Application of Computational Fluid Dynamics to Raceways Combining Paddlewheel and CO2 Spargers to Enhance Microalgae Growth

Journal of Bioscience and Bioengineering VOL. 129 No. 1, 93e98, 2020 www.elsevier.com/locate/jbiosc

Application of computational ﬂuid dynamics to raceways combining paddlewheel and CO2 spargers to enhance microalgae growth

Adi Kusmayadi,1 George P. Philippidis,2 and Hong-Wei Yen1,2,*

Department of Chemical and Material Engineering, Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Xitun District, Taichung 40704, Taiwan1 and Patel College of Global Sustainability, University of South Florida, 4202 E. Fowler Avenue, CGS101, Tampa, FL 33620, USA2

Received 16 May 2019; accepted 17 June 2019 Available online 19 July 2019 The present study investigated the effect of light intensity and mixing on microalgae growth in a raceway by comparing the performance of a paddlewheel to a combination of paddlewheel and CO2 spargers in a 20 L raceway. The increase of light intensity was known to be able to increase the microalgal growth rate. Increasing paddlewheel rotation speed from 13 to 30 rpm enhanced C. vulgaris growth by enhancing culture mixing. Simulation results using computational fluid dynamics (CFD) indicated that both the turnaround areas of the raceway and the area opposite the paddlewheel experienced very low flow velocities (dead zones) of less than 0.1 m/min, which could cause cell settling and slow down growth. The simulated CFD velocity distribution in the raceway was validated by actual velocity measurements. The installation of CO2 spargers in the dead zones greatly increased flow velocity. The increase of paddlewheel rotation speed reduced the dead zones and hence increased algal biomass production. By complementing the raceway paddlewheel with spargers providing CO2 at 30 mL/min, we achieved a dry cell weight of 5.2 ± 0.2 g/L, which was about 2.6 times that obtained without CO2 sparging. Ó 2019, The Society for Biotechnology, Japan. All rights reserved.

[Key words: Computational ﬂuid dynamics; Raceway; Chlorella vulgaris; Paddlewheel; CO2 sparging]

The threat of global warming has encouraged the development provides good light distribution and nutrient availability, as well as of renewable energy to replace carbon-intensive fossil fuels (1). heat dissipation and increased CO2 utilization, making the process Microalgae are a promising source of renewable transportation of photosynthesis more effective and leading to higher biomass fuels thanks to their high growth rate, which enables them to productivity (11). The lack of rigorous culture mixing has been re- double in mass within hours, and their high content of lipids that ported to lead to cell membrane breakdown for Spirulina (12). are used for biofuel production (2). In addition, microalgae can As a result, preventing cell settling through thorough mixing is serve as renewable sources of chemicals used in a wide range of of paramount importance to raceway algae cultivation. Recently, applications, including cosmetics and nutraceuticals (3). Algal this goal has been aided by the use of computational fluid dynamics biomass productivity is influenced by light intensity, CO2 provision, (CFD) in the design and operation of raceways (10). Researchers temperature, pH, and nutrient supplementation (4). have investigated the effect of mixing on the hydrodynamics of The cultivation of microalgae can be conducted in both closed raceways to minimize energy utilization (7). CFD simulations have and open systems (5). Closed photobioreactors (PBR) can provide been used to investigate paddlewheel rotation speeds and baffle an environment that fosters fast growth and high biomass pro- installation in raceway systems (13,14). The light/darkness (L/D) ductivity, as they allow tight control of cultivation conditions and cycles applied on microalgae cells cultivated in a raceway based on minimize the risk of contamination. However, their high capital and a Lagrangian particle tracking method have been studied by iden- operating costs are major disadvantages, especially for commodity tifying the cell trajectories and their hydrodynamic characteristics. products, such as biofuels (6e8). Moreover, PBRs are not easy to The results indicate that L/D cycles can be decreased with an in- scale-up, which impedes commercialization (3). crease in paddlewheel rotational speed in the range 5e12 rpm. The open system of raceways is often utilized for large scale Moreover, introduction of flow-deflector baffles in raceways can cultivation of microalgae (9). It has simplicity of design and oper- greatly increase the light time and the ratio of light time to L/D cycle ation and is easy to scale-up (10). However, adequate mixing in the for microalgae cells (15). raceway is required to avoid settling of microalgal biomass that, in CFD simulations have also been performed on a novel algae turn, leads to lower cell growth and biomass productivity due to raceway integrated design (ARID) system to obtain velocity profiles limited cell exposure to light and nutrients. Thorough mixing (16). This raceway was positioned on the ground at a small slope, so that water could flow in laterally-laid serpentine channels at a low rate driven by gravitation. The low flow rate of water overflowed * Corresponding author at: Department of Chemical and Material Engineering, the lateral channel walls and mixed with the main flow in the next Tunghai University, No. 1727, Sec. 4, Taiwan Boulevard, Xitun District, Taichung lower channel, thus creating better mixing. Even in such a complex þ þ 40704, Taiwan. Tel.: 886 4 23590262; fax: 886 4 23590009. raceway system, measurements and CFD simulation results E-mail address: [email protected] (H.-W. Yen).

