CFD Based Design of Solar Drying Systems

CFD Based Design of
Solar Drying Systems
Dr. Ganesh Visavale
CCTech, Pune

Motivation
• To provide a simple and suitable dryer providing better
product quality
• A well designed solar dryer can compensate the limitations of
conventional dryers
• Successful use in drying of agricultural and marine products
on commercial scale

© Copyrights 2010 : www.cctech.co.in

Outline
• What is CFD?
• Critical issues in Solar Drying Systems addressed by CFD
• Test case: Experimental and CFD validation of Solar Cabinet
Dryer
• Challenges in applying CFD
• Answer to the challenges
CCTech – Simulation is The Future


Computational Fluid Dynamics
• Flow phenomena captured on computer
– Flow of fluids and heat
– Can include mass transfer and reactions
– Single and multi-phase applications

•
•
•
•
•

Makes it possible to perform Analysis Led Design (ALD)
Predicting flow characteristics in advance
Assessing existing designs
Huge savings on cost of parametric experiments and time!!
Has been driving design changes in Automotive, HVAC, Marine,
Chemical industry, etc.


Solar Drying Systems (SDS)
Solar Cabinet Dyers

Tunnel Dryers

Greenhouse Dryers

Critical issues in SDS
• Advantages
– Many over the conventional open sun drying mode

• Limitations of Solar drying systems:
– Higher initial cost of the system
– Cost of operation
– Non-uniform drying of material


CFD’s answer to SDS
• Excellent flow visualization capabilities
• Effects like Coanda effect can be captured in CFD
– Experimental perturbations replaced by Numerical errors!

• Identifying dead zones
– Re-circulations reduce heat and mass transfer efficiencies

• Possible solution to non-uniform drying
• Quick parametric studies possible!!
• Quantitative predictions validated against one set of
experimental values
– Validated model imperative

Test Case: Solar Cabinet Dryer
3

4

5

7
2

8
1


Schematic diagram of a solar cabinet dryer

6

Test Case: Solar Cabinet Dryer

???

CFD Modelling Challenges
• Geometrical modelling and discretization (meshing)
• Boundary conditions
• Inlet: Constant mass flow rate of dry air
• Outlet: Pressure outlet

• Multi-species simulation with mixture fluid having the density
varying according to ideal gas law


Domain of Interest : 3D CAD Model

Outlet


Inlet

Domain of Interest : 3D Mesh


Equation Solution : CFD - FVM
• Physics :
– Incompressible , turbulent flow of hot air

• Inputs
– Mass flow rate of hot air at inlet
– Pressure at outlet (atmospheric pressure)

• Discritized equation solution using FVM
– ANSYS FLUENT Solver


Visualization : Virtual Simulation

Velocity contours along mid-plane


Velocity contours along vertical mid-plane


Total pressure contours along vertical mid-plane


Pathlines


Tray Section analysis
• Experimental observations:
– Right-tray section had non-uniform flow distribution due to the
preceding diverging section
– Left-tray section had uniform flow distribution
• Flow alignment done by the preceding right-tray section

Left Tray

Right Tray

• Flow non-uniformities in Left and Right tray sections

Simulation confirms the experimental findings

Particle Tracks


Challenges for applying CFD
• Domain expertise needed
• Reliable and efficient software programs
– Pre-processors: Commercial CAD packages, GAMBIT, ICEM-CFD
– Solver/Post-processor: ANSYS FLUENT, ANSYS CFX

• Computational facilities
– Fast processors and clusters
– Database management

• Initial cost of learning the CFD tools and developing the best-practices
• Running cost of retaining man-power and software licenses
• Best-practices, once developed become benchmarks for future parametric
studies


CCTech CFD Corporate Services
• Consultancy Services
– Domain Solutions
•
•
•
•
•
•
•
•

Design optimization
Renewable energy equipments
Automobile Turbomachinery
Building HVAC
Material processing
Thermal and CHT
Biomedical science
Control valves


CCTech CFD Corporate Services
• Training Services
– Student Training
• Six months professional course (DACFD)
• Six weeks course for working professionals (ICEM & FLUENT)
• Academic Internship and Mentoring program (AiM CFD)

– Corporate Training
•
•
•
•

Introductory courses - 7
Domain specific courses – 5
Industry specific courses - 7
Software specific courses - 27


Partial List of Clients


CFD Team
Sandip Jadhav
M.Tech. (Aero), IIT Bombay

Chief Executive Officer (COO)
Expertise: CAD Geometry and meshing

Vijay Mali
M.Tech. (Aero), IIT Bombay

Chief Operational Officer (COO)
Expertise: CFD, Multidisciplinary Design Optimization

Santosh Bhoosthali
M.Tech. (Thermal), IIT Bombay

VP Consultancy
Expertise: Heat Transfer, Turbomachinery

Nem Kumar
B.Tech. (Aero), Punjab Engineering
College

Chief Information Officer (CIO)
Expertise: Mathematics and Physics

Sam Mathew
B.Tech. (Chemical) IIT Bombay

Assistant Manager (CFD)
Expertise : Multiphase and Combustion Modelling

Dr. Ganesh Visavale
Ph.D. UDCT Mumbai

Program Manager (CFD)
Expertise : Heat Transfer, Solar Drying


Advisory, Consultants and Technologist
Advisory

Technologist

Consultants

Thank You


CFD Based Design of Solar Drying Systems

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (20)

Similar to CFD Based Design of Solar Drying Systems

Similar to CFD Based Design of Solar Drying Systems (20)

More from iMentor Education

More from iMentor Education (20)

Recently uploaded

Recently uploaded (20)

CFD Based Design of Solar Drying Systems