Paradigm shift to enhanced water supply planning through augmented grids, scarcity pricing and adaptive factory water : a system dynamics approach

This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.

Water security through scarcity pricing and reverse osmosis: a system dynamics approach

Water supply and demand planning is often conducted independently of social and economic strategies. There are presently no comprehensive life-cycle approaches to modelling urban water balances that incorporate economic feedbacks, such as tariff adjustment, which can in turn create a financing capacity for investment responses to low reservoir levels. This paper addresses this gap, and presents a system dynamics model that augments the usual water utility representation of the physical linkages of water grids, by adding inter-connected feedback loops in tariff structures, demand levels and financing capacity. The model, applied in the south-east Queensland region in Australia, enables simulation of alternatives and analysis of stocks and flows around a grid or portfolio of bulk supplies including an increasing proportion of rain-independent desalination plants. Such rain-independent water production plants complement the rain-dependent sources in the region and can potentially offer indefinite water security at a price. The study also shows how an alternative temporary drought pricing regime not only defers costly bulk supply infrastructure but actually generates greater price stability than traditional pricing approaches. The model has implications for water supply planners seeking to pro-actively plan, justify and finance portfolios of rain-dependent and rain-independent bulk water supply infrastructure. Interestingly, the modelling showed that a temporary drought pricing regime not only lowers the frequency and severity of water insecurity events but also reduces the long-run marginal cost of water supply for the region when compared to traditional reactive planning approaches that focus on restrictions to affect demand in scarcity periods.

CISR-ODE, A C plus plus framework with ODE solver for code based system dynamics simulation

Ordinary differential equations are used for modelling a wide range of dynamic systems. Even though there are many graphical software applications for this purpose, a fully customised solution for all problems is code-level programming of the model and solver. In this project, a free and open source C++ framework is designed to facilitate modelling in native code environment and fulfill the common simulation needs of control and many other engineering and science applications. The solvers of this project are obtained from ODEINT and specialised for Armadillo matrix library to provide an easy syntax and a fast execution. The solver code is minimised and its modification for users have become easier. There are several features added to the solvers such as controlling maximum step size, informing the solver about sudden input change and forcing custom times into the results and calling a custom method at these points. The comfort of the model designer, code readability, extendibility and model isolation have been considered in the structure of this framework. The application manages the output results, exporting and plotting them. Modifying the model has become more practical and a portion of corresponding codes are updated automatically. A set of libraries is provided for generation of output figures, matrix hashing, control system functions, profiling, etc. In this paper, an example of using this framework for a classical washout filter model is explained.

Modelling a helicopter training continuum to support system transformation

his study investigates the role of system dynamics (SD) modeling to support strategic decision making for an aviation training continuum that is going through major change. The Australian helicopter training continuum (HTC) is currently undergoing transformation, with restructure and consolidation of training schools and training platforms across multiple services. In this research, we introduce a novel SD-based HTC simulation architecture to facilitate the discovery of relationships between student and instructor development and flow dynamics. The proposed simulation architecture employs hybrid push – pull flow control to quantify transience and estimate recovery time after a policy change or disturbance. This architecture allows for multiple student and instructor types, and their respective intake levels and pass rates. Here the instructor variables include availability, specialization and experience. Enos (2011) successfully explored the application of SD modeling to understand the behavior for combat aviation training in an individual school. This research employs a similar modeling philosophy, but takes a higher level view of the system by looking across multiple training schools, which introduces complexity due to pooling, latency and the amplification of affects across the system. The ability to identify causal relationships allowed stakeholders to develop a deeper understanding of the underlying systemic problems, such as delayed transitions between schools and instructor shortages, whilst the hybrid “push-pull” design allowed us to quantify the pooling of students between schools.

Modelling relational aspects of critical infrastructure systems

The relational aspects for critical infrastructure systems are not readily quantifiable as there are numerous variability’s and system dynamics that lack uniformity and are difficult to quantify. Notwithstanding this, there is a large body of existing research that is founded in the area of quantitative analysis of critical infrastructure networks, their system relationships and the resilience of these networks. However, the focus of this research is to investigate the aspect of taking a different, more generalised and holistic system perspective approach. This is to suggest that that through applying network theory and taking a ‘soft’ system-like modelling approach that this offers an alternative approach to viewing and modelling critical infrastructure system relational aspects that warrants further enquiry.

