Cold rolling mill thickness control using the cascade-correlation neural network

The improvements in thickness accuracy of a steel strip produced by a tandem cold-roIling mill are of substantial interest to the steel industry. In this paper, we designed a direct model-reference adaptive control (MRAC)  scheme that exploits the natural level of excitation existing in the closed-loop with a dynamically constructed cascade-correlation neural network (CCNN) as a controller for cold roIling mill thickness control. Simulation results show that the combination of a such a direct MRAC scheme and the dynamically constructed CCNN significantly improves the thickness accuracy in the presence of disturbances and noise in comparison with to the conventional PID controllers.

Misunderstanding John Stuart Mill on science: Paul Feyerabend`s bad influence

Feyerabend, 1975; Feyerabend, 1981 and Feyerabend, 1987 takes J. S. Mill’s On Liberty to support the proliferation of theories in science and to emphasize the fallibility of scientific knowledge. On Liberty, according to Feyerabend, contradicts and overthrows Mill’s major study of science, A System of Logic. Staley (1999) reads the 2 works of Mill as giving complementary accounts of science. The present author rejects these interpretations of Mill, arguing that A System of Logic and On Liberty are mutually compatible since On Liberty concerns the nature of non-scientific knowledge and the methods that Mill believes are appropriate to expanding and assessing that knowledge.

Wastewater reuse and treatment options for the dairy industry

Milk-processing plants generate significant quantities of wastewater with relatively high organic matter concentrations on a daily basis. In addition to environmental damage that can result from the discharge of these wastewaters into the natural waterways, the presence of products such as milk solids into wastewater streams represents a loss of valuable product for the plants. This paper presents a review of wastewater management practices employed by six milk-processing plants in Victoria, Australia. In all six plants investigated, milk powder represents a major product. During the milk powder production, water is evaporated, condensed and can be reused for various purposes with a significant impact on water usage. Other major products are anhydrous milk fat, cheese, butter, and UHT milk. The effectiveness of the practices was assessed through two main criteria: first through the water to milk intake ratio, and the waste volume coefficient. Both parameters characterise the plant efficiency in regard of water consumption and water reuse, Information on cleaning chemical usage and recovery was also assessed as part of the review. Significant discrepancies emerge between the plants first due to the products manufacturad and water reuse possibilities available in each plant. Second the type of treatment technologies used for condensate and cleaning solution influences the figures. One of the investigated plants is almost self-sufficient for water, emphasising the benefits gained from the use of technologies like membrane separations for condensate and cleaning solution treatment. In some cases, less cost-intensive technologies such as a clarifier are successful to improve cleaning agent recovery.

Balancing environmental impacts and benefits of wastewater reuse

Wastewater reuse is being widely promulgated to help address the global freshwater resource crisis. It can assist in reducing extraction of freshwater from the environment, and reuse of wastewater lessens the need for environmental discharge, which is clearly beneficial to receiving waters. But the practice itself also has the potential to be detrimental to natural and human environments: soil structure can become degraded, aquifers may be polluted, and human health may be threatened. The challenge facing natural resource managers is to identify the potential benefits and risks, and to achieve an appropriate balance. This paper describes environmental benefits and threats concomitant with the reuse of wastewater. We frequently draw upon examples from China and Australia-two countries that face particularly daunting water resource
challenges-but the principles can be.extended far beyond these geographical bounds and are applicable to
many parts of the world.

Is the risk of illness through consuming vegetables irrigated with reclaimed wastewater different for different population groups?

The use of reclaimed wastewater for irrigation of horticultural crops is commonplace in many parts of the world and is likely to increase. Concerns about risks to human health arising from such practice, especially with respect to infection with microbial pathogens, are common. Several factors need to be considered when attempting to quantify the risk posed to a population, such as the concentration of pathogens in the source water, water treatment efficiency, the volume of water coming into contact with the crop, and the die-off rate of pathogens in the environment. Another factor, which has received relatively less attention, is the amount of food consumed. Plainly, higher consumption rates place one at greater risk of becoming infected. The amount of vegetables consumed is known to vary among ethic groups. We use Quantitative Microbial Risk Assessment Modelling (QMRA) to see if certain ethnic groups are exposed to higher risks by virtue of their consumption behaviour. The results suggest that despite the disparities in consumption rates by different ethnic groups they generally all faced comparable levels of risks. We conclude by suggesting that QMRA should be used to assess the relative levels of risk faced by groups based on divisions other than ethnicity, such as those with compromised immune systems.

