Estimation of fouling in a plate heat exchanger through the application of neural networks

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades‐offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques. Copyright © 2005 Society of Chemical Industry     

Intraoperative neurological monitoring

Intraoperative neurological monitoring (INM) is the evaluation of the nervous system within the operating room (OR) environment. In this paper, the INM system is tested in a clinical setting in comparison with conventional somatosensory evoked potential (SEP) monitoring. The study results demonstrate the capability of the INM system in extracting clearer and more stable SEP signals. The high SNR of SEP signals collected in various clinical environments, including the OR, makes the INM system a robust platform for continuous monitoring. While the current use of EP monitoring is limited to intermittent analysis by a highly trained clinical neurophysiologist, the authors believe in changing this paradigm by developing continuous monitoring systems, such as the INM system, capable of automated quantitative EP analysis. This noninvasive monitoring modality will allow for a wider range of use in clinical practice. Based on volunteer and clinical patient studies, the INM monitoring system demonstrates much greater reliability and accuracy via the artifact rejection and denoising strategies. It provides more strategic filtering options for different situations under which the clinical SEP response signal could be greatly contaminated and distorted. Furthermore, the INM system offers a promising approach to signal extraction in real-time monitoring during SEP research.     

Effects of solid retention time on the performance of submerged anoxic/oxic membrane bioreactor.

In this study, four similar bench-scale submerged Anoxic/Oxic Membrane Bioreactors (MBR) were used simultaneously to investigate the effects of solids retention time (SRT) on organic and nitrogen removal in MBR for treating domestic wastewater. COD removal efficiencies in all reactors were consistently above 94% under steady state conditions. Complete conversion of NH(4+)-N to NO(3-)-N was readily achieved over a feed NH(4+)-N concentration range of 30 to 50 mg/L. It was also observed that SRT did not significantly affect the nitrification in the MBR systems investigated. The average denitrification efficiencies for the 3, 5, 10 and 20 days SRT operations were 43.9, 32.6, 47.5 and 66.5%, respectively. In general, the average effluent nitrogen concentrations, which were mainly nitrate, were about 22.2, 27.6, 21.7 and 13.9 mg/L for the 3, 5, 10 and 20 days SRT systems, respectively. The rate of membrane fouling at 3 days SRT operation was more rapid than that observed at 5 days SRT. No fouling was noted in the 10 days and 20 days SRT systems during the entire period of study.     

Discrete-time spare ordering policy with randomized lead times and discounting

The paper considers a generalized discrete‐time order‐replacement model for a single unit system, which is subject to random failure when in operation. Two types of discrete randomized lead times are considered for a spare unit; one is for regular (preventive) order and another is for expedited (emergency) order. The model is formulated based on the discounted cost criterion. The underlying two‐dimensional optimization problem is reduced to a simple one‐dimensional one and then the optimal ordering policy for the spare unit is characterized under two extreme conditions: (i) unlimited inventory time and (ii) zero inventory time for the spare unit. A numerical example is used to determine the optimal spare‐ordering policy numerically and to examine the sensitivity of the model parameters.     

Maintenance strategy based on a multicriterion classification of equipments

In an industrial plant, the level of maintenance provided to individual equipment is directly related to the availability that is expected from it. Thus, it is hoped that the most critical equipments will not fail or, at least, that any failure will be rapidly detected and corrected in the minimum time possible. Since resources are limited, it is necessary to determine how they should be distributed, so that no important equipment remains neglected while more resources are concentrated on the most critical items. Therefore, it is necessary to classify equipment in an objective way according to its importance. The method of multicriterion classification of critical equipments (MCCE)², which is described in the present work, allows systematic and detailed quantification of the criticality of all equipment, that is to say, it provides an evaluation of the importance that its correct operation has for the plant. To provide this information, the consequences for a company of any failure in the equipment concerned are analysed. Finally, a real case example of an urban wastewater treatment plant is described, in which the MCCE method is applied.     

An Investigation on Noisy Environments in Evolutionary Multiobjective Optimization

In addition to satisfying several competing objectives, many real-world applications are also characterized by a certain degree of noise, manifesting itself in the form of signal distortion or uncertain information. In this paper, extensive studies are carried out to examine the impact of noisy environments in evolutionary multiobjective optimization. Three noise-handling features are then proposed based upon the analysis of empirical results, including an experiential learning directed perturbation operator that adapts the magnitude and direction of variation according to past experiences for fast convergence, a gene adaptation selection strategy that helps the evolutionary search in escaping from local optima or premature convergence, and a possibilistic archiving model based on the concept of possibility and necessity measures to deal with problem of uncertainties. In addition, the performances of various multiobjective evolutionary algorithms in noisy environments, as well as the robustness and effectiveness of the proposed features are examined based upon five benchmark problems characterized by different difficulties in local optimality, nonuniformity, discontinuity, and nonconvexity     

Feasibility study on the use of polyallyldiglycol-carbonate cell dishes in TUNEL assay for alpha particle radiobiological experiments

In the present work, we have studied the feasibility of a method based on polyallyldiglycol-carbonate (PADC) films to investigate the effects of alpha particles on HeLa cervix cancer cells. Thin PADC films with thickness of about 20 μm were prepared from commercially available CR-39 films by chemical etching to fabricate custom-made petri dishes for cell culture, which could accurately record alpha particle hit positions. A special method involving “base tracks” for aligning the images of cell nuclei and alpha particle hits has been proposed, so that alpha particle transversals of cell nuclei can be visually counted. Radiobiological experiments were carried out to induce DNA damages, with the TdT-mediated dUTP Nick-End Labeling (TUNEL) fluorescence method employed to detect DNA strand breaks. The staining results were investigated by flow cytometer. The preliminary results showed that more strand breaks occurred in cells hit by alpha particles with lower energies. Moreover, large TUNEL positive signals were obtained even with small percentages of cells irradiated and TUNEL signals were also obtained from non-targeted cells. These provided evidence for the bystander effect.     

Rain Scatter Interference in mm-Wave Broadband Fixed Wireless Access Networks Caused by a 2-D Dynamic Rain Environment

The classical Mie scattering theory together with the bistatic radar equation has been applied in this paper to quantify interference levels in broadband fixed wireless access (BFWA) for two different network topologies: mesh and cellular. The complete scattering analysis takes into account the realistic variations of rainfall along the propagation paths and inside the common volume. The interfering element is a rain cell model that follows closely the experimental characteristic dimension, decay and movement obtained in recent research by the authors. The signal-to-interference power ratios (S/I) for two different frequencies, 28 and 42 GHz, and several scattering angles have been calculated. They show that, when two beams cross each other, rain-induced interference must be taken into account for an efficient planning of radio communication systems operating at these millimeter-wave frequencies as well as for an adequate design and implementation of fade mitigation techniques.