Extracting material data for superplastic forming simulations

In subatomic particle physics, unstable particles can be studied with a so-called vertex detector placed inside a particle accelerator. A detecting unit close to the accelerator bunch of charged particles must be separated from the accelerator vacuum. A thin sheet with a complex 3D shape prevents the detector vacuum from polluting the accelerator vacuum. Hence, this sheet should be completely leak tight with respect to gases. To produce such a complex thin sheet, superplastic forming can be very attractive if a small number of products is needed. This is a forming process in which a sheet of superplastic material is pressed into a one-sided die by means of gas pressure.\ud In order to develop a material model which can be used in superplastic forming simulations, uniaxial and biaxial experiments are necessary. The uniaxial, tensile, experiments provide information about the one-dimensional material data, such as the stress as a function of equivalent plastic strain and strain rate. These data are extracted from the experiments by using inverse modeling, i.e. simulation of the tensile experiment. To fit these curves into a general material model, three parts in the uniaxial mechanical behavior are considered: initial flow stress, strain hardening and strain softening caused by void growth. Since failure in superplastic materials is preceded by the nucleation and growth of cavities inside the material, the void volume fractions of the tested specimens were also observed.\ud A very important factor in this research is the study of the permeability of the formed sheet with respect to gas. If internal voids start to coalesce, through-thickness channels will start to form, thereby providing a gas leak path. To study the twodimensional behavior, including the gas leakage, bulge experiments were performed. Within these experiments, circular sheets were pressed into a cylindrically shaped die. From these experiments it followed that the plastic straining is dependent on an applied backpressure during the forming stage. This backpressure can postpone cavity nucleation and growth

Superplastic forming simulation of RF detector foils

Complex-shaped sheet products, such as R(adio) F(requency) shieldings sheets, used in a subatomic particle\ud detector, can be manufactured by superplastic forming. To predict whether a formed sheet is resistant against gas leakage,\ud FE simulations are used, involving a user-defined material model. This model incorporates an initial flow stress, including\ud strain rate hardening. It also involves strain hardening and softening, the latter because of void formation and growth inside\ud the material. Also, a pressure-dependency is built in; an applied hydrostatic pressure during the forming process postpones\ud void formation. The material model is constructed in pursuance of the results of uniaxial and biaxial experiment

Multi-scale friction modeling for manufacturing processes: The boundary layer regime

This paper presents a multi-scale friction model for largescale forming simulations. A friction framework has been developed including the effect of surface changes due to normal loading and straining the underlying bulk material. A fast and efficient translation from micro to macro modeling, based on stochastic methods, is incorporated to reduce the computational effort. Adhesion and ploughing effects have been accounted for to characterize friction conditions on the micro scale. A discrete model has been adopted which accounts for the formation of contact patches ploughing through the contacting material. To simulate metal forming processes a coupling has been made with an implicit Finite Element code. Simulations on a typical metal formed product shows a distribution of friction values. The modest increase in simulation time, compared to a standard Coulomb-based FE simulation, proves the numerical feasibility of the proposed method

Technological Singularity

Hypothetically, technological singularity is considered as irreversible changes to the mankind resulted from technological growth due to the invention of artificial super intelligence (AI). The major concern is that AI will come out of the control and, finally, humanity will be deprived of their position in the world

Deep drawing simulation of Tailored Blanks

Tailored blanks are increasingly used in the automotive industry. A tailored blank consists of different metal parts, which are joined by a welding process. These metal parts usually have different material properties. Hence, the main advantage of using a tailored blank is to provide the right material properties at specific parts of the blank. The movement of the weld during forming is extremely important. Unwanted weld displacement can cause damage to both the product and the tool. This depends mainly on the original weld position and the process parameters. However experimental determination of the optimum weld position is quite expensive. Therefore a numerical tool has been developed for simulations of tailored blank forming. The Finite Element Code Dieka is used for the deep drawing simulations of some geometrically simple products. The results have been validated by comparing them with experimental data and show a satisfactory correlation

Drying process in the formation of sol-gel-derived TiO2 ceramic membrane

Accurate drying data for thin titania gel layers dried at 40°C and 20% relative humidity (RH) are given. The drying rate versus free moisture content diagram should show three regions as predicted by the classical drying theory. They are the constant rate period, the first falling rate period and the second falling rate period. The second falling rate period was not observed in the present case, because at 40°C and 20% RH the equilibrium moisture content will be enough to provide a continuous fluid network in the gel. The total drying time in the falling rate period increases with layer thickness. The drying mechanism in the first falling rate period was identified as capillary flow