820 resultados para Piling (Civil engineering)


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Australia is a country, which has much of its legislative roots in its Commonwealth heritage. However due to its size and nature, its planning and development processes are more aligned to countries such as the United States. This paper will present an overview of the Australian urban land market, its infrastructure funding mechanisms (property taxes) and current provisions in each of Australia’s seven States and Territories that provide for developer contributions for local infrastructure (impact fees).

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Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

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Railroad corridors contain large number of Insulated Rail Joints (IRJs) that act as safety critical elements in the circuitries of the signaling and broken rail identification systems. IRJs are regarded as sources of excitation for the passage of loaded wheels leading to high impact forces; these forces in turn cause dips, cross levels and twists to the railroad geometry in close proximity to the sections containing the IRJs in addition to the local damages to the railhead of the IRJs. Therefore, a systematic monitoring of the IRJs in railroad is prudent to mitigate potential risk of their sudden failure (e.g., broken tie plates) under the traffic. This paper presents a simple method of periodic recording of images using time-lapse photography and total station surveying measurements to understand the ongoing deterioration of the IRJs and their surroundings. Over a 500 day period, data were collected to examine the trends in narrowing of the joint gap due to plastic deformation the railhead edges and the dips, cross levels and twists caused to the railroad geometry due to the settlement of ties (sleepers) around the IRJs. The results reflect that the average progressive settlement beneath the IRJs is larger than that under the continuously welded rail, which leads to excessive deviation of railroad profile, cross levels and twists.

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Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve given in ISO 834. However, modern residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the performance of load bearing LSF walls was undertaken using a series of realistic design fire curves developed based on Eurocode parametric curves and Barnett’s BFD curves. It included both full scale fire tests and numerical studies of LSF walls without any insulation, and the recently developed externally insulated composite panels. This paper presents the details of fire tests first, and then the numerical models of tested LSF wall studs. It shows that suitable finite element models can be developed to predict the fire rating of load bearing walls under real fire conditions. The paper also describes the structural and fire performances of externally insulated LSF walls in comparison to the non-insulated walls under real fires, and highlights the effects of standard and real fire curves on fire performance of LSF walls.

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The LiteSteel Beam (LSB) is a new hollow flange section developed in Australia with a unique geometry consisting of torsionally rigid rectangular hollow flanges and a relatively slender web. The LSB is subjected to a relatively new Lateral Distortional Buckling (LDB) mode when used as flexural members. Unlike the commonly observed lateral torsional buckling, lateral distortional buckling of LSBs is characterised by cross sectional change due to web distortion. Lateral distortional buckling causes significant moment capacity reduction for LSBs with intermediate spans. Therefore a detailed investigation was undertaken to determine the methods of reducing the effects of lateral distortional buckling in LSB flexural members. For this purpose the use of web stiffeners was investigated using finite element analyses of LSBs with different web stiffener spacing and sizes. It was found that the use of 5 mm steel plate stiffeners welded or screwed to the inner faces of the top and bottom flanges at third span points considerably reduced the lateral distortional buckling effects in LSBs. Suitable design rules were then developed to calculate the enhanced elastic lateral distortional buckling moments and the higher ultimate moment capacities of LSBs with the chosen web stiffener arrangement. This paper presents the details of this investigation and the results.

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For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academies from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.

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Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

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A firm, as a dynamic, evolving, and quasi-autonomous system of knowledge production and application, develops knowledge management capability (KMC) through strategic learning in order to sustain competitive advantages in a dynamic environment. Knowledge governance mechanisms and knowledge processes connect and interact with each other forming learning mechanisms, which carry out double loop learning that drives genesis and evolution of KMC to modify operating routines that effect desired performance. This paper reports a study that was carried out within a context of construction contractors, a type of project-based firms, operating within the dynamic Hong Kong construction market. A multiple-case design was used to incorporate evidence from the literature and interviews, with the help of system dynamics modeling, to visualize the evolution of KMC. The study demonstrates the feasibility to visualize how a firm's KMC matches its operating environment over time. The findings imply that knowledge management (KM) applications can be better planned and controlled through evaluation of KM performance over time from a capability perspective.

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The dynamic capabilities view (DCV) focuses on renewal of firms’ strategic knowledge resources so as to sustain competitive advantage within turbulent markets. Within the context of the DCV, the focus of knowledge management (KM) is to develop the KMC through deploying knowledge governance mechanisms that are conducive to facilitating knowledge processes so as to produce superior business performance over time. The essence of KM performance evaluation is to assess how well the KMC is configured with knowledge governance mechanisms and processes that enable a firm to achieve superior performance through matching its knowledge base with market needs. However, little research has been undertaken to evaluate KM performance from the DCV perspective. This study employed a survey study design and adopted hypothesis-testing approaches to develop a capability-based KM evaluation framework (CKMEF) that upholds the basic assertions of the DCV. Under the governance of the framework, a KM index (KMI) and a KM maturity model (KMMM) were derived not only to indicate the extent to which a firm’s KM implementations fulfill its strategic objectives, and to identify the evolutionary phase of its KMC, but also to bench-mark the KMC in the research population. The research design ensured that the evaluation framework and instruments have statistical significance and good generalizabilty to be applied in the research population, namely construction firms operating in the dynamic Hong Kong construction market. The study demonstrated the feasibility of quantitatively evaluating the development of the KMC and revealing the performance heterogeneity associated with the development.

