The cooling steam of the Polar Express : historical origins, properties and implications of performance capture

As the first academically rigorous interrogation of the generation of performance within the global frame of the motion capture volume, this research presents a historical contextualisation and develops and tests a set of first principles through an original series of theoretically informed, practical exercises to guide those working in the emergent space of performance capture. It contributes a new understanding of the framing of performance in The Omniscient Frame, and initiates and positions performance capture as a new and distinct interdisciplinary discourse in the fields of theatre, animation, performance studies and film.

Management of a high grade pan stage schedule to reduce the steam consumption

MOST PAN stages in Australian factories use only five or six batch pans for the high grade massecuite production and operate these in a fairly rigid repeating production schedule. It is common that some of the pans are of large dropping capacity e.g. 150 to 240 t. Because of the relatively small number and large sizes of the pans, steam consumption varies widely through the schedule, often by ±30% about the mean value. Large fluctuations in steam consumption have implications for the steam generation/condensate management of the factory and the evaporators when bleed vapour is used. One of the objectives of a project to develop a supervisory control system for a pan stage is to (a) reduce the average steam consumption and (b) reduce the variation in the steam consumption. The operation of each of the high grade pans within the schedule at Macknade Mill was analysed to determine the idle (or buffer) time, time allocations for essential but unproductive operations (e.g. pan turn round, charging, slow ramping up of steam rates on pan start etc.), and productive time i.e. the time during boil-on of liquor and molasses feed. Empirical models were developed for each high grade pan on the stage to define the interdependence of the production rate and the evaporation rate for the different phases of each pan’s cycle. The data were analysed in a spreadsheet model to try to reduce and smooth the total steam consumption. This paper reports on the methodology developed in the model and the results of the investigations for the pan stage at Macknade Mill. It was found that the operation of the schedule severely restricted the ability to reduce the average steam consumption and smooth the steam flows. While longer cycle times provide increased flexibility the steam consumption profile was changed only slightly. The ability to cut massecuite on the run among pans, or the use of a high grade seed vessel, would assist in reducing the average steam consumption and the magnitude of the variations in steam flow.

A test rig for the condition-based maintenance application on the traction chain of very high speed trains

The preventive maintenance of traction equipment for Very High Speed Trains (VHST) nowadays is becoming very expensive owing to the high complexity and quality of these components that require high reliability. An efficient maintenance approach like the Condition-Based Maintenance (CBM) should be implemented to reduce the costs. For this purpose, an experimental full-scale test rig for the CBM of VHST traction equipment has been designed to investigate in detail failures in the main mechanical components of system, i.e. motor, bearings and gearbox. The paper describes the main characteristics of this unique test rig, able to reproduce accurately the train operating conditions, including the relative movements of the motor, the gearbox and the wheel axle. Gearbox, bearing seats and motor are equipped by accelerometers, thermocouples, torque meter and other sensors in different positions. The testing results give important information about the most suitable sensor position and type to be installed for each component and show the effectiveness of the techniques used for the signal analysis in order to identify faults of the gearbox and motor bearings.

Diagnostics of rolling element bearings for the traction system of high speed trains : experimental evidences

Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

Unbalance identification in large steam turbo-generator unit using a model-based method

Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

Cost efficiency of Japanese steam power generation companies : a Bayesian comparison of random and fixed frontier models

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

Regulation, pollution and heterogeneity in Japanese steam power generation companies

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese steam power generation companies taking into regulation and pollution. The companies are ranked according to their productivity for the period 1976-2003 and homogenous and heterogeneous variables in the cost function are disentangled. Policy implication is derived.

Technology-mediated tools for shaping experiences in urban commuter trains

This thesis presents the results of a study into ways that technology can be appropriated and designed to support urban rail commuters in their daily journeys. The study evaluated a mobile application prototype deployed along the Brisbane passenger rail network. This prototype was designed to support social interaction between passengers sharing the same trains. This thesis provides a step forward in showing the relevance of increasingly creating solutions that contribute to a more enjoyable and attractive public transport service.

