Design Optimization/ Lightweighting

Lightweighting is a concept about building cars, trucks and aircraft with the least weight possible in order to achieve better fuel efficiency and other preferred characteristics. Light weighting may also involve design (topological/shape) optimization, in which parts are redesigned to carry loads in a more efficient manner. Here, optimization refers to the process of finding the most influential design parameters that help to satisfy project requirements. Engineers typically use design of experiments (DOE), statistics, and optimization techniques to evaluate trade-offs in order to determine the best design approach.

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GENOA Probablistic Progressive Failure Analysis (PPFA) has the capacity to model these sensitivities and scatter related to specific deign variables. GENOA PPFA can help engineers evaluate the reliability of a structure in presence of uncertainties in constituent properties of the composite, properties of metal, fabrication variables, geometry, and/or service conditions.


Using GENOA PPFA and GENOA PA with a commercial FEA solver, engineers are able to:

  • Calculation of Cumulative Distribution Functions (CDF) and Probability Density Functions (PDF),
  • Calculation of sensitivities of design parameters to the response. I
  • Comparing designs to improve structural reliability.
  • Perturb random variables and extract response from FEA solvers.
  • Select robust high fidelity methods (e.g. Advanced Mean Value and Monet Carlo).
  • Study user defined response to improves design durability and reliability.
  • Evaluate reliability of aerospace and automotive composite parts and structures.
  • Rationalize between two competing designs based on failure probability.
  • Treats non-statistical uncertainty as a random variable.
  • Predicts failure in increased risk structures (e.g., pressure vessels, leading edge, chassis).

Products Used for This Application


GENOA is a durability & damage tolerance, progressive failure, and reliability software that provides engineers with predictive computational technology to characterize and qualify advanced composite materials and structures.