Systematic policymaking with the institutionalist policymaking framework

One of our most pressing needs in creating a more sustainable world is the explicit development of holistic policy. This is becoming increasingly apparent as we are faced with more and more ‘wicked problems'—the most difficult class of problems that we can conceptualise: problems which consist of ‘clusters’ of problems; problems within these clusters cannot be solved in isolation from one another, and include socio-political and moral-spiritual issues (see Rittel and Webber 1973). This paper articulates a methodology that can be applied to the analysis and design of underlying organisational structures and processes that will consistently and effectively address wicked problems. This transdisciplinary methodology—known as the institutionalist policymaking framework—has been developed from the perspective of institutional economics synthesised with perspectives from ecological economics and system dynamics. Substantive and lasting solutions to wicked problems need to be formed endogenously, that is, from within the system. The institutionalist policymaking framework is a transdisciplinary, discursive and reflexive vehicle through which this endogenous creation of solutions to wicked problems may be realised.

Development of the sustainable building and construction products industry in Australia

This paper draws on a major study the authors conducted for the Australian Government in 2009. It focuses on the diffusion issues surrounding the uptake of sustainable building and construction products in Australia. Innovative sustainable products can minimise the environmental impact during construction, while maximising asset performance, durability and re-use. However, there are significant challenges faced by designers and clients in the selection of appropriate sustainable products in consideration of the integrated design solution, including overall energy efficiency, water conservation, maintenance and durability, low-impact use and consumption. The paper is a review of the current state of sustainable energy and material product innovations in Australia. It examines the system dynamics surrounding these innovations as well as the drivers and obstacles to their diffusion throughout the Australian construction industry. The case product types reviewed comprise: solar energy technology, small wind turbines, advanced concrete technology, and warm-mixed asphalt. The conclusions highlight the important role played by Australian governments in facilitating improved adoption rates. This applies to governments in their various roles, but particularly as clients/owners, regulators, and investors in education, training, research and development. In their role as clients/owners, the paper suggests that government can better facilitate innovation within the construction industry by adjusting specification policies to encourage the uptake of sustainable products. In the role as regulators, findings suggest governments should be encouraging the application of innovative finance options and positive end-user incentives to promote sustainable product uptake. Also, further education for project-based firms and the client/end users about the long-term financial and environmental benefits of innovative sustainable products is required. As more of the economy’s resources are diverted away from business-as-usual and into the use of sustainable products, some project-based firms may face short-term financial pain in re-shaping their businesses. Government policy initiatives can encourage firms make the necessary adjustments to improve innovative sustainable product diffusion throughout the industry.

Development priority zoning (DPZ)-led scenario simulation for regional land use change : the case of Suichang County, China

China has experienced an extraordinary level of economic development since the 1990s, following excessive competition between different regions. This has resulted in many resource and environmental problems. Land resources, for example, are either abused or wasted in many regions. The strategy of development priority zoning (DPZ), proposed by the Chinese National 11th Five-Year Plan, provides an opportunity to solve these problems by coordinating regional development and protection. In line with the rational utilization of land, it is proposed that the DPZ strategy should be integrated with regional land use policy. As there has been little research to date on this issue, this paper introduces a system dynamic (SD) model for assessing land use change in China led by the DPZ strategy. Land use is characterized by the prioritization of land development, land utilization, land harness and land protection (D-U-H-P). By using the Delphi method, a corresponding suitable prioritization of D-U-H-P for the four types of DPZ, including optimized development zones (ODZ), key development zones (KDZ), restricted development zones (RDZ), and forbidden development zones (FDZ) are identified. Suichang County is used as a case study in which to conduct the simulation of land use change under the RDZ strategy. The findings enable a conceptualization to be made of DPZ-led land use change and the identification of further implications for land use planning generally. The SD model also provides a potential tool for local government to combine DPZ strategy at the national level with land use planning at the local level.

Modelling and analysis of the crush zone of a typical Australian passenger train

In this paper, a three-dimensional nonlinear rigid body model has been developed for the investigation of the crashworthiness of a passenger train using the multibody dynamics approach. This model refers to a typical design of passenger cars and train constructs commonly used in Australia. The high-energy and low-energy crush zones of the cars and the train constructs are assumed and the data are explicitly provided in the paper. The crash scenario is limited to the train colliding on to a fixed barrier symmetrically. The simulations of a single car show that this initial design is only applicable for the crash speed of 35 km/h or lower. For higher speeds (e.g. 140 km/h), the crush lengths or crush forces or both the crush zone elements will have to be enlarged. It is generally better to increase the crush length than the crush force in order to retain the low levels of the longitudinal deceleration of the passenger cars.

