The Written Report

Updated Author Roles for Reports 1-3, W25

The authorship roles for all reports in CENG 176A (W25) are as follows:

Teams of 4:
- Author 1: Abstract, Introduction, Methods, and Conclusions
- Author 2: Background and Theory
- Author 3: Results and Discussion
- Author 4: Pre-lab memo and Oral Presentation
Teams of 3:
- Author 1: Introduction, Background, and Theory
- Author 2: Methods, Results, and Discussion
- Author 3: Pre-lab memo, Abstract, Conclusions, and Oral Presentation

Each person in your team should do each authorship role at least once!

Overview

This page provides resources for your written reports. There are lots of useful topics and links here and you should review them before you start writing your report. As with any form of communication, there's plenty of room for individual preference and style but the material presented here should be considered "best practices" for this course.

You can download a copy of what your completed reports should look like at the bottom of this page. Most of the formatting will be handled automatically by Overleaf, a cloud-based LaTeX service that we'll introduce in Week 2, and you can find this template at the bottom of the page as well (compiling the template in Overleaf should give you the same PDF included at the bottom of this page). You can also view the Written Report Rubric on the course Canvas site to see how the reports are evaluated.

Regarding Plagiarism

In all aspects of this course you are never to use someone else's words. Instances of plagiarism will result in referral to the Academic Integrity Office and a 35 point deduction to the report. Plagiarism is considered as

using direct quotations (cited or uncited, quoted or not),
copying a sentence but changing a few words,
anything else covered under the usual plagiarism guidelines for the University.

In rare instances you can include a graphic or image as long as it's cited (figures with data in them should never be included).

Statement on Generative AI (GenAI)

This course has a conditional use policy for GenAI tools such as ChatGPT and Co-Pilot. These tools may be used in this course in limited ways with proper documentation, citation, and acknowledgement. In accordance with our course learning outcomes you may use GenAI tools as an assistant to help you better understand material, do some brainstorming, or in general usage for which the output is not directly used in your submission. Examples:

Orienting yourself to a new field or technology (e.g., “Summarize the major design alternatives for industrially relevant heat exchangers.”)
Clarifying terms and concepts (e.g., “How are fugacity and activity coefficients related to vapor-liquid equilibrium?”)
Looking for sources (e.g., “Where can I find out process information regarding commercial ammonia synthesis?”)
Grammar/clarity editing (e.g., “Below is what I wrote as an introductory paragraph for heat exchangers; is the grammar, spelling, and clarity ok?”)

You may not use GenAI tools in ways which short-cut learning outcomes for the class, including writing, analysis, or calculations. Examples:

Generating content used with limited or no editing (e.g., “Write me a paragraph to introduce a reader to industrially relevant heat exchangers.”)
Performing calculations or analyses (e.g., “Calculate the Reynolds number for water through a 2” pipe at room temperature at 3 gpm.” (warning: GenAI is pretty bad at a lot of these calculations right now)
Reviewing a specific document (e.g., “Review and summarize the important findings of this document I’m going to upload to you.”)
Assistance on any quiz or exam, or any other assignment on which its use is specifically restricted.

Understand that GenAI, while powerful, is not infallible and can produce misinformation or inaccurate results. You are responsible for the accuracy of your submissions and must cross-verify the information produced by these tools with reliable sources (e.g., textbooks, peer-reviewed articles, databases, etc).

Misuse of GenAI, including use of GenAI that undermines learning objectives of the course or assignment, failing to cite AI generated content (see lecture notes), over-reliance on AI for completion (see above), or submitting inaccurate information generated by AI tools, will be subject to academic penalties. Instructors may follow up with you to orally assess your process for completing an assignment and your understanding of the content contained within. Through this process, if you have not sufficiently supported your work then the matter may be referred to the Academic Integrity Office.

If you are unsure whether a GenAI tool is appropriate for a particular circumstance then you should consult with the course instructor before using it. “I didn’t know it wasn’t allowed to be used this way” is not exculpatory.

