Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

Calibration of the electron volt spectrometer, a deep inelastic neutron scattering spectrometer at the ISIS pulsed neutron spallation source

The electron Volt Spectrometer (eVS) is an inverse geometry filter difference spectrometer that has been optimised to measure the single atom properties of condensed matter systems using a technique known as Neutron Compton Scattering (NCS) or Deep Inelastic Neutron Scattering (DINS). The spectrometer utilises the high flux of epithermal neutrons that are produced by the ISIS neutron spallation source enabling the direct measurement of atomic momentum distributions and ground state kinetic energies. In this paper the procedure that is used to calibrate the spectrometer is described. This includes details of the method used to determine detector positions and neutron flight path lengths as well as the determination of the instrument resolution. Examples of measurements on 3 different samples are shown, ZrH2, 4He and Sn which show the self-consistency of the calibration procedure.

Effect of CT electron density identification on Monte Carlo simulations of radiotherapeutic treatments

Introduction: The accurate identification of tissue electron densities is of great importance for Monte Carlo (MC) dose calculations. When converting patient CT data into a voxelised format suitable for MC simulations, however, it is common to simplify the assignment of electron densities so that the complex tissues existing in the human body are categorized into a few basic types. This study examines the effects that the assignment of tissue types and the calculation of densities can have on the results of MC simulations, for the particular case of a Siemen’s Sensation 4 CT scanner located in a radiotherapy centre where QA measurements are routinely made using 11 tissue types (plus air). Methods: DOSXYZnrc phantoms are generated from CT data, using the CTCREATE user code, with the relationship between Hounsfield units (HU) and density determined via linear interpolation between a series of specified points on the ‘CT-density ramp’ (see Figure 1(a)). Tissue types are assigned according to HU ranges. Each voxel in the DOSXYZnrc phantom therefore has an electron density (electrons/cm3) defined by the product of the mass density (from the HU conversion) and the intrinsic electron density (electrons /gram) (from the material assignment), in that voxel. In this study, we consider the problems of density conversion and material identification separately: the CT-density ramp is simplified by decreasing the number of points which define it from 12 down to 8, 3 and 2; and the material-type-assignment is varied by defining the materials which comprise our test phantom (a Supertech head) as two tissues and bone, two plastics and bone, water only and (as an extreme case) lead only. The effect of these parameters on radiological thickness maps derived from simulated portal images is investigated. Results & Discussion: Increasing the degree of simplification of the CT-density ramp results in an increasing effect on the resulting radiological thickness calculated for the Supertech head phantom. For instance, defining the CT-density ramp using 8 points, instead of 12, results in a maximum radiological thickness change of 0.2 cm, whereas defining the CT-density ramp using only 2 points results in a maximum radiological thickness change of 11.2 cm. Changing the definition of the materials comprising the phantom between water and plastic and tissue results in millimetre-scale changes to the resulting radiological thickness. When the entire phantom is defined as lead, this alteration changes the calculated radiological thickness by a maximum of 9.7 cm. Evidently, the simplification of the CT-density ramp has a greater effect on the resulting radiological thickness map than does the alteration of the assignment of tissue types. Conclusions: It is possible to alter the definitions of the tissue types comprising the phantom (or patient) without substantially altering the results of simulated portal images. However, these images are very sensitive to the accurate identification of the HU-density relationship. When converting data from a patient’s CT into a MC simulation phantom, therefore, all possible care should be taken to accurately reproduce the conversion between HU and mass density, for the specific CT scanner used. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital (RBWH), Brisbane, Australia. The authors are grateful to the staff of the RBWH, especially Darren Cassidy, for assistance in obtaining the phantom CT data used in this study. The authors also wish to thank Cathy Hargrave, of QUT, for assistance in formatting the CT data, using the Pinnacle TPS. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.

