Buckling experiments on hollow flange beams with web stiffeners

The hollow flange beam (HFB) is a new cold-formed and resistance-welded section developed in Australia. Due to its unique geometry comprising two stiff triangular flanges and a slender web, the HFB is susceptible to a lateral-distortional buckling mode of failure involving web distortion. Investigation using finite-element analyses showed that the use of transverse web plate stiffeners effectively eliminated lateral-distortional buckling of HFBs and thus any associated reduction in flexural capacity. A detailed experimental investigation was then carried out to validate the results from the finite-element analysis and to improve the stiffener configuration further. This led to the development of a special stiffener that is screw-fastened to the flanges on alternate sides of the web. This paper presents the details of the experimental investigations, the results, and the final stiffener arrangement whereas the details of the finite-element analyses are presented in a companion paper.

The construction of social identity in new nuclear operators : a longitudinal study

Countless studies have stressed the importance of social identity, particularly its role in various organizational outcomes, yet questions remain as to how identities initially develop, shift and change based on the configuration of multiple, pluralistic relationships grounded in an organizational setting. The interactive model of social identity formation has been proposed recently to explain the internalization of shared norms and values – critical in identity formation – has not received empirical examination. We analyzed multiple sources of data from nine nuclear professionals over three years to understand the construction of social identity in new entrants entering an organization. Informed by our data analyses, we found support for the interactive model and that age and level of experience influenced whether they undertook an inductive or deductive route of the group norm and value internalization. This study represents an important contribution to the study of social identity and the process by which identities are formed, particularly under conditions of duress or significant organizational disruption.

Made by motion, Series one

“Made by Motion” is a collaboration between digital artist Paul Van Opdenbosch and performer and choreographer Elise May; a series of studies on captured motion data used to generating experimental visual forms that reverberate in space and time. The project investigates the invisible forces generated by and influencing the movement of a dancer. Along with how the forces can be captured and applied to generating visual outcomes that surpass simple data visualisation, projecting the intent of the performer’s movements. The source or ‘seed’ comes from using an Xsens MVN - Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. In this first series the visual investigation focused on manipulating the movement date at the instance of capture, capture been the recording of three-dimensional movement as ‘seen’ by the hardware and ‘understood’ through the calibration of software. By repositioning the capture hardware on the body we can effectively change how the same sequence of movements is ‘seen’ by the motion capture system thus generating a different visual result from effetely identical movement. The outcomes from the experiments clearly demonstrates the effectiveness of using motion capture hardware as a creative tool to manipulate the perception of the capture subject, in this case been a sequence of dance movements. The creative work exhibited is a cross-section of the experiments conducted in practice with the first animated work (Movement A - Control) using the motion capture hardware in its default ‘normal’ configuration. Following this is the lower body moved to the upper body (Lb-Ub), right arm moved onto the left arm (Ra-La), right leg moved onto the left leg (Rl-Ll) and finally the left leg moved onto a object that is then held in the left hand (Ll-Pf (Lh)).

On parallel hybrid-electric propulsion system for unmanned aerial vehicles

This paper presents a review of existing and current developments and the analysis of Hybrid-Electric Propulsion Systems (HEPS) for small fixed-wing Unmanned Aerial Vehicles (UAVs). Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. One technology with potential in this area is with the use of HEPS. In this paper, information on the state-of-art technology in this field of research is provided. A description and simulation of a parallel HEPS for a small fixed-wing UAV by incorporating an Ideal Operating Line (IOL) control strategy is described. Simulation models of the components in a HEPS were designed in the MATLAB Simulink environment. An IOL analysis of an UAV piston engine was used to determine the most efficient points of operation for this engine. The results show that an UAV equipped with this HEPS configuration is capable of achieving a fuel saving of 6.5%, compared to the engine-only configuration.

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Design of physiological control and magnetic levitation systems for a total artificial heart

Total Artificial Hearts are mechanical pumps which can be used to replace the failing natural heart. This novel study developed a means of controlling a new design of pump to reproduce physiological flow bringing closer the realisation of a practical artificial heart. Using a mathematical model of the device, an optimisation algorithm was used to determine the best configuration for the magnetic levitation system of the pump. The prototype device was constructed and tested in a mock circulation loop. A physiological controller was designed to replicate the Frank-Starling like balancing behaviour of the natural heart. The device and controller provided sufficient support for a human patient while also demonstrating good response to various physiological conditions and events. This novel work brings the design of a practical artificial heart closer to realisation.

