A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Model-based procedure for scale-up of wet, overflow ball mills - Part II: Worked example

A new ball mill scale-up procedure is developed which uses laboratory data to predict the performance of MI-scale ball mill circuits. This procedure contains two laboratory tests. These laboratory tests give the data for the determination of the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of the full-scale mill circuit. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw. A worked example shows how the new ball mill scale-up procedure is executed. This worked example uses laboratory data to predict the performance of a full-scale re-grind mill circuit. This circuit consists of a ball mill in closed circuit with hydrocyclones. The MI-scale ball mill has a diameter (inside liners) of 1.85m. The scale-up procedure shows that the full-scale circuit produces a product (hydrocyclone overflow) that has an 80% passing size of 80 mum. The circuit has a recirculating load of 173%. The calculated power draw of the full-scale mill is 92kW (C) 2001 Elsevier Science Ltd. All rights reserved.

Model-based procedure for scale-up of wet, overflow ball mills - Part III: Validation and discussion

A new ball mill scale-up procedure is developed. This procedure has been validated using seven sets of Ml-scale ball mil data. The largest ball mills in these data have diameters (inside liners) of 6.58m. The procedure can predict the 80% passing size of the circuit product to within +/-6% of the measured value, with a precision of +/-11% (one standard deviation); the re-circulating load to within +/-33% of the mass-balanced value (this error margin is within the uncertainty associated with the determination of the re-circulating load); and the mill power to within +/-5% of the measured value. This procedure is applicable for the design of ball mills which are preceded by autogenous (AG) mills, semi-autogenous (SAG) mills, crushers and flotation circuits. The new procedure is more precise and more accurate than Bond's method for ball mill scale-up. This procedure contains no efficiency correction which relates to the mill diameter. This suggests that, within the range of mill diameter studied, milling efficiency does not vary with mill diameter. This is in contrast with Bond's equation-Bond claimed that milling efficiency increases with mill diameter. (C) 2001 Elsevier Science Ltd. All rights reserved.

n-fold Weibull multiplicative model

In this paper we study the n-fold multiplicative model involving Weibull distributions and examine some properties of the model. These include the shapes for the density and failure rate functions and the WPP plot. These allow one to decide if a given data set can be adequately modelled by the model. We also discuss the estimation of model parameters based on the WPP plot. (C) 2001 Elsevier Science Ltd. All rights reserved.

A generalised dynamic model for char particle gasification with structure evolution and peripheral fragmentation

A generalised model for the prediction of single char particle gasification dynamics, accounting for multi-component mass transfer with chemical reaction, heat transfer, as well as structure evolution and peripheral fragmentation is developed in this paper. Maxwell-Stefan analysis is uniquely applied to both micro and macropores within the framework of the dusty-gas model to account for the bidisperse nature of the char, which differs significantly from the conventional models that are based on a single pore type. The peripheral fragmentation and random-pore correlation incorporated into the model enable prediction of structure/reactivity relationships. The occurrence of chemical reaction within the boundary layer reported by Biggs and Agarwal (Chem. Eng. Sci. 52 (1997) 941) has been confirmed through an analysis of CO/CO2 product ratio obtained from model simulations. However, it is also quantitatively observed that the significance of boundary layer reaction reduces notably with the reduction of oxygen concentration in the flue gas, operational pressure and film thickness. Computations have also shown that in the presence of diffusional gradients peripheral fragmentation occurs in the early stages on the surface, after which conversion quickens significantly due to small particle size. Results of the early commencement of peripheral fragmentation at relatively low overall conversion obtained from a large number of simulations agree well with experimental observations reported by Feng and Bhatia (Energy & Fuels 14 (2000) 297). Comprehensive analysis of simulation results is carried out based on well accepted physical principles to rationalise model prediction. (C) 2001 Elsevier Science Ltd. AH rights reserved.

Predicting coal ash slag flow characteristics (viscosity model for the Al2O3-CaO-'FeO'-SiO2 system)

A model has been developed which enables the viscosities of coal ash slags to be predicted as a function of composition and temperature under reducing conditions. The model describes both completely liquid and heterogeneous, i.e. partly crystallised, slags in the Al2O3-CaO-'FeO'-SiO2 system in equilibrium with metallic iron. The Urbain formalism has been modified to describe the viscosities of the liquid slag phase over the complete range of compositions and a wide range of temperatures. The computer package F * A * C * T was used to predict the proportions of solids and the compositions of the remaining liquid phases. The Roscoe equation has been used to describe the effect of presence of solid suspension (slurry effect) on the viscosity of partly crystallised slag systems. The model provides a good description of the experimental data of fully liquid, and liquid + solids mixtures, over the complete range of compositions and a wide range of temperatures. This model can now be used for viscosity predictions in industrial slag systems. Examples of the application of the new model to coal ash fluxing and blending are given in the paper. (C) 2001 Elsevier Science Ltd. All rights reserved.

