Fire Tests of Cold-formed Steel Wall Systems

Cold-formed steel stud walls are an important component of Light Steel Framing (LSF) building systems used in commercial, industrial and residential buildings. In the conventional LSF stud wall systems, thin-walled steel studs are protected from fire by placing one or two layers of plasterboard on both sides with or without cavity insulation. However, there is very limited data about the structural and thermal performance of these wall systems while past research showed contradicting results about the benefits of cavity insulation. This research proposed a new LSF stud wall system in which a composite panel made of two plasterboards with insulation between them was used to improve the fire rating of walls. Full scale fire tests were conducted using both conventional steel stud walls with and without the use of cavity insulation and the new composite panel system. Eleven full scale load bearing wall specimens were tested to study the thermal and structural performances of the load bearing wall assemblies under standard fire conditions. These tests showed that the use of cavity insulation led to inferior fire performance of walls while also providing good explanations and supporting test data to overcome the incorrect industry assumptions about cavity insulation. Tests demonstrated that the use of external insulation in a composite panel form enhanced the thermal and structural performances of stud walls and increased their fire resistance rating significantly. This paper presents the details of the full scale fire tests of load-bearing wall assemblies lined with plasterboards and different types of insulation under varying load ratios. Test results including the temperature and deflection profiles of walls measured during the fire tests will be presented along with their failure modes and failure times.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Experimental studies of non-load bearing steel wall systems under fire conditions

Fire safety of buildings has been recognised as very important by the building industry and the community at large. Traditionally, increased fire rating is provided by simply adding more plasterboards to light gauge steel frame (LSF) walls, which is inefficient. Many research studies have been undertaken to investigate the thermal behaviour of traditional LSF stud wall systems under standard fire conditions. However, no research has been undertaken on the thermal behaviour of LSF stud walls using the recently proposed composite panel. Extensive fire testing of both non-load bearing and load bearing wall panels was conducted in this research based on the standard time-temperature curve in AS1530.4. Three groups of LSF wall specimens were tested with no insulation, cavity insulation and the new composite panel based on an external insulation layer between plasterboards. This paper presents the details of this experimental study into the thermal performance of non-load bearing walls lined with various configurations of plasterboard and insulation. Extensive descriptive and numerical results of the tested non-load bearing wall panels given in this paper provide a thorough understanding of their thermal behaviour, and valuable time-temperature data that can be used to validate numerical models. Test results showed that the innovative composite stud wall systems outperformed the traditional stud wall systems in terms of their thermal performance, giving a much higher fire rating.

A 3D collision avoidance strategy for UAVs in a non-cooperative environment

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs.

Nonlinear H_infinity control of UAVs for collision avoidance in gusty environments

This paper proposes a nonlinear H_infinity controller for stabilization of velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in a windy environment. The suggested controller aims to achieve a steady-state flight condition in the presence of wind gusts such that the host UAV can be maneuvered to avoid collision with other UAVs during cruise flight with safety guarantees. This paper begins with building a proper model capturing flight aerodynamics of UAVs. Then a nonlinear controller is developed with gust attenuation and rapid response properties. Simulations are conducted for the Shadow UAV to verify performance of the proposed con- troller. Comparative studies with the proportional-integral-derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight of UAVs.

Hand-held monocular SLAM in thermal-infrared

Thermal-infrared imagery is relatively robust to many of the failure conditions of visual and laser-based SLAM systems, such as fog, dust and smoke. The ability to use thermal-infrared video for localization is therefore highly appealing for many applications. However, operating in thermal-infrared is beyond the capacity of existing SLAM implementations. This paper presents the first known monocular SLAM system designed and tested for hand-held use in the thermal-infrared modality. The implementation includes a flexible feature detection layer able to achieve robust feature tracking in high-noise, low-texture thermal images. A novel approach for structure initialization is also presented. The system is robust to irregular motion and capable of handling the unique mechanical shutter interruptions common to thermal-infrared cameras. The evaluation demonstrates promising performance of the algorithm in several environments.

