Prof.
Jörn Ihlemann
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Research
C01 Simultaneous optimisation of geometry and graded fibre orientation distributions
Summary
The DediGrad subproject C01 develops methodological foundations for the simultaneous optimisation of geometry and graded fibre-orientation distributions in fibre-reinforced polymer structures. The starting point lies in microstructure-based material models, homogenised description methods, and parameterised finite-element models, which are coupled with efficient sensitivity analyses and optimisation algorithms. The objective is to describe feasible design spaces, incorporate manufacturing constraints in a systematic way, and provide optimised designs for graded demonstrators. In this way, C01 makes a central contribution to the mechanically consistent design of complex lightweight structures at the interface between structural performance and process constraints.
Structural and Geometric Optimisation
- Formulation of a microstructure-based material model for fibre-reinforced polymers
- Development of efficient parameterised FE simulations for demonstrators with graded fibre distributions
- Determination of optimised geometries and fibre distributions
- Incorporation of manufacturing constraints into the design process
- Provision of sensitivities as guidance for further developments
Multiscale Structural Modelling
- How can a suitable material model be determined on the basis of homogenised microstructural simulations?
- Which parameterisation of fibre distribution and geometry is appropriate for describing a large range of feasible designs?
- Which objective function best represents the desired properties?
- Which methods allow reliable and efficient optimisation while incorporating process constraints?
Related Project Members
Dr.
Hans Wulf
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Florian Rückert
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C02 Integrative numerical design methods for component and process
AI-based simulation and optimisation of complex manufacturing processes
C03 Model reduction and formalisation for increased efficiency of integrative simulation chains
Rapid prediction of local material properties using data-driven models
C04 Methodical derivation of process-structure-property relations based on hybrid data spaces
Linking experimental and simulation data spaces for hybrid process models
C05 Generative design for actively controlled mould systems with high system complexity and functional density
Generative AI for the development of adaptive mould systems
C06 Collection and context-sensitive distribution of process data
Context-based utilisation of process data across the entire production chain
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