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This paper reports the findings of an in-depth literature review, which was designed as the first phase of a study that ultimately aims to rank the importance of key governance mechanisms on collaborative construction projects, in terms of impact on value-for-money. The absence of such information in the global knowledge base has prompted the current study. Seminal research completed recently concluded that deductive evidence with regard to the performance outcomes of collaborative procurement mechanisms is currently limited (Eriksson and Westerberg 2011). The authors aim to address this gap in current understanding. The literature review identifies key features of both formal and informal mechanisms which have been applied within collaborative contracting contexts. The literature review lays a solid foundation for designing a deductive research strategy to be implemented in the second phase of the study, which will employ a large-scale quantitative survey to shed light on the governance structures of collaborative contracts, and the ways in which they impact on realisation of VfM during project delivery in the Australian infrastructure industry. The current paper aims to identify the main categories of formal and informal governance mechanisms currently being employed globally. This will provide structure for the development of the survey in the second phase of the study.

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In recent times, light gauge steel frame (LSF) wall systems are increasingly used in the building industry. They are usually made of cold-formed and thin-walled steel studs that are fire-protected by two layers of plasterboard on both sides. A composite LSF wall panel system was developed recently, where an insulation layer was used externally between the two plasterboards to improve the fire performance of LSF wall panels. In this research, finite element thermal models of the new composite panels were developed using a finite element program, SAFIR, to simulate their thermal performance under both standard and Eurocode design fire curves. Suitable apparent thermal properties of both the gypsum plasterboard and insulation materials were proposed and used in the numerical models. The developed models were then validated by comparing their results with available standard fire test results of composite panels. This paper presents the details of the finite element models of composite panels, the thermal analysis results in the form of time-temperature profiles under standard and Eurocode design fire curves and their comparisons with fire test results. Effects of using rockwool, glass fibre and cellulose fibre insulations with varying thickness and density were also investigated, and the results are presented in this paper. The results show that the use of composite panels in LSF wall systems will improve their fire rating, and that Eurocode design fires are likely to cause severe damage to LSF walls than standard fires.

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This paper investigates the critical role of knowledge sharing (KS) in leveraging manufacturing activities, namely integrated supplier management (ISM) and new product development (NPD) to improve business performance (BP) within the context of Taiwanese electronic manufacturing companies. The research adopted a sequential mixed method research design, which provided both quantitative empirical evidence as well as qualitative insights, into the moderating effect of KS on the relationships between these two core manufacturing activities and BP. First, a questionnaire survey was administered, which resulted in a sample of 170 managerial and technical professionals providing their opinions on KS, NPD and ISM activities and the BP level within their respective companies. On the basis of the collected data, factor analysis was used to verify the measurement model, followed by correlation analysis to explore factor interrelationships, and finally moderated regression analyses to extract the moderating effects of KS on the relationships of NPD and ISM with BP. Following the quantitative study, six semi-structured interviews were conducted to provide qualitative in-depth insights into the value added from KS practices to the targeted manufacturing activities and the extent of its leveraging power. Results from quantitative statistical analysis indicated that KS, NPD and ISM all have a significant positive impact on BP. Specifically, IT infrastructure and open communication were identified as the two types of KS practices that could facilitate enriched supplier evaluation and selection, empower active employee involvement in the design process, and provide support for product simplification and the modular design process, thereby improving manufacturing performance and strengthening company competitiveness. The interviews authenticated many of the empirical findings, suggesting that in the contemporary manufacturing context KS has become an integral part of many ISM and NPD activities and when embedded properly can lead to an improvement in BP. The paper also highlights a number of useful implications for manufacturing companies seeking to leverage their BP through innovative and sustained KS practices.

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Despite a considerable amount of research on traffic injury severities, relatively little is known about the factors influencing traffic injury severity in developing countries, and in particular in Bangladesh. Road traffic crashes are a common headline in daily newspapers of Bangladesh. It has also recorded one of the highest road fatality rates in the world. This research identifies significant factors contributing to traffic injury severity in Dhaka – a mega city and capital of Bangladesh. Road traffic crash data of 5 years from 2007 to 2011 were collected from the Dhaka Metropolitan Police (DMP), which included about 2714 traffic crashes. The severity level of these crashes was documented in a 4-point ordinal scale: no injury (property damage), minor injury, severe injury, and death. An ordered Probit regression model has been estimated to identify factors contributing to injury severities. Results show that night time influence is associated with a higher level injury severity as is for individuals involved in single vehicle crashes. Crashes on highway sections within the city are found to be more injurious than crashes along the arterial and feeder roads. There is a lower likelihood of injury severity, however, if the road sections are monitored and enforced by the traffic police. The likelihood of injuries is lower on two-way traffic arrangements than one-way, and at four-legged intersections and roundabouts compare to road segments. The findings are compared with those from developed countries and the implications of this research are discussed in terms of policy settings for developing countries.

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Driving on an approach to a signalized intersection while distracted is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. Given the prevalence and importance of this particular scenario, the decisions and actions of distracted drivers during the onset of yellow lights are the focus of this study. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of Iowa - National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examination has been conducted from a traditional regression-based approach, which does not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that novice (16-17 years) and young drivers’ (18-25 years) have heightened yellow light running risk while distracted by a cell phone conversation. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Overall, distracted drivers across most tested groups tend to reduce the propensity of yellow light running as the distance to stop line increases, exhibiting risk compensation on a critical driving situation.