A Systems-level approach to building sustainable assessment cultures : moderation, quality task design and dependability of judgement

This paper considers the conditions that are necessary at system and local levels for teacher assessment to be valid, reliable and rigorous. With sustainable assessment cultures as a goal, the paper examines how education systems can support local level efforts for quality learning and dependable teacher assessment. This is achieved through discussion of relevant research and consideration of a case study involving an evaluation of a cross-sectoral approach to promoting confidence in school-based assessment in Queensland, Australia. Building on the reported case study, essential characteristics for developing sustainable assessment cultures are presented, including: leadership in learning; alignment of curriculum, pedagogy and assessment; the design of quality assessment tasks and accompanying standards, and evidence-based judgement and moderation. Taken together, these elements constitute a new framework for building assessment capabilities and promoting quality assurance.

Controlled emergency landing of an unpowered unmanned aerial system

The ability to perform autonomous emergency (forced) landings is one of the key technology enablers identified for UAS. This paper presents the flight test results of forced landings involving a UAS, in a controlled environment, and which was conducted to ascertain the performances of previously developed (and published) path planning and guidance algorithms. These novel 3-D nonlinear algorithms have been designed to control the vehicle in both the lateral and longitudinal planes of motion. These algorithms have hitherto been verified in simulation. A modified Boomerang 60 RC aircraft is used as the flight test platform, with associated onboard and ground support equipment sourced Off-the-Shelf or developed in-house at the Australian Research Centre for Aerospace Automation (ARCAA). HITL simulations were conducted prior to the flight tests and displayed good landing performance, however, due to certain identified interfacing errors, the flight results differed from that obtained in simulation. This paper details the lessons learnt and presents a plausible solution for the way forward.

Flight guardian: a common avionics architecture for collision avoidance and safe emergency landing for unmanned aerial systems

This paper presents an approach to derive requirements for an avionics architecture that provides onboard sense-and-avoid and autonomous emergency forced landing capabilities to a UAS. The approach is based on two design paradigms that (1) derive requirements analyzing the common functionality between these two functions to then derive requirements for sensors, computing capability, interfaces, etc. (2) consider the risk and safety mitigation associated with these functions to derive certification requirements for the system design. We propose to use the Aircraft Certification Matrix (ACM) approach to tailor the system Development Assurance Levels (DAL) and architecture requirements in accordance with acceptable risk criteria. This architecture is developed under the name “Flight Guardian”. Flight Guardian is an avionics architecture that integrates common sensory elements that are essential components of any UAS that is required to be dependable. The Flight Guardian concept is also applicable to conventionally piloted aircraft, where it will serve to reduce cockpit workload.

Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX.

Security constrained economic dispatch considering wind energy conversion systems

The available wind power is stochastic and requires appropriate tools in the OPF model for economic and reliable power system operation. This paper exhibit the OPF formulation with factors involved in the intermittency of wind power. Weibull distribution is adopted to find the stochastic wind speed and power distribution. The reserve requirement is evaluated based on the wind distribution and risk of under/over estimation of the wind power. In addition, the Wind Energy Conversion System (WECS) is represented by Doubly Fed Induction Generator (DFIG) based wind farms. The reactive power capability for DFIG based wind farm is also analyzed. The study is performed on IEEE-30 bus system with wind farm located at different buses and with different wind profiles. Also the reactive power capacity to be installed in the wind farm to maintain a satisfactory voltage profile under the various wind flow scenario is demonstrated.

Maintaining a cognitive map in darkness : the need to fuse boundary knowledge with path integration

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of Global Navigation Satellite Systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods, and compared with the decorrelation number and with the condition number which are currently used as the judging criterion to measure the correlation of ambiguity variance-covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations respectively, showing the potential for processing high dimension integer parameters in multi-GNSS environment.

Investigation of decision making issues in the use of current clinical information systems

Clinical information systems have become important tools in contemporary clinical patient care. However, there is a question of whether the current clinical information systems are able to effectively support clinicians in decision making processes. We conducted a survey to identify some of the decision making issues related to the use of existing clinical information systems. The survey was conducted among the end users of the cardiac surgery unit, quality and safety unit, intensive care unit and clinical costing unit at The Prince Charles Hospital (TPCH). Based on the survey results and reviewed literature, it was identified that support from the current information systems for decision-making is limited. Also, survey results showed that the majority of respondents considered lack in data integration to be one of the major issues followed by other issues such as limited access to various databases, lack of time and lack in efficient reporting and analysis tools. Furthermore, respondents pointed out that data quality is an issue and the three major data quality issues being faced are lack of data completeness, lack in consistency and lack in data accuracy. Conclusion: Current clinical information systems support for the decision-making processes in Cardiac Surgery in this institution is limited and this could be addressed by integrating isolated clinical information systems.