Characterisation and modelling of the plastic material behaviour and its application in sheet metal forming simulation

The application of simulation models in sheet metal forming in automotive industry has proven to be beneficial to reduce tool costs in the designing stage and for optimising current processes. Moreover, it is a promising tool for a material supplier to optimise material choice and development for both its final application and its forming capacity. The present practice requires a high predictive value of these simulations. The material models in these simulation models need to be developed sufficiently to meet the requirement of the predictions. For the determination of parameters for the material models, mechanical tests at different strain paths are necessary 1. Usually, the material models implemented in the simulation models are not able to describe the plastic material behaviour during monotonic strain paths sufficiently accurate 2. This is true for the strain hardening model, the influence of strain rate and the description of the yield locus in these models. A first stage is to implement the improved material models which describe this single strain path behaviour in a better way. In this work, different yield criteria, a hardening model and their comparison to experiments are described extensively. The improved material model has been validated initially on forming limit curves which are determined experimentally with Nakazima strips. These results will be compared with predictions using Marciniak-Kuczinsky-analysis with both the new material model and the conventional material model. Finally, the validation on real pressed products will be shown by comparing simulation results using different material models with the experimental data. The next challenge is the description of the material after a change of strain path. Experimental evidence given here shows that this behaviour cannot be treated using the classical approach of an equivalent strain as the only history variable

A crystal plasticity model for strain-path changes in metals

A model is proposed that deals with the transient mechanical anisotropy during strain-path changes in metals. The basic mechanism is assumed to be latent hardening or softening of the slip systems, dependent on if they are active or passive during deformation, reflecting microstructural mechanisms that depend on the deformation mode rather than on the crystallography. The new model captures the experimentally observed behaviour of cross hardening in agreement with experiments for an AA3103 aluminium alloy. Generic results for strain reversals qualitatively agree with two types of behaviour reported in the literature - with or without a plateau on the stress-strain curve. The influence of the model parameters is studied through detailed calculations of the response of three selected parameter combinations, including the evolution of yield surface sections subsequent to 10% pre-strain. The mathematical complexity is kept to a minimum by avoiding explicit predictions related directly to underpinning microstructural changes. The starting point of the model is a combination of conventional texture and work hardening approaches, where an adapted full-constraints Taylor theory and a simple single-crystal work-hardening model for monotonic strain are used. However, the framework of the model is not restricted to these particular models.status: publishe

Accurate prediction of plastic properties and assessment of property variability using statistical grain-interaction modeling

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Hierarchical multi-scale modeling of texture and substructure for FE simulations of multi-stage forming processes

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Thermal Conductivity and Stability of Novel Aqueous Graphene Oxide–Al2O3 Hybrid Nanofluids for Cold Energy Storage

Thermal ice storage has gained a lot of interest due to its ability as cold energy storage. However, low thermal conductivity and high supercooling degree have become major issues during thermal cycling. For reducing the cost and making full use of the advantages of the graphene oxide–Al2O3, this study proposes heat transfer enhancement of thermal ice storage using novel hybrid nanofluids of aqueous graphene oxide–Al2O3. Thermal conductivity of aqueous graphene oxide–Al2O3 nanofluid was measured experimentally over a range of temperatures (0–70 °C) and concentrations. Thermal conductivity of ice mixing with the hybrid nanoparticles was tested. The influences of pH, dispersant, ultrasonic power and ultrasonic time on the stability of the hybrid nanofluids were examined. A new model for the effective thermal conductivity of the hybrid nanofluids considering the structure and Brownian motion was proposed. The results showed that pH, dispersant, ultrasonic power level and ultrasonication duration are important factors affecting the stability of the hybrid nanofluids tested. The optimum conditions for stability are pH = 11, 1% SDS, 375 W ultrasonic power level and 120 min ultrasonic application time. The thermal conductivity of hybrid nanofluids increases with the increase of temperature and mass fraction of nanoparticles. A newly proposed thermal conductivity model considering the nanofluid structure and Brownian motion can predict the thermal conductivity of hybrid nanofluids reasonably well

Therapeutic paradigm of dual targeting VEGF and PDGF for effectively treating FGF-2 off-target tumors

Anti-VEGF therapy has many limitations that might be resolved by using combination treatment approaches. Here, the authors demonstrate that the dual-targeting of VEGF and PDGF is required for targeting resistant FGF2+ tumors which depend on the recruitment of pericytes on tumor microvessels