Report Sections

Abstract

A fancy word for "summary," the Abstract gives the reader a quick overview of what's to come and is the first opportunity to "tell them what you're going to tell them." A good abstract is about four to six sentences long and addresses the following points, succinctly summarized by Celia Elliott at the University of Illinois:

Give the context and motivation.
Tell what you did in sufficient detail so the audience knows if your work is relevant.
Summarize your key results.
Tell the reader what you think the results mean, and their implications for future work.

A consequence of this list is that the Abstract is often the very last paragraph in the entire report to be written because it's only after the Discussion and Conclusions have been finalized that the latter points are known. Be sure to review Ms. Elliott's summary on Writing Effective Abstracts and take note of the five things which must never appear in an abstract! You can also look to JACS or Angewandte Chemie to see decent (or sometimes not) examples of abstracts; Nature, Science, and PNAS often have extended abstracts that are a bit longer than what you need to provide.

Introduction

The Introduction is the "widest" part of the report in the sense that it represents your opportunity to supply context for your experiment at the broadest level. A good Introduction will do the following:

What is the topic you're going to talk about?
Where is this topic relevant? Put another way, what fields or industry find this topic relevant?
Why is this topic relevant?
When has this topic been investigated? Put another way, what's a brief history of the development of this topic?

The most critical aspect of these points is that they be well-documented with reliable citations. Consequently, you need a minimum of three unique citations in the Introduction (internet sources are not appropriate, nor are multiple citations to one textbook or handbook). If you're lost, start with either your textbooks and track down the references therein, or check out the relevant experiment page and use those references as a starting points. Once you have a good idea of the relevant terminology or a few references to start with, use the ISI Web of Knowledge to track down appropriate support material for the statements you make in the Introduction.

Note: There should be at least three unique, peer-reviewed articles (not textbooks, not review articles, not websites). There can be more than three, but that is the minimum. Textbooks can be cited, but will not count towards one of the three (to be summarized - see appendix).

Background

Here, we begin to narrow the field to the specific topic of interest for the report. If the Introduction is the "30,000 ft overview" of the field, then the Background is the "5,000 ft view" before the ground-level view is provided in the remainder of the report. Ultimately the narrative you choose to tell in the Introduction and Background is up to you because various topics can be presented in different contexts. Here are a few hypothetical experiments along with examples of the restricted scope of the Background compared to the Introduction:

Experiment: Shell-and-Tube heat exchanger:
- Introduction: Heat exchanger styles and uses in industry.
- Background: Shell-and-Tube heat exchanger design and operational principles.
Experiment: Particle separation using microfluidic flows
- Introduction: Small particle separation techniques in microfluidic devices (e.g., electrostatic, electrodynamic, magnetic, barrier, flow patterns, etc).
- Background: Design considerations of flow pattern-based particle separation including (but not limited to) types of particles that can be separated, separation principle, and device fabrication.
Experiment: Numerical simulation of molten carbonate fuel cells
- Introduction: Types of fuel cells (hydrogen, methanol, natural gas, etc), their uses, advantages, disadvantages, and variations.
- Background: Hydrogen fuel cell principles, challenges, and the need for numerical simulation to support and facilitate experimental design.

Note that these are merely suggestions; there are many acceptable ways to decide on the content in the Introduction and Background. For example, the "Numerical Simulation" example could equally have focused on the numerical simulation aspect rather than the fuel cell:

Experiment: Numerical simulation of molten carbonate fuel cells
- Introduction: Numerical simulation styles, principles, software packages, applications, advantages, and disadvantages.
- Background: Molten carbonate fuel cell basics and appropriate numerical simulation requirements.

The last paragraph in your background section should be a paragraph that starts with "Here, we show..." This paragraph provides a transition from the Introduction and Background--which talk about things other authors have done--to the remainder of the report--which talk about the things your team did. A good example of this kind of paragraph is in Dr. Zhang's paper that we reviewed in class as part of our "How to find information in a paper" lecture. In general, you should be able to find a similar paragraph at the introductory material in most published papers (sometimes they don't label their sections "Introduction" and "Background" so you might have to search around a little bit).