FIG. 1. Effect of light intensity on the growth of C. vulgaris in the raceway.

matched in a satisfactory way, indicating that CFD simulations are a water and air with a coefficient of surface tension of about 72 mN m 1 at 25C. reliable tool in designing raceways for algae cultivation. The selection of the QUICK scheme was discretized for convective terms and the diffusions terms were central-differenced. The setting of time size in the solution The main objective of this study was to determine the effect of tab of the ANSYS FLUENT was 0.01 s (9). Finally, the walls and the floor of the culture mixing on algae growth in a raceway by comparing mixing raceway system were defined as no slip boundaries in the simulation. provided by a paddlewheel at a variable rotation speed with mixing provided by a combination of paddlewheel and CO2 spargers stra- tegically placed in low flow velocity areas. The flow velocity profile RESULTS AND DISCUSSION in the raceway was simulated using CFD and was validated with flow velocity measurements. Effect of light intensity on algal growth in a raceway For the growth of microalgae, the effect of light intensity on the microalgal concentration is significant while the light intensity less MATERIALS AND METHODS than the saturation level. In stirred PBRs, the light availability of microalgal cultivation usually switches between the photosyn- Microalgae and the culture of medium The strain utilized in this study was Chlorella vulgaris, which was kindly provided by professor Jo-Shu Chang, National thesis (near the surface) area and the light-limitation area (down to Cheng Kung University, Taiwan. Algal basal medium was used to cultivate the the bottom), while mutual shading of cells causes the steep microalgae in the raceway system. The composition of the algal basal medium gradients of light intensity decreasing (19). Therefore, it was , was 1.25 g/L KNO3, 1.25 g/L KH2PO4, 1.00 g/L MgSO4 7H2O, 0.5 g/L EDTA, 0.1142 g/ confirmed that the severe mixing can avoid the cells continuous LHBO , 0.0882 g/L ZnSO ,7H O, 0.0498 g/L FeSO ,7H O, 0.111 g/L CaCl ,2H O, 3 3 4 2 4 2 2 2 staying in the dark area and retard the growth rate. The effects of 0.0142 g/L MnCl2,4H2O, 0.0071 g/L MnO3, 0.0157 g/L CuSO4,5H2O, and 0.0049 g/L Co(NO3),6H2O. Dry cell biomass of g/L was measured in this study using the light intensity on the growth of Chlorella in a raceway at 20 rpm moisture meter. The cultivations were performed at room temperature of of paddlewheel speed were examined in this study. 25e30 C for all tests. As shown in Fig. 1, the growth of Chlorella in this raceway can be Configuration of the raceway system The experiments were conducted in a obviously enhanced by the increase of light intensity at 20 rpm of lab-scale raceway system made of fiberglass with dimensions of 50 cm fi paddlewheel speed. The nal biomass concentration will be almost length 30 cm width 14 cm depth. The paddlewheel was constructed of e m stainless steel and consisted of 4 blades with 18 cm length and 10 cm width. The proportional to the light intensity within the range of 19 38 mol/ 2 paddlewheel velocity for mixing was set at 13, 20, and 30 rpm for 14 days. All the m s. The results indicated that the light intensity will be the critical raceway experiments were carried out with 20 L of medium resulting in a culture factor in the raceway operation with the fixed wheelpaddle rota- e fl depth of 7 cm. A continuous light intensity was provided by using 2 4 uorescent tion speed. Even the paddlewheel can only provide the horizontal lamps at 9.5 (mmol/m2 s) each lamp. Culture flow velocities were measured using flow that might be not sufficiency for the vertical flow. And also the a flow velocity measurement device (model FW450, JDC Corporation, Taipei City, 2 Taiwan). maximum light intensity providing of 38 mmol/m s providing in CFD modeling of velocity profile in a raceway The CFD package ANSYS was this study has not achieved the saturation level. Therefore, the in- employed to simulate algae culture flow in the raceway system. The CFD simulation crease of light intensity will be almost proportional to the biomass required the construction of a geometric model in the ANSYS Design Modeler concentration. Algal cultures become photoinhibited once the (ANSYS Software Company, Canonsburg, PA, USA). The raceway system was divided photosynthetically active radiation (PAR) value exceeds the satu- into a paddlewheel movement zone and a culture medium zone, which intersect at the cylindrical interface (17). The tetrahedral structural mesh was selected in ANSYS ration threshold. It was reported the rate of photosynthesis does 2 Design Mesh with 209,960 nodes and 183,615 elements for the simulation (18). The not increase beyond a PAR value of about 100e200 mmol/m s and mesh was divided into two parts: a sliding mesh for the cylindrical area surrounding all the excess light is wasted (20). An increasing incident irradiance the paddlewheel and a stationary mesh for the remaining domain of the level generally increases raceway productivity, as the local irradi- computation. The simulator used a multiphase model to attain steady state and ance level in the broth declines rapidly with culture depth and a select a transient simulation. Turbulent flow was calculated by a standard k-ε turbulence model, which was selected because of its wide range of applications. high surface irradiance generally means a larger illuminated cul- The volume of fluid (VOF) method is commonly used to track the free interface of ture volume. VOL. 129, 2020 CFD ON RACEWAY DESIGN 95

