Comprehensive computational model for combining fluid hydrodynamics, light transport and biomass growth in a Taylor vortex algal photobioreactor: Eulerian approach

Systematic CFD-based evaluation of physical factors influencing the spatiotemporal distribution patterns of microplastic particles in lakes

Spatiotemporal distribution patterns of microplastic (MP) particles in lakes hinge on both the physical conditions in the lake and particle properties. Using numerical simulations, we systematically investigated the influence of lake depth and bathymetry, wind and temperature conditions, MP particle release location and timing, as well as particle diameter (10, 20, and 50 μm). Our results indicate that maximum lake depth had the greatest effect on the residence time in the water column, as it determines the settling timescale and occurrence of hydrodynamic complexity such as density-driven flows in the lake. Increasing particle size from 10 to 20 and 50 μm also significantly reduced the residence time making particle size the factor with the second strongest effect on the residence time and, in turn, on the availability of MP particles for uptake by organisms. Changing bathymetry from a uniform to a non-uniform had a less pronounced effect on particle residence time compared to maximum depth and particle size. Release location, wind conditions, and release time had comparably little effect on particle behavior but became more important as MP particle size decreased. The release of the 10 μm MP particles in the deeper lakes with uniform bathymetry during summer with stable thermal stratification, resulted in a nearly month-long turnover phase in the fall in which both settling and rising of particles occurred simultaneously. This was caused by convective heat and water transport during this period. In these scenarios about 2.6 to 5.4 % of the released MP particles were held in or returned to the water layers near the lake surface. While acknowledging the dominant role of lake depth and MP particle size on the particle residence time, this study further emphasizes that it is ultimately a particular combination of different factors and their interactions that shape MP distribution patterns in lakes.

Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.

Recent advances in computational fluid dynamics (CFD) modelling of photobioreactors: Design and applications

The development of photobioreactor is important for sustainable production of renewable fuels, wastewater treatment and CO₂ fixation. For the design and scale-up of a photobioreactor, CFD can be used as an indispensable tool. The present study reviews the recent status of computational flow modelling of various types of photobioreactors, involving fluid dynamics, light transport, and algal growth kinetics. An integrated modelling approach of hydrodynamics, light intensity, mass transfer, and biokinetics in photobioreactor is discussed further. Also, this reviews intensified system to improve the mixing, and light intensity of photobioreactors. Finally, the prospects and challenges of CFD modelling in photobioreactors are discussed. Multi-scale modelling approach and development of low-cost efficient computational framework are the areas to be considered for modelling of photobioreactor in near future. In addition, it is necessary to use process intensification techniques for photobioreactors for improving their hydrodynamics, mixing and mass transfer performances, and algal growth productivity.

Study on Numerical Simulation for Component Transportation and Oil Displacement of a Microbial System

Component transportation is one of the main mechanisms for numerical simulation in microbial oil recovery. However, the research on the component transportation considering the inhibition of metabolites is very limited. A mathematical model of oil displacement in a microorganism system including microbial growth and metabolism equation, component transport equation, and porous media physical property variation equation was established in this paper. The equation was discretized and solved by implicit pressure and explicit saturation. The MATLAB simulation results showed that the chromatographic separation between microorganisms and nutrients happened because of the adsorption of porous media and the activity of microorganisms during the transportation, and the separation degree of the chromatography became higher as the permeability became lower and the injection speed became slower. The multislug alternative injection mode could reduce the degree of chromatographic separation, and the recovery rate can be increased to 50.82%. The results of this study could provide theoretical guidance for the popularization and application of microbial enhanced oil recovery (MEOR).

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Synergising biomass growth kinetics and transport mechanisms to simulate light/dark cycle effects on photo-production systems

Light attenuation is a primary challenge limiting the upscaling of photobioreactors for sustainable bio-production. One key to this challenge, is to model and optimise the light/dark cycles so that cells within the dark region can be frequently transferred to the light region for photosynthesis. Therefore, this study proposes the first mechanistic model to integrate the light/dark cycle effects into biomass growth kinetics. This model was initially constructed through theoretical derivation based on the intracellular reaction kinetics, and was subsequently modified by embedding a new parameter, effective light coefficient, to account for the effects of culture mixing. To generate in silico process data, a new multiscale reactive transport modelling strategy was developed to couple fluid dynamics with biomass growth kinetics and light transmission. By comparing against previous experimental and computational studies, the multiscale model shows to be of high accuracy. Based on its simulation result, an original correlation was proposed to link effective light coefficient with photobioreactor gas inflow rate; this has not been done before. The impact of this study is that by using the proposed mechanistic model and correlation, we can easily control and optimise photobioreactor gas inflow rates to alleviate light attenuation and maintain a high biomass growth rate.

