An optimization study is a structured comparison within a stated set of choices and constraints. This exercise teaches you to define that comparison, inspect which candidates are feasible and preserve the search settings so that the selected result can be understood and reproduced.
Open this exercise in Workbench
Prepare the baseline
Run or inspect the baseline first, then enter the objective, bounds, constraints and sampling or search controls exactly as specified. Record the seed where one is provided. Keep infeasible outcomes visible: they help explain the constraints and should not be silently discarded or treated as a solver success.
Worked procedure
1. Open Simulation and identify its thermal load, laminate and Process schedule. In Optimize → Process select that thermal case; inspect source temperatures, layer conductivity/capacity and film coefficients.
2. Use duration objective, target core temperature 120 °C, required hold 10 min, maximum part temperature 200 °C and maximum through-thickness difference 30 °C. Sweep time scale 0.75–1.25 and temperature scale 0.90–1.10 with 5 samples per axis and 21 through-thickness nodes.
3. Keep cure exotherm off for this thermal-only exercise and acknowledge the displayed assumptions. Run; inspect feasible candidates, temperature histories and the best sampled duration. If none are feasible, report that outcome and adjust a constraint deliberately.
4. Save as Thermal cycle-time study. Reopen Optimizations → Process and inspect saved boundaries, layers, constraints and source cycle. Create a candidate cycle separately, then rerun the coupled simulation; thermal feasibility alone does not establish cure or strength.
Review checkpoints
The schedule is prescribed boundary temperature, not oven dynamics. This example is not UV or pultrusion optimization.
Compare a refined grid before accepting the best sampled candidate. Thermal-only feasibility is not cure completion or a strength pass.
Model limits
Guided optimization case study using shared database records. Configure the documented search in Optimize, then save its results and inputs. No precomputed optimum or benchmark-validation claim. One-dimensional through-thickness transport; lateral heat loss and oven airflow are not resolved. Inspect linked cure settings before interpreting reaction heating.
Interpret the comparison
Describe the best feasible candidate found within this search, not an unqualified global optimum. Inspect neighbouring samples or repeat the stated search comparison where requested, then create and rerun the candidate in the relevant analysis. A saved optimization snapshot and a newly evaluated design are separate pieces of evidence.
How information passes between models
Micro → Laminates: Predicted ply stiffness, strength, density and expansion properties.
Materials → Micro: Constituent stiffness, strength, density and thermal / moisture properties.
Thermal → Simulation: SIMULATION selects this case and its analysis model; the case owns its applicable cycle and input references.
Laminates → Thermal: Ply angles and thicknesses, stiffness, mass and ply properties.
Models → Micro: Applied model assignment: Halpin–Tsai. Model parameters and formulation are used by Micro.
Models → Thermal: Applied model assignment: 1D transient heat transfer. Model parameters and formulation are used by Thermal.
Further reading and evidence
- Optimization cases: complete inputs and guided studies
- Enter a process cycle and boundary conditions
- Cure exotherm and evolving modulus
Review the recorded validation scope. Retain the original inputs and solver notices with the results. Representative teaching data are not design allowables.
References and source sections
References are retained with the formulations they support. Software instructions describe implementation scope; a cited source does not establish independent validation of a CDS calculation.