Modelling a biomass supply chain through discrete-event simulation

The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided

Forest-based supply chain modelling using the SimPy simulation framework

Proper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Applying ontologies to business and systems modelling techniques and perspectives: Lessons learned

For many years in the area of business systems analysis and design, practitioners and researchers alike have been searching for some comprehensive basis on which to evaluate, compare, and engineer techniques that are promoted for use in the modelling of systems' requirements. To date, while many frameworks, factors, and facets have been forthcoming, none appear to be based on a sound theory. In light of this dilemma, over the last 10 years, attention has been devoted by researchers to the use of ontology to provide some theoretical basis for the advancement of the business systems modelling discipline. This paper outlines how we have used a particular ontology for this purpose over the last five years. In particular we have learned that the understandability and the applicability of the selected ontology must be clear for IS professionals, the results of any ontological evaluation must be tempered by economic efficiency considerations of the stakeholders involved, and ontologies may have to be focused for the business purpose and type of user involved in the modelling situation.

Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type. (C) 2003 IMACS. Published by Elsevier B.V. All rights reserved.

Modelling of different measures for improving removal in a stormwater pond

The effect of retrofitting an existing pond on removal efficiency and hydraulic performance was modelled using the commercial software Mike21 and compartmental modelling. The Mike21 model had previously been calibrated on the studied pond. Installation of baffles, the addition of culverts under a causeway and removal of an existing island were all studied as possible improvement measures in the pond. The subsequent effect on hydraulic performance and removal of. suspended solids was then evaluated. Copper, cadmium, BOD, nitrogen and phosphorus removal were,also investigated for that specific improvement measure showing the best results. Outcomes of this study reveal that all measures increase the removal efficiency of suspended solids. The hydraulic efficiency is improved for all cases, except for the case where the island is removed. Compartmental modelling was also used to evaluate hydraulic performance and facilitated a better understanding of the way each of the different measures affected the flow pattern and performance. It was concluded that the installation of baffles is the best of the studied measures resulting in a reduction in the annual load on the receiving lake by approximately 8,000 kg of suspended solids (25% reduction of the annual load), 2 kg of copper (10% reduction of the annual load) and 600 kg of BOD (10% reduction of the annual load).

Modelling of two-stage anaerobic digestion using the IWA Anaerobic Digestion Model No. 1 (ADM1)

The aim of the study presented was to implement a process model to simulate the dynamic behaviour of a pilot-scale process for anaerobic two-stage digestion of sewage sludge. The model implemented was initiated to support experimental investigations of the anaerobic two-stage digestion process. The model concept implemented in the simulation software package MATLAB(TM)/Simulink(R) is a derivative of the IWA Anaerobic Digestion Model No.1 (ADM1) that has been developed by the IWA task group for mathematical modelling of anaerobic processes. In the present study the original model concept has been adapted and applied to replicate a two-stage digestion process. Testing procedures, including balance checks and 'benchmarking' tests were carried out to verify the accuracy of the implementation. These combined measures ensured a faultless model implementation without numerical inconsistencies. Parameters for both, the thermophilic and the mesophilic process stage, have been estimated successfully using data from lab-scale experiments described in literature. Due to the high number of parameters in the structured model, it was necessary to develop a customised procedure that limited the range of parameters to be estimated. The accuracy of the optimised parameter sets has been assessed against experimental data from pilot-scale experiments. Under these conditions, the model predicted reasonably well the dynamic behaviour of a two-stage digestion process in pilot scale. (C) 2004 Elsevier Ltd. All rights reserved.

Use of CLIMEX modelling to identify prospective areas for exploration to find new biological control agents for prickly acacia

Selection of biocontrol agents that are adapted to the climates in areas of intended release demands a thorough analysis of the climates of the source and release sites. We present a case study that demonstrates how use of the CLIMEX software can improve decision making in relation to the identification of prospective areas for exploration for agents to control the woody weed, prickly acacia Acacia nilotica ssp. indica in the arid areas of north Queensland.

Modelling trickle irrigation: Comparison of analytical and numerical models for estimation of wetting front position with time

Irrigation practices that are profligate in their use of water have come under closer scrutiny by water managers and the public. Trickle irrigation has the propensity to increase water use efficiency but only if the system is designed to meet the soil and plant conditions. Recently we have provided a software tool, WetUp (http://www.clw.csiro.au/products/wetup/), to calculate the wetting patterns from trickle irrigation emitters. WetUp uses an analytical solution to calculate the wetted perimeter for both buried and surface emitters. This analytical solution has a number of assumptions, two of which are that the wetting front is defined by water content at which the hydraulic conductivity (K) is I mm day(-1) and that the flow occurs from a point source. Here we compare the wetting patterns calculated with a 2-dimensional numerical model, HYDRUS2D, for solving the water flow into typical soils with the analytical solution. The results show that the wetting patterns are similar, except when the soil properties result in the assumption of a point source no longer being a good description of the flow regime. Difficulties were also experienced with getting stable solutions with HYDRUS2D for soils with low hydraulic conductivities. (c) 2005 Elsevier Ltd. All rights reserved.

A formal framework for modelling and analysing mobile systems

This paper presents a formal framework for modelling and analysing mobile systems. The framework comprises a collection of models of the dominant design paradigms which are readily extended to incorporate details of particular technologies, i.e., programming languages and their run-time support, and applications. The modelling language is Object-Z, an extension of the well-known Z specification language with explicit support for object-oriented concepts. Its support for object orientation makes Object-Z particularly suited to our task. The system structuring techniques offered by object-orientation are well suited to modelling mobile systems. In addition, inheritance and polymorphism allow us to exploit commonalities in mobile systems by defining more complex models in terms of simpler ones.

Modelling and using imperfect context information

Most recently developed context-aware software applicationsmake unrealistic assumptions about the quality of the available context information, which can lead to inappropriate actions by the application and frustration on the part of the user. In this paper, we explore the problem of imperfect context information and some of its causes, and propose a novel approach for modelling incomplete and inaccurate information. Additionally, we present a discussion of our experiences in developing a contextaware communication application, highlighting design issues that are pertinent when developing applications that rely on imperfect context information.

Do process modelling techniques get better? A comparative ontological analysis of BPMN

Current initiatives in the field of Business Process Management (BPM) strive for the development of a BPM standard notation by pushing the Business Process Modeling Notation (BPMN). However, such a proposed standard notation needs to be carefully examined. Ontological analysis is an established theoretical approach to evaluating modelling techniques. This paper reports on the outcomes of an ontological analysis of BPMN and explores identified issues by reporting on interviews conducted with BPMN users in Australia. Complementing this analysis we consolidate our findings with previous ontological analyses of process modelling notations to deliver a comprehensive assessment of BPMN.

Modelling context information with ORM

Context-aware applications rely on implicit forms of input, such as sensor-derived data, in order to reduce the need for explicit input from users. They are especially relevant for mobile and pervasive computing environments, in which user attention is at a premium. To support the development of context-aware applications, techniques for modelling context information are required. These must address a unique combination of requirements, including the ability to model information supplied by both sensors and people, to represent imperfect information, and to capture context histories. As the field of context-aware computing is relatively new, mature solutions for context modelling do not exist, and researchers rely on information modelling solutions developed for other purposes. In our research, we have been using a variant of Object-Role Modeling (ORM) to model context. In this paper, we reflect on our experiences and outline some research challenges in this area.