Note: There should be at least three unique, peer-reviewed articles (not textbooks, not review articles, not websites). These are NOT the same as the three required in the introduction. There can be more than three, but that is the minimum. Textbooks and any references in the introduction can be cited, but they will not count towards one of the three (to be summarized - see appendix). At this point, there should be a minimum of six unique, peer-reviewed articles in your report.

Theory

With Theory the goal is to present the relevant design and analysis principles to enable the reader to understand and follow the detailed Results and Discussion sections. A good Theory section will have the following characteristics:

Equations and variables will be appropriately and consistently used throughout the document; the Theory section should define and describe all equations and variables needed for the Results and Discussion section, excluding "support" equations such as propagation of error or linear regression.
Equations will be integrated into sentences:

Incorrect:

The continuity equation is a statement equivalent to conservation of mass for a constant density system.

Where v is the velocity vector

Correct:

The continuity equation,

where v is the velocity vector, is a statement equivalent to conservation of mass for constant-density system.

Derivations will be simplified to one or two lines, if presented at all. General equations such as the conservation equations most common "engineering" equations (e.g., the Bernoulli Equation) can be used without derivation and without citation. More specific equations, such as those derived for the cooling tower, should be presented as a result of applying various assumptions and approximations to the relevant conservation equations. In these cases, a citation to the full derivation can be provided (if you can find such a citation), or you can supply the derivation in an appendix along with a brief, parenthetical statement such as (see Appendix I for derivation) in the report itself.
Operating principles of relevant experimental equipment or processes will be provided. For a heat exchanger these principles might take the form of an energy balance or dimensionless number; in other experiments such as the Liposome Nanoparticle or LPCVD Simulation this might be a more qualitative description of the how the simulation or analysis equipment operates.
Interpretation of relevant equations will be provided. As an engineer you should understand the meaning of the equations, not merely how to use them to arrive at a number. The continuity equation, for example, does not merely state "the sum of the velocity derivatives is zero when density is constant"; it means that mass is conserved in such a system. An incomplete list of quantities for which you should provide interpretation is as follows:
- Timescales. If a timescale appears in your equations, for example in an energy or mass balance, then you should provide a physical interpretation of that timescale.
- Non-dimensional quantities. Nearly all dimensionless groups can be interpreted as the ratio of two quantities (e.g., the ratio of viscous and inertial forces for the Reynolds number) and you should provide such an interpretation.
- Adjustable coefficients. The coefficients in a PID controller, for example, have a clear physical interpretation in terms of the system's time-dependent response.
- Differential equations. Each term in an ODE or PDE represents the influence of something on something else and you should elaborate as needed. Often this or a scaling analysis is the basis for eliminating terms from general conservation equations; you can use similar reasoning to explain why some terms remain after simplification.

Methods

Most Methods sections are 1 paragraph long while a rare few are 2 paragraphs long. There's a simple question that should guide you when writing the Methods section: How could someone with similar but not identical equipment repeat your experiment? It's not always immediately obvious what should be included and what should be omitted; you'll have to use your own judgment to decide which features of your experiment are critical to its reproduction and which are incidental. Here are a few examples:

Often included:
- Flow patterns: The slurry was pumped from the sedimentation vessel to the reactor.
- Operating conditions: A seven-stage, trayed column was operated at atmospheric pressure.
- Critical equipment or steps: The liposome solution was extruded through a 100 nm filter.
- Measured variables: Salt concentration of batch samples was determined by conductivity probe.
Never included:
- Specific identifiers or steps: Valve 6 was used to adjust the flow rate of Stream 3. Even if a reader tries to recreate your experiment it's highly unlikely that she will choose to label her equipment in exactly the same way as yours. Instead, describe what was done rather than how it was accomplished: A ball valve was used to control the feed stream flow rate.
- Equipment-specific settings: The reboiler heater was set to 95 until the column reached steady state after 30 minutes. Unless the reader has exactly the same piece of equipment, an equipment-specific setting like this is useless. Again, describe what was done rather than how it was accomplished: The column was operated at total reflux until steady state was achieved, defined as a constant temperature profile and pressure drop across the column.
- Non-critical equipment or steps: The solution was pipetted into a 50 mL beaker with a 5 mL bulb pipette. Rule of thumb: if it's a piece of equipment you might find or use in a high school or first-year chemistry laboratory then it's probably not needed in your report.

