For decades the classical laminate theory with linear material models has been used to calculate stress in layered composite part and then predict the load carrying behavior of laminates in structures using a failure criterion are used to predict.
Using modern phenomenological based non-linear material models with modal based failure criteria could lead not only to a better prediction of the load carrying behavior of structures but also can minimize CO2 by using less material in production and having less weight in operation of a vehicle. This presentation will concentrate on different materials from composite materials, e.g. Unidirectional and woven, through honeycombs and adhesive and finally power-bed additive manufactured metals. The way of how the phenomenological based non-linear material models are described and the physics behind modal based failure criteria will be presented. Verification and validation will close the presentation.
Jens Bold

Born in Germany, Jens studied aerospace engineering at TU Munich, finishing with diploma degree followed by two jobs for two different automotive engineering companies in Munich.
From 1998 to 2001 Jens worked for Europcoper in helicopter and aircraft doors development. He then joined Airbus, Hamburg, Germany, working in fuselage and fin stress, with responsibility for 110 employees in three nations. Finally he organized and led worldwide composite training inside Airbus.
In 2008 he joined the Toyota Formula 1 racing team in Cologne as stress engineer for monocoque and suspension parts, after which contracted with the DLR on various aircraft wing design projects while starting his PhD thesis, in which he developed the Cuntze-Bold failure and material model for composites. He then joined Johnson Controls as Manager of New Technologies Composites, followed by Boeing BR&T in 2016 in their newly-created office in Munich.
He received his Dr.-Ing. in 2019.
Since 2023 his non-linear material model combined with Cuntze modal based failure criteria has been embedded in core MSC Nastran as MATCB.