Improvement of springback prediction in sheet metal forming

Finite element simulation of sheet metal forming is a well-established tool which is\ud used in industrial practice to evaluate geometrical defects caused by elastic springback.\ud Springback can be defined as an elastically-driven change of shape of the deformed\ud part upon removal of external loads. This phenomenon results in a deviation of the\ud real product geometry from that defined in the design phase and can cause significant\ud problems during assembly. To keep the product development time and manufacturing\ud costs low, finite element analysis aims to provide reliable information necessary for the\ud modification of tool and product geometry. Therefore, the accuracy of information\ud obtained in a numerical simulation of springback is essential for the product designers\ud and die makers.\ud This thesis deals with the improvement of numerical prediction of the springback\ud phenomenon in sheet metal forming. Modelling guidelines and advanced numerical\ud algorithms are presented that better satisfy industrial requirements for an accurate\ud simulation of springback

Numerical product design: Springback prediction, compensation and optimization

Numerical simulations are being deployed widely for product design. However, the accuracy of the numerical tools is not yet always sufficiently accurate and reliable. This article focuses on the current state and recent developments in different stages of product design: springback prediction, springback compensation and optimization by finite element (FE) analysis. To improve the springback prediction by FE analysis, guidelines regarding the mesh discretization are provided and a new through-thickness integration scheme for shell elements is launched. In the next stage of virtual product design the product is compensated for springback. Currently, deformations due to springback are manually compensated in the industry. Here, a procedure to automatically compensate the tool geometry, including the CAD description, is presented and it is successfully applied to an industrial automotive part. The last stage in virtual product design comprises optimization. This article presents an optimization scheme which is capable of designing optimal and robust metal forming processes efficiently

Adaptive Kronrod-Patterson integration of non-linear finite-element matrices

Efficient simulation of unsaturated moisture flow in porous media is of great importance in many engineering fields. The highly non-linear character of unsaturated flow typically gives sharp moving moisture fronts during wetting and drying of materials with strong local moisture permeability and capacity variations as result. It is shown that these strong variations conflict with the common preference for low-order numerical integration in finite element simulations of unsaturated moisture flow: inaccurate numerical integration leads to errors that are often far more important than errors from inappropriate discretization. In response, this article develops adaptive integration, based on nested Kronrod–Patterson–Gauss integration schemes: basically, the integration order is adapted to the locally observed grade of non-linearity. Adaptive integration is developed based on a standard infiltration problem, and it is demonstrated that serious reductions in the numbers of required integration points and discretization nodes can be obtained, thus significantly increasing computational efficiency. The multi-dimensional applicability is exemplified with two-dimensional wetting and drying applications. While developed for finite element unsaturated moisture transfer simulation, adaptive integration is similarly applicable for other non-linear problems and other discretization methods, and whereas perhaps outperformed by mesh-adaptive techniques, adaptive integration requires much less implementation and computation. Both techniques can moreover be easily combined.status: publishe

Characterisation and modelling of in-plane springback in a commercially pure titanium (CP-Ti)

Effective prediction of springback during sheet metal forming is critically important for automotive and aerospace industries, especially when forming metals with high strength to weight ratio such as Titanium. This requires materials mechanical data during plastic deformation and their dependencies on parameters like strain, strain rate and sample orientation. In this study, springback is quantified experimentally as elastic strain recovery, degradation in Young’s modulus and inelastic strain recovery on unloading in a commercially pure titanium type 50A (CP-Ti-50A). The results show strain rate dependent anisotropic mechanical behaviours and a degradation in Young’s modulus with increased level of plastic deformation. The level of degradation in Young’s modules increases gradually from 13% for samples parallel to the rolling direction (RD) to 20% for those perpendicular to the RD. A measurable non-linear strain recovery was also observed on unloading that is orientation dependent. The level of springback is characterised as the sum of elastic recovery and the contributions from both the degradation in Young’s modulus and anelastic strain recovery. It is shown that the Chord modulus can estimate springback with a reasonable accuracy taking into consideration the elastic strain recovery, degradation in Young’s modulus and anelastic strain recovery