Common-sense primer for successful research - conducting and communicating

1. Common-sense primer for successful research - conducting and communicating Paul D. Ronney (ronney@usc.edu) Department of Aerospace & Mechanical Engineering Univ. of Southern California, Los Angeles, CA, 90089

2. 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 combustor make your mistakes quickly and cheaply and safely! • Any measurement consists of • Transducer • Data acquisition • Algorithm for data processing and 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!

3. 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!

4. 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 butput a caption and a scale in every video clip!

5. 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

6. 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

7. 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?

8. 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)

9. 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!

10. 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 emmcee squared” (the audience already sees that)

11. 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)

12. 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

13. AME 514 - Spring 2013 - Lecture 13 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