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Microalgal cultivation for biodiesel...

Arudchelvam, Yalini.

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Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization./
Author:	Arudchelvam, Yalini.
Description:	302 p.
Notes:	Source: Dissertation Abstracts International, Volume: 74-07(E), Section: B.
Contained By:	Dissertation Abstracts International74-07B(E).
Subject:	Engineering, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3537714
ISBN:	9781267986450

Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization.
Arudchelvam, Yalini.

Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization. - 302 p.

Source: Dissertation Abstracts International, Volume: 74-07(E), Section: B.

Thesis (Ph.D.)--New Mexico State University, 2012.

Traditionally, algal cultivation in sparged photobioreactors has been optimized to maximize biomass productivity without taking into consideration the energy input or the energy that could be harvested. In this study, an energy-based methodology is presented to maximize the net energy gain of the cultivation process by minimizing the energy input and by maximizing the energy output. Options for minimizing the energy input through optimal gas-culture volume ratio and CO2-air ratio and options for maximizing the energy output in terms of lipid production through optimal levels of nutrition and CO2 are presented and validated with experimental results from 900-mL bubble column reactors.

ISBN: 9781267986450Subjects--Topical Terms:

1020744
Engineering, General.

Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization.
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008 150210s2012 ||||||||||||||||| ||eng d
020 $a 9781267986450
035 $a (UMI)AAI3537714
035 $a AAI3537714
040 $a UMI $c UMI
100 1 $a Arudchelvam, Yalini. $3 2092175
245 1 0 $a Microalgal cultivation for biodiesel production: Process analysis, modeling, and energetic optimization.
300 $a 302 p.
500 $a Source: Dissertation Abstracts International, Volume: 74-07(E), Section: B.
500 $a Adviser: N. Nirmalakhandan.
502 $a Thesis (Ph.D.)--New Mexico State University, 2012.
520 $a Traditionally, algal cultivation in sparged photobioreactors has been optimized to maximize biomass productivity without taking into consideration the energy input or the energy that could be harvested. In this study, an energy-based methodology is presented to maximize the net energy gain of the cultivation process by minimizing the energy input and by maximizing the energy output. Options for minimizing the energy input through optimal gas-culture volume ratio and CO2-air ratio and options for maximizing the energy output in terms of lipid production through optimal levels of nutrition and CO2 are presented and validated with experimental results from 900-mL bubble column reactors.
520 $a For this purpose, 15 different options were tested and analyzed in this study in a bubble column reactor with working volume of 900 mL under constant light, with a test species Nannochloropsis salina. Of the options tested in this study, the two-stage operation was found to result in high power yields in the range of 9 to 72 W m-3.
520 $a As part of this study, new correlation models were developed and validated for timely assessment of lipid content and FAME content of algal biomass that can be of significant benefit in day-to-day operation of large-scale cultivation systems. These models were developed from biochemical reasoning presented in this study in terms of routinely measured spectrophotometric optical density readings at 680 nm and 750 nm. These correlations were calibrated and validated using experimental data on Nannochloropsis salina obtained under a range of laboratory conditions in bubble columns and under outdoor conditions in a closed photobioreactor. Lipid predictions by this correlation agreed well with the measured ones (r2 = 0.88). The ratio of the absorbance at the two wavelengths correlated well with total FAME for the calibration data set (r2 = 0.87, n = 21); and predicted well for the validation dataset (r2 = 0.72, n = 74). Based on this level of prediction, this correlation seems to hold promise for low-cost, continuous, onsite estimation of lipid content and FAME content in algal cultivation systems.
590 $a School code: 0143.
650 4 $a Engineering, General. $3 1020744
650 4 $a Engineering, Civil. $3 783781
650 4 $a Engineering, Environmental. $3 783782
690 $a 0537
690 $a 0543
690 $a 0775
710 2 $a New Mexico State University. $3 783784
773 0 $t Dissertation Abstracts International $g 74-07B(E).
790 1 0 $a Nirmalakhandan, N., $e advisor
790 $a 0143
791 $a Ph.D.
792 $a 2012
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3537714