UiPath Platform: The Backend Engine Powering Your Automation - Session 1
151 shastri
1. Optimization of a Novel
Photobioreactor Design using
Computational Fluid Dynamics
Abhinav Soman
Department of Biotechnology
VIT University, Vellore
Yogendra Shastri
Department of Chemical Engineering
Indian Institute of Technology Bombay
2. Algal biofuels: Potential fuel
option with many challenges
Advantages:
Higher
yield per unit area
Productive
land not required
Compatible
with fresh and saline water
Challenges:
High
cost of cultivation and harvesting
Low
yield requiring significant drying
3. Closed Photobioreactor (PBR)
cultivation shows promise
Attribute
Open-pond
Photobioreactor
Cost
Low
High
Yield
Low
High
Contamination
High
Low
Target
yield: 2-3 gm/liters
4. Several bottlenecks exist in using
a photobioreactor (PBR)
Expensive to build and maintain
High power consumption
Overall efficiency is low
Limitations to scalability
5. PBR design plays a crucial role
in its performance
Performance parameters of interest:
Light
penetration
Hydrodynamics
Mixing
and settling
Proposal:
Develop
a novel PBR design
Develop
a computational fluid dynamics (CFD) model
Compare
the performance of the novel design with
conventional design using CFD
6. Two promising designs – Air lift
and Flat plate PBR
• Less photoinhibition, even under
high light intensity
• Better liquid flow
• Enhanced gas exchange
• Better irradiation cycle
• Suitable for shear sensitive strains
Courtesy Xu et al. (2009)
• Low surface area to volume ratio
• Strong self shading for poorly
circulated PBRs
• Scale up not economical
7. Two promising designs – Air lift
and Flat plate PBR
• High surface area to volume
ration
• Lower accumulation of
dissolved oxygen
• Low power consumption
• Good mass transfer
capability
Courtesy Singh and Sharma (2012)
• Photoinhibition likely for
high intensity radiations
• Low photosynthetic
efficiency
• Damage to cells due to
high stress
9. Proposed design combines the airlift
and flat plate PBR designs
Outer body
with flat plates
for better light
intake
Central draft
tube from an
air-lift reactor
14. Computational Fluid Dynamics
(CFD) simulations
Develop a CFD model for a air-lift PBR design
published in literature
Validate the conventional model results using
the CFD model
Adapt the CFD model for the proposed novel
design
Compare the simulation results of the
conventional and novel design
15. CFD Model Development and
Validation
Air-lift model studied by Luo and AL-Dahan (2011)
Outer tube:
• Height: 1.13 m
• Diameter: 0.13 m
Inner tube:
• Height: 1.05 m
• Diameter: 0.09 m
Boundary Conditions:
• Inlet : Superficial gas velocity –
1cm/s
• Incident radiation : 50 W/m2
• Outlet : Pressure outlet
Courtesy : Luo and AlDahan (2011)
Geometry used
for FLUENT
simulation
16. CFD Model Details
• 3D steady state simulation with coarse griding
• Flow Modelling: Eulerian –Eulerian multiphase
modelling
• Turbulence Modelling : Standard k-ɛ model
with mixture multiphase model
• Drag Force : Schiller-Naumann drag correlation
• Irradiation simulation: Discrete Ordinates Model
(DO)
• Particle trajectory tracking : Discrete Phase
Modelling (DPM)
17. The observations reported in Luo and AlDahan (2011) were reproduced reasonably
Slight deviations were probably due to a different drag model
21. “Width” had a significant impact
on the irradiance
Good irradiance history for small
width (2 cm)
Particle trapped in the
concentric space due to higher
width (6 cm)
22. Optimized design was determined
based on the simulation results
Property
Value
Outer cuboid
height (m)
1.15
Inner draft tube
height (m)
“Width” (m)
1.05
Draft tube inner
diameter (m)
0.09
Top and bottom
clearance (m)
0.05
0.02
25. Conclusions
The novel design has better light/dark cycling
patterns for algal cells.
A higher superficial gas velocity must be to
achieve higher gas holdup and turbulent
kinetic energy
Additional simulations with algal growth kinetics
needed
26. References
Hu-Ping Luo, Muthanna H. Al-Dahhan.(2011). Verification and validation of
CFD simulations for local flow dynamics in a draft tube airlift
bioreactor, Chemical Engineering Science. 66: 907-923.
Ling Xu, Pamela J. Weathers, Xue-Rong Xiong, Chun-Zhao Liu. (2009)
Microalgal bioreactors: Challenges and opportunities, Eng. Life Sci. 3: 178–
189.
O. Pulz. (2001). Photobioreactors: production systems for phototrophic
microorganisms, Appl Microbiol Biotechnol. 57: 287–293.
Aditya M. Kunjapur and R. Bruce Eldridge.( 2010), Photobioreactor Design
for Commercial Biofuel Production from Microalgae, Ind. Eng. Chem. Res.
49: 3516–3526.
R.N. Singh, Shaishav Sharma.(2012). Development of suitable
photobioreactor for algae production – A review, Renewable and
Sustainable Energy Reviews, Volume 16, Issue 4, 2347-2353
30. Air-lift model studied by Luo and ALDahan (2011)
•
Unstructured tetrahedral mesh was generated comprising
68864 elements
•
The bubble diameter was set 0.005 m (Simcik et al., 2011)
•
Air inlet velocity of 0.38 m/s in the axial direction
•
Air volume fraction was set to 0.5
•
Simulation was initialized with 0.01 volume fraction and 0.01
m/s air inlet velocity
•
Single wavelength region (400 nm to 700 nm) for DO model
•
Water refractive index was set to 1.34 and absorbtion
coefficient was set to 0.3
•
Surface injection was used to inject 44 particles from the inlet
surface that mimic the microalgae size (5 µm) and neutral
buoyancy (998 g/m3)