Advanced CFD model of multiphase photobioreactors for microalgal derived biomass production

Development of more efficient algal photobioreactors (PBRs) is driven by increasing interest in algaculture for the production of fuels, chemicals, food, animal feed, and medicine, as well as carbon capture. While at present, the cost and microalgae production capacity are one of its restrictions when competition with other biodiesel feedstock. The objective of the present work is to develop and validate better computational models to investigate the interplay between fluid hydrodynamics, radiation transport and algae growth, which is crucial to determine the performance and scalability of algae photobioreactors. First, a detailed review of the pertinent information required for developing a comprehensive computation model for photobioreactors was conducted. The current status of the submodels, including hydrodynamics and mass transfer multiphase CFD models, radiation transport models, microalgae growth rate models, and coupling method for developing a comprehensive model for PBRs was outlined. Second, an Eulerian two-fluid model for gas-liquid Taylor-Couette flow was proposed and validated. The CFD was based on the RANS approach with constitutive closures for interphase forces and liquid turbulence. The model was validated by comparison with previously published experimental data. The mechanism of bubble radial non-uniformity distribution was discussed and the relative importance of various interphase forces was demonstrated. Third, the validated two fluid CFD model was employed to simulate the local values of the mass transfer coefficient based on the Higbie theory. A novel approach was proposed to estimate the mass transfer exposure time. This approach automatically selects the appropriate expression (either the penetration model or eddy cell model) based on local flow conditions. The simulation predictions agree well with experimental foundlings, which demonstrates that the adaptive mass transfer model has the ability to correctly description of both local and global mass transfer of oxygen in a semi-batch gas–liquid Taylor–Couette reactor. Forth, microalgae culture experiment was conducted to identify the limiting factor in the Taylor-Couette photobioreactor. The characteristic time scales for mixing, mass transfer and biomass growth was compared. It is found that algal growth rate in Taylor vortex reactors is not limited by fluid mixing or interphase mass transfer, and therefore the observed biomass productivity improvements are likely attributable to improved light utilization efficiency (high-frequency light/dark cycles). Fifth, a commonly used Lagrangian strategy for coupling the various factors influencing algal growth was employed whereby results from computational fluid dynamics and radiation transport simulations were used to compute numerous microorganism light exposure histories, and this information, in turn, was used to estimate the global biomass specific growth rate. The simulation predictions were compared with experimental measurements and the origin of weaknesses of the commonly used Lagrangian approach model was traced. Sixth, an alternative Eulerian computational approach for predicting photobioreactor performance was proposed, wherein a transport equation for algal growth kinetics is solved, thereby obviating the need to carry out thousands of particle tracking simulations. The simulation predictions were compared with experimental measurements and commonly used Lagrangian approach model

Simulation and analysis of open raceway pond system at Manit, Bhopal

Microalgae can become completely faster than terrestrial plants and are a successful feedstock for viable appreciation including items that envelop pharmaceuticals, neutraceuticals, proteins and most significantly biofuels. Since the biomass productivity of microalgae absolutely depends emphatically on the temperature of development, point-by-point data on the temperature of the reactor as a component of time and topographic area is essential to assess the sincere capability of microalgae as a traditional feedstock. Microalgae is indeed a promising source of renewable biofuels, and techno-financial upgrades can be made by improving and controlling the stage of biomass development. This research explores the improved performance of a first-standard green growth development display that encompasses the effect of regular (and such) notions of climate in an open system related to creation. Thus, the simulation of the procedure is stochastic just as basic; it helps restore the dissemination of outcomes from normal changeability that speak to the daily acknowledgement. It also communicates variety day-to-night in the vitality based on cycling sunlight. The simulation is then used to optimize the design of the pond and the manages (growth time, depth of the raceway, pH control, etc.) to enhance protability. Because the simulation is stochastic, nonlinear, and with different optima, an optimization method for multiplayer direct inquiry is used with relentless state assembly criteria. Conclusions are that (1) representing common variety in optimization prompts detectable protability improvement, (2) model impact investigation uncovers where key science exploration is expected to support basic techno-monetary wonders, and (3) the stochastic optimization approach is broadly relevant

Simulations of Photobioreactors from Hydrodynamics and Mass Transfer Point of View

Simulations of photobioreactors with microalgae-specific cultures is a field that connects microbiology with the multiphase fluid dynamics. With microalgae cultivation, it is necessary to account various phenomena, e.g., multiphase hydrodynamics with water, CO2 bubbles and microalgae, multiphase species mass transfer, radiation transport, light attenuation, growth and culmination of microalgae and their effect on fluid properties. Computational model presented in this doctoral dissertation thesis links multiphase hydrodynamic model and the species mass transfer model. In the thesis, there is an overview of applicable computational models for the given types of photobioreactors. The multiphase hydrodynamic model and the species mass transfer model then draw from this overview. Next, the accuracy of these sub-models was compared with laboratory experiments. As a result, the developed computational model of the photobioreactor can be further extended with other sub-models, i.e., the irradiation model and the biomass growth model.Simulations of photobioreactors with microalgae-specific cultures is a field that connects microbiology with the multiphase fluid dynamics. With microalgae cultivation, it is necessary to account various phenomena, e.g., multiphase hydrodynamics with water, CO2 bubbles and microalgae, multiphase species mass transfer, radiation transport, light attenuation, growth and culmination of microalgae and their effect on fluid properties. Computational model presented in this doctoral dissertation thesis links multiphase hydrodynamic model and the species mass transfer model. In the thesis, there is an overview of applicable computational models for the given types of photobioreactors. The multiphase hydrodynamic model and the species mass transfer model then draw from this overview. Next, the accuracy of these sub-models was compared with laboratory experiments. As a result, the developed computational model of the photobioreactor can be further extended with other sub-models, i.e., the irradiation model and the biomass growth model.