Results

With Results, we establish a data set on which we will base the forthcoming Discussion and Conclusions. Only rarely do raw measurements appear in the Results section; far more commonly the raw data are used as input to an analysis procedure to determine scaling behavior, investigate published or expected relations, or evaluate the effectiveness of a procedure as it relates to a particular metric.

The following points illustrate the kind of data which generally do or do not appear in the Results, but--with the exception of the "Never included" category, these should be interpreted as general guidelines rather than specific requirements: your team may choose to include something which is generally omitted if it's central to your story, or to omit something that is generally included if it is irrelevant.

Often included:
- Scaling relations between non-dimensional groups. For excellent examples, review your fluid mechanics textbooks: nearly all correlations are provided in terms of dimensionless groups such as the Reynolds number (think friction factor, drag coefficient, etc).
- Data needed to determine experimental coefficients. Many experimental quantities of interest--rate coefficients, filter properties, heat or mass transfer coefficients--are derived or approximated by the slope or intercept of a linear plot, and such a plot should be included so that the reader can evaluate the accuracy of your data and fitting procedure. Note that error bars are critical to such plots.
- Graphical procedures. Mostly the McCabe-Thiele procedure, but sometimes graphical interpretations are helpful with other analyses such as the Merkel equation.
Rarely included:
- Intermediate results. Consider a non-ideal flash calculation: the details of the Antoine equation and whatever non-ideal model you used are not as important as the results of the flash calculation itself (note that both details are important in the sense that the reader needs to be told which assumptions and models were used, but that's a responsibility of the Theory author). Other examples of rarely included "intermediate results" are demonstration of steady-state operation, start-up behavior, and the "beloved failures" mentioned in The Report as a Whole.
- Experimental apparatus. These images have virtually no value beyond "ooo shiny!!" and therefore should not be included. Use a process flow diagram if you need to diagram a complex system such as a distillation column, reverse osmosis unit, or heat exchanger.
- Number lists. In most cases, you're better served by a figure or table as opposed to a list of numbers. The following statement would be inappropriate in most instances:

The conversion at 25 Pa, 50 Pa, and 100 Pa was 30%, 40%, and 45%.

If the goal was to imply a relationship between pressure and conversion then a plot would have been more effective. If the goal was to present a contrast between a few numbers then a table might be more appropriate. In either case, simply listing data in a paragraph is rarely the most effective form of communications.

Never included:
- Calibration curves. If you made a calibration curve as part of your experiment, put it in the Appendix (be sure to include the prediction intervals and error bars), never the main report. The reader assumes that if you state that concentration was measured by adsorption spectrophotometry then you were using the equipment properly, which implies an accurate calibration curve; it's not a "result" in and of itself.
- Large lists of (usually raw) data. These data have no place in the main report, and are rarely included even as an Appendix. You must retain all experimental data in case it's ever requested but it doesn't have to be included anywhere in the report.
- Only figures and tables (no supporting text). Sometimes called a "data dump," this is as useless as simply listing the raw data. See the comment below regarding combined Results and Discussion sections if you think you're light on supporting text in the Results section.
- Repeated data. If you have a plot of data then there is no need to list that data explicitly in the text. As noted above, there's rarely a need to list data explicitly in the text in any circumstance.

There are four primary methods of communicating data to the reader in a written report. It's again up to you to decide which are most appropriate for what your particular experiment:

Figures. (includes plots, charts, and images) This is the preferred format wherever possible. See the Wiki page regarding effective figures for more information.
Tables. A table is a good way to summarize a few numbers, perhaps half a dozen or less. Large tables are often difficult to interpret and can usually be transformed into a plot.
Numbers. A list of numbers is better suited to a figure or table, but occasionally a single number--a regression coefficient, for example, or HETP--can be reported directly in the text.
Text. Text alone is best used for qualitative observations which were not or could not be quantified or communicated by any of the above methods.