TrainYarn: Probing perceptions of social space in urban commuter trains

We studied the ways that urban commuter train passengers experience their journeys. We present the design process and in-situ evaluation of TrainYarn, a mobile app prototype designed to facilitate social interaction between co-located urban train passengers. Through the deployment of the prototype, we sought to probe perceptions of social space with a view to positively impact the assessment of public transport. Our results support that our target users saw value in the use of TrainYarn, perceiving it as emancipatory, in alignment with their communicative needs, and having the ability to transform their perceptions of social space. To further inform future research and practice, we put forward a series of design recommendations.

The potential benefits of divergent thinking and metacognitive skills in STEAM learning: A discussion paper

In the wake of an almost decade long economic downturn and increasing competition from developing economies, a new agenda in the Australian Government for science, technology, engineering, and mathematics (STEM) education and research has emerged as a national priority. However, to art and design educators, the pervasiveness and apparent exclusivity of STEM can be viewed as another instance of art and design education being relegated to the margins of curriculum (Greene, 1995). In the spirit of interdisciplinarity, there have been some recent calls to expand STEM education to include the arts and design, transforming STEM into STEAM in education (Maeda, 2013). As with STEM, STEAM education emphasises the connections between previously disparate disciplines, meaning that education has been conceptualised in different ways, such as focusing on the creative design thinking process that is fundamental to engineering and art (Bequette & Bequette, 2012). In this article, we discuss divergent creative design thinking process and metacognitive skills, how, and why they may enhance learning in STEM and STEAM.

Pilot-scale cellulosic ethanol production using eucalyptus biomass pre-treated by dilute acid and steam explosion

The widespread deployment of commercial-scale cellulosic ethanol currently hinges on developing and evaluating scalable processes whilst broadening feedstock options. This study investigates whole Eucalyptus grandis trees as a potential feedstock and demonstrates dilute acid pre-treatment (with steam explosion) followed by pre-saccharification simultaneous saccharification fermentation process (PSSF) as a suitable, scalable strategy for the production of bioethanol. Biomass was pre-treated in dilute H2SO4 at laboratory scale (0.1 kg) and pilot scale (10 kg) to evaluate the effect of combined severity factor (CSF) on pre-treatment effectiveness. Subsequently, pilot-scale pre-treated residues (15 wt.%) were converted to ethanol in a PSSF process at 2 L and 300 L scales. Good polynomial correlations (n = 2) of CSF with hemicellulose removal and glucan digestibility with a minimum R2 of 0.91 were recorded. The laboratory-scale 72 h glucan digestibility and glucose yield was 68.0% and 51.3%, respectively, from biomass pre-treated at 190 °C /15 min/ 4.8 wt.% H2SO4. Pilot-scale pre-treatment (180 °C/ 15 min/2.4 wt.% H2SO4 followed by steam explosion) delivered higher glucan digestibility (71.8%) and glucose yield (63.6%). However, the ethanol yields using PSSF were calculated at 82.5 and 113 kg/ton of dry biomass for the pilot and the laboratory scales, respectively. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

Sounds of the suburb

Sounds of the Suburb was a commissioned public art proposal based upon a brief set by Queensland Rail for the major redevelopment at their Brunswick Street Railway Station, Fortitude Valley, Brisbane. I proposed a large scale, electronic artwork to be distributed across the glass fronted structure of their station’s new concourse building. It was designed as a network of LED based ‘tracking’ - along which would travel electronically animated, ‘trains’ of text synchronised to the actual train timetables. Each message packet moved endlessly through a complex spatial network of ‘tracks’ and ‘stations’ set both inside, outside and via the concourse. The design was underpinned by large scale image of sound waves etched onto the architecture’s glass and was accompanied by two inset monitors each presenting ghosted images of passenger movements within the concourse, time-delay recorded and then cross-combined in realtime to form new composites.----- Each moving, reprogrammable phrase was conceived as a ‘train of thought’ and ostensibly contained an idea or concept about popular cultures surrounding contemporary music – thereby meeting the brief that the work should speak to the diverse musical cultures central to Fortitude Valley’s image as an entertainment hub. These cultural ‘memes’, gathered from both passengers and the music press were situated alongside quotes from philosophies of networking, speed and digital ecologies. These texts would continually propagate, replicate and cross fertlise as they moved throughout the ‘network’, thereby writing a constantly evolving ‘textual soundcape’ of that place. This idea was further cemented through the pace, scale and rhythm of passenger movements continually recorded and re-presented on the smaller screens.

Search engine content analysis

Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.