Overview on the hydrodynamic conditions found in industrial systems and its impact in (bio)fouling formation

Supplementary data to this article can be found online at https://doi.org/10.1016/j.cej.2021.129348.Biofouling is the unwanted accumulation of deposits on surfaces, composed by organic and inorganic particles and (micro)organisms. Its occurrence in industrial equipment is responsible for several drawbacks related to operation and maintenance costs, reduction of process safety and product quality, and putative outbreaks of pathogens. The understanding on the role of operating conditions in biofouling development highlights the hydrodynamic conditions as key parameter. In general, (bio)fouling occurs in a higher extension when laminar flow conditions are used. However, the characteristics and resilience of biofouling are highly dependent on the hydrodynamic conditions under which it is developed, with turbulent conditions being associated to recalcitrant biodeposits. In industrial settings like heat exchangers, fluid distribution networks and stirred tanks, hydrodynamics play a dual function, affecting the process effectiveness while favouring biofouling formation. This review summarizes the hydrodynamics played in conventional industrial settings and provides an overview on the relevance of hydrodynamic conditions in biofouling development as well as in the effectiveness of industrial processes.This work was financially supported by: Base Funding - UIDB/00511/2020 of LEPABE and UIDB/00081/2020 of CIQUP funded by national funds through the FCT/MCTES (PIDDAC); Project Bio cide_for_Biofilm - PTDC/BII-BTI/30219/2017 - POCI-01-0145-FEDER 030219, ABFISH – PTDC/ASP-PES/28397/2017 - POCI-01-0145- FEDER-028397 and ALGAVALOR - POCI-01-0247-FEDER-035234, fun ded by FEDER funds through COMPETE2020 – Programa Operacional Competitividade e Internacionalizaçao ˜ (POCI) and by national funds (PIDDAC) through FCT/MCTES; Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER 000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte; FCT/ SFRH/BD/147276/2019 (Susana Fernandes) and SFRH/BSAB/150379/2019 (Manuel Simoes).info:eu-repo/semantics/publishedVersio

A review of process intensification applied to solids handling

Process intensification (PI) is a strategy aimed at transforming conventional chemical processes into more economical, productive and green processes. Its fundamental concept hinges upon the volume reduction of processing equipment resulting in enhanced mixing and heat/mass transfer as well as a multitude of other benefits. To date, the focus of PI has been on processes mainly involving gas/liquid systems. Solids handling applications have been more limited as fouling and blockages can occur due to large concentrations of solids in smaller equipment sizes. Appropriately designed equipment is therefore a key consideration for intensifying industrially-relevant solids handling processes. In this review paper, we highlight a number of solid processing applications including precipitation, separation, granulation and milling, etc. where PI has been demonstrated. Much effort has been directed at reactive crystallization and precipitation in various intensified technologies, exploiting their enhanced mixing capabilities to produce uniformly distributed nano-particles. Generally, the objective in many of these processes has focused on transforming solids handling in batch processes into continuous ones with processing time reduction and improved energy efficiency. The review highlights the considerable opportunity for further development of multifunctional technologies in solids handling applications such as granulation and drying, the subject of a European Commission-funded HORIZON 2020 project

Microalgae for aquaculture

In 2007, the project ‘Zeeuwse Tong’ (Zeeland Sole) was founded with support of the province of Zeeland, the Netherlands. The aim of the Zeeuwse Tong project was to establish an innovative land-based integrated multi-trophic aquaculture sector, which is producing sole, ragworms, algae, shellfish and saline crops in close harmony with nature. The project was divided into two sub-projects: The integrated saline aquaculture farm and the integrated nursery. The research described in this thesis resides within the integrated nursery subproject. In this project the rearing of fingerlings of sole would be combined with the cultivation of microalgae as feed for shellfish larvae and spat inside a greenhouse. An integrated nursery in a greenhouse has several advantages: a greenhouse with a multipurpose use of space, sole culture combined with the cultivation of microalgae and shellfish larvae or spat, an integrated thermoregulation and the reuse of nutrients from the wastewater of the fish basins for the production of microalgae in closed photobioreactors (PBRs). For this thesis, a horizontal tubular PBR needed to be designed and constructed to investigate the productivity and yield of microalgae applied as feed for shellfish larvae or spat, within the context of an integrated nursery

Updating the Lambda modes of a nuclear power reactor

[EN] Starting from a steady state configuration of a nuclear power reactor some situations arise in which the reactor configuration is perturbed. The Lambda modes are eigenfunctions associated with a given configuration of the reactor, which have successfully been used to describe unstable events in BWRs. To compute several eigenvalues and its corresponding eigenfunctions for a nuclear reactor is quite expensive from the computational point of view. Krylov subspace methods are efficient methods to compute the dominant Lambda modes associated with a given configuration of the reactor, but if the Lambda modes have to be computed for different perturbed configurations of the reactor more efficient methods can be used. In this paper, different methods for the updating Lambda modes problem will be proposed and compared by computing the dominant Lambda modes of different configurations associated with a Boron injection transient in a typical BWR reactor. (C) 2010 Elsevier Ltd. All rights reserved.This work has been partially supported by the Spanish Ministerio de Educacion y Ciencia under projects ENE2008-02669 and MTM2007-64477-AR07, the Generalitat Valenciana under project ACOMP/2009/058, and the Universidad Politecnica de Valencia under project PAID-05-09-4285.González Pintor, S.; Ginestar Peiro, D.; Verdú Martín, GJ. (2011). Updating the Lambda modes of a nuclear power reactor. Mathematical and Computer Modelling. 54(7):1796-1801. https://doi.org/10.1016/j.mcm.2010.12.013S1796180154