Process Modelling for Control of Product Wall Thickness in Thermoforming

The present paper describes the results of an investigation into the modelling of plug assisted thermoforming. The objective of this work was to improve the finite element modelling of thermoforming through an enhanced understanding of the physical elements underlying the process. Experiments were carried out to measure the effects on output of changes in major parameters and simultaneously simple finite element models were constructed. The experimental results show that the process creates conflicting and interrelated contact friction and heat transfer effects that largely dictate the final wall thickness distribution. From the simulation work it was demonstrated that a high coefficient of friction and no heat transfer can give a good approximation of the actual wall thickness distribution. However, when conduction was added to the model the results for lower friction values were greatly improved. It was concluded that further work is necessary to provide realistic measurements and models for contact effects in thermoforming.

Shape optimization of interior cutouts in composite panels

This paper presents validated results of the optimization of cutouts in laminated carbon-fibre composite panels by adapting a recently developed optimization procedure known as Evolutionary Structural Optimization (ESO). An initial small cutout was introduced into each finite element model and elements were removed from around this cutout based on a predefined rejection criterion. In the examples presented, the limiting ply within each plate element around the cutout was determined based on the Tsai-Hill failure index. Plates with values below the product of the average Tsai-Hill number and a rejection ratio (RR) were subsequently removed. This process was iterated until a steady state was reached and the RR was then incremented by an evolutionary rate (ER). The above steps were repeated until a cutout of a desired area was achieved.

Advanced Modelling and Optimization of Infared Oven in Injection Stretch Blow-moulding for Energy Saving

In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with partial swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.

Virtual Ergonomics and Time optimization of a Railway Coach Assembly Line

The recent drive towards timely multiple product realizations has caused most Manufacturing Enterprises (MEs) to develop more flexible assembly lines supported by better manufacturing design and planning. The aim of this work is to develop a methodology which will support feasibility analyses of assembly tasks, in order to simulate either a manufacturing process or a single work-cell in which digital human models act. The methodology has been applied in a case study relating to a railway industry. Simulations were applied to help standardize the methodology and suggest new solutions for realizing ergonomic and efficient assembly processes in the railway industry.

Performance projections and design optimization of planar double gate SOI MOSFETs for logic technology applications

In this paper, by investigating the influence of source/drain extension region engineering (also known as gate-source/drain underlap) in nanoscale planar double gate (DG) SOI MOSFETs, we offer new insights into the design of future nanoscale gate-underlap DG devices to achieve ITRS projections for high performance (HP), low standby power (LSTP) and low operating power (LOP) logic technologies. The impact of high-kappa gate dielectric, silicon film thickness, together with parameters associated with the lateral source/drain doping profile, is investigated in detail. The results show that spacer width along with lateral straggle can not only effectively control short-channel effects, thus presenting low off-current in a gate underlap device, but can also be optimized to achieve lower intrinsic delay and higher on-off current ratio (I-on/I-off). Based on the investigation of on-current (I-on), off-current (I-off), I-on/I-off, intrinsic delay (tau), energy delay product and static power dissipation, we present design guidelines to select key device parameters to achieve ITRS projections. Using nominal gate lengths for different technologies, as recommended from ITRS specification, optimally designed gate-underlap DG MOSFETs with a spacer-to-straggle (s/sigma) ratio of 2.3 for HP/LOP and 3.2 for LSTP logic technologies will meet ITRS projection. However, a relatively narrow range of lateral straggle lying between 7 to 8 nm is recommended. A sensitivity analysis of intrinsic delay, on-current and off-current to important parameters allows a comparative analysis of the various design options and shows that gate workfunction appears to be the most crucial parameter in the design of DG devices for all three technologies. The impact of back gate misalignment on I-on, I-off and tau is also investigated for optimized underlap devices.

Optimization of image quality and dose for Varian aS500 electronic portal imaging devices (EPIDs)

This study was carried out to investigate whether the electronic portal imaging (EPI) acquisition process could be optimized, and as a result tolerance and action levels be set for the PIPSPro QC-3V phantom image quality assessment. The aim of the optimization process was to reduce the dose delivered to the patient while maintaining a clinically acceptable image quality. This is of interest when images are acquired in addition to the planned patient treatment, rather than images being acquired using the treatment field during a patient's treatment. A series of phantoms were used to assess image quality for different acquisition settings relative to the baseline values obtained following acceptance testing. Eight Varian aS500 EPID systems on four matched Varian 600C/D linacs and four matched Varian 2100C/D linacs were compared for consistency of performance and images were acquired at the four main orthogonal gantry angles. Images were acquired using a 6 MV beam operating at 100 MU min(-1) and the low-dose acquisition mode. Doses used in the comparison were measured using a Farmer ionization chamber placed at d(max) in solid water. The results demonstrated that the number of reset frames did not have any influence on the image contrast, but the number of frame averages did. The expected increase in noise with corresponding decrease in contrast was also observed when reducing the number of frame averages. The optimal settings for the low-dose acquisition mode with respect to image quality and dose were found to be one reset frame and three frame averages. All patients at the Northern Ireland Cancer Centre are now imaged using one reset frame and three frame averages in the 6 MV 100 MU min(-1) low-dose acquisition mode. Routine EPID QC contrast tolerance (+/-10) and action (+/-20) levels using the PIPSPro phantom based around expected values of 190 (Varian 600C/D) and 225 (Varian 2100C/D) have been introduced. The dose at dmax from electronic portal imaging has been reduced by approximately 28%, and while the image quality has been reduced, the images produced are still clinically acceptable.

