The robust optimisation of metal forming processes

Robustness, reliability, optimisation and Finite Element simulations are of major importance\ud to improve product quality and reduce costs in the metal forming industry. In this paper,\ud we review several possibilities for combining these techniques and propose a robust optimisation\ud strategy for metal forming processes. The importance of including robustness during optimisation\ud is demonstrated by applying the robust optimisation strategy to an analytical test function: for constrained\ud cases, deterministic optimisation will yield a scrap rate of about 50% whereas the robust\ud counterpart reduced this to the required 3 c reliability level

A Robust Optimisation Strategy for Metal Forming Processes

Robustness, reliability, optimisation and Finite Element simulations are of major importance to improve product\ud quality and reduce costs in the metal forming industry. In this paper, we propose a robust optimisation strategy for metal\ud forming processes. The importance of including robustness during optimisation is demonstrated by applying the robust\ud optimisation strategy to an analytical test function and an industrial hydroforming process, and comparing it to deterministic\ud optimisation methods. Applying the robust optimisation strategy significantly reduces the scrap rate for both the analytical\ud test function and the hydroforming proces

Computational optimisation of robust sheet forming processes

Mathematical optimisation consists of the modelling and solving of optimisation problems. Although both the modelling and the solving are essential for successfully optimising metal forming problems, much of the research published until now has focussed on the solving part, i.e. the development of a specific optimisation algorithm and its application to a specific optimisation problem for a specific metal forming process. We propose a generally applicable optimisation strategy which makes use of FEM simulations of metal forming processes. It consists of a methodology for modelling optimisation problems related to metal forming. Subsequently, screening is applied to reduce the size of the optimisation problem by selecting only the most important design variables. Finally, the reduced optimisation problem is solved by an efficient optimisation algorithm. However, the above strategy is deterministic, which implies that the robustness of the optimum solution is not taken into account. Robustness is a major item in the metal forming industry, hence the deterministic strategy is extended in order to include noise variables (e.g. material variation) in optimisation. This yields a robust optimisation strategy that enables to optimise to a robust solution of the problem, which contributes significantly to the industrial demand to design robust metal forming processes. Just as the deterministic optimisation strategy, it consists of a modelling, screening and solving stage. The deterministic and robust optimisation strategies are compared to each other by application to an analytical test function

Overview CGMS and related tools

The main purpose of Crop Growth Monitoring System CGMS is to estimate the influence of weather conditions on crop growth and yield on regional scale (provinces, countries, continents). Therefore, CGMS combines aspects of both weather data processing and collection as well as modelling crop growth and development

Accounting for material scatter in sheet metal forming simulations

Robust design of forming processes is gaining attention throughout the industry. To analyze the robustness of a sheet metal forming process using Finite Element (FE) simulations, an accurate input in terms of parameter variation is required. This paper presents a pragmatic, accurate and economic approach for measuring and modeling one of the main inputs, i.e. material properties and its associated scattering. For the purpose of this research, samples of 41 coils of a forming steel DX54D+Z (EN 10327:2004) from multiple batches have been collected. Fully determining the stochastic material behavior to the required accuracy for precise modeling in FE simulations would involve performing many mechanical experiments. Instead, the present work combines mechanical testing and texture analysis to limit the required effort. Moreover, use is made of the correlations between the material parameters to efficiently model the material property scatter for use in the numerical robustness analysis. The proposed approach is validated by the forming of a series of cup products using the collected material. The observed experimental scatter can be reproduced efficiently using FE simulations, demonstrating the potential of the modeling approach and robustness analysis in general

Inhomogeneous superconductivity induced in a weak ferromagnet

Under certain conditions, the order parameter induced by a superconductor (S) in a ferromagnet (F) can be inhomogeneous and oscillating, which results e.g. in the so-called pi-coupling in S/F/S junctions. In principle, the inhomogeneous state can be induced at T_c as function of the F-layer thickness d_F in S/F bilayers and multilayers, which should result in a dip-like characteristic of T_c(d_F). We show the results of measurements on the S/F system Nb/Cu_{1-x}Ni_x, for Ni-concentrations in the range x = 0.5-0.7, where such effects might be expected. We find that the critical thickness for the occurrence of superconductivity is still relatively high, even for these weak ferromagnets. The resulting dip then is intrinsically shallow and difficult to observe, which explains the lack of a clear signature in the T_c(d_F) data.Comment: 4 pages, 4 figures. To be publishedin Physica C (proceedings of the Second Euroconference on Vortex Matter in Superconductors, Crete, 2001

Resistance of superconducting nanowires connected to normal metal leads

We study experimentally the low temperature resistance of superconducting nanowires connected to normal metal reservoirs. We find that a substantial fraction of the nanowires is resistive, down to the lowest temperature measured, indicative of an intrinsic boundary resistance due to the Andreev-conversion of normal current to supercurrent. The results are successfully analyzed in terms of the kinetic equations for diffusive superconductors

Understanding urban hydrology through measurements of infiltration capacity of permeable pavements under real-live circumstances

Over the past decades various types of permeable pavements have been implemented in different municipalities in the Netherlands in order to improve infiltration capacity in urban areas and therewith being able to better treat stormwater runoff. With initial promising results this adaptation measure seemed to be the solution for urban flooding due to extreme precipitation. However, in practice, foreseen infiltration capacities were usually not met, often due unknown reasons. To better understand the functioning of permeable pavements in practice, we have studied - as part of the project Infiltrating Cities - over 100 existing permeable pavement installations in the Netherlands. At each location, infiltration capacity was tested through a full-scale infiltration testing procedure (flooded area about 40 m2) while conditional on-site factors were collected (location, age, type of permeable pavement, street-type, traffic density, vicinity of urban green, regular maintenance regime, etc.). By coupling this information we analyzed how these factors influence the infiltration capacity of permeable pavements in practice, e.g. through accelerated deterioration of infiltration capacity through time. In addition, we evaluated for a selected number of installations, how various types of maintenance may counteract this deterioration, hence improving the infiltration capacity of permeable pavements