Calibration of the electron volt spectrometer, a deep inelastic neutron scattering spectrometer at the ISIS pulsed neutron spallation source

The electron Volt Spectrometer (eVS) is an inverse geometry filter difference spectrometer that has been optimised to measure the single atom properties of condensed matter systems using a technique known as Neutron Compton Scattering (NCS) or Deep Inelastic Neutron Scattering (DINS). The spectrometer utilises the high flux of epithermal neutrons that are produced by the ISIS neutron spallation source enabling the direct measurement of atomic momentum distributions and ground state kinetic energies. In this paper the procedure that is used to calibrate the spectrometer is described. This includes details of the method used to determine detector positions and neutron flight path lengths as well as the determination of the instrument resolution. Examples of measurements on 3 different samples are shown, ZrH2, 4He and Sn which show the self-consistency of the calibration procedure.

Effects of free flow state highway traffic parameters on the performance of amplify and forward cooperative multi-hop vehicular networks

In this paper we analyse the effects of highway traffic flow parameters like vehicle arrival rate and density on the performance of Amplify and Forward (AF) cooperative vehicular networks along a multi-lane highway under free flow state. We derive analytical expressions for connectivity performance and verify them with Monte-Carlo simulations. When AF cooperative relaying is employed together with Maximum Ratio Combining (MRC) at the receivers the average route error rate shows 10-20 fold improvement compared to direct communication. A 4-8 fold increase in maximum number of traversable hops can also be observed at different vehicle densities when AF cooperative communication is used to strengthen communication routes. However the theorical upper bound of maximum number of hops promises higher performance gains.

Property case competition : multi-stakeholder reflection

Pacific Rim Real Estate Society has conducted four property case competitions from 2009 to 2012. The competition provides opportunities for undergraduate students to present their proposal on a given case study. All students were locked down with their four team members for five hours without external help to ensure a level playing field across participants. Students prepared their presentation and defended their arguments in front of experts in property industry and academia. The aim of this paper is reflecting on the feedback received from stakeholders involved in the case competition. Besides exploring what students have gained from the competitions, this paper provides an insight on the opportunities and challenges for the new format of competition to be introduced in 2013. Over the last four competitions, there were three universities participated in all the four consecutive events, four universities partook in two events and another four universities only competed once. Some universities had a great advantage by having previous experiences by participating in similar international business competitions. Findings show that the students have benefited greatly from the event including improving their ability in problem solving and other non-technical skills. Despite the aforementioned benefits, the PRRES closed-book case competition is proven not viable thus future competition needs to minimise the travel and logistic cost.

Classifier selection using sequential error ratio criterion for multi-instance and multi-sample fusion

Classifier selection is a problem encountered by multi-biometric systems that aim to improve performance through fusion of decisions. A particular decision fusion architecture that combines multiple instances (n classifiers) and multiple samples (m attempts at each classifier) has been proposed in previous work to achieve controlled trade-off between false alarms and false rejects. Although analysis on text-dependent speaker verification has demonstrated better performance for fusion of decisions with favourable dependence compared to statistically independent decisions, the performance is not always optimal. Given a pool of instances, best performance with this architecture is obtained for certain combination of instances. Heuristic rules and diversity measures have been commonly used for classifier selection but it is shown that optimal performance is achieved for the `best combination performance' rule. As the search complexity for this rule increases exponentially with the addition of classifiers, a measure - the sequential error ratio (SER) - is proposed in this work that is specifically adapted to the characteristics of sequential fusion architecture. The proposed measure can be used to select a classifier that is most likely to produce a correct decision at each stage. Error rates for fusion of text-dependent HMM based speaker models using SER are compared with other classifier selection methodologies. SER is shown to achieve near optimal performance for sequential fusion of multiple instances with or without the use of multiple samples. The methodology applies to multiple speech utterances for telephone or internet based access control and to other systems such as multiple finger print and multiple handwriting sample based identity verification systems.

Predicate encryption for multi-inner-products

Predicate encryption is a new primitive that supports flexible control over access to encrypted data. We study predicate encryption systems, evaluating a wide class of predicates. Our systems are more expressive than the existing attribute-hiding systems in the sense that the proposed constructions support not only all existing predicate evaluations but also arbitrary conjunctions and disjunctions of comparison and subset queries. Toward our goal, we propose encryption schemes supporting multi-inner-product predicate and provide formal security analysis. We show how to apply the proposed schemes to achieve all those predicate evaluations.

