditions needs attention concerning the AD performance prediction and biochemical process non-uniformities.

Optimization of Reaction Selectivity Using CFD-Based Compartmental Modeling and Surrogate-Based Optimization

Mixing is considered as a critical process parameter (CPP) during process development due to its significant influence on reaction selectivity and process safety. Nevertheless, mixing issues are difficult to identify and solve owing to their complexity and dependence on knowledge of kinetics and hydrodynamics. In this paper, we proposed an optimization methodology using Computational Fluid Dynamics (CFD) based compartmental modelling to improve mixing and reaction selectivity. More importantly, we have demonstrated that through the implementation of surrogate-based optimization, the proposed methodology can be used as a computationally non-intensive way for rapid process development of reaction unit operations. For illustration purpose, reaction selectivity of a process with Bourne competitive reaction network is discussed. Results demonstrate that we can improve reaction selectivity by dynamically controlling rates and locations of feeding in the reactor. The proposed methodology incorporates mechanistic understanding of the reaction kinetics together with an efficient optimization algorithm to determine the optimal process operation and thus can serve as a tool for quality-by-design (QbD) during product development stage.

Modelling of Chemical Reactors: From Systemic Approach to Compartmental Modelling

To take into account the impact of hydrodynamics on their behavior, chemical reactors are traditionally modeled as an association of smaller ideal reactors: perfectly stirred or plug flow reactors. This modeling is mainly based on the reactor hydrodynamics but sometimes also on phenomena governing the considered process such as heat or mass transfer or chemical reaction. The approaches encountered in the literature start from the most basic one in which the whole reactor is considered as an ideal reactor, up to a very fine discretization using Computational Fluid Dynamics (CFD). In between, the reactor can be described as an association of a small number of ideal reactors: this is the systemic approach. Another intermediate approach has also been recently developed: the compartmental method, where all compartments are assumed to be perfectly mixed. In the compartment method, the compartment number is significantly more important than in the systemic approach - but lower than for CFD. Furthermore, these compartments are chosen to be relevant regarding their position in space as opposed to systemic models in which, in most of cases, only the global physical behavior is taken into account. Compared to CFD, compartment models are less computationally demanding while taking into account the most important flow features. The present review describes the different types of modeling commonly used in chemical reaction engineering during the last 60 years from the systemic approach to CFD, with a focus on the attractive compartmental modelling. In particular, the methodologies encountered to determine the compartment structure are detailed, as well as the different possibilities to determine the turbulent fluxes between compartments.

Effect of sensor location on controller performance in a wastewater treatment plant

Complete mixing is hard to achieve in large bioreactors in wastewater treatment plants. This often leads to a non-uniform distribution of components such as dissolved oxygen and, hence, the process rates depend on them. Furthermore, when these components are used as input for a controller, the location of the sensor can potentially affect the control action. In this contribution, the effect of sensor location and the choice of setpoint on the controller performance were examined for a non-homogeneously mixed pilot bioreactor described by a compartmental model. The impacts on effluent quality and aeration cost were evaluated. It was shown that a dissolved oxygen controller with a fixed setpoint performs differently as a function of the location of the sensor. When placed in a poorly mixed location, the controller increases the aeration intensity to its maximum capacity leading to higher aeration costs. When placed just above the aerated zone, the controller decreases the aeration rate resulting in lower dissolved oxygen concentrations in the remainder of the system, compromising effluent quality. In addition to the location of the sensor, the selection of an appropriate setpoint also impacts controller behavior. This suggests that mixing behavior of bioreactors should be better quantified for proper sensor location and controller design.

Evaluating hydraulic and disinfection efficiencies of a full-scale ozone contactor using a RANS-based modeling framework

The capability of predicting hydraulic and disinfection efficiencies of ozone disinfection contactors is essential for evaluating existing contactors and improving future designs. Previous attempts based on ideal and non-ideal models for the hydraulics and simplified mechanisms for chemical reaction modeling have resulted in low accuracy and are restricted to contactors with simple geometries. This manuscript develops a modeling framework for the ozonation process by combining computational fluid dynamics (CFD) with a kinetics-based reaction modeling for the first time. This computational framework has been applied to the full-scale ozone contactor operated by the City of Tampa Water Department. Flow fields, residence time distribution, ozone concentration distribution, and concentration-contact time (CT) distribution within the contactor have been predicted via the computational framework. The predictions of ozone and bromate concentrations at sample points agree well with physical experimental data measured in the contactor. The predicted CT values at the contactor outlet demonstrate that the disinfection performance of the ozone contactor operated by the City of Tampa Water Department is sufficient to meet regulation requirements. The impact of seasonal flow rate change on disinfection performance is found to be significant and deserves attention during the management and operation of a water treatment plant.

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.