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Modeling of carbon monoxide, methyli...

Bostic, David Roy Boozell.

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Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds./
Author:	Bostic, David Roy Boozell.
Description:	151 p.
Notes:	Adviser: Dennis G. Watson.
Contained By:	Masters Abstracts International44-05.
Subject:	Agriculture, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1435545
ISBN:	9780542646973

Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds.
Bostic, David Roy Boozell.

Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds. - 151 p.

Adviser: Dennis G. Watson.

Thesis (M.S.)--Southern Illinois University at Carbondale, 2006.

Despite years of environmental concerns and increased regulations our society continues to rely on the fossil fueled internal combustion engine (ICE). The availability and flexibility of ICEs results in new uses on a regular basis. This is especially true in agricultural industries where remote power requirements are common. The first objective of this research was to conduct a customized emissions test and an ISO standard test of a John Deere 4045T diesel engine. The second objective was to create mathematical prediction models based on the two data sets then compare them to determine which test creates better prediction models. The models based on the customized emissions test performed better than the models based on ISO data. The performance based StatNet(TM) models for all three gases were better at predicting emissions than ISO based StatNet(TM) models or models created by the multiple regression formula. Using performance based StatNet(TM) models; CO, HC, and NOx g/hp/hr can be predicted with R2 values of 0.88, 0.96, and 0.89 respectively.

ISBN: 9780542646973Subjects--Topical Terms:

1017510
Agriculture, General.

Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds.
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100 1 $a Bostic, David Roy Boozell. $3 1291333
245 1 0 $a Modeling of carbon monoxide, methylidyne, and nitrogen oxides emissions of a diesel engine operating at constant loads and speeds.
300 $a 151 p.
500 $a Adviser: Dennis G. Watson.
500 $a Source: Masters Abstracts International, Volume: 44-05, page: 2185.
502 $a Thesis (M.S.)--Southern Illinois University at Carbondale, 2006.
520 $a Despite years of environmental concerns and increased regulations our society continues to rely on the fossil fueled internal combustion engine (ICE). The availability and flexibility of ICEs results in new uses on a regular basis. This is especially true in agricultural industries where remote power requirements are common. The first objective of this research was to conduct a customized emissions test and an ISO standard test of a John Deere 4045T diesel engine. The second objective was to create mathematical prediction models based on the two data sets then compare them to determine which test creates better prediction models. The models based on the customized emissions test performed better than the models based on ISO data. The performance based StatNet(TM) models for all three gases were better at predicting emissions than ISO based StatNet(TM) models or models created by the multiple regression formula. Using performance based StatNet(TM) models; CO, HC, and NOx g/hp/hr can be predicted with R2 values of 0.88, 0.96, and 0.89 respectively.
590 $a School code: 0209.
650 4 $a Agriculture, General. $3 1017510
650 4 $a Engineering, Agricultural. $3 1019504
650 4 $a Environmental Sciences. $3 676987
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710 2 0 $a Southern Illinois University at Carbondale. $3 718932
773 0 $t Masters Abstracts International $g 44-05.
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1435545