Kevin Cronin

Analysis of temperature variability during the thermal processing of hazelnuts

Abstract The variability in temperature that occurs between hazelnuts during roasting is investigated. Two deterministic models of unsteady state heat transfer in a hazelnut are developed; one is based on the analytical solution for a spherical solid body and the other is a numerical model of heat flow in a hollow sphere. The mean and standard deviation in the thermal and physical properties of hazelnuts have been measured. Also the mean and standard deviation in hazelnut temperature vs. time during a roasting process has been quantified. Theoretical solutions based on functions of random variables are employed to characterise the output of such a thermal process where the rate constants are randomly distributed. In addition, the Monte Carlo method is applied to both the analytical solid sphere and numerical hollow sphere heat transfer models to estimate temperature variability. All three approaches gave satisfactory predictions of mean hazelnut temperature vs. time. However, only the Monte Carlo solution of the numerical hollow sphere model provided a good estimate of the standard deviation in hazelnut temperature vs. time. The prediction of variability in hazelnut temperature during roasting is important in the context of optimising the roasting process with respect to uniformity in product quality and safety.

Grape Drying: A Review

The drying of grapes is a more complex process compared to the dehydration of other agricultural materials due to the necessity both of a pretreatment operation prior to drying and further processing operations after drying. To date, most researchers have concentrated on pretreatment and drying where the primary effects of pretreatment on drying have been evaluated. It seems appropriate that a review should now be presented to critically examine all the corresponding published data in the literature and to compare the conditions used in these studies in order to highlight the grape drying process by considering the important aspects of both the pretreatment and post-drying operations. The result of this study will be useful in identifying the future research directions needed for grape drying and also to facilitate the development of an analytical framework for the design of novel drying equipment.

A statistical analysis of biscuit physical properties as affected by baking

The variability in the dimensions, weight and moisture content of commercial and laboratory Rich Tea type biscuits has been quantified. An experimental study has been conducted comparing dispersion in dough piece weight and thickness to that of the resulting biscuits. The sensitivity of these biscuit properties to deviations in the baking process and in dough ingredient levels has been investigated. It was found that the dispersion in biscuit weight is primarily due to variability in dough piece weight, which in turn is linked to spatial variations in the thickness of the dough sheet from which the pieces are cut. The baking stage can slightly diminish the distribution in weight by reducing the variability in moisture content between biscuits. The mechanism by which this happens is that wetter dough pieces dry proportionally more than those with lower moisture levels. Biscuit moisture content is sensitive to fluctuations in oven temperature and dough piece moisture content though at a level that may not be commercially significant.

ANALYSIS OF RANDOM VARIABILITY IN BISCUIT COOLING

Abstract The cooling of biscuits after baking can be considered as a random phenomenon. The Fourier field equation for transient heat transfer is used as the basis for the deterministic modelling of a single biscuit in a laboratory cooler. The Monte Carlo method is applied to the Fourier equation to predict the dispersion in biscuit surface temperature at the end of the cooling process. Theoretical solutions are also used to characterise the variability in biscuit temperature by considering biscuit cooling as a probabilistic thermal process. The mean and standard deviation in biscuit thermal properties, initial biscuit temperature and heat transfer coefficient are measured and are considered as the input random variables. The numerical output and theoretical solutions are compared with experimental results. Parameter studies are conducted with the probabilistic model to assess the influence of variability in thermal properties on final biscuit temperature variability and to suggest process improvement strategies.

Probabilistic Analysis of Timber Drying Schedules

Abstract Timber drying schedules are primarily chosen to achieve a certain final moisture content accompanied by a minimum amount of board degrade. However the schedule adopted also influences the dispersion in moisture content between boards at the end of drying. A simple double set point schedule consisting of two distinct and sequential equilibrium moisture contents is selected to illustrate the concept. Theoretical expressions that predict mean and standard deviation in board moisture content vs. time are developed. The predictions of these equations are compared with the output of a Monte Carlo model of timber drying and with experimental measurements from a laboratory kiln. The advantages of a double set point over a single set point schedule are explained and an optimum double set point schedule is determined. The behavior of a commercial drying schedule is analyzed and its performance with respect to the optimum schedule is quantified. Finally some inherent characteristics of the variability in timber drying systems are outlined.