A methodology for estimating exposure-controlled crash risk using traffic Police crash data

Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

A novel energy efficient controllable stiffness joint

Achieving energy efficient legged locomotion is an important goal for the future of robot mobility. This paper presents a novel joint for legged locomotion that is energy efficient for two reasons. The first reason is the configuration of the elastic elements and actuator which we show analytically has lower energy losses than the typical arrangement. The second is that the joint stiffness, and hence stance duration, is controllable without requiring any energy from the actuator. Further, the joint stiffness can be changed significantly during the flight phase, from zero to highly rigid. Results obtained from a prototype hopper, demonstrate that the joint allows continuous and peak hopping via torque control. The results also demonstrate that the hopping frequency can be varied between 2.2Hz and 4.6Hz with associated stance duration of between 0.35 and 0.15 seconds.

FRC erection stages dynamic behaviour under wind loads

Buffeting response of a cable-stayed bridge under construction is investigated through wind tunnel tests and numerical simulations. Two configurations of the erection stage have been considered and compared in terms of dynamic response and internal forces using the results of the experimental aeroelastic models. Moreover the results of a numerical model able to simulate the simultaneous effects of vortex shedding from tower and aeroelastic response of the deck are compared to the wind tunnel ones.

Predicting the fatigue life of internal fracture fixation plates

Failures of fracture fixation plates, often related to fatigue fractures of the implants, have been reported (Banovetz et al, 1996). While metallurgical defects can usually be excluded, many of these fractures can be explained with the biomechanical situation. This study investigated the biomechanics of two clinical cases, both of which used a 14-hole locking compression plate. In the first case, a titanium plate was used in a rigid configuration with 12 screws resulting in plate breakage after 7 weeks (Sommer et al, 2003). In the second case, a stainless steel plate, which endured the entire healing process, was used in a flexible application with only 6 screws.

Firmicutes dominate the bacterial taxa within sugar-cane processing plants

Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Significant variation (p , 0.05) in community structure occurred between samples collected from ‘floor dump sediment’, ‘cooling tower water’, and ‘bagasse leachate’. Many bacterial Classes contributed to these differences, however most were of low numerical abundance. Separation in community composition was also linked to Classes of Firmicutes, particularly Bacillales, Lactobacillales and Clostridiales, whose dominance is likely to be linked to their physiology as ‘lactic acid bacteria’, capable of fermenting the sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Selection et controle de modes de deplacement pour un robot mobile autonome en environnements naturels

Autonomous navigation and locomotion of a mobile robot in natural environments remain a rather open issue. Several functionalities are required to complete the usual perception/decision/action cycle. They can be divided in two main categories : navigation (perception and decision about the movement) and locomotion (movement execution). In order to be able to face the large range of possible situations in natural environments, it is essential to make use of various kinds of complementary functionalities, defining various navigation and locomotion modes. Indeed, a number of navigation and locomotion approaches have been proposed in the literature for the last years, but none can pretend being able to achieve autonomous navigation and locomotion in every situation. Thus, it seems relevant to endow an outdoor mobile robot with several complementary navigation and locomotion modes. Accordingly, the robot must also have means to select the most appropriate mode to apply. This thesis proposes the development of such a navigation/locomotion mode selection system, based on two types of data: an observation of the context to determine in what kind of situation the robot has to achieve its movement and an evaluation of the behavior of the current mode, made by monitors which influence the transitions towards other modes when the behavior of the current one is considered as non satisfying. Hence, this document introduces a probabilistic framework for the estimation of the mode to be applied, some navigation and locomotion modes used, a qualitative terrain representation method (based on the evaluation of a difficulty computed from the placement of the robot's structure on a digital elevation map), and monitors that check the behavior of the modes used (evaluation of rolling locomotion efficiency, robot's attitude and configuration watching. . .). Some experimental results obtained with those elements integrated on board two different outdoor robots are presented and discussed.

A near-to-far non-parametric learning approach for estimating traversability in deformable terrain

It is well recognized that many scientifically interesting sites on Mars are located in rough terrains. Therefore, to enable safe autonomous operation of a planetary rover during exploration, the ability to accurately estimate terrain traversability is critical. In particular, this estimate needs to account for terrain deformation, which significantly affects the vehicle attitude and configuration. This paper presents an approach to estimate vehicle configuration, as a measure of traversability, in deformable terrain by learning the correlation between exteroceptive and proprioceptive information in experiments. We first perform traversability estimation with rigid terrain assumptions, then correlate the output with experienced vehicle configuration and terrain deformation using a multi-task Gaussian Process (GP) framework. Experimental validation of the proposed approach was performed on a prototype planetary rover and the vehicle attitude and configuration estimate was compared with state-of-the-art techniques. We demonstrate the ability of the approach to accurately estimate traversability with uncertainty in deformable terrain.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.