Recent advances in modeling the vulnerability of transportation networks

It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Modeling kinect sensor noise for improved 3D reconstruction and tracking

We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.

Probabilistic power system contingency analysis considering wind

This thesis was a step forward in developing probabilistic assessment of power system response to faults subject to intermittent generation by renewable energy. It has investigated the wind power fluctuation effect on power system stability, and the developed fast estimation process has demonstrated the feasibility for real-time implementation. A better balance between power network security and efficiency can be achieved based on this research outcome.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

Modeling and control of a CLC resonant dual active bridge

This paper proposes a linear large signal state-space model for a phase controlled CLC (Capacitor Inductor Capacitor) Resonant Dual Active Bridge (RDAB). The proposed model is useful for fast simulation and for the estimation of state variables under large signal variation. The model is also useful for control design because the slow changing dynamics of the dq variables are relatively easy to control. Simulation results of the proposed model are presented and compared to the simulated circuit model to demonstrate the proposed model's accuracy. This proposed model was used for the design of a Proportional-Integral (PI) controller and it has been implemented in the circuit simulation to show the proposed models usefulness in control design.

Finite element modeling of carbon fibre reinforced polymer (CFRP) strengthened steel tubes under axial impact

Steel hollow sections used in structures such as bridges, buildings and space structures involve different strengthening techniques according to their structural purpose and shape of the structural member. One such technique is external bonding of CFRP sheets to steel tubes. The performance of CFRP strengthening for steel structures has been proven under static loading while limited studies have been conducted on their behaviour under impact loading. In this study, a comprehensive numerical investigation is carried out to evaluate the response of CFRP strengthened steel tubes under dynamic axial impact loading. Impact force, axial deformation impact velocities are studied. The results of the numerical investigations are validated by experimental results. Based on the developed finite element (FE) model several output parameters are discussed. The results show that CFRP wrapping is an effective strengthening technique to increase the axial dynamic load bearing capacity by increasing the stiffness of the steel tube.

A theory of process modeling impact

Process modeling – the design and use of graphical documentations of an organization’s business processes – is a key method to document and use information about the operations of businesses. Still, despite current interest in process modeling, this research area faces essential challenges. Key unanswered questions concern the impact of process modeling in organizational practice, and the mechanisms through which impacts are developed. To answer these questions and to provide a better understanding of process modeling impact, I turn to the concept of affordances. Affordances describe the possibilities for goal-oriented action that a technical object offers to a user. This notion has received growing attention from IS researchers. The purpose of my research is to further develop the IS discipline’s understanding of affordances and impacts from information objects, such as process models used by analysts for information systems analysis and design. Specifically, I seek to extend existing theory on the emergence, perception and actualization of affordances. I develop a research model that describes the process by which affordances emerge between an individual and an object, how affordances are perceived, and how they are actualized by the individual. The proposed model also explains the role of available information for the individual, and the influence of perceived actualization effort. I operationalize and test this research model empirically, using a full-cycle, mixed methods study consisting of case study and experiment.

Establishing statistical foundations early : data modeling with young learners

This paper addresses research from a three-year longitudinal study that engaged children in data modeling experiences from the beginning school year through to third year (6-8 years). A data modeling approach to statistical development differs in several ways from what is typically done in early classroom experiences with data. In particular, data modeling immerses children in problems that evolve from their own questions and reasoning, with core statistical foundations established early. These foundations include a focus on posing and refining statistical questions within and across contexts, structuring and representing data, making informal inferences, and developing conceptual, representational, and metarepresentational competence. Examples are presented of how young learners developed and sustained informal inferential reasoning and metarepresentational competence across the study to become “sophisticated statisticians”.