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FTI Announces Coupled Hybrid Inverse Solver


Forming Technologies Inc. (FTI), a leading developer of solutions for design, simulation, and costing of sheet metal components, today announces their latest technology breakthrough, Coupled Hybrid Inverse (CHI) Solver.

CHI is a Finite Element based coupled membrane/bending formulation, developed to handle strain gradients at feature lines and tight radii (R/t<=3). CHI tracks material particles using a passive force formulation. CHI’s unique technology uniformly handles complex folding, traditional simulated via FEM techniques, and CAD 2D straight bends traditionally calculated via a user input K-factor. Unlike Incremental and Inverse Solvers, CHI predicts shift in neutral surfaces (3D K- factor) to eliminate the blank size calculation inaccuracy of up to 2.2% per radius. Incremental and Inverse Solvers are handicapped by the thin shell approximation that overlooks accurate strain gradients at feature lines and tight radii.

“Coupled Hybrid Inverse Solver will change the way the industry and market uses software, including Incremental users,” said Michael Gallagher, Vice President of Sales and Marketing, FTI. “CHI more accurately simulates through-thickness strains thus eliminating up to 7% error in membrane strains around tight feature lines. Increasing this accuracy will definitely improve Springback predictability.”

Coupled Hybrid Inverse Solver is the most accurate blank calculation engine on the market. It is the only solver to track shift of neutral fibre during bending - especially important for thick parts. This feature is analogous to a 3D blank development K-factor for general curvatures. CHI improves blank size and formability results and is the only solution to provide accurate blanks for Thick parts or Tight Radii

“Our new Coupled Hybrid Inverse Solver challenges the role of the incremental solvers on the market today and it changes the landscape of formability and springback simulation as well as blank size calculation as we know it” adds Gallagher. “This 3D K-factor effect can all be achieved without jeopardizing speed and computer resources as well as providing improved formability predictions at a very competitive price.”


Date: September 19, 2006