Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.

Reconstructing the event stratigraphy from the complex structural - stratigraphic architecture of an Archaean volcanic – intrusive – sedimentary succession : the Boorara Domain, Eastern Goldfields Superterrane, Western Australia

Two main deformational phases are recognised in the Archaean Boorara Domain of the Kalgoorlie Terrane, Eastern Goldfields Superterrane, Yilgarn Craton, Western Australia, primarily involving southover- north thrust faulting that repeated and thickened the stratigraphy, followed by east northeast – west-southwest shortening that resulted in macroscale folding of the greenstone lithologies. The domain preserves mid-greenschist facies metamorphic grade, with an increase to lower amphibolite metamorphic grade towards the north of the region. As a result of the deformation and metamorphism, individual stratigraphic horizons are difficult to trace continuously throughout the entire domain. Volcanological and sedimentological textures and structures, primary lithological contacts, petrography and geochemistry have been used to correlate lithofacies between faultbounded structural blocks. The correlated stratigraphic sequence for the Boorara Domain comprises quartzo-feldspathic turbidite packages, overlain by high-Mg tholeiitic basalt (lower basalt), coherent and clastic dacite facies, intrusive and extrusive komatiite units, an overlying komatiitic basalt unit (upper basalt), and at the stratigraphic top of the sequence, volcaniclastic quartz-rich turbidites. Reconstruction of the stratigraphy and consideration of emplacement dynamics has allowed reconstruction of the emplacement history and setting of the preserved sequence. This involves a felsic, mafic and ultramafic magmatic system emplaced as high-level intrusions, with localised emergent volcanic centres, into a submarine basin in which active sedimentation was occurring.

Effective discrimination of acoustic emission source signals for structural health monitoring

Acoustic emission (AE) is the phenomenon where stress waves are generated due to rapid release of energy within a material caused by sources such as crack initiation or growth. AE technique involves recording the stress waves by means of sensors and subsequent analysis of the recorded signals to gather information about the nature of the source. Though AE technique is one of the popular non destructive evaluation (NDE) techniques for structural health monitoring of mechanical, aerospace and civil structures; several challenges still exist in successful application of this technique. Presence of spurious noise signals can mask genuine damage‐related AE signals; hence a major challenge identified is finding ways to discriminate signals from different sources. Analysis of parameters of recorded AE signals, comparison of amplitudes of AE wave modes and investigation of uniqueness of recorded AE signals have been mentioned as possible criteria for source differentiation. This paper reviews common approaches currently in use for source discrimination, particularly focusing on structural health monitoring of civil engineering structural components such as beams; and further investigates the applications of some of these methods by analyzing AE data from laboratory tests.

Assessment of “change in flexibility method” in structural health monitoring systems

The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

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.

Structural performance of reinforced concrete beams repairing from spalling

The effectiveness of a repair work for the restoration of spalled reinforced concrete (r.c.) structures depends to a great extent, on their ability to restore the structural integrity of the r.c. element, to restore its serviceability and to protect the reinforcements from further deterioration. This paper presents results of a study concocted to investigate the structural performance of eight spalled r.c. beams repaired using two advanced repair materials in various zones for comparison purposes, namely a free flowing self compacting mortar (FFSCM) and a polymer Modified cementitious mortar (PMCM). The repair technique adopted was that for the repair of spalled concrete in which the bond between the concrete and steel was completely lost due to reinforcement corrosion or the effect of fire or impact. The beams used for the experiment were first cast, then hacked at various zones before they were repaired except for the control beam. The beam specimens were then loaded to failure under four point loadings. The structural response of each beam was evaluated in terms of first crack load, cracking behavior, crack pattern, deflection, variation of strains in the concrete and steel, collapse load and the modes of failure. The results of the test showed that, the repair materials applied on the various zones of the beams were able to restore more than 100% of the beams’ capacity and that FFSCM gave a better overall performance.

Measurement of structural changes to a food material during dehydration

Rates of dehydration/rehydration are important quality parameters for dried products. Theoretically, if there are no adverse effects on the integrity of the tissue structure, it should absorb water to the same moisture content of the initial product before drying.The purpose of this work is to semi-automate the process of detection of cell structure boundaries as a food is dehydrated and rehydrated. This will enable food materials researchers to quantify changes to material’s structure as these processes take place. Images of potato cells as they were dehydrated and rehydrated were taken using an electron microscope. Cell boundaries were detected using an image processing algorithm. Average cell area and perimeter at each stage of dehydration were calculated and plotted versus time. The results show that the algorithm can successfully identify cell boundaries.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

Structural characterisation of kaolinite : NaCl intercalate and its derivatives

Kaolinite:NaCl intercalates with basal layer dimensions of 0.95 and 1.25 nm have been prepared by direct reaction of saturated aqueous NaCl solution with well-crystallized source clay KGa-1. The intercalates and their thermal decomposition products have been studied by XRD, solid-state 23Na, 27Al, and 29Si MAS NMR, and FTIR. Intercalate yield is enhanced by dry grinding of kaolinite with NaCl prior to intercalation. The layered structure survives dehydroxylation of the kaolinite at 500°–600°C and persists to above 800°C with a resultant tetrahedral aluminosilicate framework. Excess NaCl can be readily removed by rinsing with water, producing an XRD ‘amorphous’ material. Upon heating at 900°C this material converts to a well-crystallized framework aluminosilicate closely related to low-camegieite, NaAlSiO4, some 350°C below its stability field. Reaction mechanisms are discussed and structural models proposed for each of these novel materials.

