Pages that link to "Item:Q2631538"
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The following pages link to Identification of material properties using indentation test and shape manifold learning approach (Q2631538):
Displaying 9 items.
- Material model calibration by indentation, imprint mapping and inverse analysis (Q557276) (← links)
- Nonlinear shape-manifold learning approach: concepts, tools and applications (Q1639578) (← links)
- On the value of test data for reducing uncertainty in material models: computational framework and application to spherical indentation (Q1986902) (← links)
- Datadriven HOPGD based computational vademecum for welding parameter identification (Q1999553) (← links)
- Taguchi-based design of experiments in training POD-RBF surrogate model for inverse material modelling using nanoindentation (Q2974015) (← links)
- (Q4551331) (← links)
- Machine learning for material characterization with an application for predicting mechanical properties (Q6068271) (← links)
- Automatic parameter identification of a shape memory alloy model using characteristic experimental data points (Q6558113) (← links)
- Phenomenological constitutive laws for the dissipative behaviour of highly compressible elastomers and their finite element implementation (Q6658496) (← links)
