Reliability analysis and economic equipment replacement appraisal for substation and sub-transmission systems with explicit inclusion of non-repairable failures

The modern society has come to expect the electrical energy on demand, while many of the facilities in power systems are aging beyond repair and maintenance. The risk of failure is increasing with the aging equipments and can pose serious consequences for continuity of electricity supply. As the equipments used in high voltage power networks are very expensive, economically it may not be feasible to purchase and store spares in a warehouse for extended periods of time. On the other hand, there is normally a significant time before receiving equipment once it is ordered. This situation has created a considerable interest in the evaluation and application of probability methods for aging plant and provisions of spares in bulk supply networks, and can be of particular importance for substations. Quantitative adequacy assessment of substation and sub-transmission power systems is generally done using a contingency enumeration approach which includes the evaluation of contingencies, classification of the contingencies based on selected failure criteria. The problem is very complex because of the need to include detailed modelling and operation of substation and sub-transmission equipment using network flow evaluation and to consider multiple levels of component failures. In this thesis a new model associated with aging equipment is developed to combine the standard tools of random failures, as well as specific model for aging failures. This technique is applied in this thesis to include and examine the impact of aging equipments on system reliability of bulk supply loads and consumers in distribution network for defined range of planning years. The power system risk indices depend on many factors such as the actual physical network configuration and operation, aging conditions of the equipment, and the relevant constraints. The impact and importance of equipment reliability on power system risk indices in a network with aging facilities contains valuable information for utilities to better understand network performance and the weak links in the system. In this thesis, algorithms are developed to measure the contribution of individual equipment to the power system risk indices, as part of the novel risk analysis tool. A new cost worth approach was developed in this thesis that can make an early decision in planning for replacement activities concerning non-repairable aging components, in order to maintain a system reliability performance which economically is acceptable. The concepts, techniques and procedures developed in this thesis are illustrated numerically using published test systems. It is believed that the methods and approaches presented, substantially improve the accuracy of risk predictions by explicit consideration of the effect of equipment entering a period of increased risk of a non-repairable failure.

Comparative Studies Simplified in GPFlow

We present a novel, web-accessible scientific workflow system which makes large-scale comparative studies accessible without programming or excessive configuration requirements. GPFlow allows a workflow defined on single input values to be automatically lifted to operate over collections of input values and supports the formation and processing of collections of values without the need for explicit iteration constructs. We introduce a new model for collection processing based on key aggregation and slicing which guarantees processing integrity and facilitates automatic association of inputs, allowing scientific users to manage the combinatorial explosion of data values inherent in large scale comparative studies. The approach is demonstrated using a core task from comparative genomics, and builds upon our previous work in supporting combined interactive and batch operation, through a lightweight web-based user interface.

Explicit, latent and meta-criteria : types of criteria at play in professional judgement practice

This paper engages with debates about whether comprehensive prior specification of criteria and standards is sufficient for informed professional judgement. A preoccupation has emerged with the specificity and explication of criteria intended to regulate judgement. This has resulted in criteria-compliance in the use of defined standards to validate judgements and improve reliability and consistency. Compliance has become a priority, the consequence being the prominence of explicit criteria, to the lack of acknowledgement of the operation of latent and meta-criteria within judgement practice. This paper examines judgement as a process involving three categories of assessment criteria in the context of standards-referenced systems: explicit, latent and meta-criteria. These are understood to be wholly interrelated and interdependent. A conceptualisation of judgement involving the interplay of the three criteria types is presented with an exploration of how they function to focus or alter assessments of quality in judgements of achievement in English and Mathematics.

Consumer guarantees and the supply of educational services by higher education providers

The higher education sector is undergoing a number of significant changes, the implications of which have yet to emerge. One such change is the increasing reliance by higher education providers on the revenue generated by full fee paying international students to fund their operating expenses. The report by the Victorian Ombudsman, Investigation into how Universities Deal with International Students ('Victorian Ombudsman's Report') tabled in the Victorian Parliament on 27 October 2011, provides evidence that Australian higher education providers may be failing to meet their legal obligations to international students. The Victorian Ombudsman's Report is the result of an investigation into four Victorian universities teaching international students with a focus on accounting and nursing schools. The report contains evidence that the universities were admitting students with scores below, or at the lower end of, the International English Language Testing System ('IELTS') score considered acceptable. Alternatively, they were relying upon their own language testing admission standards and not on an independent test like the IELTS test. While the universities provided English language support services for their international students after they had been admitted, the Ombudsman was concerned that the universities 'have not dedicated sufficient resources to meet the level of need amongst international students'.

Making mentoring explicit : articulating pedogogical knowledge practices

Mentoring pedagogical knowledge is fundamental towards developing preservice teachers’ practices. As a result of a train-the-trainer mentoring program, this study aimed to understand how mentors’ engagement in a professional development program on mentoring contributes to their mentoring of pedagogical knowledge practices. This qualitative research analyses the mentoring of pedagogical knowledge from six paired mentor teachers and preservice teachers (n=12) after a four-week professional school experience. Findings indicated the train-the-trainer model was successful for mentoring pedagogical knowledge on 10 of the 11 advocated practices. This suggested that a well-constructed professional development program on mentoring can advance the quality of mentoring for enhancing preservice teachers’ practices.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Methodological issues in defining aggression for content analyses of sexually explicit material

There exists an important tradition of content analyses of aggression in sexually explicit material. The majority of these analyses use a definition of aggression that excludes consent. This article identifies three problems with this approach. First, it does not distinguish between aggression and some positive acts. Second, it excludes a key element of healthy sexuality. Third, it can lead to heteronormative definitions of healthy sexuality. It would be better to use a definition of aggression such as Baron and Richardson's (1994) in our content analyses, that includes a consideration of consent. A number of difficulties have been identified with attending to consent but this article offers solutions to each of these.

Making the implicit explicit : successful student skills for commencing cohorts

Making institutional expectations explicit using clear and common language engages commencing students and promotes help-seeking behaviour. When first year students enter university they cross the threshold into an unfamiliar environment (Devlin, Kift, Nelson, Smith & McKay, 2012). Universities endeavour to provide appropriate learning support services and resources; however research suggests that there is limited up take of these services, particularly in high risk students (Nelson-Field & Goodman, 2005). The Successful Student Skills Checklist is a tool which will be trialled during the 2013 Orientation period at the QUT Caboolture campus. The new tool is a response to the university’s commitment to provide “an environment where [students] are supported to take responsibility for their own learning, and to embrace an active role in succeeding to their full potential” (QUT, 2012, 6.2.1). This paper will outline the design of the support tool implemented during Orientation, as well as discuss the anticipated outcomes of the trial.