MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Modelling grain boundary migration during geometric dynamic recrystallization

High-angle grain boundary migration is predicted during geometric dynamic recrystallization (GDRX) by two types of mathematical models. Both models consider the driving pressure due to curvature and a sinusoidal driving pressure owing to subgrain walls connected to the grain boundary. One model is based on the finite difference solution of a kinetic equation, and the other, on a numerical technique in which the boundary is subdivided into linear segments. The models show that an initially flat boundary becomes serrated, with the peak and valley migrating into both adjacent grains, as observed during GDRX. When the sinusoidal driving pressure amplitude is smaller than 2 pi, the boundary stops migrating, reaching an equilibrium shape. Otherwise, when the amplitude is larger than 2 pi, equilibrium is never reached and the boundary migrates indefinitely, which would cause the protrusions of two serrated parallel boundaries to impinge on each other, creating smaller equiaxed grains.

Thermodynamic modelling of an Al(2)O(3)-MnO system using the ionic model

The thermodynamic assessment of an Al(2)O(3)-MnO pseudo-binary system has been carried out with the use of an ionic model. The use of the electro-neutrality principles in addition to the constitutive relations, between site fractions of the species on each sub-lattice, the thermodynamics descriptions of each solid phase has been determined to make possible the solubility description. Based on the thermodynamics descriptions of each phase in addition to thermo-chemical data obtained from the literature, the Gibbs energy functions were optimized for each phase of the Al(2)O(3)-MnO system with the support of PARROT(R) module from ThemoCalc(R) package. A thermodynamic database was obtained, in agreement with the thermo-chemical data extracted from the literature, to describe the Al(2)O(3)-MnO system including the solubility description of solid phases. (C) 2009 Elsevier Ltd. All rights reserved.

Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Modelling the potential distribution of the invasive tomato red spider mite, Tetranychus evansi (Acari: Tetranychidae)

Predicting the potential geographical distribution of a species is particularly important for pests with strong invasive abilities. Tetranychus evansi Baker & Pritchard, possibly native to South America, is a spider mite pest of solanaceous crops. This mite is considered an invasive species in Africa and Europe. A CLIMEX model was developed to predict its global distribution. The model results fitted the known records of T. evansi except for some records in dry locations. Dryness as well as excess moisture stresses play important roles in limiting the spread of the mite in the tropics. In North America and Eurasia its potential distribution appears to be essentially limited by cold stress. Detailed potential distribution maps are provided for T. evansi in the Mediterranean Basin and in Japan. These two regions correspond to climatic borders for the species. Mite establishment in these areas can be explained by their relatively mild winters. The Mediterranean region is also the main area where tomato is grown in open fields in Europe and where the pest represents a threat. According to the model, the whole Mediterranean region has the potential to be extensively colonized by the mite. Wide expansion of the mite to new areas in Africa is also predicted. Agricultural issues highlighted by the modelled distribution of the pest are discussed.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Modelling the progress of Asiatic citrus canker on Tahiti lime in relation to temperature and leaf wetness

The combined effect of temperature (15A degrees C, 20A degrees C, 25A degrees C, 30A degrees C, 35A degrees C, 40A degrees C and 42A degrees C) and leaf wetness duration (0, 4, 8 12, 16, 20 and 24 h) on infection and development of Asiatic citrus canker (Xanthomonas citri subsp. citri) on Tahiti lime plant was examined in growth chambers. No disease developed at 42A degrees C and zero hours of leaf wetness. Periods of leaf wetness as short as 4 h were sufficient for citrus canker infection. However, a longer leaf duration wetness (24 h) did not result in much increase in the incidence of citrus canker, but led to twice the number of lesions and four times the disease severity. Temperature was the greatest factor influencing disease development. At optimum temperatures (25-35A degrees C), there was 100% disease incidence. Maximum disease development was observed at 30-35A degrees C, with up to a 12-fold increase in lesion density, a 10-fold increase in lesion size and a 60-fold increase in disease severity.

