Optimization of double pulse pumping for Ni-like Sm x-ray lasers

We report a systematic study of double pulse pumping of the Ni-like Sm x-ray laser at 73 Angstrom, currently the shortest wavelength saturated x-ray laser. It is found that the Sm x-ray laser output can change by orders of magnitude when the intensity ratio of the pumping pulses and their relative delay are varied. Optimum pumping conditions are found and interpreted in terms of a simple model. (C) 1999 American Institute of Physics. [S0021-8979(99)07102-9].

SUPERCONDUCTING YBA2CU3O7 THIN-FILMS ON MGO BY KRF LASER ABLATION - OPTIMIZATION OF DEPOSITION PARAMETERS

The optimization of interrelated deposition parameters during deposition of in situ YBa2Cu3O7 thin films on MgO substrates by KrF laser ablation was systematically studied in a single experimental chamber. The optimum condition was found to be a substrate temperature of 720-degrees-C and a target-substrate distance of 5 cm in an oxygen partial pressure of 100 mTorr. These conditions produced films with T(c) = 87 K. The presence of YO in the plasma plume was found to be important in producing good quality films. The films were characterized by resistance-temperature measurements, energy dispersive x-ray analyses, scanning electron microscopy, and x-ray-diffraction measurements, and the physical reasons underlying film quality degradation at parameter values away from optimal are discussed.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

Design optimization of cold-formed steel portal frames taking into account the effect of building topology

Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes.A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.

Virtual Engineering Centre - Examples of Virtual Prototyping and Multidisciplinary Design Optimization

The requirement for the use of Virtual Engineering, encompassing the construction of Virtual Prototypes using Multidisciplinary Design Optimisation, for the development of future aerospace platforms and systems is discussed. Some of the activities at the Virtual Engineering Centre, a University of Liverpool initiative, are described and a number of case studies involving a range of applications of Virtual Engineering illustrated.

An exploration of small business Website optimization: Enablers, influencers and an assessment approach

The literature reveals a need for more integrated research contributions to small business Internet adoption and theoretical development. There is also a need for these developments to relate more closely to effective, or optimized, use of web applications in business processes and growth. To address this, and building upon recent integrated theoretical developments, the aim of this study is to explore the determinants and outcomes relating to small business Website optimization. Five determining variables isolated from recent theoretical developments relate to small business Website adoption outcomes. Utilizing an optimization rating instrument with these variables a methodological approach produced four key findings. From these findings we develop an optimization model and focus important contributions as propositions. These propositions provide a new understanding of the enablers and influencers of small business Website optimization and a basis for research to develop further insights in this area.