Mill specific prediction of worsted yarn performance

Different spinning mills use different raw materials, processing methodologies, and equipment, all of which influence the quality of the yarns produced. Because of many variables, there is a difficulty in developing a universal empirical/theoretical model. This work presents a multilayer perceptron algorithm (MLP) model for the purpose of building a mill specific worsted spinning performance prediction tool. Sixteen inputs are used to predict key yarn properties and spinning performance, including number of fibers in cross-section, unevenness (U%), thin places, neps, yarn tenacity, elongation at break, thick places, and spinning ends-down. Validation of the model on mill specific commercial data set shows that the general fit to the target values is good. Importantly, the performance of the MLP shows a certain degree of stability to different, random selections of independent test data. Subsequent comparison against the predicted outputs of Sirolan Yarnspec™ confirms the overall performance of the artificial neural network (ANN) method to be more accuratefor mill specific predictions.

Predicting the rolling force in hot steel rolling mill using an ensemble model

Accurate prediction of the roll separating force is critical to assuring the quality of the final product in steel manufacturing. This paper presents an ensemble model that addresses these concerns. A stacked generalisation approach to ensemble modeling is used with two sets of the ensemble model members, the first set being learnt from the current input-output data of the hot rolling finishing mill, while another uses the available information on the previous coil in addition to the current information. Both sets of ensemble members include linear regression, multilayer perceptron, and k-nearest neighbor algorithms. A competitive selection model (multilayer perceptron) is then used to select the output from one of the ensemble members to be the final output of the ensemble model. The ensemble model created by such a stacked generalization is able to achieve extremely high accuracy in predicting the roll separation force with the average relative accuracy being within 1% of the actual measured roll force.

Photocatalytic degradation of dyes in wastewater using TiO2/UV in a flat-plate reactor

The photocatalyst TiO₂ with UV irradiation was used to degrade dyes in textile effluent in a flat-plate photoreactor. A test system was built with the reactor area of 1 x 0.3m2, UV light of six 36W-blacklight. TiO₂ powder P25 with BET surface area 50±15m2/g, average primary particle size 21 nm, purity> 99.5% and content of 83.9% anatase and 16.1 % rutile was used as the photocatalyst. A number of dyes commonly present in dyeing wastewater were tested in this study. The different operating parameters, such as dosage of photocatalyst, the structure of the reactor, flow rates through the flat-plate reactor, UV radiation intensity and tilted angle of the reactor, were investigated. The results showed that the photocatalytic process could efficiently remove most of the colour contained in the dyeing wastewater. It was experimentally observed that first-order kinetics was adequate for characterising the process. The flow rate and the tilted angle had some influence on the film thickness of the fluid in the reactor and the empirical correlation between the film thickness of the fluid and these two parameters was developed. The photoreaction rate was mainly determined by the film thickness of the fluid on the reactor surface and the dosage of the photocatalyst. Optimum operating parameters of the system were found to be at the film thickness of about 1.4mm and a TiO₂ dosage of 1 gIL. The higher the UV intensity, the faster the reaction rate was. The results of these experiments showed that this method has the great potential for colour removal from wastewater at commercial scale.

To overcome the common difficulty of separating the used TiO₂ suspension after treatment precipitation followed with filtration was used in this study to determine the separation efficiencies. On the other hand, TiO₂ in a small pillar shape was also studied for photocatalytic degradation of textile dye effluent. The pillar pellet was made in Oegussa Company, Germany ranging from 2.5 to 5.3mm long and with a diameter of 3.7mm. It was almost pure TiO₂ (83.2% anatase and 16.8% rutile), with a S-content of <20 ppm and a CI content of the order of 0.1 wt. %. No further elements are present in contents above 0.05 wt.%. The TiO₂ pillars were placed on the flat-plate reactor that was divided by the rectangular slots and irradiated under UV light when the treated solution went through the reactor. Four dyes and their mixtures were tested. The results showed that the photocatalytic process under this configuration efficiently remove the colour from textile dyeing effluent, and pillar shape TiO₂ photocatalyst was not dissolved in water and very easy to be separated from solution, enabling it to be reused many times. The first-order kinetics was adequate for characterising the photocatalytic degradation process and the photocatalytic performance was comparable to TiO₂ powder. It is believed that the TiO₂ pellet would be a preferable form of photocatalyst in applications for textile effluent treatment process, and other wastewater treatment processes.