Mechanical Engineering Research

Mechanical Engineering Research

Skill Suite

Use this skill as the cross-cutting coordinator when a request spans multiple research activities. For a focused deliverable, use the specialist skill that owns it:

• thermal-fluid-analysis: thermal-fluid physics, experiments, CFD, correlations, uncertainty, scaling, and design tradeoffs.
• research-writing-literature: literature synthesis, citations, introductions, manuscript sections, and figure-led discussion.
• research-proposal-development: solicitation-aligned proposals, review criteria, preliminary results, milestones, risks, and proposal figures.
• research-data-analysis: baseline cases, hypothesis-driven DOE, reproducible analysis, plots, CFD/experimental data, and ML evaluation.
• research-slide-design: research talks, posters, visual logic, speaker notes, and presentation QA.
• research-schematic-design: publication-quality editable facility, mechanism, workflow, and graphical-abstract schematics.
• research-mentor-review: constructive student-facing feedback with prioritized, actionable next steps.
• reviewer-author-loop: iterative reviewer critique, author revision, verification, and re-review.

The coordinator retains the evidence and integrity gates below. Do not load all specialist skills by default; select the smallest combination that fits the actual deliverable.

Core Workflow

1. Define the engineering decision or research question.

   • Identify the system, geometry, materials or fluid, operating regime, boundary and initial conditions, outputs, constraints, and intended user.
   • Ask only for missing information that materially changes scientific validity or the work path. Otherwise state bounded assumptions and proceed.

2. Classify the evidence before interpreting it.

   • Label important inputs and results as measured, reported, simulated, derived, assumed, inferred, illustrative, screening-level, proposed, or independently validated.
   • Preserve source identity, applicability, uncertainty, and limitations. Treat search results and AI summaries as discovery aids, not evidence.

3. Establish the technical invariants.

   • Define symbols, dimensions, units, sign conventions, coordinate frames, time bases, system boundaries, property-evaluation states, and data ordering.
   • Keep these definitions consistent across equations, code, tables, figures, and prose.

4. Select the simplest credible method.

   • Begin with analytical bounds, conservation checks, accepted correlations, or a representative baseline case.
   • Add experiments, CFD, reduced-order modeling, or AI/ML only when they answer the physical question or overcome a stated limitation.

5. Verify in proportion to claim strength and consequence.

   • Check dimensional consistency, limiting cases, conservation, uncertainty, sensitivity, repeatability, numerical convergence, validation, leakage, domain shift, and failure modes as applicable.
   • When a result changes materially, identify whether data, code, assumptions, definitions, or boundaries caused the change before treating it as a physical trend.

6. Produce and verify the actual deliverable.

   • Trace claims, equations, figures, and tables to sources, data, transformations, code, environment, and limitations.
   • Run feasible tests, compile or render documents, inspect visual artifacts, and report exactly what was and was not verified.

Integrity Gates

• Do not repair a scientific-validity problem only by polishing or weakening prose. Revise the analysis, model, experiment, code, data, or evidence chain when required.
• Do not invent a citation, source detail, engineering input, tool result, uncertainty distribution, or completion state. Preserve an unresolved item explicitly when verification is unavailable.
• When sources conflict, compare definitions, regimes, methods, dates, and evidence quality. Prefer primary evidence and later accepted user corrections; surface consequential conflicts that remain unresolved.
• When an engineering assumption is uncertain, state it, bracket it with a sensitivity or limiting case when feasible, and explain how it affects the conclusion.
• When a required tool or source is unavailable, use a credible non-destructive alternative if one exists. Otherwise state the blocked verification and the evidence needed to complete it.
• Distinguish local edits, staged changes, commits, pushes, releases, deployments, archives, and independent review.

Task Router

Read only the references needed for the task.

For document, PDF, spreadsheet, or presentation files, also use any available format-specific skill for file manipulation and rendering. Keep this skill responsible for engineering validity and scientific interpretation.

For a manuscript authored or supervised by Han Hu, read han-hu-research-style.md together with the task-specific paper and figure references even when the request does not explicitly ask for style matching. When the user provides or configures a private style-calibration corpus, also read han-hu-style-calibration-protocol.md, retrieve only genre-matched evidence, and report the evidence status of the exemplars used.

For iterative peer-review work, use reviewer-author-loop as the process scaffold when available. Apply this skill to physics, equations, instrumentation, uncertainty, data reduction, figures, modeling assumptions, and claim support.

Output Contract

• Lead with the engineering answer, finding, or decision.
• State material assumptions, definitions, units, validity ranges, and evidence class.
• Explain the governing mechanism and compare credible alternatives or bounds.
• Report uncertainty, validation, failure modes, and residual risk at the level needed by the claim.
• Provide traceable artifacts and exact verification results when files or code are involved.
• End with the smallest useful next calculation, experiment, simulation, source check, or author decision.