FIG. 2. Effect of paddlewheel rotation speed on the growth of C. vulgaris in the raceway.

Effect of paddlewheel speed on algal growth in a hydrodynamic flow and potentially better CO2 dissolution in the raceway In the raceway operation, the paddlewheel rotation culture medium that enhances cell growth. Higher speeds, speed is an important parameter due to the requirement for hy- however, may lead to culture overflow outside the raceway and drodynamic flow across the length of the raceway to support the will incur higher energy consumption, which will increase growth of microalgae. Thorough culture mixing enhances CO2 operating costs at commercial scale. To reduce energy dissolution and prevents the cells from settling to the bottom of the consumption in raceway cultivations, researchers have tried to raceway, which leads to poor growth due to light and nutrient modify the paddlewheel design to enhance flow dynamics and limitations. Three paddlewheel rotation speeds were tested at 13, cell growth (8). As a result of inclining the paddlewheel blades by 20, and 30 rpm and the results are shown in Fig. 2. The paddlewheel 15, Chlorella pyrenoidosa achieved a higher growth rate in a rotation speed of 30 rpm resulted in the highest terminal 1.85 g/L of raceway than with a traditional paddlewheel. Maximum attained dry biomass, which is higher than that obtained at 13 rpm and biomass concentration was 11% higher at 0.92 g/L and areal 20 rpm. Apparently, high rotation speed leads to intense productivity was 17% higher at 11.89 g/m2/day (8).

FIG. 3. Combined effect of paddlewheel (at 20 rpm) and spargers at various CO2 ﬂow rates on C. vulgaris growth in the raceway. 96 KUSMAYADI ET AL. J. BIOSCI.BIOENG.,

FIG. 4. Correlation between CFD-simulated flow velocities and actual flow velocities determined with the use of a flow measurement device in the raceway at a paddlewheel rotation speed of 20 rpm.

