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Factorial Design of Experiments for CAE Parameter Studies

30 Chapters

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Factorial DOE in CAE context

motivation, terminology, and workflow integration for parameter studies.

Defining factors and responses

selecting CAE input parameters, output metrics, and measurement scales.

Definingresponses

Full factorial designs

structure, run count, and baseline execution in a CAE solver.

factorialstructure

Main effects and interaction effects

computation and engineering interpretation from simulation results.

interactioncomputation

Two-level factorial designs

coding factors, sign tables, and alias structure for CAE screening.

Two-levelfactorial

Replication and randomization in deterministic CAE

handling numerical noise and solver variability.

Replicationrandomization

Blocking strategies for CAE studies

accounting for mesh, solver version, and hardware effects.

Blockingstrategies

Fractional factorial designs

resolution, confounding, and efficient parameter screening in CAE.

Fractionalfactorial

Plackett-Burman designs

ultra-efficient screening of many CAE parameters with limited runs.

Plackett-Burmanultra-efficient

Design resolution and alias chains

assessing confounding risk before running CAE simulations.

resolutionassessing

Model adequacy checking

residual analysis, lack-of-fit, and diagnostics for CAE response models.

adequacychecking

ANOVA for factorial CAE experiments

partitioning variance and testing significance of parameter effects.

Effect plots and interaction plots

visualizing CAE parameter sensitivities for engineering decisions.

interactionvisualizing

Regression modeling from factorial CAE data

building predictive metamodels for parameter studies.

Regressionmodeling

full factorial study of a structural FEA model with geometric and material factors.

factorialstructural

fractional factorial screening of CFD boundary and turbulence parameters.

fractionalfactorial

factorial analysis of thermal management parameters in a conjugate heat transfer CAE model.

factorialanalysis

multi-response factorial study in crashworthiness simulation with trade-off analysis.

multi-responsefactorial

Handling multi-response CAE studies

desirability functions and Pareto-based parameter selection.

Handlingmulti-response

Augmenting factorial designs

foldover, projection, and sequential experimentation in CAE workflows.

Augmentingfactorial

Robust parameter design in CAE

incorporating noise factors and signal-to-noise ratios.

Factorial designs with mixed levels

accommodating continuous and categorical CAE parameters.

Factorialaccommodating

Optimal and space-filling designs as complements

when factorial DOE is insufficient for CAE studies.

space-fillingcomplements

Automation of factorial CAE runs

scripting, job scheduling, and metadata management.

Automationfactorial

Design evaluation before execution

power analysis, sample size, and run budget for CAE studies.

evaluationexecution

Practical pitfalls in CAE factorial DOE

factor ranges, solver convergence, and extrapolation risks.

Verification and validation of factorial DOE results

cross-checking with physical tests and higher-fidelity models.

Verificationvalidation

Integrating factorial DOE with CAE optimization loops

screening, metamodeling, and refinement.

Integratingfactorial

Reporting and documentation

presenting factorial CAE study results to engineering stakeholders.

Reportingdocumentation

Capstone project

end-to-end factorial DOE for a CAE parameter study from problem definition to recommendations.

Capstoneend-to-end