Development of the palliative care needs assessment tool (PC-NAT) for use by multi-disciplinary health professionals

Needs assessment strategies can facilitate prioritisation of resources. To develop a needs assessment tool for use with advanced cancer patients and caregivers, to prompt early intervation. A convenience sample of 103 health professionals viewed three videotaped consultations involving a simulated patient, his/her caregiver and a health professional, completed the Palliative Care Needs Assessment Tool (PC-NAT) and provided feedback on clarity, content and acceptability of the PC-NAT. Face and content validity, acceptability and feasibility of the PC-NAT were confirmed. Kappa scores indicated adequate inter-rater reliability for the majority of domains; the patient spirituality domain and the caregiver physical and family and relationship domains had low reliability. The PC-NAT can be used by health professionals with a range of clinical expertise to identify individuals' needs, thereby enabling early intervention. Further psychometric testing and an evaluation to assess the impact of the systematic use of the PC-NAT on quality of life, unmet needs and service utilisation of patients and caregivers are underway.

CubIT : Large-scale multi-user presentation and collaboration

CubIT is a multi-user, large-scale presentation and collaboration framework installed at the Queensland University of Technology’s (QUT) Cube facility, an interactive facility made up 48 multi-touch screens and very large projected display screens. CubIT was built to make the Cube facility accessible to QUT’s academic and student population. The system allows users to upload, interact with and share media content on the Cube’s very large display surfaces. CubIT implements a unique combination of features including RFID authentication, content management through multiple interfaces, multi-user shared workspace support, drag and drop upload and sharing, dynamic state control between different parts of the system and execution and synchronisation of the system across multiple computing nodes.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.

Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

In situ observation of structural changes in polycrystalline silver catalysts by environmental scanning electron microscopy

Morphology changes induced in polycrystalline silver catalysts as a result of heating in either oxygen, water or oxygen-methanol atmospheres have been investigated by environmental scanning electron microscopy (ESEM), FT-Raman spectroscopy and temperature programmed desorption (TPD). The silver catalyst of interest consisted of two distinct particle types, one of which contained a significant concentration of sub-surface hydroxy species (in addition to surface adsorbed atomic oxygen). Heating the sample to 663 K resulted in the production of 'pin-holes' in the silver structure as a consequence of near-surface explosions caused by sub-surface hydroxy recombination. Furthermore, 'pin-holes' were predominantly found in the vicinity of surface defects, such as platelets and edge structures. Reaction between methanol and oxygen also resulted in the formation of 'pin-holes' in the silver surface, which were inherently associated with the catalytic process. A reaction mechanism is suggested that involves the interaction of methanol with sub-surface oxygen species to form sub-surface hydroxy groups. The sub-surface hydroxy species subsequently erupt through the silver surface to again produce 'pin-holes'.

A combined environmental scanning electron microscopy and Raman microscopy study of methanol oxidation on silver(I) oxide

The techniques of environmental scanning electron microscopy (ESEM) and Raman microscopy have been used to respectively elucidate the morphological changes and nature of the adsorbed species on silver(I) oxide powder, during methanol oxidation conditions. Heating Ag2O in either water vapour or oxygen resulted firstly in the decomposition of silver(I) oxide to polycrystalline silver at 578 K followed by sintering of the particles at higher temperature. Raman spectroscopy revealed the presence of subsurface oxygen and hydroxyl species in addition to surface hydroxyl groups after interaction with water vapour. Similar species were identified following exposure to oxygen in an ambient atmosphere. This behaviour indicated that the polycrystalline silver formed from Ag2O decomposition was substantially more reactive than silver produced by electrochemical methods. The interaction of water at elevated temperatures subsequent to heating silver(I) oxide in oxygen resulted in a significantly enhanced concentration of subsurface hydroxyl species. The reaction of methanol with Ag2O at high temperatures was interesting in that an inhibition in silver grain growth was noted. Substantial structural modification of the silver(I) oxide material was induced by catalytic etching in a methanol/air mixture. In particular, "pin-hole" formation was observed to occur at temperatures in excess of 773 K, and it was also recorded that these "pin- holes" coalesced to form large-scale defects under typical industrial reaction conditions. Raman spectroscopy revealed that the working surface consisted mainly of subsurface oxygen and surface Ag=O species. The relative lack of sub-surface hydroxyl species suggested that it was the desorption of such moieties which was the cause of the "pin-hole" formation.