Our results suggest that stronger mixing resulting from high (dark zone) to the surface of the raceway (light zone), which is paddlewheel rotation speeds can enhance cell growth. They are in crucial for photosynthetic efficiency. Efforts have been reported on agreement with previous reports on the need to enhance nutrient designing raceway ponds in ways that enhance vertical mixing and distribution in the culture and prevent cell settling and shortage of CO2 residence time (21). It should be noted that given the shallow light and carbon dioxide (21). In addition to growth inhibition depth of the culture in our raceway (7 cm), sparged CO2 at low flow resulting from insufficient mixing, it has been reported that oxygen rates does not have sufficient residence time in the liquid culture to supersaturation can also lead to a reduction in biomass productivity dissolve and become available to the cells. This may be the reason in raceways (22). To avoid oxygen accumulation in the culture, CO2 why at 10 mL/min CO2 the cell OD560 achieved was statistically sparging can be used during raceway operation to rapidly remove indistinguishable from that without any CO2 sparging. oxygen. As mentioned previously, increasing paddlewheel rotation CFD application to the raceway operation Given the fl speed has its limitations from a ow and energy consumption complexity of fluid flow in a raceway, CFD simulations were per- standpoint. As a result, we next examined the introduction of CO2 formed to calculate the flow velocity of the algal culture throughout spargers at several points in the raceway to assess the effect of a the raceway at various paddlewheel rotation speeds. The flow ve- combination of horizontal and vertical mixing on microalgal locity predictions of the CFD model were compared to actual ve- growth. locity measurements taken with the use of a flow velocity meter at Effect of combining paddlewheel and gas spargers on algal several points in the raceway. The flow velocity comparison was growth Two CO2 spargers were installed in the two areas of examined at 5 paddlewheel rotation speeds of 13, 20, 30, 40 and the raceway with the lowest flow rate (turnaround area of the 50 rpm. As shown in Fig. 4, the correlation between predictions (y) raceway after the paddlewheel and on the side of the raceway and measurements (x) was strong, as described by the derived opposite the paddlewheel), as identified by the CFD simulations equation y ¼ 1.0764x þ 0.0841 with a correlation coefficient of presented in the next section. This way, in terms of mixing, the R2 ¼ 0.9918. Hence, the CFD-simulated depiction of the raceway horizontal culture flow created by the rotation of the paddlewheel appears to provide a good representation of its actual operation. was complemented by the vertical flow force of the gas spargers, as The CFD simulations were conducted at five settings of intense mixing in the raceway can lead to higher growth rate of paddlewheel speed (13, 20, 30, 40 and 50 rpm) and the resulting microalgae (12). Nevertheless, excessive shear stress can cause flow velocity profile of the raceway is shown in Fig. 5. increased cell mortality, decreased growth rate and cell viability, As seen in Fig. 5, the areas with the slowest velocity, less than or even cell lysis. For the strain-Chlorella used in this study, the 0.1 m/s, are located in the turnaround area of the raceway after the tip-speed of 0e5.89 m/s is the suggested range of shear stress (23). paddlewheel and on the side of the raceway opposite the paddle- In this part of the study, the paddlewheel rotation speed was wheel. A minimum channel velocity of 0.2 m/s has been suggested fixed at 20 rpm. The two gas spargers were supplied with a mix of to ensure that the velocity everywhere in the raceway is sufficient air and CO2 and were operated at 5 mL/min pure CO2 each (total to keep the cells suspended in the culture (20). Areas having a fluid 10 mL/min of gas), 10 mL/min (total 20 mL/min), and 15 mL/min velocity of less than 0.1 m/s have been termed dead zones, as cell (total 30 mL/min). As seen in Fig. 3, the introduction of CO2 spargers settling may occur there due to the inadequacy of culture flow to enhanced cell growth significantly. A maximum dry biomass of maintain cells in suspension (7,24). In such dead zones cell growth 5.2 0.2 was obtained at 30 mL/min CO2, as compared to 3.2 0.2, rate will be retarded due to insufficient light intensity and possibly 1.9 0.1, and 1.7 0.2 of dry biomass in the raceway runs with 20, limited nutrient availability. Therefore, CO2 provision through 10, and 0 mL/min CO2 sparged, respectively. Hence, providing CO2 spargers and the resulting vertical mixing can play an important at the selected two areas of the raceway appeared to have a role in enhancing cell growth (25). noticeably positive effect on cell growth, which is in agreement As clearly seen in Fig. 5, increasing paddlewheel rotation speed with cell growth enhancement reported in the literature (11). decreases the dead zone areas (blue areas), especially in the turn- Vertical mixing influences microalgal growth as it affects the fre- around area of the raceway. Due to friction at the bends of the quency at which cells will travel from the bottom of the raceway raceway, flow velocity drops in the turnaround area. This drop, in VOL. 129, 2020 CFD ON RACEWAY DESIGN 97

