An integrated modeling and risk analysis tool for mine water interactions

Poor mine water management can lead to corporate, environmental and social risks. These risks become more pronounced as mining operations move into areas of water scarcity and/or increase climatic variability while also managing increased demand, lower ore grades and increased strip ratios. Therefore, it is vital that mine sites better understand these risks in order to implement management practices to address them. Systems models provide an effective approach to understand complex networks, particularly across multiple scales. Previous work has represented mine water interactions using systems model on a mine site scale. Here, we expand on that work by present an integrated tool that uses a systems modeling approach to represent mine water interactions on a site and regional scale and then analyses the risks associated with events stemming from those interactions. A case study is presented to represent three indicative corporate, environmental and social risks associated with a mine site that exists in a water scarce region. The tool is generic and flexible, and can be used in many scenarios to provide significant potential utility to the mining industry.

Course evaluation : reconfigurations for learning with learning management systems

The introduction of online delivery platforms such as learning management systems (LMS) in tertiary education has changed the methods and modes of curriculum delivery and communication. While course evaluation methods have also changed from paper-based in-class-administered methods to largely online-administered methods, the data collection instruments have remained unchanged. This paper reports on a small exploratory study of two tertiary-level courses. The study investigated why design of the instruments and methods to administer surveys in the courses are ineffective measures against the intrinsic characteristics of online learning. It reviewed the students' response rates of the conventional evaluations for the courses over an eight-year period. It then compared a newly developed online evaluation and the conventional methods over a two-year period. The results showed the response rates with the new evaluation method increased by more than 80% from the average of the conventional evaluations (below 30%), and the students' written feedback was more detailed and comprehensive than in the conventional evaluations. The study demonstrated the possibility that the LMS-based learning evaluation can be effective and efficient in terms of the quality of students' participation and engagement in their learning, and for an integrated pedagogical approach in an online learning environment.

Space vector modulated cascade multi-level inverter for PMSG wind generation systems

Modulation and control of a cascade multilevel inverter, which has a high potential in future wind generation applications, are presented. The inverter is a combination of a high power, three level “bulk inverter” and a low power “conditioning inverter”. To minimize switching losses, the bulk inverter operates at a low frequency producing square wave outputs while high frequency conditioning inverter is used to suppress harmonic content produced by the bulk inverter output. This paper proposes an improved Space Vector Modulation (SVM) algorithm and a neutral point potential balancing technique for the inverter. Furthermore, a maximum power tracking controller for the Permanent Magnet Synchronous Generator (PMSG) is described in detail. The proposed SVM technique eliminates most of the computational burdens on the digital controller and renders a greater controllability under varying DC-link voltage conditions. The DC-link capacitor voltage balancing of both bulk and conditioning inverters is carried out using Redundant State Selection (RSS) method and is explained in detail. Experimental results are presented to verify the proposed modulation and control techniques.

A cascade multilevel STATCOM for wind generation systems

This paper presents a novel STATCOM configuration for voltage quality improvement in wind power generation systems. The proposed STATCOM is formed by cascading two 3-level inverters, `bulk inverter' and `conditioning inverter', through a coupling transformer. Both inverters are powered by dc-link capacitors and they are charged by a small amount of active power drawn from the grid. To minimize switching losses, the high power bulk inverter operates at low frequency while low power high frequency conditioning inverter is used to suppress harmonic content produced by the bulk inverter output. With only 24 switches this topology can synthesize a nine level inverter, if the dc-link voltage ratio is maintained at 3:1. Modulation and control techniques have been developed to meet this requirement. Reactive power of the STATCOM is controlled to mitigate voltage sags or swells caused by sudden wind changes. Simulation and experimental results are presented to verify the efficacy of the proposed modulation and control techniques used in the STATCOM.

Energy storage systems in distributed generation schemes

An overview is given of the various energy storage technologies which can be used in distributed generation (DG) schemes. Description of the recent photovoltaic DG initiative in Singapore is included, in which several of the storage systems can find ready applications. Schemes pertaining to the use of solid oxide fuel cell for power quality enhancement and battery energy storage system used in conjunction with wind power generation are also described.

Users’ perception of using web search engines and their impact on the perceived intention to reuse the systems

In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Assessment of robust autonomy for unmanned systems : progress and challenges

The growing number of potential applications of Unmanned Aircraft Systems (UAS) in civilian operations and national security is putting pressure of National Airworthiness Authorities to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends not only on developments in improved UAS reliability and safety, but also on regulations for certification, and methodologies for operational performance and safety assessment. This paper focuses on the latter and describes progress in relation to a previously proposed framework for evaluating robust autonomy of UAS. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It discusses how the data from the proposed evaluation can be used as an aid for decision making in certification and UAS designs. Finally, it discusses challenges associated with the evaluation.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Audio signalling as a backup communication channel for multi-robot systems

This paper presents a low-bandwidth multi-robot communication system designed to serve as a backup communication channel in the event a robot suffers a network device fault. While much research has been performed in the area of distributing network communication across multiple robots within a system, individual robots are still susceptible to hardware failure. In the past, such robots would simply be removed from service, and their tasks re-allocated to other members. However, there are times when a faulty robot might be crucial to a mission, or be able to contribute in a less communication intensive area. By allowing robots to encode and decode messages into unique sequences of DTMF symbols, called words, our system is able to facilitate continued low-bandwidth communication between robots without access to network communication. Our results have shown that the system is capable of permitting robots to negotiate task initiation and termination, and is flexible enough to permit a pair of robots to perform a simple turn taking task.

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Integrating PV systems into distribution networks with battery energy storage systems

Integrating Photovoltaic (PV) systems with battery energy storage in the distribution network will be essential to allow for continued uptake of domestic PV system installations. With increasing concerns regarding environmental and climate change issues, incorporating sources of renewable energy into power networks across the world will be key for a sustainable future. Australia is well placed to utilise solar energy as a significant component of its future energy generation and within the last 5 years there has been a rapid growth in the penetration levels seen by the grid. This growth of PV systems is causing a number of issues including intermittency of supply, negative power flow and voltage rises. Using the simulator tool GridLAB-D with a model of a typical South-East Queensland (SEQ) 11 kV distribution feeder, the effect of various configurations of PV systems have been offset with Battery Energy Storage Systems (BESS). From this, combinations of PV and storage that are most effective at mitigating the issues were explored.

Fuzzy logic to evaluate driving maneuvers: An integrated approach to improve training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

Efficient multiple relay selection for cooperative communication using alamouti-coded virtual transmit antenna systems

An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

Utilizing reactive capability of PV inverters and battery systems to improve voltage profile of a residential distribution feeder

Significant increase in installation of rooftop Photovoltaic (PV) in the Low-Voltage (LV) residential distribution network has resulted in over voltage problems. Moreover, increasing peak demand creates voltage dip problems and make voltage profile even worse. Utilizing the reactive power capability of PV inverter (RCPVI) can improve the voltage profile to some extent. Resistive caharcteristic (higher R/X ratio) limits the effectiveness of reactive power to provide voltage support in distribution network. Battery Energy Storage (BES), whereas, can store the excess PV generation during high solar insolation time and supply the stored energy back to the grid during peak demand. A coordinated algorithm is developed in this paper to use the reactive capability of PV inverter and BES with droop control. Proposed algorithm is capable to cater the severe voltage violation problem using RCPVI and BES. A signal flow is also mentioned in this research work to ensure smooth communication between all the equipments. Finally the developed algorithm is validated in a test distribution network.