Systems modelling of mine water and energy tradeoffs

In the coming decades, the mining industry faces the dual challenge of lowering both its water and energy use. This presents a difficulty since technological advances that decrease the use of one can increase the use of the other. Historically, energy and water use have been modelled independently, making it difficult to evaluate the true costs and benefits from water and energy improvements. This paper presents a hierarchical systems model that is able to represent interconnected water and energy use at a whole of site scale. In order to explore the links between water and energy four technologies advancements have been modelled: use of dust suppression additives, the adoption of thickened tailings, the transition to dry processing and the incorporation of a treatment plant. The results show a synergy between decreased water and energy use for dust suppression additives, but a trade-off for the others.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Predicting risk and benefit a priori in biological control of invasive plant species: a systems modelling approach

While the method using specialist herbivores in managing invasive plants (classical biological control) is regarded as relatively safe and cost-effective in comparison to other methods of management, the rarity of strict monophagy among insect herbivores illustrates that, like any management option, biological control is not risk-free. The challenge for classical biological control is therefore to predict risks and benefits a priori. In this study we develop a simulation model that may aid in this process. We use this model to predict the risks and benefits of introducing the chrysomelid beetle Charidotis auroguttata to manage the invasive liana Macfadyena unguis-cati in Australia. Preliminary host-specificity testing of this herbivore indicated that there was limited feeding on a non-target plant, although the non-target was only able to sustain some transitions of the life cycle of the herbivore. The model includes herbivore, target and non-target life history and incorporates spillover dynamics of populations of this herbivore from the target to the non-target under a variety of scenarios. Data from studies of this herbivore in the native range and under quarantine were used to parameterize the model and predict the relative risks and benefits of this herbivore when the target and non-target plants co-occur. Key model outputs include population dynamics on target (apparent benefit) and non-target (apparent risk) and fitness consequences to the target (actual benefit) and non-target plant (actual risk) of herbivore damage. The model predicted that risk to the non-target became unacceptable (i.e. significant negative effects on fitness) when the ratio of target to non-target in a given patch ranged from 1:1 to 3:2. By comparing the current known distribution of the non-target and the predicted distribution of the target we were able to identify regions in Australia where the agent may be pose an unacceptable risk. By considering risk and benefit simultaneously, we highlight how such a simulation modelling approach can assist scientists and regulators in making more objective decisions a priori, on the value of releasing specialist herbivores as biological control agents.

A complex systems modelling approach for decentralized simulation of electrical microgrids

ICECCS 2010

Effect of fluid dynamics and device mechanism on biofluid behaviour in microchannel systems: modelling biofluids in a microchannel biochip separator

Biofluid behaviour in microchannel systems is investigated in this paper through the modelling of a microfluidic biochip developed for the separation of blood plasma. Based on particular assumptions, the effects of some mechanical features of the microchannels on behaviour of the biofluid are explored. These include microchannel, constriction, bending channel, bifurcation as well as channel length ratio between the main and side channels. The key characteristics and effects of the microfluidic dynamics are discussed in terms of separation efficiency of the red blood cells with respect to the rest of the medium. The effects include the Fahraeus and Fahraeus-Lindqvist effects, the Zweifach-Fung bifurcation law, the cell-free layer phenomenon. The characteristics of the microfluid dynamics include the properties of the laminar flow as well as particle lateral or spinning trajectories. In this paper the fluid is modelled as a single-phase flow assuming either Newtonian or Non-Newtonian behaviours to investigate the effect of the viscosity on flow and separation efficiency. It is found that, for a flow rate controlled Newtonian flow system, viscosity and outlet pressure have little effect on velocity distribution. When the fluid is assumed to be Non-Newtonian more fluid is separated than observed in the Newtonian case, leading to reduction of the flow rate ratio between the main and side channels as well as the system pressure as a whole.

Introduction to Soft Systems Modelling

Two lectures that introduce the idea of modelling in the large, and contrasts hard system and soft system modelling. The second lecture goes into detail on a number of specific methods for analysing a system (CATWOE and CSH) and on modelling a system (Systems Diagrams and Personas).

Exploring smart grid possibilities: a complex systems modelling approach

Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders.

Benchmarks for critical infrastructure systems modelling

This paper draws together previous security assessment research and builds upon the current systems modelling research investigation into the application of potential modelling styles that can be applied to model critical infrastructure systems, networks, their inter-relationships and functionality. The emphasis here is to develop appropriate benchmarks as a means of assessment to determine the appropriateness of various systems modelling styles and techniques and their suitability for modelling critical infrastructure systems. The benchmarks are applicable on a number of differing levels to determine the ‘best fit’ for modelling critical infrastructure systems, to aid in identifying potential system or inter-network vulnerabilities.

Critical infrastructure systems modelling : benchmarking CPN tools

This paper reports on the application of systems modelling benchmarks to determine the viability of systems modelling software and its suitability for modelling critical infrastructure systems. This research applies the earlier research that related to developing benchmarks that when applied to systems modelling software will indicate its likely suitability to modelling critical infrastructure systems. In this context, the systems modelling benchmarks will assess the practicality of CPNTools to the task of modelling critical infrastructure systems.

Evaluation of chlorine decay kinetics expressions for drinking water distribution systems modelling

The decay of chlorine in drinking water involves a complex set of reactions that is usually simplified to first order kinetics in models of water quality in distribution systems. However, to be useful in optimising chlorine dosing regimes, the kinetics expression should accurately describe the shape of the chlorine decay curve for different chlorine doses and be able to simulate re-chlorination. After considering the nature of the reactions involved in chlorine decay, five simplified reaction schemes were evaluated for their suitability to describe chlorine concentration in bulk water. Each scheme was fitted to a sample of experimental data of chlorine decay in raw water obtained from Warragamba Dam (the major source of water supplied to Sydney, Australia). A scheme involving two parallel reactions of organic carbon compounds with chlorine is both necessary and sufficient to satisfy the requirements of modelling chlorine decay accurately.