A dynamic wheel-rail impact analysis of railway track under wheel flat by Finite Element Analysis

Wheel–rail interaction is one of the most important research topics in railway engineering. It involves track impact response, track vibration and track safety. Track structure failures caused by wheel–rail impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. Wheel–rail impact forces occur because of imperfections in the wheels or rails such as wheel flats, irregular wheel profiles, rail corrugations and differences in the heights of rails connected at a welded joint. A wheel flat can cause a large dynamic impact force as well as a forced vibration with a high frequency, which can cause damage to the track structure. In the present work, a three-dimensional (3-D) finite element (FE) model for the impact analysis induced by the wheel flat is developed by use of the finite element analysis (FEA) software package ANSYS and validated by another validated simulation. The effect of wheel flats on impact forces is thoroughly investigated. It is found that the presence of a wheel flat will significantly increase the dynamic impact force on both rail and sleeper. The impact force will monotonically increase with the size of wheel flats. The relationships between the impact force and the wheel flat size are explored from this finite element analysis and they are important for track engineers to improve their understanding of the design and maintenance of the track system.

Visualizing the evolution of knowledge management capability in construction firms

A firm, as a dynamic, evolving, and quasi-autonomous system of knowledge production and application, develops knowledge management capability (KMC) through strategic learning in order to sustain competitive advantages in a dynamic environment. Knowledge governance mechanisms and knowledge processes connect and interact with each other forming learning mechanisms, which carry out double loop learning that drives genesis and evolution of KMC to modify operating routines that effect desired performance. This paper reports a study that was carried out within a context of construction contractors, a type of project-based firms, operating within the dynamic Hong Kong construction market. A multiple-case design was used to incorporate evidence from the literature and interviews, with the help of system dynamics modeling, to visualize the evolution of KMC. The study demonstrates the feasibility to visualize how a firm's KMC matches its operating environment over time. The findings imply that knowledge management (KM) applications can be better planned and controlled through evaluation of KM performance over time from a capability perspective.

Dynamic modeling for construction innovation

Previous research on construction innovation has commonly recognized the importance of the organizational climate and key individuals, often called “champions,” for the success of innovation. However, it rarely focuses on the role of participants at the project level and addresses the dynamics of construction innovation. This paper therefore presents a dynamic innovation model that has been developed using the concept of system dynamics. The model incorporates the influence of several individual and situational factors and highlights two critical elements that drive construction innovations: (1) normative pressure created by project managers through their championing behavior, and (2) instrumental motivation of team members facilitated by a supportive organizational climate. The model is qualified empirically, using the results of a survey of project managers and their project team members working for general contractors in Singapore, by assessing casual relationships for key model variables. Finally, the paper discusses the implications of the model structure for fostering construction innovations.

An overview of the marine systems simulator (MSS) : a Simulink toolbox for marine control systems

The Marine Systems Simulator (MSS) is an environment which provides the necessary resources for rapid implementation of mathematical models of marine systems with focus on control system design. The simulator targets models¡Xand provides examples ready to simulate¡Xof different floating structures and its systems performing various operations. The platform adopted for the development of MSS is Matlab/Simulink. This allows a modular simulator structure, and the possibility of distributed development. Openness and modularity of software components have been the prioritized design principles, which enables a systematic reuse of knowledge and results in efficient tools for research and education. This paper provides an overview of the structure of the MSS, its features, current accessability, and plans for future development.

Non-linear model predictive control for UAVs with slung/swung load

Suspended loads on UAVs can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present software and flight system architecture to test controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Transport and health in China : recent collaborative research relating to vehicle factors and pollution

