A novel approach to dynamic modelling of polymer extrusion for improved process control

Polymer extrusion is a complex process and the availability of good dynamic models is key for improved system operation. Previous modelling attempts have failed adequately to capture the non-linearities of the process or prove too complex for control applications. This work presents a novel approach to the problem by the modelling of extrusion viscosity and pressure, adopting a grey box modelling technique that combines mechanistic knowledge with empirical data using a genetic algorithm approach. The models are shown to outperform those of a much higher order generated by a conventional black box technique while providing insight into the underlying processes at work within the extruder.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.

Multivariate prediction of clarified butter composition using Raman spectroscopy

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R-2=0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was 1.25%. The Raman method has the best prediction ability for unsaturated FA (R-2=0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 tDelta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R-2=0.80) and solid fat content at low temperature (R-2=0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R-2=0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.

Synchrophasor Broadcast over Internet Protocol for Distributed Generator Synchronization

Synchronous islanded operation involves continuously holding an islanded power network in virtual synchronism with the main power system to aid paralleling and avoid potentially damaging out-of-synchronism reclosure. This requires phase control of the generators in the island and the transmission of a reference signal from a secure location on the main power system. Global positioning system (GPS) time-synchronized phasor measurements transmitted via an Internet protocol (IP) are used for the reference signal. However, while offering low cost and a readily available solution for distribution networks, IP communications have variable latency and are susceptible to packet loss, which can make time-critical control applications difficult. This paper investigates the ability of the phase-control system to tolerate communications latency. Phasor measurement conditioning algorithms that can tolerate latency are used in the phase-control loop of a 50-kVA diesel generator. © 2010 IEEE.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

Atmospheric pressure, nonthermal plasma inactivation of MS2 bacteriophage: effect of oxygen concentration on virucidal activity

AimsThe main aim of this study was to determine the virucidal inactivation efficacy of an in-house-designed atmospheric pressure, nonthermal plasma jet operated at varying helium/oxygen feed gas concentrations against MS2 bacteriophage, widely employed as a convenient surrogate for human norovirus.

Methods and ResultsThe effect of variation of percentage oxygen concentration in the helium (He) carrier gas was studied and found to positively correlate with MS2 inactivation rate, indicating a role for reactive oxygen species (ROS) in viral inactivation. The inactivation rate constant increased with increasing oxygen concentrations up to 075% O-2. 3 log(10) (999%) reductions in MS2 viability were achieved after 3min of exposure to the plasma source operated in a helium/oxygen (9925%:075%) gas mixture, with >7 log(10) reduction after 9min exposure.

ConclusionsAtmospheric pressure, nonthermal plasmas may have utility in the rapid disinfection of virally contaminated surfaces for infection control applications.

Significance and Impact of StudyThe atmospheric pressure, nonthermal plasma jet employed in this study exhibits rapid virucidal activity against a norovirus surrogate virus, the MS2 bacteriophage, which is superior to previously published inactivation rates for chemical disinfectants.

Analysis of IL6 Signal Transduction Model using Reduced Rank Regression

This work presents the application of reduced rank regression to the field of systems biology. A computational approach is used to investigate the mechanisms of the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in hepatic cells stimulated by interleukin-6. The results obtained identify the contribution of individual reactions to the dynamics of the model. These findings are compared to previously available results from sensitivity analysis of the model which focused on the parameters involved and their effect. This application of reduced rank regression allows for an understanding of the individual reaction terms involved in the modelled signal transduction pathways and has the benefit of being computationally inexpensive. The obtained results complement existing findings and also confirm the importance of several protein complexes in the MAPK pathway which hints at benefits that can be achieved by further refining the model.

Identification of Dynamics of Surface Suction Over an Airfoil at Low Reynolds Numbers

This paper deals with identification of dynamics in suction control of airfoils for low Reynolds number regimes (8 x 10^4 - 5 x 10^5). In particular, the dynamics of interest is the map that relates suction pressure and surface pressure. Identification of such dynamics is of use to a variety of active control applications including suction control in small/medium wind turbines which operate in these Reynolds number regimes. Prior research has largely focused on higher Reynolds number regimes, creating a need for such a study. Towards identifying the said dynamic relations, experiments were conducted on NACA0012 airfoil in a wind tunnel. The dynamic relation between suction and surface pressure was identified as an overdamped second order system.

Modelling of Evaporator in Waste Heat Recovery System using Finite Volume Method and Fuzzy Technique

The evaporator is an important component in the Organic Rankine Cycle (ORC)-based Waste Heat Recovery (WHR) system since the effective heat transfer of this device reflects on the efficiency of the system. When the WHR system operates under supercritical conditions, the heat transfer mechanism in the evaporator is unpredictable due to the change of thermo-physical properties of the fluid with temperature. Although the conventional finite volume model can successfully capture those changes in the evaporator of the WHR process, the computation time for this method is high. To reduce the computation time, this paper develops a new fuzzy based evaporator model and compares its performance with the finite volume method. The results show that the fuzzy technique can be applied to predict the output of the supercritical evaporator in the waste heat recovery system and can significantly reduce the required computation time. The proposed model, therefore, has the potential to be used in real time control applications.