Modelling moisture uptake in a cereal grain

auther to whom correspondence should be addressed. Email: k.landman{at}ms.unimelb.edu.au.E-mail: cpp{at}maths.soton.ac.uk Recent experimental data have revealed the spatial and temporalstructure of moisture content within a cereal grain immersedin boiling water. A simple model of the water's motion is presented,guided by the observed behaviour, which allows for nonlinear(exponential) diffusion within the grain and a constant mass-transfercoefficient to represent the pericarp on the outer surface.Numerical results are presented illustrating the close relationshipof the predictions to the experimental results, with the mass-transfercoefficient as a fitting parameter. The model is studied usingasymptotic analysis, in the limit of large activation energyin the diffusion coefficient and large mass transfer. The analysisgives insight into the three phases of the process, consistingof initial linear diffusion, linear motion of the moisture frontinto the grain, and slow filling of the grain in a relativelyuniform manner. The problem is also studied using mean-action-timeanalysis to derive simple expressions for the time for the grainto saturate.     

Modelling the wetting and cooking of a single cereal grain

Three models are presented for the wetting of whole grains ofcereal. Two are for temperatures below gelatinization temperatures,one of which incorporates the effects of swelling of the grain.A third model is presented for wetting of a grain at temperaturesabove gelatinization, and hence cooking the grain. The modelsare developed as partial differential equations, and solvedin a variety of ways. A model that ignores swelling at temperaturesbelow gelatinization is solved for wetting times by using theconcept of mean action time, which reduces the problem to anexactly solvable linear Poisson equation. The other two models,which include swelling and cooking respectively, are solvedapproximately, taking advantage of the steep nonlinear diffusionfronts that develop. The aim of the modelling is to improveunderstanding of the cooking of whole-grain cereals prior toprocessing into breakfast cereals. Moisture penetration curvesare obtained and compared. Regions where the penetration rateis approximately linear are noted, suggesting that nonlineardiffusion equations are a promising way to model grain wettingand cooking.     

Modelling of discontinuities through dipole distribution

An indirect boundary element method using dipole distribution is employed in order to model discontinuities inside the flow region. The problem of flow under a dam is treated with a sheet-pile in its foundation. The discontinuity across the sheet-pile is demonstrated, a general boundary element procedure for a mixed problem is outlined and the coefficients of the linear system are given in analytical form. Very good agreement with existing analytical results is obtained.     

Modelling and simulation of heat exchange and moisture content in a cereal storage silo

ABSTRACT

In this paper, a mathematical model is developed based on the heat transfer of stored grains aerated in a cylindrical silo. This work is a part of study that aims to model the whole process of cereal storage system including a dehumidifier. The use of dehumidifier is intended to remove excess moisture from the airflow injected by the ventilator system in the silo filled with wheat, and to keep hygroscopic properties of grain in safe level during the storage period. Temperature and humidity are the two important variables coupled to control the process and to preserve grain quality. The laboratory device permitted us to achieve several tests for different conditions of grain stored in silo without aeration. A simulation of the airflow through the thermal space of the silo and grain parameters has been carried out. The results are reasonably in agreement with experiments and other published data. The system performance is evaluated at critical conditions of storage boundaries.     

On the filtration through porous media with partially soluble permeable grains

In this paper we consider the incompressible viscous fluid flow through a porous medium whose grains are also permeable and release mass to the flow. In each component porosity and permeability depend on saturation. The flow is modelled with a nonlinear parabolic equation for the pressure, with a degenerate parabolic term, depending not only on the saturations, but also on the space variable and on time averages of the saturation. We generalize the classic approach of Alt and Luckhaus to this situation and establish existence of at least one weak solution and bounds for its absolute value. Received December 1998     

