manifold system for testing exhaust on a ramjet combustion engine ravi kurani 1 and alex...

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Manifold System for Testing Exhaust on a RAMJET Combustion Engine Ravi Kurani 1 and Alex Coologeorgen 2 1 Univeristy of California, Riverside 2 University of Illinois The optimization of a “Liquid Fueled, Swirled Air Combustion Chamber” will be proven through the hypothesis that a higher swirl number will directly correlate to lower emissions. Efficiency in the swirled air process lowers emissions in terms of the output of NO x , CO, and CO 2 . By using the axial inputs, tangential inputs, and the fuel nozzle; variations on the swirl number will be accomplished. K1 Kerosene fuel will be used to fuel the chamber at during these experiments. We will use this swirled air jet engine to conduct experiments which will further the hypothesis that a higher swirl number will directly correlate with lower emission readings. In this study, particulate samples were measured in response to the different swirl numbers. Data suggests strongly that there is a decrease in particulate matter in response to the increase in swirl number ratios. Using this swirled air jet engine, experiments were conducted in order to further evaluate the hypothesis that a higher swirl number directly correlates to lower emissions. Through the concern for lower emissions and pollutant formation regarding jet engines particulate samples were experimented with. Using 55mm Whatman Filter papers we captured exhaust through a manifold system that we built out of 1 inch copper piping. Diluting the air by using lab insert we kept a common pressure reading at 25PSI. Capturing these particulates on the filter paper proved to coincide with the combustion group’s hypothesis that a Experimental Logic (Top Bottom) Mechanical Drawing of Final Combustion Chamber Experiments on Swirling Jets and Flow Manufactured SS Filter Holder Combustion Chamber with Swirled Combusted Air and Probe Our Manifold System to Measure Emissions Whiteness vs. Swirl Number As seen in “Whiteness vs. Swirl Number” the growth with increasing swirl number directly correlates to the “Swirl Number Hypothesis.” With White – 1 and Black – 0 (given the average of the blanks), the growth from 0 swirl number to theoretical ∞ (10000) is immense. Not surprisingly, is the value of the ∞. This value is right in the region of the equipment blank 0 10 20 30 40 50 60 70 80 0 1 2 3 4 5 6 7 8 9 10 Sw irlN um ber NOx NO X C h NOX Linear(NO X C h) Linear(NOX) NO x vs. Swirl Number In this graph when the combustion team tested for NO x the values were more comparable to the hypothesis, however when we tested the values at the end of the copper manifold the values were not comparable to the teams. Our reasoning for this would be due to the dilution of the lab air, that is diluting the NO x specimens. 0 2 4 6 8 10 12 14 16 18 20 0 1 2 3 4 5 6 7 8 9 10 Sw irlN um ber O 2 (% ) O 2% Ch O 2% Linear(O2% C h) Linear(O2% ) Oxygen vs. Swirl Number In the Oxygen vs. Swirl number graph, noticeable is the decline in oxygen in respect to the higher swirl speeds. This more efficient combustion process that happens during the higher swirl numbers uses more oxygen. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 10 100 1000 10000 Equipm entblank results Increasing Swirl Number With a rising concern for lower emissions and pollutant formation regarding jet engines, this study concentrated on particulate matter in simulated jet exhaust. Finding the correlation that higher emissions give higher particulates, proves that the lower the emission the lower the particulate samples. Using the swirl theory we found that at higher swirl numbers, there is a direct correlation between NOx, Oxygen, and Swirl Number. As the swirl number was increased we saw a decreasing trend in the particulate samples that were collected. Using MATHCAD, Excel, and RGB Analysis we were able to find how ‘black or white’ a particular specimen is in regards to the test sample. Using this data furthers the “Swirl Number Hypothesis”. Crist Khachikian – CSULA Elisa Brown – CSULA Mark Baum – Oakcrest CEA-CREST Tom Durbin – UCR NSF REU Antonino Monterrosa – CSULA Dr. Guillaume - CSULA Erastus Yiu – CSULA Christian Dominguez

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Page 1: Manifold System for Testing Exhaust on a RAMJET Combustion Engine Ravi Kurani 1 and Alex Coologeorgen 2 1 Univeristy of California, Riverside 2 University