A new design of sliding mode control systems

A new sliding mode control technique for a class of SISO dynamic systems is presented in this chapter. It is seen that the stability status of the closed-loop system is first checked, based on the approximation of the most recent information of the first-order derivative of the Lyapunov function of the closed-loop system, an intelligent sliding mode controller can then be designed with the following intelligent features: (i) If the closed-loop system is stable, the correction term in the controller will continuously adjust control signal to drive the closed-loop trajectory to reach the sliding mode surface in a finite time and the desired closed-loop dynamics with the zero-error convergence can then be achieved on the sliding mode surface. (ii) If, however, the closed-loop system is unstable, the correction term is capable of modifying the control signal to continuously reduce the value of the derivative of the Lyapunov function from the positive to the negative and then drives the closed-loop trajectory to reach the sliding mode surface and ensures that the desired closed-loop dynamics can be obtained on the sliding mode surface. The main advantages of this new sliding mode control technique over the conventional one are that no chattering occurs in the sliding mode control system because of the recursive learning control structure; the system uncertainties are embedded in the Lipschitz-like condition and thus, no priori information on the upper and/or the lower bounds of the unknown system parameters and uncertain system dynamics is required for the controller design; the zero-error convergence can be achieved after the closed-loop dynamics reaches the sliding mode surface and remains on it. The performance for controlling a third-order linear system is evaluated in the simulation section to show the effectiveness and efficiency of the new sliding mode control technique.

Sliding mode-like learning control for SISO complex systems with T-S fuzzy models

In this paper, a sliding mode-like learning control scheme is developed for a class of single input single output (SISO) complex systems. First, the Takagi-Sugeno (T-S) fuzzy modelling technique is employed to model the uncertain complex dynamical systems. Second, a sliding mode-like learning control is designed to drive the sliding variable to converge to the sliding surface, and the system states can then asymptotically converge to zero on the sliding surface. The advantages of this scheme are that: 1) the information about the uncertain system dynamics and the system model structure is not required for the design of the learning controller; 2) the closed-loop system behaves with a strong robustness with respect to uncertainties; 3) the control input is chattering-free. The sufficient conditions for the sliding mode-like learning control to stabilise the global fuzzy model are discussed in detail. A simulation example for the control of an inverted pendulum cart is presented to demonstrate the effectiveness of the proposed control scheme.

A robust learning control for SISO Nonlinear systems with T-S Fuzzy Model : C02-robust control

In this paper, a robust learning control is developed for a class of single input single output (SISO) nonlinear systems with T-S fuzzy model. It is seen that the proposed sliding mode learning control with the powerful Lipshitz-like condition can guarantee the stability, convergence and robustness of the closed-loop system without involving any assumptions on uncertain system dynamics. In addition, theconcept that the local system with the maximum membership function dominates the system dynamic behaviours helps to greatly simplify the control system design. It will be further seen that the continuous learning control ensures the advantage of chattering-free that may occur in conventional sliding mode systems. Simulation examples are presented to demonstrate the effectiveness of the proposed learning control through the comparison with the H-infinity control.

Drought and desalination: Melbourne water supply and development choices in the twenty-first century

Sharply reduced catchment inflows across Australia around the end of the twentieth century led to a sequence of water restrictions followed, as the drought persisted, by approximately $10 billion of investments in desalination plants near Perth, Adelaide, Melbourne, Sydney and Brisbane. This Deakin University project jointly with Griffith University, for the National Centre of Excellence in Desalination (NCEDA), follows these new investments. We ask how best to manage bulk water supply and retail supply given the facts and fears of uncertain rainfall, modelled over a 100 year simulation period. We use Monte Carlo style studies aiming to capture the new tensions and trade-offs regarding uncertain climate, rainfall and water supply. There are presently no comprehensive life-cycle approaches to model city water balances that incorporate economic feedbacks, such as tariff adjustment, which can in turn create a financing capacity for such investment responses to low catchment levels, models that could provide significant policy implications for water planners. This project addresses the gap, and presents excerpts from a system dynamics model that augments the usual water utility representation of the physical linkages and water grids. We add inter-connected feedback loops in tariff structures, demand levels and financing capacity. Tariffs are reset in association with drought and the modelling of responses both in terms of reduced consumption and increased revenue to the utility, depending on the elasticities of demand responses to higher tariffs, both short and long term, while also allowing effects from any transitional restrictions. Before reporting on parts of the simulations applied to Melbourne, this paper will first review the general issues surrounding whether desalination is or can be a “game changer” for economic development that hinges on secure water supply. We then explore options in bulk water supply management when desalination augments the choices, including catchments, dams, recycling, pipelines from rivers and savings in irrigation. Finally, the paper addresses the intriguing and important question of the value and cost of providing water for environmental uses.

Long-term water supply planning in an Australian coastal city : Dams or desalination?

Water resource managers and planners are continually involved in defining and evaluating alternative policies to better meet changing water supply conditions and the expectations of society. To undertake such long-term water supply planning, this study developed a novel integrated system dynamics model to combine economic, social and scientific variables and considerations within the planning horizon. Extensive sensitivity analysis for these variables was considered in this long term water resource planning process. The analysis suggests that over a longer time horizon, desalination provides a more viable, cost effective and secure bulk water supply alternative when compared to building large rain-dependent dams.