A model of factors affecting an information system's change in state

Management are keen to maximize the life span of an information system because of the high cost, organizational disruption, and risk of failure associated with the re-development or replacement of an information system. This research investigates the effects that various factors have on an information system's life span by understanding how the factors affect an information system's stability. The research builds on a previously developed two-stage model of information system change whereby an information system is either in a stable state of evolution in which the information system's functionality is evolving, or in a state of revolution, in which the information system is being replaced because it is not providing the functionality expected by its users. A case study surveyed a number of systems within one organization. The aim was to test whether a relationship existed between the base value of the volatility index (a measure of the stability of an information system) and certain system characteristics. Data relating to some 3000 user change requests covering 40 systems over a 10-year period were obtained. The following factors were hypothesized to have significant associations with the base value of the volatility index: language level (generation of language of construction), system size, system age, and the timing of changes applied to a system. Significant associations were found in the hypothesized directions except that the timing of user changes was not associated with any change in the value of the volatility index. Copyright (C) 2002 John Wiley Sons, Ltd.

A formal model of real-time program compilation

Program compilation can be formally defined as a sequence of equivalence-preserving transformations, or refinements, from high-level language programs to assembler code, Recent models also incorporate timing properties, but the resulting formalisms are intimidatingly complex. Here we take advantage of a new, simple model of real-time refinement, based on predicate transformer semantics, to present a straightforward compilation formalism that incorporates real-time constraints. (C) 2002 Elsevier Science B.V. All rights reserved.

Vertical fluxes of sediment in oscillatory sheet flow

Time series of vertical sediment fluxes are derived from concentration time series in sheet flow under waves. While the concentrations C(z,t) vary very little with time for \z\ < 10d(50), the measured vertical sediment fluxes Q(zs)(z,t) vary strongly with time in this vertical band and their time variation follows, to some extent, the variation of the grain roughness Shields parameter 02,5(t). Thus, sediment distribution models based on the pickup function boundary condition are in some qualitative agreement with the measurements. However, the pickup function models are only able to model the upward bursts of sediment during the accelerating phases of the flow. They are, so far, unable to model the following strong downward sediment fluxes, which are observed during the periods of flow deceleration. Classical pickup functions, which essentially depend on the Shields parameter, are also incapable of modelling the secondary entrainment fluxes, which sometimes occur at free stream velocity reversal. The measured vertical fluxes indicate that the effective sediment settling velocity in the high [(0.3 < C(z,t) < 0.4] concentration area is typically only a few percent of the clear water settling velocity, while the measurements of Richardson and Jeronimo [Chem. Eng. Sci. 34 (1979) 1419], from a different physical setting, lead to estimates of the order 20%. The data does not support gradient diffusion as a model for sediment entrainment from the bed. That is, detailed modelling of the observed near-bed fluxes would require diffusivities that go negative during periods of flow deceleration. An observed general trend for concentration variability to increase with elevation close to the bed is also irreconcilable with diffusion models driven by a bottom boundary condition. (C) 2002 Published by Elsevier Science B.V.

Entanglement in the steady state of a collective-angular-momentum (Dicke) model

We model the behavior of an ion trap with all ions driven simultaneously and coupled collectively to a heat bath. The equations for this system are similar to the irreversible dynamics of a collective angular momentum system known as the Dicke model. We show how the steady state of the ion trap as a dissipative many-body system driven far from equilibrium can exhibit quantum entanglement. We calculate the entanglement of this steady state for two ions in the trap and in the case of more than two ions we calculate the entanglement between two ions by tracing over all the other ions. The entanglement in the steady state is a maximum for the parameter values corresponding roughly to a bifurcation of a fixed point in the corresponding semiclassical dynamics. We conjecture that this is a general mechanism for entanglement creation in driven dissipative quantum systems.

Upstream porthole injection in a 2-D scramjet model

Injection from portholes upstream of the combustion chamber was investigated as a method of delivering fuel into a scramjet. This method reduces the viscous drag on a model by allowing a reduction in the length of the combustion chamber. At experimental enthalpies of 3.0 MJ/kg in the T4 shock tunnel, there was no evidence of combustion in the intake, either by shadowgraph or pressure measurements. Combustion was observed in the combustion chamber. A theoretical extension of these results is made to a hot wall scenario.

A framework for table driven testing of Java classes

With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.