AME 514

Applications of Combustion

Lecture 13A: Common-sense primer for successful research

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Designing and building an experiment

Do the simplest thing first, then build on experience, e.g. Bic lighter and thermometer Bunsen flame and thermocouple Counterflowing jet burner, thermocouple and Labview Coherent Anti-Stokes Raman Spectroscopy (CARS) and gas turbine

combustormake your mistakes quickly and cheaply and safely!

Any measurement consists of Transducer Data acquisition Algorithm for data processingand all 3 must be valid, otherwise your measurement is invalid

Noise and shielding Differential input Twisted wires Average multiple readings with computerized DAS

First test of any instrument must be a reality check, e.g. Temperature measurement - check ice water and boiling water Pressure measurement - check atmospheric and vacuum

Know how your control programs (e.g. LabView) work - you can't rely on something written many years ago!

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Conducting an experiment

NEVER TRUST ANY INSTRUMENT Turn only one knob at a time Skip around Choose conditions wisely - plot as you go

Take more data where the action is Re-check suspicious points Take data at x = 1, 1.5, 2.3, 3.3, 5, NOT 1, 2, 3, 4, 5 Turn the knobs as far to the left and the right as you safely can

Use all your information Never base a conclusion on one data point!

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Conducting an experiment (continued)

Don't base conclusions on polynomial fits to small data sets Check repeatability - what is random and what is real?

What happens if I do exactly the same test 10 times? What is the standard deviation as a percent of the mean value?

What happens if I repeat some of the points on the curve? Do I get the same trend?

What happens if I turn off the instrument? Does my signal change? Know what your units are (volts is not a unit of pressure or

temperature!) Use video but put a caption and a scale in every video clip!

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Scrutinizing your analysis

First level - smoke test - do the units work? (Pv = R/T doesn't) Anything added must have the same units Anything inside an exp, ln, sin, etc. must be dimensionless Anything units inside a square root must be a square (e.g. m2/s2)

Second level - function test - do the results make physical sense? Is the sign reasonable? (Pv = -RT isn't) Is it reasonable that as x increases, y decreases? (Pv = R/T isn't) Take the limit as x ∞ or x 0

Third level - performance test - how accurate is the result? Pv = 7RT passes smoke and function test, but not performance test Need to compare prediction to previous analysis, experiment, detailed

numerical computation, etc. that you trust

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Scrutinizing your computation

Any colorful computer generated 3D orthographic projection of results with shading from the northwest looks correct

First level - smoke test - are mass, momentum, energy, species, etc. conserved? Goal of most computational methods is to conserve these

quantities at every cell, but as a first check, is it conserved globally?

Second level - performance test Compare your result to a known analytical solution in a

simplified geometry with simplified (e.g. constant) property relations

Compare to previous computation that you trust Third level - function test - how accurate is the result?

Similar to function test for analyses

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Communicating with others

Use electronic format, not hard copies Name files with something more descriptive than

results.dat!!! Significant figures - usually 1.1 or 1.13, not 1, not

1.34098753987 Make a xerox of hard-copy equipment manuals, or email an

electronic copy Meetings must have

An agenda - what will be discussed Minutes - what was said and done Action items - what will be done differently as a result of the

meeting?otherwise, what was the purpose of the meeting?

Make a backup of everything!!! What would happen if your hard disk crashed right now? What would happen if the lab burned down right now??? Is your electronic and hard-copy data safe?

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Making a decent figure

Upper plot: lousy figure, many problems

Text is too small to read Scales are weird, not 1, 2, 3, … No units on vertical scale Legend means nothing to audience

(what does Test 117 mean?) Some data sets have connecting lines,

others not - why? Too much white space Too many grid lines Plot symbols are too small to read Jagged connecting lines look clumsy -

use smoothed line Need vertical log scale since data spans

> 10x range Tick marks inside and outside, too thin,

no distinction between major and minor tick marks

Lower plot: better figure (same data)

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Oral presentations - preparing

Golden rule: ask yourself, “if I were seeing this presentation for the first time, would I understand it?”

Format Introduction

»What is your topic and why is it important?»Complain about what's lacking in the current knowledge

Objectives - what are you trying to measure or predict or prove that is better than what has been done before?

Approach to experiment, computation or analysis Results - what did you learn and how sure are you? Conclusions - what did you measure or predict or prove? What is your

MESSAGE? No “bonus” text or figures - if it doesn't add to your message, leave it

out! A picture is worth 1000 words, and a video is worth 1000 pictures Every picture has a length scale, every movie has a length and time

scale Print a hard copy on 8.5” x 11” paper, put pages on the floor, can you

read it standing up? If not, the text/figures are too small!

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Oral presentations - doing

Test your computer in advance Don't start out by reading your title! Face and address the audience: “This plot shows you the

effect of ABC on DEF…” Don't read equations, e.g. E = mc2

Say “this equation shows that the energy contained by a substance (point to E) is equal to its mass (point to m) times the speed of light squared (point to c)

DON'T say “this equation shows that eee equals emm cee squared” (the audience already sees that)

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Written papers

Golden rule: ask yourself, “if I were reading this paper for the first time, would I understand it?”

Format similar to oral presentation, plus abstract (before), acknowledgments & references (after)

Every figure Is mentioned in the text and labeled in the order it is first

mentioned Has a caption with all relevant conditions stated Has all symbols and lines defined in the caption

References are numbered in the order they are first cited in the text (unless the Harvard system, e.g. Smith and Jones, 1972)

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Why was my paper rejected?

Acceptable papers Have a clear, consistent message –

all information helps convey the message

State what is different from & better than prior work

State modeling assumptions & identify empirical constants

Have a minimum # of pictures, scatter plots, extensive equations & derivations - focus on quantitative results & their relation to the message

Respond to the reviewers' comments

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White paper

Part of your HW #5 assignment will be to prepare a “white paper” research pre-proposal (≈ 2 pages + figures) on an original topic State what your topic is and why it is important State what is known about the subject Complain about what is lacking in the current state of knowledge Explain what you would do that would improve the state of knowledge (i.e.

specifically what computer simulation or experiment or analysis you would perform)

Describe how you would analyze or interpret the data Speculate as to what results you might obtain State how the results advance the state of knowledge of the field

Verify that what you propose hasn’t already been done; e.g. check the ISI Web of Science

AME 514 - Spring 2013 - Lecture 13