Reliability and scale effect in toughness of concrete structures

In the present work, the distribution of the random toughness characteristics (i.e. critical energy release rate, G_1c) has been evaluated on the basis of experimental observations. Fracture test results from three groups of geometrically similar concrete specimens of size (width×total depth×thickness), 420×420×50–1680×1680×200 mm³, made with different maximum aggregate size of 9.5, 19, 38, and 76 mm were analyzed using a recently proposed distribution of extremes. In applications of probability, it is important to use an appropriate distribution type and adequate techniques for estimating the parameters of distribution. In this study, a new type distribution of minima is employed for probability computations. It was noticed that the entropy of distribution increases with the crack length, i.e. the uncertainty of toughness, G_1c, value increases with crack length. A non-linear reduction of the maximum allowable splitting force with the defect size, a, was noticed. For large specimens, the maximum allowable splitting load is more sensitive to the required reliability level than that for small specimens. Reliability increases with aggregate size when all other conditions were constant.     

Evolving artificial neural network ensembles

Using a coordinated group of simple solvers to tackle a complex problem is not an entirely new idea. Its root could be traced back hundreds of years ago when ancient Chinese suggested a team approach to problem solving. For a long time, engineers have used the divide-and-conquer strategy to decompose a complex problem into simpler sub-problems and then solve them by a group of solvers. However, knowing the best way to divide a complex problem into simpler ones relies heavily on the available domain knowledge. It is often a manual process by an experienced engineer. There have been few automatic divide-and-conquer methods reported in the literature. Fortunately, evolutionary computation provides some of the interesting avenues to automatic divide-and-conquer methods. An in-depth study of such methods reveals that there is a deep underlying connection between evolutionary computation and ANN ensembles. Ideas in one area can be usefully transferred into another in producing effective algorithms. For example, using speciation to create and maintain diversity had inspired the development of negative correlation learning for ANN ensembles, and an in-depth study of diversity in ensembles. This paper will review some of the recent work in evolutionary approaches to designing ANN ensembles.     

Algorithms in the W-Hierarchy

We show new upper bounds for problems in the W-hierarchy of fixed-parameter complexity. A crucial ingredient of our proofs is an extension to the W-RAM model, which permits more-powerful operations but remains equivalent to the original. We use the extended model to give new upper bounds for Subsetsum, Maximum Irredundant Set, and various problems concerning intersection of finite-state machines.     

Estimation of the Substrate Concentration Profiles in Petroleum Pipelines Containing Biofilms

In industrial systems, the formation of biofilms can cause many problems, such as an increase in the flow resistance of pipelines, energy losses in fluid transport and heat exchangers, product contamination, materials deterioration, and biocorrosion. As a result, biofilms contribute substantially to economic losses in the industry. Corrosion is particularly an issue in the petroleum industry and its implications range from down-hole completion through petroleum processing units. Much of this corrosion is attributed to microbial activities. This paper proposes a mathematical model for predicting substrate concentration for such microbial growth. Substrate concentrations in the system and near the biofilm surface are one of the parameters that has a great effect in determining the extent of the problems associated with biofilms. In this study, a convective-diffusion model under various flow conditions (stagnant, laminar, and turbulent) has been solved using the finite difference technique, employing the alternating direction implicit (ADI) method. The model assumes that a liquid containing substrate and bacteria is flowing in a pipeline with known concentrations at the inlet and then predicts the variation of the transient (as a function of time) substrate concentration along the pipeline and as a function of the pipe radius. The model is then used to predict and estimate the substrate concentration profiles on the biofilm surface under different environmental conditions. A parametric study was also conducted to study the effect of the different parameters influencing the substrate concentration profiles in the system and on the biofilm surface.     

A mechanical model for the deformational behavior of the polymeric membranes operating in pressure-driven processes

A mechanical model consisting of three elements (elastic, viscoelastic, and plastic) is proposed to describe the deformational behavior of a polymeric membrane operating in a pressure-driven process. The changes in the membrane thickness are proposed to be calculated from the experimentally obtained flux data. The advantages of a mechanical model over the conventional method of hysteresis area measurement as the mechanical stability of the polymeric membranes are discussed. © 1992 John Wiley & Sons, Inc.     

Low-loss high power RF switching using multifinger AlGaN/GaN MOSHFETs

We demonstrate a novel RF switch based on a multifinger AlGaN/GaN MOSHFET. Record high saturation current and breakdown voltage, extremely low gate leakage current and low gate capacitance of the III-N MOSHFETs make them excellent active elements for RF switching. Using a single element test circuit with 1-mm wide multifinger MOSHFET we achieved 0.27 dB insertion loss and more than 40 dB isolation. These parameters can be further improved by impedance matching and by using submicron gate devices. The maximum switching power extrapolated from the results for 1A/mm 100 /spl mu/m wide device exceeds 40 W for a 1-mm wide 2-A/mm MOSHFET.     

Study of Density Behavior During LHCD and IBW Heating in the HT-7 Superconducting Tokamak

A new method using special shape parameters has been introduced to study density behavior with synergy of lower hybrid current drive (LHCD) and ion Bernstein wave (IBW) heating in the HT-7 superconducting tokamak. During the synergy of the LHCD and IBW heating an improved confinement plasma was achieved, and the electron density was increased and peaked.     

Cost effective second generation AC-modules: Development and testing aspects

In the framework of the European research project PV2GO, a new AC-module inverter was developed, taking into account all relevant aspects from a European market's point of view (standards, market, application, and research and development goals). The project goal was to achieve the overall system costs of 3 Euro per Wp for a modular plug-and-play photovoltaic system. For the photovoltaic-module, a standard 130-Wp Eurosolare module was chosen. The research and development (R&D) goal was to develop an advanced DC-control system consisting of a state-of-the-art programmable digital device and an Application Specific Integrated Circuit (ASIC) for the AC-control of the inverter. According to the topology concept, thermal and magnetic designs were optimized with regard to production technology and packaging for large-scale production. The new AC-modules were tested in a number of field-test sites in various parts of Europe and their reliability was assessed through Highly Accelerated Stress Tests. Efficiency and power quality have been tested in the laboratory. Further in the PV2GO project an optimization study of the manufacturing process of the new generation of AC-modules for high volume output was done. Another task was the pre-certification procedure to assure compliance with the European guidelines and standards.