Modelling of containerized air cargo forwarding problems under uncertainty

This paper examines air container renting and cargo loading problems experienced by freight forwarding companies. Containers have to be booked in advance, in order to obtain discounted rental rates from airlines; renting or returning containers on the day of shipping will incur a heavy penalty. We first propose a mixed-integer model for the certain problem, in which shipment information is known with certainty, when booking. We then present a two-stage recourse model to handle the uncertainty problem, in which accurate shipment information cannot be obtained when booking, and all cargoes have to be shipped without delay. The first-stage decision is made at the booking stage, to book specific numbers of different types of containers. The second-stage decision is made on the day of shipping, depending on the extent to which the uncertainty has been realized. The decisions include number of additional containers of different types that are required to be rented, or the number of containers to be returned, under the scenario that might occur on the day of shipping. We then extend the recourse model into a robust model for dealing with the situation in which cargoes are allowed to be shipped later. The robust model provides a quantitative method to measure the trade-off between risk and cost. A series of experiments demonstrate the effectiveness of the robust model in dealing with risk and uncertainty.     

Effective medium model for flow through beds of porous cylindrical fibres

We have used effective medium model for beds of circular cylindrical porous fibres in order to estimate the overall bed permeability (OBP). It is assumed that a representative circular porous cylindrical fibre is inside a fluid envelope beyond which effective medium is used. Both inside the cylindrical fibre and in the effective medium, Brinkman equation is used, however of different permeabilities and in the fluid envelope Stokes equation is used. The OBP corresponding to the porous fibres is estimated when the flow direction is perpendicular to the axis of the cylindrical fibres as well as parallel to the fibres. This in turn is used to estimate the OBP corresponding to a collection of porous cylindrical fibres that are randomly oriented. We have compared the results with some existing literature.     

Modelling of extreme wave heights and periods through copulas

Optimal design of coastal or offshore structures requires the estimation of extreme quantiles of oceanographic data such as wave heights and wave periods. Since there are strong correlations between oceanographic variables, it is necessary to use multivariate models in order to capture its dependencies. To achieve this, an approach based on copulas is proposed and is compared to a model based on the physical behaviour of waves.     

Modelling the flow of congestive heart failure patients through a hospital system

The number of hospital admissions in England due to heart failure is projected to increase by over 50% during the next 25 years. This will incur greater pressures on hospital managers to allocate resources in an effective manner. A reliable indicator for measuring the quantity of resources consumed by hospital patients is their length of stay (LOS) in care. This paper proposes modelling the length of time heart failure patients spend in hospital using a special type of Markov model, where the flow of patients through hospital can be thought of as consisting of three stages of care—short-, medium- and longer-term care. If it is assumed that new admissions into the ward are replacements for discharges, such a model may be used to investigate the case-mix of patients in hospital and the expected patient turnover during some specified period of time. An example is illustrated by considering hospital admissions to a Belfast hospital in Northern Ireland, between 2000 and 2004.     

Modelling of airflow through a stack in a timber-drying kiln

A two-dimensional pore-scale model is used to predict air flow through a wood drying stack for which both the interstitial and the average flow can be considered as two-dimensional.     

Modelling dynamic network loading ontransportation networks through a continuous

The efforts spent by researchers in the last few years in traffic modelling have been focused on the modelization of dynamic behaviour of the several components making up a transportation system.In the field of traffic assignment, a large number of models and procedures have been proposed in order to perform Dynamic Network Loading (DNL), that is the reproduction of within-day variable link performances once a corresponding Origin/Destination (O/D) demand and users' choice model has been given. These models can be used both to evaluate traffic flows and, what is more relevant, to simulate the effects of regulation strategies on users' behaviour.

In this paper, after a brief review of the state of the art in this field, a continuous dynamic network loading model is proposed; it removes some of the drawbacks of other packet approach models proposed in literature and explicitly allows the en-route modification of the followed path. An algorithmic development of the model and a set of applications on text networks are also proposed.     