Protein monoubiquitination and polyubiquitination generate structural diversity to control distinct biological processes

Ubiquitination involves the attachment of ubiquitin (Ub) to lysine residues on substrate proteins or itself, which can result in protein monoubiquitination or polyubiquitination. Polyubiquitination through different lysines (seven) or the N-terminus of Ub can generate different protein-Ub structures. These include monoubiquitinated proteins, polyubiqutinated proteins with homotypic chains through a particular lysine on Ub or mixed polyubiquitin chains generated by polymerization through different Ub lysines. The ability of the ubiquitination pathway to generate different protein-Ub structures provides versatility of this pathway to target proteins to different fates. Protein ubiquitination is catalyzed by Ub-conjugating and Ub-ligase enzymes, with different combinations of these enzymes specifying the type of Ub modification on protein substrates. How Ub-conjugating and Ub-ligase enzymes generate this structural diversity is not clearly understood. In the current review, we discuss mechanisms utilized by the Ub-conjugating and Ub-ligase enzymes to generate structural diversity during protein ubiquitination, with a focus on recent mechanistic insights into protein monoubiquitination and polyubiquitination.

Contribution of DEAF1 structural domains to the interaction with the breast cancer oncogene LMO4

The proteins LMO4 and DEAF1 contribute to the proliferation of mammary epithelial cells. During breast cancer LMO4 is upregulated, affecting its interaction with other protein partners. This may set cells on a path to tumour formation. LMO4 and DEAF1 interact, but it is unknown how they cooperate to regulate cell proliferation. In this study, we identify a specific LMO4-binding domain in DEAF1. This domain contains an unstructured region that directly contacts LMO4, and a coiled coil that contains the DEAF1 nuclear export signal (NES). The coiled coil region can form tetramers and has the typical properties of a coiled coil domain. Using a simple cell-based assay, we show that LMO4 modulates the activity of the DEAF NES, causing nuclear accumulation of a construct containing the LMO4-interaction region of DEAF1.

Socio-structural influences on the work participation of refugees : an exploratory systematic mixed studies review

This systematic mixed studies review aimed at synthesizing evidence from studies related to the influences on the work participation of people with refugee status (PWRS). The review focused on the role of proximal socio-structural barriers on work participation by PWRS while foregrounding related distal, intermediate, proximal, and meta-systemic influences. For the systematic search of the literature, we focused on databases that addressed work, well-being, and social policy in refugee populations, including, Medline, CINAHL, PsycInfo, Web of Science, Scopus, and Sociological Abstracts. Of the studies reviewed, 16 of 39 met the inclusion criteria and were retained for the final analysis. We performed a narrative synthesis of the evidence on barriers to work participation by PWRS, interlinking clusters of barriers potent to their effects on work participation. Findings from the narrative synthesis suggest that proximal factors, those at point of entry to the labor market, influence work participation more directly than distal or intermediate factors. Distal and intermediate factors achieve their effects on work participation by PWRS primarily through meta-systemic interlinkages, including host-country documentation and refugee administration provisions.

Reliable and valid survey design for structural equation modelling

My quantitative study asks how Chinese Australians’ “Chineseness” and their various resources influence their Chinese language proficiency, using online survey and snowball sampling. ‘Operationalization’ is a challenging process which ensures that the survey design talks back to the informing theory and forwards to the analysis model. It requires the attention to two core methodological concerns, namely ‘validity’ and ‘reliability’. Construction of a high-quality questionnaire is critical to the achievement of valid and reliable operationalization. A series of strategies were chosen to ensure the quality of the questions, and thus the eventual data. These strategies enable the use of structural equation modelling to examine how well the data fits the theoretical framework, which was constructed in light of Bourdieu’s theory of habitus, capital and field.

Molecular and structural requirements of the ß1L-adrenoceptor

Noradrenaline which occurs naturally in the body binds to beta-adrenoceptors on the heart, causing the heart to beat faster and with greater force in response to increased demand. This enables the heart to provide oxygenated blood to vital organs. Prolonged overstimulation by noradrenaline can be harmful to the heart and lead to the progression of heart disease. In these circumstances beta-adrenoceptors are blocked with drugs called beta-blockers. Beta-blockers block the effects of noradrenaline by binding to the same site on the beta-adrenoceptor. Some beta-blockers such as CGP12177 can also cause increases in heart rate. Therefore it was proposed that CGP12177 could bind in a different place to noradrenaline. The aim of this study was to determine where CGP12177 binds to on the beta-adrenoceptor. The results have revealed a separate binding site named beta-1-low. These results may lead to the development of improved -blockers for the management of heart conditions.