A community based systems diagram of obesity causes

INTRODUCTION: Application of system thinking to the development, implementation and evaluation of childhood obesity prevention efforts represents the cutting edge of community-based prevention. We report on an approach to developing a system oriented community perspective on the causes of obesity. METHODS: Group model building sessions were conducted in a rural Australian community to address increasing childhood obesity. Stakeholders (n = 12) built a community model that progressed from connection circles to causal loop diagrams using scripts from the system dynamics literature. Participants began this work in identifying change over time in causes and effects of childhood obesity within their community. The initial causal loop diagram was then reviewed and elaborated by 50 community leaders over a full day session. RESULTS: The process created a causal loop diagram representing community perceptions of determinants and causes of obesity. The causal loop diagram can be broken down into four separate domains; social influences; fast food and junk food; participation in sport; and general physical activity. DISCUSSION: This causal loop diagram can provide the basis for community led planning of a prevention response that engages with multiple levels of existing settings and systems.

Formulating policy activities to promote healthy and sustainable diets

OBJECTIVE: To develop a policy formulation tool for strategically informing food and nutrition policy activities to promote healthy and sustainable diets (HSD). DESIGN: A policy formulation tool consisting of two complementary components was developed. First, a conceptual framework of the environment-public health nutrition relationship was constructed to characterise and conceptualise the food system problem. Second, an 'Orders of Food Systems Change' schema drawing on systems dynamics thinking was developed to identify, assess and propose policy options to redesign food systems. SETTING: Food and nutrition policy activities to promote HSD have been politicised, fragmented and lacking a coherent conceptual and strategic focus to tackle complex food system challenges. RESULTS: The tool's conceptual framework component comprises three integrated dimensions: (i) a structure built around the environment and public health nutrition relationship that is mediated via the food system; (ii) internal mechanisms that operate through system dynamics; and (iii) external interactions that frame its nature and a scope within ecological parameters. The accompanying schema is structured around three orders of change distinguished by contrasting ideological perspectives on the type and extent of change needed to 'solve' the HSD problem. CONCLUSIONS: The conceptual framework's systems analysis of the environment-public health nutrition relationship sets out the food system challenges for HSD. The schema helps account for political realities in policy making and is a key link to operationalise the framework's concepts to actions aimed at redesigning food systems. In combination they provide a policy formulation tool to strategically inform policy activities to redesign food systems and promote HSD.

A multi-level approach to planning and scheduling resources for aviation training

This paper describes a multi-level system dynamics (SD) / discrete event simulation (DES) approach for assessing planning and scheduling problems within an aviation training continuum. The aviation training continuum is a complex system, consisting of multiple aviation schools interacting through interschool student and instructor flows that are affected by external triggers such as resource availability and the weather.
SD was used to model the overall training continuum at a macro level to ascertain relationships between system entities. SD also assisted in developing a shared understanding of the training continuum, which involves constructing the definitions of the training requirements, resources and policy objectives. An end-to-end model of the continuum is easy to relate to, while dynamic visualisation of system behaviour provides a method for exploration of the model.
DES was used for micro level exploration of an individual school within the training continuum to capture the physical aspects of the system including resource capacity requirements, bottlenecks and student waiting times. It was also used to model stochastic events such as weather and student availability. DES has the advantage of being able to represent system variability and accurately reflect the limitations imposed on a system by resource constraints.
Through sharing results between the models, we demonstrate a multi-level approach to the analysis of the overall continuum. The SD model provides the school’s targeted demand to the DES model. The detailed DES model is able to assess schedules in the presence of resource constraints and variability and provide the expected capacity of a school to the high level SD model, subjected to constraints such as instructor availability or budgeted number of training systems. The SD model allows stakeholders to assess how policy and planning affect the continuum, both in the short and the long term.
The development of this approach permits moving the analysis of the continuum between SD and DES models as appropriate for given system entities, scales and tasks. The resultant model outcomes are propagated between the continuum and the detailed DES model, iteratively generating an assessment of the entire set of plans and schedule across the continuum. Combining data and information between SD and DES models and techniques assures relevance to the stakeholder needs and effective problem scoping and scaling that can also evolve with dynamic architecture and policy requirements.
An example case study shows the combined use of the two models and how they are used to evaluate a typical scenario where increased demand is placed on the training continuum. The multi-level approach provides a high level indication of training requirements to the model of the new training school, where the detailed model indicates the resources required to achieve those particular student levels.

Sodium ion dynamics in a sulfonate based ionomer system studied by 23Na solid-state nuclear magnetic resonance and impedance spectroscopy

A poly(2-acrylamido-2-methyl-1-propane-sulphonate) (PAMPS) ionomer containing both sodium and quaternary ammonium cations functionalised with an ether group, has been characterised in terms of its thermal properties, ionic conductivity and sodium ion dynamics. The ether oxygen was incorporated to reduce the Na+ association with the anionic sulfonate groups tethered to the polymer backbone, thereby promoting ion dissociation and ultimately enhancing the ionic conductivity. This functionalised ammonium cation led to a significant reduction in the ionomer Tg compared to an analogue system without an ether group, resulting in an increase in ionic conductivity of approximately four orders of magnitude. The sodium ion dynamics were probed by 23Na solid-state NMR, which allowed the signals from the dissociated (mobile) and bound Na+ cations to be distinguished. This demonstrates the utility of 23Na solid-state NMR as a probe of sodium dynamics in ionomer systems.