FIG. 5. Velocity distribution in the raceway with counter clockwise flow as determined by CFD simulations at paddlewheel rotation speeds of (A) 13 rpm, (B) 20 rpm, (C) 30 rpm, (D) 35 rpm, and (E) 50 rpm. turn, results in low velocities also in the central area of the raceway paddlewheel speeds will result in higher energy use and possibly in opposite the paddlewheel. With the increase in rotation speed, the operational issues, such as culture spillage outside the raceway, an blue areas shrink significantly as paddlewheel speed rises from 13 to optimization analysis should be performed before selecting the best 50 rpm, although this improvement comes at the expense of higher paddlewheel speed value for a particular raceway system. For the power consumption (10). Regarding the suggested minimum veloc- geometry of our raceway reactor carrying 20 L of culture at a depth of ity value of 0.2 m/s (20), it seems that a paddlewheel rotation speed 7 cm, a paddlewheel rotation speed of 20 rpm combined with CO2 of 50 rpm can adequately achieve a velocity profile in excess of that spargers at the previously cited two areas was deemed to be the most value practically everywhere in the raceway (Fig. 5E). Since high suitable selection for proper operation. 98 KUSMAYADI ET AL. J. BIOSCI.BIOENG.,

ACKNOWLEDGMENTS 11. Putt, R., Singh, M., Chinnasamy, S., and Das, K. C.: An efficient system for carbonation of high-rate algae pond water to enhance CO2 mass transfer, Bioresour. Technol., 102, 3240e3245 (2011). The authors gratefully acknowledge the financial support 12. Ali, H., Cheema, T. A., Yoon, H. S., Do, Y., and Park, C. W.: Numerical pre- received for this study from Taiwan’s Ministry of Science and Tech- diction of algae cell mixing feature in raceway ponds using particle tracing nology (MOST) under grant numbers MOST 107-2621-M-029-001. methods, Biotechnol. Bioeng., 112, 297e307 (2015). 13. Chen, Z., Jiang, Z., Zhang, X., and Zhang, J.: Numerical and experimental study on the CO2 gas-liquid mass transfer in flat-plate airlift photobioreactor with fl e References different baf es, Biochem. Eng. J., 106, 129 138 (2016). 14. Pirasaci, T., Manisali, A. Y., Dogaris, I., Philippidis, G., and Sunol, A. K.: Hy- drodynamic design of an enclosed horizontal bioreactor (HBR) for algae 1. Hreiz, R., Sialve, B., Morchain, J.Ô., Escudié, R., Steyer, J. P., and Guiraud, P.: cultivation, Algal Res., 28,57e65 (2017). Experimental and numerical investigation of hydrodynamics in raceway re- 15. Chen, Z., Zhang, X., Jiang, Z., Chen, X., He, H., and Zhang, X.: Light/dark cycle e actors used for algaculture, Chem. Eng., 250, 230 239 (2014). of microalgae cells in raceway ponds: effects of paddlewheel rotational speeds 2. Slegers, P. M., Lösing, M. B., Wijffels, R. H., van Straten, G., and van and baffles installation, Bioresour. Technol., 219, 387e391 (2016). Boxtel, A. J. B.: Scenario evaluation of open pond microalgae production, Algal 16. Xu, B., Li, P., and Waller, P.: Study of the flow mixing in a novel arid raceway Res., 2, 358e368 (2013). for algae production, Renew. Energy, 62, 249e257 (2014). 