Cloning, expression, molecular modelling and docking analysis of glutathione transferase from Saccharum officinarum

Sugarcane yield and quality are affected by a number of biotic and abiotic stresses. In response to such stresses, plants may increase the activities of some enzymes such as glutathione transferase (GST), which are involved in the detoxification of xenobiotics. Thus, a sugarcane GST was modelled and molecular docked using the program LIGIN to investigate the contributions of the active site residues towards the binding of reduced glutathione (GSH) and 1-chloro-2,4-dinitrobenzene (CDNB). As a result, W13 and I119 were identified as key residues for the specificity of sugarcane GSTF1 (SoGSTF1) towards CDNB. To obtain a better understanding of the catalytic specificity of sugarcane GST (SoGSTF1), two mutants were designed, W13L and I119F. Tertiary structure models and the same docking procedure were performed to explain the interactions between sugarcane GSTs with GSH and CDNB. An electron-sharing network for GSH interaction was also proposed. The SoGSTF1 and the mutated gene constructions were cloned and expressed in Escherichia coli and the expressed protein purified. Kinetic analyses revealed different Km values not only for CDNB, but also for GSH. The Km values were 0.2, 1.3 and 0.3 mM for GSH, and 0.9, 1.2 and 0.5 mM for CDNB, for the wild type, W13L mutant and I119F mutant, respectively. The V(max) values were 297.6, 224.5 and 171.8 mu mol min(-1) mg(-1) protein for GSH, and 372.3, 170.6 and 160.4 mu mol min(-1) mg(-1) protein for CDNB.

Influence of Plasma Protein Binding on Pharmacodynamics: Estimation of In Vivo Receptor Affinities of beta Blockers Using a New Mechanism-Based PK-PD Modelling Approach

The objective of this investigation was to examine in a systematic manner the influence of plasma protein binding on in vivo pharmacodynamics. Comparative pharmacokinetic-pharmacodynamic studies with four beta blockers were performed in conscious rats, using heart rate under isoprenaline-induced tachycardia as a pharmacodynamic endpoint. A recently proposed mechanism-based agonist-antagonist interaction model was used to obtain in vivo estimates of receptor affinities (K(B),(vivo)). These values were compared with in vitro affinities (K(B),(vitro)) on the basis of both total and free drug concentrations. For the total drug concentrations, the K(B),(vivo) estimates were 26, 13, 6.5 and 0.89 nM for S(-)-atenolol, S(-)-propranolol, S(-)-metoprolol and timolol. The K(B),(vivo) estimates on the basis of the free concentrations were 25, 2.0, 5.2 and 0.56 nM, respectively. The K(B),(vivo)-K(B),(vitro) correlation for total drug concentrations clearly deviated from the line of identity, especially for the most highly bound drug S(-)-propranolol (ratio K(B),(vivo)/K(B),(vitro) similar to 6.8). For the free drug, the correlation approximated the line of identity. Using this model, for beta-blockers the free plasma concentration appears to be the best predictor of in vivo pharmacodynamics. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:3816-3828, 2009

Bubbly Flow Structure in Hydraulic Jump

In an open channel, a hydraulic jump is the rapid transition from super- to sub-critical flow associated with strong turbulence and air bubble entrainment in the mixing layer. New experiments were performed at relatively large Reynolds numbers using phase-detection probes. Some new signal analysis provided characteristic air-water time and length scales of the vortical structures advecting the air bubbles in the developing shear flow. An analysis of the longitudinal air-water flow structure suggested little bubble clustering in the mixing layer, although an interparticle arrival time analysis showed some preferential bubble clustering for small bubbles with chord times below 3 ms. Correlation analyses yielded longitudinal air-water time scales Txx*V1/d1 of about 0.8 in average. The transverse integral length scale Z/d1 of the eddies advecting entrained bubbles was typically between 0.25 and 0.4, irrespective of the inflow conditions within the range of the investigations. Overall the findings highlighted the complicated nature of the air-water flow

A simple data logger for student-designed rocket experiments.

The final-year project for Mechanical & Space Engineering students at UQ often involves the design and flight testing of an experiment. This report describes the design and use of a simple data logger that should be suitable for collecting data from the students' flight experiments. The exercise here was taken as far as the construction of a prototype device that is suitable for ground-based testing, say, the static firing of a hybrid rocket motor.

A randomized and controlled trial of a participative ergonomics intervention to reduce injuries associated with manual tasks: physical risk and legislative

A participative ergonomics approach to reducing injuries associated with manual tasks is widely promoted; however only limited evidence from uncontrolled trials has been available to support the efficacy of such an approach. This paper reports on a randomized and controlled trial of PErforM, a participative ergonomics intervention designed to reduce the risks of injury associated with manual tasks. One hundred and seventeen small to medium sized food, construction, and health workplaces were audited by government inspectors using a manual tasks risk assessment tool (ManTRA). Forty-eight volunteer workplaces were then randomly assigned to Experimental and Control groups with the Experimental group receiving the PErforM program. Inspectors audited the workplaces again, 9 months following the intervention. The results showed a significant decrease in estimates of manual task risk and suggested better legal compliance in the Experimental group.

Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.