Use this to structure manuscripts, strengthen argument, and match scholarly style. Engineering/AEC venues reward clarity, explicit contribution, and methodological transparency over rhetorical flourish.
1. IMRaD and the shape of a paper
Title → Abstract → Keywords → 1 Introduction → 2 (Background/Literature) → 3 Methods → 4 Results → 5 Discussion → 6 Conclusion → Acknowledgements → Declarations → References → Appendices
The classic "hourglass": broad context → narrow to the specific gap/question → method & findings (narrow)
→ broaden again to implications. Empirical AEC papers follow IMRaD; review papers, DSR papers and
conceptual papers vary (state your structure).
2. Section-by-section
Title
Specific, informative, keyword-rich, honest. State the topic + (often) the contribution/method/context.
Avoid vague ("A study on…"), over-claiming, and undefined acronyms. (See /aec-scholar:title-keywords.)
Abstract (150–250 words typically; check venue)
Structured or unstructured per venue. Cover: context/problem → gap/objective → method → key results (with concrete specifics) → contribution/implication. No citations, no undefined acronyms, no content absent from the paper. The abstract is what gets read and indexed — make it self-contained and concrete (numbers beat adjectives).
Introduction — earn the gap (CARS model, Swales)
- Establish the territory — why this matters (real-world + scholarly relevance; keep brief).
- Establish the niche — what is missing/unresolved/contradictory in prior work (the gap move — be specific and fair; don't strawman the literature).
- Occupy the niche — state objective/RQs/hypotheses, your approach, contribution, and (often) a roadmap. End the introduction with an explicit "This paper contributes…" sentence. Make the gap and contribution unmissable — reviewers look for them first.
Background / Literature review
Synthesize, don't list ("author X said… author Y said…" is a red flag). Organize by theme/concept/
chronology/method. Critically position prior work, build toward your gap, and define key terms & the
conceptual/theoretical framework. (For standalone reviews see systematic-review/bibliometric-analysis.)
Methods
Enough detail to reproduce. Justify choices (link to research-methods). Cover design, data/sample,
instruments/tools (+ versions), procedure, analysis, and validity/reliability measures. Use past tense,
often passive for procedure. Include ethics approval where relevant. For simulation: assumptions, inputs,
calibration/validation. A figure of the research workflow helps.
Results
Report findings without interpretation (interpretation belongs in Discussion — though many AEC venues accept a combined Results & Discussion; choose one and be consistent). Lead with the answer to each RQ. Use tables/figures for data, text for the narrative — don't duplicate. Report effect sizes/CIs/uncertainty, not just significance. Every figure/table must be referenced and self-explanatory.
Discussion
Interpret: what do the results mean? Answer the RQs explicitly. Compare with prior work (agree/conflict/ extend — cite). State theoretical and practical/industry implications (AEC reviewers want both). Be honest about limitations (generalizability, sample, validation) and turn them into future work. Don't introduce new results here.
Conclusion
Concise: restate contribution and key findings (no new data), implications, limitations, future directions. Should stand alone. Avoid merely repeating the abstract verbatim.
Declarations (increasingly required)
Funding, conflicts of interest, data/code availability, author contributions (CRediT taxonomy), ethics
approval/consent, and AI-use disclosure per venue policy (see research-ethics-integrity).
3. Style & mechanics
- Clarity > complexity. Prefer plain, precise wording; one idea per sentence where possible.
- Paragraphs = one point each, topic sentence first, then evidence, then link.
- Signposting: "First… Second… In contrast… Consequently…" to guide the reader.
- Tense: present for established knowledge & your claims ("BIM improves…"); past for what you/others did ("we measured…", "Smith (2021) found…").
- Voice: active for clarity & agency ("we developed"); passive acceptable for methods. Check venue norms.
- Hedging vs over-claiming: calibrate. "suggests/indicates/may" for inference; reserve strong claims for strong evidence. Engineering reviewers punish over-claiming and unsupported generalization.
- Acronyms: define on first use; don't over-abbreviate.
- Numbers & units: SI units, consistent significant figures, correct unit spacing; report uncertainty.
- Citations: support every non-obvious claim; cite primary sources; match venue style (see
citation-formats). Never cite something you haven't read or can't verify. - Cohesion: given→new information flow; keep terminology consistent (don't elegantly vary "model" / "framework" / "system" if they mean the same thing).
4. Reporting guidelines (use the right one)
- PRISMA 2020 / PRISMA-ScR — systematic/scoping reviews.
- CONSORT — randomized trials; STROBE — observational studies; SRQR/COREQ — qualitative.
- TRIPOD — prediction models; CHEERS — economic evaluations.
- Discipline checklists for energy modeling/LCA (e.g., ISO 14044 reporting). State which you followed.
5. Revision protocol
- Structure pass — does each section do its job? Is the contribution explicit and consistent across abstract/intro/conclusion?
- Argument pass — claim → evidence → warrant for every key point; remove unsupported claims.
- Flow pass — topic sentences, transitions, given-new ordering.
- Concision pass — cut redundancy, hedge-stacking, throat-clearing ("It is important to note that…").
- Mechanics pass — tense, units, acronyms, figure/table references, citation style.
- Reviewer-empathy pass — what will a skeptical reviewer attack? Pre-empt it (limitations, validity).
6. AEC-specific reviewer expectations
- Explicit gap and contribution statements.
- Practical/industry implications, not just academic novelty.
- Honest generalizability limits (single case/building is the norm — acknowledge it).
- Reproducibility: tool versions, inputs, data/code availability.
- Validation against reality for any model/tool/algorithm.
- Correct use of standards & terminology (
aec-standards-codes,aec-domains).