Experimental design and batch experiments for optimization of Cr(VI) removal from aqueous solutions by hydrous cerium oxide nanoparticles

Hydrous cerium oxide (HCO) was synthesized by intercalation of solutions of cerium(III) nitrate and sodium hydroxide and evaluated as an adsorbent for the removal of hexavalent chromium from aqueous solutions. Simple batch experiments and a 2⁵ factorial experimental design were employed to screen the variables affecting Cr(VI) removal efficiency. The effects of the process variables; solution pH, initial Cr(VI) concentration, temperature, adsorbent dose and ionic strength were examined. Using the experimental results, a linear mathematical model representing the influence of the different variables and their interactions was obtained. Analysis of variance (ANOVA) demonstrated that Cr(VI) adsorption significantly increases with decreased solution pH, initial concentration and amount of adsorbent used (dose), but slightly decreased with an increase in temperature and ionic strength. The optimization study indicates 99% as the maximum removal at pH 2, 20 °C, 1.923 mM of metal concentration and a sorbent dose of 4 g/dm³. At these optimal conditions, Langmuir, Freundlich and Redlich–Peterson isotherm models were obtained. The maximum adsorption capacity of Cr(VI) adsorbed by HCO was 0.828 mmol/g, calculated by the Langmuir isotherm model. Desorption of chromium indicated that the HCO adsorbent can be regenerated using NaOH solution 0.1 M (up to 85%). The adsorption interactions between the surface sites of HCO and the Cr(VI) ions were found to be a combined effect of both anion exchange and surface complexation with the formation of an inner-sphere complex.

OPTIMIZATION OF THE SLOW-MODE PLASMON POLARITON IN LIGHT-EMITTING TUNNEL-JUNCTIONS

Light emitted from metal/oxide/metal tunnel junctions can originate from the slow-mode surface plasmon polariton supported in the oxide interface region. The effective radiative decay of this mode is constrained by competition with heavy intrinsic damping and by the need to scatter from very small scale surface roughness; the latter requirement arises from the mode's low phase velocity and the usual momentum conservation condition in the scattering process. Computational analysis of conventional devices shows that the desirable goals of decreased intrinsic damping and increased phase velocity are influenced, in order of priority, by the thickness and dielectric function of the oxide layer, the type of metal chosen for each conducting electrode, and temperature. Realizable devices supporting an optimized slow-mode plasmon polariton are suggested. Essentially these consist of thin metal electrodes separated by a dielectric layer which acts as a very thin (a few nm) electron tunneling barrier but a relatively thick (several 10's of nm) optically lossless region. (C) 1995 American Institute of Physics.

Cross-layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems

Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence,purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44%.

Investigation of Utilizing Single Surface Depressions in Optimization of NLF Aerofoil Design

An environment has been created for the optimisation of aerofoil profiles with inclusion of small surface features. For TS wave dominated flows, the paper examines the consequences of the addition of a depression on the aerodynamic optimisation of an NLF aerofoil, and describes the geometry definition fidelity and optimisation algorithm employed in the development process. The variables that define the depression for this optimisation investigation have been fixed, however a preliminary study is presented demonstrating the sensitivity of the flow to the depression characteristics. Solutions to the optimisation problem are then presented using both gradient-based and genetic algorithm techniques, and for accurate representation of the inclusion of small surface perturbations it is concluded that a global optimisation method is required for this type of aerofoil optimisation task due to the nature of the response surface generated. When dealing with surface features, changes in the transition onset are likely to be of a non-linear nature so it is highly critical to have an optimisation algorithm that is robust, suggesting that for this framework, gradient-based methods alone are not suited.

Implementing a structural continuity constraint and a halting method for the topology optimization of energy absorbers

This study investigates topology optimization of energy absorbing structures in which material damage is accounted for in the optimization process. The optimization objective is to design the lightest structures that are able to absorb the required mechanical energy. A structural continuity constraint check is introduced that is able to detect when no feasible load path remains in the finite element model, usually as a result of large scale fracture. This assures that designs do not fail when loaded under the conditions prescribed in the design requirements. This continuity constraint check is automated and requires no intervention from the analyst once the optimization process is initiated. Consequently, the optimization algorithm proceeds towards evolving an energy absorbing structure with the minimum structural mass that is not susceptible to global structural failure. A method is also introduced to determine when the optimization process should halt. The method identifies when the optimization method has plateaued and is no longer likely to provide improved designs if continued for further iterations. This provides the designer with a rational method to determine the necessary time to run the optimization and avoid wasting computational resources on unnecessary iterations. A case study is presented to demonstrate the use of this method.