In M08, you converted the model into reusable macros. In M09, you will complete the core path
by automating the design decision: sweep several heights with
*DO, consolidate a decision CSV, and select the smallest acceptable section
without touching the GUI.
Your mission
You will evaluate at least three beam heights, validate each case against theory, and automatically choose the smallest beam_h alternative that satisfies deflection, stress, and equilibrium requirements.
Guiding question: can the script decide for you unambiguously?
Objectives
After completing M09, you will be able to:
- Orchestrate a parametric sweep with
*DOand arrays. - Rebuild the model in each iteration without residual state.
- Distinguish
validation_pass(M07–M08) fromfeasible(design limits). - Consolidate one CSV as a decision table.
- Automatically select the acceptable design with the smallest section.
- Demonstrate reproducibility in two clean runs.
- Document assumptions, validation, and limitations in a brief report.
Prerequisites and downloads
- M08: driver with
build,solve, andextractsubmacros. - M07: deflection, interior-stress, and equilibrium tolerances.
- M01: analytical references and design limits (
uy_limit,stress_limit).
09_start.mac— starting point.09_parametric_study.mac— base driver (3 designs).09_parametric_core.mac— sweep core.09_build.mac— rebuild for each case.09_solve.mac— solution.09_extract.mac— per-case validation.09_bug_hunt.mac— five sweep faults.09_challenge.mac— four-design challenge.09_expected_results.csv— self-check contract.09_project_report.md— report template.height-displacement.svg— height–deflection trend.automated-decision-flow.svg— decision flow.
How to use this lesson
| Path | Duration | Coverage |
|---|---|---|
| First win | 30–35 min | Prediction, three-height sweep, and first automatic selection. |
| Complete | 70–75 min | Also: bug hunt, four-design challenge, report, and completion of the core path. |
Session map
- Mission: objectives, downloads, and prediction for three heights.
- Mental model: automate the decision, not just the calculation.
- Demonstration: criteria, residual-state-free sweep, CSV, and selection.
- Bug hunt: residual state, mixed verdicts, and incorrect selection.
- Challenge: four designs and reproducibility in two clean runs.
- Mastery: final test completing the M00–M09 core path.