Date of Publication

12-2-2011

Document Type

Master's Thesis

Degree Name

Master of Science in Mechanical Engineering

Subject Categories

Mechanical Engineering

College

Gokongwei College of Engineering

Department/Unit

Mechanical Engineering

Thesis Adviser

Aristotle T. Ubando

Defense Panel Chair

Alvin Y. Chua

Defense Panel Member

Alvin Y. Culaba
Raymond Girard R. Tan
Jose Bienvenido Manuel M. Biona

Abstract/Summary

One of the most promising sources of biofuel is microalgae. Microalgae are unicellular photosynthetic organisms that have a high photosynthetic efficiency (10 to 20%) compared to other plant species (0.5%) (Huntley, et al., 2007). However, the large initial moisture content of microalgae (80 to 90%, wet-basis) causes problems during oil extraction. According to Halim, et al. (2011), the lipid yield of dried microalgae is 33% higher than wet microalgae using hexane extraction. The study aims to predict the drying performance of microalgae biomass as a function of solar dryer design. The best combination of direct radiation, convective heat input and air flow rate was determined. A computational model for predicting the drying air temperature and relative humidity was solved using a spreadsheet program. The results of both models were validated by means of actual experimentation with a fabricated solar dryer and ANSYS Computational Fluid Dynamics simulation. Statistical analysis of the results showed that direct radiation (Qr) is more efficient than the convective heat input in increasing the drying rate. Qr allows the biomass surface temperature to get over the drying airs wet bulb temperature, giving rise to a significant increase in the drying rate. High air velocity results to inefficient drying. The computational model predicted the temperature and relative humidity of the drying air with an error percentage of 4.3% and 11.8%, respectively. ANSYS-CFD simulation was congruent with the assumptions used in the computational model. The regression equation generated from the characterization experiment was able to predict the average drying rate with an error percentage of 10%. The computational model was able to predict the temperatures and relative humidity of the drying chamber with an error percentage of 4.3% and 11.8%, respectively. Overall, the results show that drying rate is maximum at low air flow rate, high direct radiation and high convective heat input. Also, based on the measured available energy inside the solar dryer from actual experimentations, a microalgae dry mass yield of 800g/m2-hr which will be able to produce 180mL of oil per hour on a good sunny day was computed.

Abstract Format

html

Language

English

Format

Electronic

Electronic File Format

MS WORD

Accession Number

CDTG005071

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

123 leaves : ill. ; 1 computer optical disc

Keywords

Biomass energy; Microalgae

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