Discussion

The Discussion portion of the report is your opportunity to provide an interpretation and analysis of the results from the previous section. You can (and probably should) address the following questions:

How does your experiment provide useful data or insight into this technology?
What high-impact message do you want the reader to conclude from your report?
How do your results compare to theoretical predictions or the results of others?

Remember that you're supposed to be interpreting the data, not merely presenting and describing it. Consider the following hypothetical statements in a Discussion section about double-pipe heat exchangers:

The overall heat transfer coefficient at 30 kg/s was negative, which isn't possible. The outlet hot water thermocouple was probably giving incorrect results which could produce such a result.

The second sentence in particular is about as weak an explanation as you could possible provide: "probably" and "could" imply just about zero confidence in or effort at an interpretation of the results. Replace "outlet hot water thermocouple" with any other piece of equipment and the validity of the statement (if it can be called that) is unchanged. There are actually many problems with these two sentences associated with its lack of specificity, problems which could be addressed by answering the following questions:

Why is a negative coefficient problematic? Why isn't it possible?
Why are the thermocouples suspect, and why the outlet hot water thermocouple specifically? Were any other sources investigated? Why were they dismissed?
How could an erroneous thermocouple reading produce a negative coefficient? How large a departure from reality is necessary to produce the observed result? Is such a magnitude likely? What other effects would this produce?
Was there something unique about the measurement for 30 kg/s? Presumably other flow rates were measured and the implication is that they're ok but this one is not; why?

Regarding Combined Results and Discussion Sections

Sometimes it's more effective to combine the Results and Discussion sections into a single section. In this way a particular result can be presented (usually in the form of a figure or table), then immediately discussed and interpreted. This could be the case if your results are fairly straightforward and don't need a great number of supporting or descriptive paragraphs, or if the results and interpretation of one experiment directly and sequentially inform the results and discussion of another experiment. If you'd like to combine the two sections then you're welcome to do so; simply re-label the "Results" header as "Results and Discussion" and remove the "Discussion" header.

Conclusions

And finally we come to the last part of the report, the section where you "tell the reader what you told them." In about a paragraph or two the Conclusions should provide an accurate summary of the relevant observations noted in the Discussion (trends, metrics, etc.) and, importantly, what your team can conclude from these observations.

For example, if the overall heat transfer coefficient of the aforementioned double-pipe heat exchanger was outside the expected values, perhaps we would conclude that the thermocouple was indeed faulty and therefore the experiment must be repeated after repairing or replacing the thermocouple. Or perhaps we observed that the effect of flow rate on the overall heat transfer coefficient agreed with the predicted behavior, from which we could conclude that our simplified model was an accurate representation of the equipment.

Lastly, you should include a recommendation for future avenues of research. As offered in the example above, an obvious recommendation is to repair faulty equipment; if you offer this recommendation it must be made obvious in the Discussion section that said equipment is indeed the most likely source of whatever error you seek to remedy. Even if the experiment went swimmingly, there are always sources of error that can be further minimized by better protocols or advanced analyses; having recently completed the experiment and analysis, you're in an excellent position to provide such advice.

Appendix

There are only two items which must be present in your Appendix:

A summary of the six unique, peer-reviewed articles you used in the Introduction and Background (three each). Each summary of each article should include the following information:
- Author(s)
- Title of the paper
- Year published
- Journal title
- Brief summary of 1-3 major accomplishments reported by paper
Calibration curves, if applicable. Curves should include data points with error bars, a line representing the equation of best fit, the equation of best fit, values and uncertainties of fit coefficients, and properly labeled axes.

Other material that can be included in your Appendix are lengthy derivations, summaries of intermediate calculations, or figures that are substantially similar to ones in the Results section (e.g., you could show one representative figure in Results and include more in the Appendix).

Keep in mind that the Appendix is not to be used to circumvent the 10 page limit! If the content is critical to the interpretation of the report then it should be included in the main body of the report.