Manifold System for Testing Exhaust on a RAMJET Combustion Engine

Ravi Kurani1 and Alex Coologeorgen2

1Univeristy of California, Riverside 2University of Illinois

The optimization of a “Liquid Fueled, Swirled Air Combustion Chamber” will be proven through the hypothesis that a higher swirl number will directly correlate to lower emissions. Efficiency in the swirled air process lowers emissions in terms of the output of NOx, CO, and CO2. By using the axial inputs, tangential inputs, and the fuel nozzle; variations on the swirl number will be accomplished. K1 Kerosene fuel will be used to fuel the chamber at during these experiments. We will use this swirled air jet engine to conduct experiments which will further the hypothesis that a higher swirl number will directly correlate with lower emission readings. In this study, particulate samples were measured in response to the different swirl numbers. Data suggests strongly that there is a decrease in particulate matter in response to the increase in swirl number ratios.

Using this swirled air jet engine, experiments were conducted in order to further evaluate the hypothesis that a higher swirl number directly correlates to lower emissions. Through the concern for lower emissions and pollutant formation regarding jet engines particulate samples were experimented with. Using 55mm Whatman Filter papers we captured exhaust through a manifold system that we built out of 1 inch copper piping. Diluting the air by using lab insert we kept a common pressure reading at 25PSI. Capturing these particulates on the filter paper proved to coincide with the combustion group’s hypothesis that a higher swirl number will result in less emissions (and particulates).

Experimental Logic (Top Bottom)

Mechanical Drawing of Final Combustion Chamber

Experiments on Swirling Jets and Flow

Manufactured SS Filter Holder

Combustion Chamber with Swirled Combusted Air and Probe

Our Manifold System to Measure Emissions

Whiteness vs. Swirl Number

As seen in “Whiteness vs. Swirl Number” the growth with increasing swirl number directly correlates to the “Swirl Number Hypothesis.”

With White – 1 and Black – 0 (given the average of the blanks), the growth from 0 swirl number to theoretical ∞ (10000) is immense. Not surprisingly, is the value of the ∞. This value is right in the region of the equipment blank results.

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5 6 7 8 9 10

Swirl Number

NO

x

NOX Ch

NOX

Linear (NOX Ch)

Linear (NOX)

NOx vs. Swirl Number

In this graph when the combustion team tested for NOx the values were more comparable to the hypothesis, however when we tested the values at the end of the copper manifold the values were not comparable to the teams. Our reasoning for this would be due to the dilution of the lab air, that is diluting the NOx specimens.

0

2

4

6

8

10

12

14

16

18

20

0 1 2 3 4 5 6 7 8 9 10

Swirl Number

O2

(%)

O2% Ch

O2%

Linear (O2%Ch)

Linear (O2%)

Oxygen vs. Swirl Number

In the Oxygen vs. Swirl number graph, noticeable is the decline in oxygen in respect to the higher swirl speeds. This more efficient combustion process that happens during the higher swirl numbers uses more oxygen.

00.10.20.30.40.50.60.70.80.9

1

1 10 100 1000 10000

Equipment blank results

Increasing Swirl Number

With a rising concern for lower emissions and pollutant formation regarding jet engines, this study concentrated on particulate matter in simulated jet exhaust. Finding the correlation that higher emissions give higher particulates, proves that the lower the emission the lower the particulate samples. Using the swirl theory we found that at higher swirl numbers, there is a direct correlation between NOx, Oxygen, and Swirl Number. As the swirl number was increased we saw a decreasing trend in the particulate samples that were collected. Using MATHCAD, Excel, and RGB Analysis we were able to find how ‘black or white’ a particular specimen is in regards to the test sample. Using this data furthers the “Swirl Number Hypothesis”.

Crist Khachikian – CSULA Elisa Brown – CSULA

Mark Baum – Oakcrest CEA-CREST

Tom Durbin – UCR NSF REU

Antonino Monterrosa – CSULA Dr. Guillaume - CSULA

Erastus Yiu – CSULA Christian Dominguez

NASA Andrew Clark