Modelling the aqueous extraction of soluble substances from ground roasted coffee

This work aims to study and model the extraction of soluble substances from coffee grounds having different particle sizes. The results demonstrate that coffee brewing cannot be considered a simple diffusion mechanism as reported in the literature. The phenomenon has two phases: a washing phase where surface soluble substances instantaneously dissolve and are transferred to the extract by a convection mechanism, and a diffusion phase involving the solubles within the porous particles. A model was set up to calculate extraction yield as the addition of the two phases. It was also demonstrated that the effect of washing shows a linear correlation with the external surface area of particles and that the composition of the extracts does not depend on extraction time.     

Generalized model for the simulation of food refrigeration. Development and validation of the predictive numerical method

A generalized mathematical model was developed to simulate food refrigeration in air. The model takes into account surface water evaporation. It allows food physical properties to be considered as functions of temperature and/or composition, while providing means for including internal heat generation, composite materials (for instance, flesh and skin) and time-varying external temperature and humidity. Wetted surfaces and packaging can also be accounted for by the model, which can be used for spheres, infinite or finite cylinders, slabs. The numerical method was developed using the Crank-Nicolson scheme, and compared with exact analytical solutions as well as with experimental data on the refrigeration of various foods.     

Treatment and Disposal Scheme for the Sewage of Athens

The sewage from the Greater Athens area is discharged without treatment to the nearby Saronicos Gulf. Recently the Greek government decided to implement an appropriate treatment and disposal scheme, on the basis of a study of the hydrodynamic behaviour of the Gulf and the fate of the discharged pollutants. The study was conducted with the aid of suitable hydrodynamic and water quality models for a number of alternative treatment schemes, ranging from primary treatment to biological treatment with seasonal nitrogen removal, combined with outfalls of different lengths. The results indicate that, although none of the examined schemes will lead to an immediate substantial impact, the scheme that includes biological treatment with seasonal nitrogen removal can eliminate the danger of serious ecological disturbances at a reasonable cost.     

An Intelligent Knowledge-Based System for Product Cost Modelling

An intelligent knowledge-based system for product cost modellingis presented in this paper. The developed system has the capability of selecting a material, as well as machining processes and parameters based on a set of design and production parameters; and of estimating the product cost throughout the entire product development cycle including assembly cost. The proposed system is applied without the need for detailed design information, so that it can be used at an early design stage, and, consequently, redesign cost and longer lead time can be avoided. Hybrid knowledge representation techniques, such as production rules, frame and object oriented are employed to represent manufacturing knowledge. Fuzzy logic-based knowledge representation is applied to deal with uncertainty in the knowledge of cost model to generate reliable cost estimation. This paper deals with cost modelling of both a machining component and an injection moulding component, which is a process that gives high production rates, excellent quality and accuracy of products, and low manufacturing cost. Based on the analysis of the moulded product life cycle, a computer-based cost model was developed which integrated the relationship between cost factors, product development activities, and product geometry. The estimated cost included the costs of material, mould and processing. The system has been validated through a case study.     

Adaptive linear quadratic gaussian (LQG) control of a bioreactor

The paper deals with the modelling and adaptive control of a continuous-flow fermentation process for the production of alcohol. The fermenter model has been developed from mass balance and leads to nonlinear differential equations. In practice, control strategies are difficult to derive using this non-linear model. The dilution rate and the substrate concentration have been considered as control and controlled variables, respectively. The adaptive control algorithm implemented is based on the linear quadratic control approach, where the associated Riccati equation is iterated until the system closed-loop poles belong to a restricted stability domain which is included in the unit circle. A single input/output model is used for control purposes. The model parameters are estimated on-line using a robust identification algorithm which includes: data normalization, time-varying forgetting factor, covariance matrix factorization, etc. Experimental results show the performance of this adaptive scheme and its ability to control biotechnological processes.     

Numerical and experimental investigation of melting of ice involving natural convection

Two‐dimensional transient melting of ice in a rectangular enclosure was numerically and experimentally investigated. Natural convection in the liquid phase due to the temperature dependency of water density was considered in the numerical model. The implicit finite difference method with fixed staggered grid approach was utilized. The SIMPLER algorithm was followed for the solution of pressure and velocity fields in the liquid phase. The prediction of the model was found to be satisfactory through preliminary experimentation. Copyright © 2002 John Wiley & Sons, Ltd.     

Simulation of the detection of underwater objects from air

Simulation modelling of the detection through a water-air boundary of underwater objects by means of a CCD camera is performed. The situation using active illumination by pulses of laser radiation is considered. Calculation is performed for the special case of the minimum size of an object detected at a prescribed depth of submersion in relation to its reflection factor. __________ Translated from Izmeritel’naya Tekhnika, No. 9. pp. 32–36, September, 2007.     

Modelling and prediction of phyto- and zooplankton dynamics in Lake Kasumigaura by artificial neural networks

An artificial neural network model was developed for Lake Kasumigaura to predict timing and magnitudes for chlorophyll a, five species of blue-green algae and three zooplankton groups. The model was trained by 8 years of limnological time series and validated by two independent years. The validation showed the potential of neural networks as predictive tools for highly non-linear phenomena such as blue-green algal blooms in freshwater lakes.     

Modelling the change in colour of potassium sorbate powder during heating

Colour change of potassium sorbate caused by heating was statistically modelled to examine its potential as a time–temperature process indicator. A full factorial design with five levels of heating time ( t ) and temperature ( T ) was used. L , a and b values were measured by a HunterLab colorimeter, and second-order polynomial models were developed. Heating significantly reduced L and increased b values, causing the potassium sorbate powder to turn dark yellow, possibly because of non-enzymatic browning reactions. Statistically significant models with good fit were developed for L and b , and their response surfaces were generated. This potassium sorbate-based system may be a suitable indicator for high-temperature heating processes such as dry heat sterilizers or baking ovens.