Request Evaluation

DESIGN OPTIMIZATION-LIGHTWEIGHTING

The ultimate goal of lightweighting is to build with the least weight possible in order to achieve better fuel efficiency. 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.

 

Our Solution

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 sensitivities of design parameters to the response.

  • 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).

  • Improve design durability and reliability with study user-defined response.

  • Evaluate reliability of aerospace and automotive composite parts and structures.

  • Rationalize between two competing designs based on failure probability.

  • Treat non-statistical uncertainty as a random variable.

  • Predict failure in increased risk structures (e.g., pressure vessels, leading edge, chassis).

Lightweighting

Case Studies

Download the latest case study.

PDF-Icon

Datasheet

Download the latest datasheets.

Products Used for This Application

genoa_MS

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

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from - Youtube
Vimeo
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google
Spotify
Consent to display content from - Spotify
Sound Cloud
Consent to display content from - Sound
Request Evaluation