Comparison of non-cohesive resolved and coarse grain DEM models for gas flow through particle beds

The Discrete Element Method (DEM) is a widely used approach for modelling granular systems. Currently, the number of particles which can be tractably modelled using DEM is several orders of magnitude lower than the number of particles present in common large-scale industrial systems. Practical approaches to modelling such industrial system therefore usually involve modelling over a limited domain, or with larger particle diameters and a corresponding assumption of scale invariance. These assumption are, however, problematic in systems where granular material interacts with gas flow, as the dynamics of the system depends heavily on the number of particles. This has led to a number of suggested modifications for coupled gas–grain DEM to effectively increase the number of particles being simulated. One such approach is for each simulated particle to represent a cluster of smaller particles and to re-formulate DEM based on these clusters. This, known as a representative or ‘coarse grain’ method, potentially allows the number of virtual DEM particles to be approximately the same as the real number of particles at relatively low computational cost. We summarise the current approaches to coarse grain models in the literature, with emphasis on discussion of limitations and assumptions inherent in such approaches. The effectiveness of the method is investigated for gas flow through particle beds using resolved and coarse grain models with the same effective particle numbers. The pressure drop, as well as the pre and post fluidisation characteristics in the beds are measured and compared, and the relative saving in computational cost is weighed against the effectiveness of the coarse grain approach. In general, the method is found perform reasonably well, with a considerable saving of computational time, but to deviate from empirical predictions at large coarse grain ratios.     

Modelling and analysis of thermal networks through subnetworks for multizone passive solar buildings

An efficient method is presented for the computer analysis in the frequency domain of multizone passive solar buildings. This method models heat conduction and convection between rooms, heat flows which are often not accounted for in order to reduce computation time. Heat transfer through a building is modelled by a thermal network. Massive walls are represented as two-port elements, analogous to non-inductive electrical transmission lines. Nodes representing exterior surfaces, whose temperatures do not have to be explicitly determined, are eliminated by the Norton theorem. The resulting simplified, but still complex networks, are split into subnetworks corresponding to rooms by removing a few simple components; the solutions for the subnetworks are found by means of the nodal formulation and are then coupled to give the system solution, without ever having to solve directly the initial complex network. There are no errors introduced by this decomposition process. This significantly simplifies the analysis of the building network and provides physical insight into the modelling and coupling of its subsystems.     

Modelling Inference in Argumentation through Labelled Deduction: Formalization and Logical Properties

Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a confluence point for many alternative logical frameworks. Different formalisms have been developed, most of them sharing the common notions of argument and warrant. In defeasible argumentation, an argument is a tentative (defeasible) proof for reaching a conclusion. An argument is warranted when it ultimately prevails over other conflicting arguments. In this context, defeasible consequence relationships for modelling argument and warrant as well as their logical properties have gained particular attention. This article analyzes two non-monotonic inference operators C_arg and C_war intended for modelling argument construction and dialectical analysis (warrant), respectively. As a basis for such analysis we will use the LDS_ar framework, a unifying approach to computational models of argument using Labelled Deductive Systems (LDS). In the context of this logical framework, we show how labels can be used to represent arguments as well as argument trees, facilitating the definition and study of non-monotonic inference operators, whose associated logical properties are studied and contrasted. We contend that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks. Mathematics Subject Classification (2000): Primary 03B22; Secondary 03B42.     

Modelling the Pulsating Process

We continue research on machine-oracle modelling of second-order arithmetic. The pulsating process described in [1, 2] is simulated using oracles of so-called autonomous hierarchies. The outcome is constructing a generalized constructive model for a fragment of second-order arithmetic described in [2].     

Modelling the Recurrence of Bladder Cancer

The risk of a new tumor recurrence after transurethral resection (surgical operation) in patients with primary superficial bladder carcinoma is evaluated. As the exact time of the event is not known, it is suggested to consider interval-censored survival data methodology. We use the model of Farrington to perform a prognostic model for predicting a new recurrence and to determine the clinicopathologic factors associated within interval-censored data framework. The implementation of this method is easy using standard statistical packages. Anyway, we use diagnostic methods for the validation of the model developed by the same author for interval-censored data. The obtained model is easily interpretable and let us to individualize the course of follow-up and treatment of each patient in order to improve the patient’s quality of life.      

Modelling the Process of Multiattribute Choice

In most of the multiattribute utility models it is assumed that the analytical forms of partial and overall utility functions are known, and hence the problem becomes one of estimating the values of model parameters. This assumption is rather restrictive since one may not possess prior knowledge as to the analytical forms of such functions. The present paper is an attempt to eliminate some of the shortcomings of the existing models by proposing two new formulations of the multiattribute choice problem without a priori limitation to any strict form of partial utility function.