Process optimization strategies to diminish variability in the quality of discrete packaged foods during thermal processing

A distribution in food product thermal properties will produce a distribution in product temperature throughout a heating or cooling process. This in turn will cause a permanent dispersion in product quality through the mechanism of the temperature sensitivity of product quality thermal degradation kinetics. To guarantee acceptable food safety, the slowest heating product must receive adequate thermal treatment, implying that the majority of the products are over-cooked. Strategies to ameliorate this problem are suggested by determining the optimum processing temperature to minimize the final quality dispersion. As an example, the batch sterilization of packaged foods is analyzed and described by a set of three partial differential equations for (i) the heat transfer, (ii) the quality change and (iii) the microbial reduction. In this case process optimization aims to reduce the final standard deviation in quality (without affecting the final safety) by optimizing schedules for the retort temperature.

Is attending lectures still relevant in engineering education

A case study was conducted on a group of undergraduate chemical engineering students to assess the relevance of attending lectures from a student perspective and to understand why these students attend and do not attend lectures with a view to developing approaches to teaching, which are of greater interest and benefit to student learning. The students were surveyed by means of a questionnaire-type survey, which collected both quantitative and qualitative data from them. The majority of students stated that lectures are still very beneficial to their learning and are not an out-of-date mode of education. The major reasons for lecture non-attendance were time priority and curriculum overload issues with other scholarly activities and poor quality teaching. The students provided a number of suggestions to improve lectures and lecture attendance, including the incorporation of active learning in lectures, linking lectures to assessment and adding extra value to what is already in the notes.

Monte Carlo modelling of a vegetable tray dryer

The objective in food dehydration is to dry the product to a specified uniform moisture content. In practice, a distribution in final moisture content is unavoidable, arising from the intrinsic variability of food properties and the probabilistic nature of the food drying process. For commercial dryers there are significant costs associated with this deviation in final moisture. To investigate the variability in the dehydration of vegetables, a model of a tray dryer was constructed, based on the empirical Page equation. It was solved using the Monte Carlo technique by describing the initial moisture content and the drying rate with probability distribution functions. A series of experiments were conducted to provide constants and statistical data for the model and to validate it. The utility of this approach is illustrated by applying the probabilistic drying model to quantifying and optimising the final moisture content distribution.

Drying Lumber In Kilns: A Methodology for Stochastic Analysis Using Markov Modelling

ABSTRACT The value of dried lumber to the kiln operator is to a large extent dependent on the final moisture content distribution of the batch. This variation in moisture content arises from the intrinsic heterogeneity of wood and the stochastic nature of the timber drying process. Theoretical analyses of wood drying have hitherto relied upon deterministic models and have limited practical applicability. A methodology is proposed herein whereby the inherent probabilistic dynamics of batch drying can be modelled efliciently using Markov chains. The discretization of the variables of moisture and time that is necessary for this approach is discussed. By simulating the drying process with the model, the progressive transformation of the batch moisture distribution throughout the drying cycle can be studied. Output from the model is compared with experimental drying results to test its validity. There are

PROBABILISTIC ANALYSIS AND DESIGN OF THE INDUSTRIAL TIMBER DRYING PROCESS

ABSTRACT The distribution in the moisture content of dried planks is an important parameter for kiln operators. The evolution of variability in the moisture content of timber boards during a batch drying process is investigated. This random variability in moisture content arises from a distribution in plank initial moisture content and dispersion in plank drying rate. A simple deterministic model of timber drying is outlined. Theoretical probabilistic analysis is applied to this model to predict the mean and standard deviation in board moisture content as a function of time. The solution is assessed with representative industrial kiln drying data. The utility of the approach in suggesting strategies to promote uniformity in final moisture content is outlined using some design studies. These strategies include sorting of the timber by moisture content and adjusting the drying rate and equilibrium moisture content to reduce variability. It is also demonstrated that the probabilistic approach can yield a better estimation of kiln average moisture content.