Maternal mortality at Queen Elizabeth Central Hospital, 1989 to 1990

No Abstrac

Efficient Robust Optimization of Metal Forming Processes using a Sequential Metamodel Based Strategy

The coupling of Finite Element (FE) simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a new and generally applicable structured methodology for modeling and solving robust optimization problems. Stochastic design variables or noise variables are taken into account explicitly in the optimization procedure. The metamodel-based strategy is combined with a sequential improvement algorithm to efficiently increase the accuracy of the objective function prediction. This is only done at regions of interest containing the optimal robust design. Application of the methodology to an industrial V-bending process resulted in valuable process insights and an improved robust process design. Moreover, a significant improvement of the robustness (> 2s ) was obtained by minimizing the deteriorating effects of several noise variables. The robust optimization results demonstrate the general applicability of the robust optimization strategy and underline the importance of including uncertainty and robustness explicitly in the numerical optimization procedure

A numerical approach to robust in-line control of roll forming processes

The quality of roll formed products is known to be highly sensitive and dependent on the process parameters and thus the unavoidable variations of these parameters during mass production. To maintain a constant high product quality, a new roll former with an adjustable final roll forming stand is developed at Deakin University enabling the continuous compensation for possible shape defects. In this work, a numerical approach to robust in-line control of the roll forming of a V-section profile is presented, combining the aspects of robust process design and in-line compensation methods. A numerical study is performed to determine the relationship between controllable process settings and uncontrollable variation of incoming material properties with respect to the common product defects longitudinal bow and springback. The computationally expensive non-linear FE simulations used in this study are subsequently replaced by metamod-els based on efficient Single Response Surfaces. Using these metamodels, the optimal setting for the adjustable stand is determined with robust optimization techniques and the effect on product quality analyzed. It is shown that the subsequent adjustment of the final roll stand position leads to a significantly improved product quality by preventing product defects and minimizing the deteriorating effects of scattering variables

Computation of Multi-Dimensional Material Response Coupled to Hypersonic Flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97085/1/AIAA2012-2873.pd

Coupled Computation of Fluid and Material Response for Non-Charring Ablative Materials in Hypersonic Flow

Hypersonic vehicles are subjected to high heat loads throughout their flight trajectories, and as a result, some form of thermal protection system (TPS) is required to ensure the vehicle’s survival. Accurate prediction of the behavior of these materials in a hypersonic environment is crucial to the efficient design of a hypersonic flight vehicle. It can be very costly and difficult, however, to experimentally replicate the flow conditions found in many hypersonic regimes, and for this reason it is desirable to be able to simulate the behavior of TPS materials under these flight conditions. This study aims to improve the modeling of the coupled fluid-material response problem for TPS materials in realistic hypersonic flows by coupling a hypersonic CFD code with an axisymmetric material response code

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