4 resultados para particle Swarm Optimization
em Greenwich Academic Literature Archive - UK
Resumo:
A particle swarm optimisation approach is used to determine the accuracy and experimental relevance of six disparate cure kinetics models. The cure processes of two commercially available thermosetting polymer materials utilised in microelectronics manufacturing applications have been studied using a differential scanning calorimetry system. Numerical models have been fitted to the experimental data using a particle swarm optimisation algorithm which enables the ultimate accuracy of each of the models to be determined. The particle swarm optimisation approach to model fitting proves to be relatively rapid and effective in determining the optimal coefficient set for the cure kinetics models. Results indicate that the singlestep autocatalytic model is able to represent the curing process more accurately than more complex model, with ultimate accuracy likely to be limited by inaccuracies in the processing of the experimental data.
Resumo:
Optimal design of a power electronics module isolation substrate is assessed using a combination of finite element structural mechanics analysis and response surface optimisation technique. Primary failure modes in power electronics modules include the loss of structural integrity in the ceramic substrate materials due to stresses induced through thermal cycling. Analysis of the influence of ceramic substrate design parameters is undertaken using a design of experiments approach. Finite element analysis is used to determine the stress distribution for each design, and the results are used to construct a quadratic response surface function. A particle swarm optimisation algorithm is then used to determine the optimal substrate design. Analysis of response surface function gradients is used to perform sensitivity analysis and develop isolation substrate design rules. The influence of design uncertainties introduced through manufacturing tolerances is assessed using a Monte-Carlo algorithm, resulting in a stress distribution histogram. The probability of failure caused by the violation of design constraints has been analyzed. Six geometric design parameters are considered in this work and the most important design parameters have been identified. Overall analysis results can be used to enhance the design and reliability of the component.
Resumo:
This paper presents an analysis of biofluid behavior in a T-shaped microchannel device and a design optimization for improved biofluid performance in terms of particle liquid separation. The biofluid is modeled with single phase shear rate non-Newtonian flow with blood property. The separation of red blood cell from plasma is evident based on biofluid distribution in the microchannels against various relevant effects and findings, including Zweifach-Fung bifurcation law, Fahraeus effect, Fahraeus-Lindqvist effect and cell free phenomenon. The modeling with the initial device shows that this T-microchannel device can separate red blood cell from plasma but the separation efficiency among different bifurcations varies largely. In accordance with the imbalanced performance, a design optimization is conducted. This includes implementing a series of simulations to investigate the effect of the lengths of the main and branch channels to biofluid behavior and searching an improved design with optimal separation performance. It is found that changing relative lengths of branch channels is effective to both uniformity of flow rate ratio among bifurcations and reduction of difference of the flow velocities between the branch channels, whereas extending the length of the main channel from bifurcation region is only effective for uniformity of flow rate ratio.
Resumo:
An innovative methodology has been used for the formulation development of Cyclosporine A (CyA) nanoparticles. In the present study the static mixer technique, which is a novel method for producing nanoparticles, was employed. The formulation optimum was calculated by the modified Shepard's method (MSM), an advanced data analysis technique not adopted so far in pharmaceutical applications. Controlled precipitation was achieved injecting the organic CyA solution rapidly into an aqueous protective solution by means of a static mixer. Furthermore the computer based MSM was implemented for data analysis, visualization, and application development. For the optimization studies, the gelatin/lipoid S75 amounts and the organic/aqueous phase were selected as independent variables while the obtained particle size as a dependent variable. The optimum predicted formulation was characterized by cryo-TEM microscopy, particle size measurements, stability, and in vitro release. The produced nanoparticles contain drug in amorphous state and decreased amounts of stabilizing agents. The dissolution rate of the lyophilized powder was significantly enhanced in the first 2 h. MSM was proved capable to interpret in detail and to predict with high accuracy the optimum formulation. The mixer technique was proved capable to develop CyA nanoparticulate formulations.