CFD Based Design of Solar Drying Systems

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Information about CFD Based Design of Solar Drying Systems

Published on January 28, 2014

Author: DrGaneshVisavale



The presentation was made at the "Business Meet on Applications of solar drying systems in domestic, industrial and commercial applications", SPRERI, Anand, India.
It presents the advantages of CFD as a design tool to design better 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 :

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 © Copyrights 2010 :

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. © Copyrights 2010 :

Solar Drying Systems (SDS) Solar Cabinet Dyers Tunnel Dryers Greenhouse Dryers © Copyrights 2010 :

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 © Copyrights 2010 :

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 © Copyrights 2010 :

Test Case: Solar Cabinet Dryer 3 4 5 7 2 8 1 © Copyrights 2010 : Schematic diagram of a solar cabinet dryer 6

Test Case: Solar Cabinet Dryer ??? © Copyrights 2010 :

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 © Copyrights 2010 :

Domain of Interest : 3D CAD Model Outlet © Copyrights 2010 : Inlet

Domain of Interest : 3D Mesh © Copyrights 2010 :

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 © Copyrights 2010 :

Visualization : Virtual Simulation Velocity contours along mid-plane © Copyrights 2010 :

Visualization : Virtual Simulation Velocity contours along vertical mid-plane © Copyrights 2010 :

Visualization : Virtual Simulation Total pressure contours along vertical mid-plane © Copyrights 2010 :

Visualization : Virtual Simulation Pathlines © Copyrights 2010 :

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 © Copyrights 2010 : Right Tray

Visualization : Virtual Simulation • Flow non-uniformities in Left and Right tray sections Simulation confirms the experimental findings © Copyrights 2010 :

Visualization : Virtual Simulation Particle Tracks © Copyrights 2010 :

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 © Copyrights 2010 :

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 © Copyrights 2010 :

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 © Copyrights 2010 :

Partial List of Clients © Copyrights 2010 :

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 © Copyrights 2010 :

Advisory, Consultants and Technologist Advisory Technologist Consultants © Copyrights 2010 :

Thank You © Copyrights 2010 :

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