Influence of photobioreactor configuration on microalgal biomass production

Biodiesel production from microalgae depends on the biomass concentration and lipid content in microalgal cells. Photobioreactors (PBRs) facilitates cultivation of microalgae and renders better process control than open systems. However, reactor configuration and consequential hydrodynamics considerably influence biomass and lipid production from microalgae. Here, four different configurations of PBRs, viz. airlift and bubble column with orifice sparger and newly designed ring sparger, were investigated. Resulting volumetric mass transfer coefficient, mixing time, and shear stress were analyzed at different air flow rates to realize their influence on biomass and lipid production from Neochloris oleoabundans UTEX 1185. Bubble column reactor with ring sparger was observed to exhibit superior performance, which was subsequently simulated using a two-phase Eulerian model to comprehend the influence of air flow rates on mixing time. The developed computational model corroborates well with the experimental findings of optimum air flow rate for maximum biomass yield in bubble column configuration.

Hydrodynamic performance of floating photobioreactors driven by wave energy

BACKGROUND

Unlike conventional cultivation systems, liquid mixing in floating photobioreactors (PBRs) is solely induced by their hydrodynamic movement in response to waves, and this movement is affected by the wave conditions (wave height and wave period), the PBR configuration and the culture depth. However, to the best of our knowledge, a practical study of the hydrodynamic movements of PBRs has not been previously conducted.

RESULTS

This study aims to investigate the hydrodynamic performance of floating PBRs in response to wave conditions. First, the effects of the experimental wave height (2-10 cm) and wave period (0.8-1.8 s) on movement was investigated using two 1.0 m2 PBR models: a square PBR (1.0 m/1.0 m; length/width) and a rectangular PBR (1.7 m/0.6 m). The results indicated that wave movement became not only more intense with increasing wave height, but also less intense when the wave period decreased. However, the square PBR experienced more intense movement than the rectangular PBR, but also little mooring force. The effects of culture depth (0.5, 1.0 and 2.0 cm) were investigated and the results showed that the culture depth significantly affected the hydrodynamic movements of the PBRs; however, the mooring forces were unaffected. Finally, the movement and mooring-line forces of PBRs equipped with different mooring systems were investigated. The use of two different mooring systems had little effect on PBR movement; however, a mooring system with floaters was able to significantly reduce the mooring line forces compared to a system without floaters. During this study, the greatest force (10.5 N) was found for the rectangular PBR using a mooring system without floaters, whereas the lowest force (0.67 N) was observed for a rectangular PBR using a mooring system with floaters.

CONCLUSIONS

These studies have provided basic data describing the fluid dynamics of floating PBRs; as well as their structural design and scale up. These results also provide guidance for the selection of ocean fields with suitable wave conditions; as well as a proper mooring methods to ensure safe operation.

A critical review on designs and applications of microalgae-based photobioreactors for pollutants treatment

The development of the photobioreactors (PBs) is recently noticeable as cutting-edge technology while the correlation of PBs' engineered elements such as modellings, configurations, biomass yields, operating conditions and pollutants removal efficiency still remains complex and unclear. A systematic understanding of PBs is therefore essential. This critical review study is to: (1) describe the modelling approaches and differentiate the outcomes; (2) review and update the novel technical issues of PBs' types; (3) study microalgae growth and control determined by PBs types with comparison made; (4) progress and compare the efficiencies of contaminants removal given by PBs' types and (5) identify the future perspectives of PBs. It is found that Monod model's shortcoming in internal substrate utilization is well fixed by modified Droop model. The corroborated data also remarks an array of PBs' types consisting of flat plate, column, tubular, soft-frame and hybrid configuration in which soft-frame and hybrid are the latest versions with higher flexibility, performance and smaller foot-print. Flat plate PBs is observed with biomass yield being 5 to 20 times higher than other PBs types while soft-frame and membrane PBs can also remove pharmaceutical and personal care products (PPCPs) up to 100%. Looking at an opportunity for PBs in sustainable development, the flat plate PBs are applicable in PB-based architectures and infrastructures indicating an encouraging revenue-raising potential.

Multiphysics simulation of algal growth in an airlift photobioreactor: Effects of fluid mixing and shear stress

A multiphysics model has been developed to predict the effects of fluid mixing and shear stress on microalgal growth in an airlift photobioreactor. The model integrates multiphase flow dynamics, radiation transport, shear stress, and algal growth kinetics using an Eulerian approach. The model is first validated by comparing its predictions with experimental data, and then the radiation transport and algal growth kinetics submodels are added to predict biomass accumulation under different flow conditions. The simulations correctly predict biomass growth curves for a wide range of superficial gas flow rates and demonstrate that biomass productivity increases with increased gas flow rate due to better light delivery to microorganisms. However, at the higher gas flow rates considered, shear stress on microorganisms inhibits biomass growth. Lastly, it is shown that the Eulerian approach used here provides a less cumbersome computational approach and provides better predictions than the circulation time and Lagrangian approaches.