3. Pires, J. C. M., Alvim-Ferraz, M. C. M., and Martins, F. G.: Photobioreactor 17. Yang, Z., Cheng, J., Ye, Q., Liu, J., Zhou, J., and Cen, K.: Decrease in light/dark design for microalgae production through computational fluid dynamics: a cycle of microalgal cells with computational fluid dynamics simulation to review, Renew. Sust. Energ. Rev., 79, 248e254 (2017). improve microalgal growth in a raceway pond, Bioresour. Technol., 220, 4. Mata, T. M., Martins, A. A., and Caetano, N. S.: Microalgae for biodiesel pro- 352e359 (2016). duction and other applications: a review, Renew. Sust. Energ. Rev., 14, 18. Nikolaou, A., Booth, P., Gordon, F., Yang, J., Matar, O., and Chachuat, B.: e 217 232 (2010). Multi-physics modeling of light-limited microalgae growth in raceway ponds, 5. Wigmosta, M. S., Coleman, A. M., Skaggs, R. J., Huesemann, M. H., and IFAC-PapersOnLine, 49, 324e329 (2016). Lane, L. J.: National microalgae biofuel production potential and resource de- 19. Carvalho, A. P., Silva, S. O., Baptista, J. M., and Malcata, F. X.: Light re- mand, Water Res., 47,1e13 (2011). quirements in microalgal photobioreactors: an overview of biophotonic as- 6. Dogaris, I., Welch, M., Meiser, A., Walmsley, L., and Philippidis, G.: A novel pects, Appl. Microbiol. Biotechnol., 89, 1275e1288 (2011). horizontal photobioreactor for high density cultivation of microalgae, Bio- 20. Chisti, Y.: Large-scale production of algal biomass: raceway ponds, pp. 21e40, resour. Technol., 198, 316e324 (2015). in: Bux, F. and Chisti, Y. (Eds.), Algae biotechnology. Green energy and Tech- 7. Hadiyanto, H., Elmore, S., Van Gerven, T., and Stankiewicz, A.: Hydrodynamic nology. Springer, Cham (2016). e evaluations in high rate algae pond (HRAP) design, Chem. Eng. J., 217, 231 239 21. Kumar, K., Mishra, S. K., Shrivastav, A., Park, M. S., and Yang, J. W.: Recent (2013). trends in the mass cultivation of algae in raceway ponds, Renew. Sust. Energ. 8. Zeng, F., Huang, J., Meng, C., Zhu, F., Chen, J., and Li, Y.: Investigation on novel Rev., 51, 875e885 (2015). raceway pond with inclined paddle wheels through simulation and microalgae 22. Mendoza, J. L., Granados, M. R., de Godos, I., Acién, F. G., Molina, E., culture experiments, Bioprocess Biosyst. Eng., 39, 169e180 (2016). Heaven, S., and Banks, C. J.: Oxygen transfer and evolution in microalgal 9. Amini, H., Hashemisohi, A., Wang, L., Shahbazi, A., Bikdash, M., KC, D., and culture in open raceways, Bioresour. Technol., 137, 188e195 (2013). Yuan, W.: Numerical and experimental investigation of hydrodynamics and 23. Wang, C. and Lan, C. Q.: Effects of shear stress on microalgae e a review, light transfer in open raceway ponds at various algal cell concentrations and Biotechnol. Adv., 36, 986e1002 (2018). e medium depths, Chem. Eng. Sci., 156,11 23 (2016). 24. Sompech, K., Chisti, Y., and Srinophakun, T.: Design of raceway ponds for 10. Huang, J., Qu, X., Wan, M., Ying, J., Li, Y., Zhu, F., Wang, J., Shen, G., Chen, J., producing microalgae, Biofuels, 3, 387e397 (2012). and Li, W.: Investigation on the performance of raceway ponds with internal 25. Perner-Nochta, I. and Posten, C.: Simulations of light intensity variation in structures by the means of cfd simulations and experiments, Algal Res., 10, photobioreactors, J. Biotechnol., 131, 276e285 (2007). 64e71 (2015).