The nature of the transport system contributes to public health outcomes in a range of ways. The clearest contribution to public health is in the area of traffic crashes, because of their direct impact on individual death and disability and their direct costs to the health system. Other papers in this conference address these issues. This paper outlines some collaborative research between the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) at QUT and Chinese researchers in areas that have indirect health impacts. Heavy vehicle dynamics: The integrity of the road surface influences crash risk, with ruts, pot-holes and other forms of road damage contributing to increased crash risks. The great majority of damage to the road surface from vehicles is caused by heavy trucks and buses, rather than cars or smaller vehicles. In some cases this damage is due to deliberate overloading, but in other cases it is due to vehicle suspension characteristics that lead to occasional high loads on particular wheels. Together with a visiting researcher and his colleagues, we have used both Queensland and Chinese data to model vehicle suspension systems that reduce the level of load, and hence the level of road damage and resulting crash risk(1-5). Toll worker exposure to vehicle emissions: The increasing construction of highways in China has also involved construction of a large number of toll roads. Tollbooth workers are potentially exposed to high levels of pollutants from vehicles, however the extent of this exposure and how it relates to standards for exposure are not well known. In a study led by a visiting researcher, we conducted a study to model these levels of exposure for a tollbooth in China(6). Noise pollution: The increasing presence of high speed roads in China has contributed to an increase in noise levels. In this collaborative study we modelled noise levels associated with a freeway widening near a university campus, and measures to reduce the noise(7). Along with these areas of research, there are many other areas of transport with health implications that are worthy of exploration. Traffic, noise and pollution contribute to a difficult environment for pedestrians, especially in an ageing society where there are health benefits to increasing physical activity. By building on collaborations such as those outlined, there is potential for a contribution to improved public health by addressing transport issues such as vehicle factors and pollution, and extending the research to other areas of travel activity. 1. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2014). Stiffness-damping matching method of an ECAS system based on LQG control. Journal of Central South University, 21:439-446. DOI: 10.1007/s1177101419579 2. Chen, Y., He, J., King, M., Feng, Z. and Chang, W. (2013). Comparison of two suspension control strategies for multi-axle heavy truck. Journal of Central South University, 20(2): 550-562. 3. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2013). Effect of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions. Science China Technological Sciences, 56(3): 666-676. DOI: 10.1007/s11431-012-5091-3 4. Chen, Y., He., J., King, M., Chen, W. and Zhang, W. (2013). Model development and dynamic load-sharing analysis of longitudinal-connected air suspensions. Strojniški Vestnik - Journal of Mechanical Engineering, 59(1):14-24. 5. Chen, Y., He, J., King, M., Liu, H. and Zhang, W. (2013). Dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-1117. 6. He, J., Qi, Z., Hang, W., King, M., and Zhao, C. (2011). Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models. Transportation Research Part C, 19(2011):510-520. 7. Zhang, C., He, J., Wang, Z., Yin, R. and King, M. (2013). Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-2016.

Evaluation of knowledge management performance: An organic approach

Knowledge management (KM) strategy is the planned or actual coordination of a firm's major goals and learning in time; this coordination continually co-aligns the firm's knowledge-based resources with the environment. Based on the organic perspective of strategy, a KM performance evaluation approach should be able to 1) review the knowledge governance mechanisms and learning routines that underpin the KM strategy, as well as the performance outcomes driven by the strategy, and 2) predict the evolution of performance drivers and outcomes into the future to facilitate strategic planning. This study combined a survey study and a system dynamics (SD) simulation to demonstrate the transformation from a mechanistic to an organic perspective on KM strategy and performance evaluation. The survey study was conducted based on a sample of 143 construction contractors and used structural equation modeling (SEM) techniques to develop a KM performance index for reviewing the key elements that underpin KM strategy. The SD simulation predicted the development of KM strategy configurations and the evolution of KM performance over time. The organic KM performance evaluation approach demonstrated by this study has significant potential to improve the alignment of KM strategy within an increasingly dynamic business environment.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

On food security and alternative food networks: Understanding and performing food security in the context of urban bias

This paper offers one explanation for the institutional basis of food insecurity in Australia, and argues that while alternative food networks and the food sovereignty movement perform a valuable function in building forms of social solidarity between urban consumers and rural producers, they currently make only a minor contribution to Australia’s food and nutrition security. The paper begins by identifying two key drivers of food security: household incomes (on the demand side) and nutrition-sensitive, ‘fair food’ agriculture (on the supply side). We focus on this second driver and argue that healthy populations require an agricultural sector that delivers dietary diversity via a fair and sustainable food system. In order to understand why nutrition-sensitive, fair food agriculture is not flourishing in Australia we introduce the development economics theory of urban bias. According to this theory, governments support capital intensive rather than labour intensive agriculture in order to deliver cheap food alongside the transfer of public revenues gained from rural agriculture to urban infrastructure, where the majority of the voting public resides. We chart the unfolding of the Urban Bias across the twentieth century and its consolidation through neo-liberal orthodoxy, and argue that agricultural policies do little to sustain, let alone revitalize, rural and regional Australia. We conclude that by observing food system dynamics through a re-spatialized lens, Urban Bias Theory is valuable in highlighting rural–urban socio-economic and political economy tensions, particularly regarding food system sustainability. It also sheds light on the cultural economy tensions for alternative food networks as they move beyond niche markets to simultaneously support urban food security and sustainable rural livelihoods.

Correction factors for dynamic state estimation of aggregated generators

This paper presents an approach for dynamic state estimation of aggregated generators by introducing a new correction factor for equivalent inter-area power flows. The spread of generators from the center of inertia of each area is summarized by the correction term α on the equivalent power flow between the areas and is applied to the identification and estimation process. A nonlinear time varying Kalman filter is applied to estimate the equivalent angles and velocities of coherent areas by reducing the effect of local modes on the estimated states. The approach is simulated on two test systems and the results show the effect of the correction factor and the performance of the state estimation by estimating the inter-area dynamics of the system.