Now showing 1 - 8 of 8
  • Publication
    Probabilistic study of lifetime load effect distribution of bridges
    Assessment of highway bridge safety requires a prediction of the probability of occurrence of extreme load effects during the remaining life of the structure. While the assessment of the strength of an existing bridge is relatively well understood, the traffic loading it is subject to, has received less attention in the literature. The recorded traffic data are often limited to a number of days or weeks due to the cost of data collection. Studies in the literature have used many different methods to predict the lifetime maximum bridge load effect using a small amount of data, including fitting block maximum results to a Weibull distribution and raising maximum daily or maximum weekly distributions to an appropriate power. Two examples are used in this study to show the importance of the quantity of data in predicting the lifetime maximum distribution. In the first, a simple example is used for which the exact theoretical probabilities are available. Hence, the errors in estimations can be assessed directly. In the second, ‘long-run’ simulations are used to generate a very large database of load effects from which very accurate estimates can be deduced of lifetime maximum effects. Results are presented for bidirectional traffic, with one lane in each direction, based on Weigh-in-Motion data from the Netherlands.
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  • Publication
    Probabilistic analysis of potential impact of extreme weather events on infrastructures
    In recent years, a variety of extreme weather events, including droughts, rain induced landslides, river floods, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions across Europe and worldwide. These events can have devastating impact on critical infrastructure systems. The 7th Framework RAIN project will address these issues, involving partners from Ireland, Belgium, Germany, Finland, Italy, Netherlands, Slovenia and Spain. In this project, the impact of critical infrastructure failure on society, on security issues and on the economy will be examined. Based on the impacts of the failures, quantifiable benefits (from a societal, security and economic standpoint) of providing resilient infrastructure will be identified. In this project, a means of quantifying the level of risk will be established, first due to single land transport mode failures, and second due to selected multi-mode-interdependent failure scenarios (e.g. failure of power stations result in failure of electrical train lines). This paper introduces the RAIN project and its goal of developing a methodology to create an advanced risk assessment procedure, including a probabilistic based approach, to derive a measurable indicator of risk.
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  • Publication
    Quantifying the Impact of Critical Infrastructure Failure due to Extreme Weather Events
    The recent extreme weather events in Europe and around the world have raised issues about the organization and management of critical infrastructure. There is uncertainty and a lack of information on how infrastructure should be managed when subject to these extreme events. The existence of chaos and uncertainty in these situations can result in disruptions to transport, power outages and in the most extreme instances, loss of life. The 7th Framework RAIN (Risk Analysis of Infrastructure Networks in response to extreme weather) project is addressing these issues, involving partners from Ireland, Belgium, Germany, Finland, Italy, Netherlands, Slovenia and Spain. The objective of the RAIN project is to provide an operational analysis framework to minimize the impact of major weather events in the EU. This paper summarizes the work that will be performed in one of the work packages of the RAIN project. This work package will examine the impact of critical infrastructure failure on society, security issues and the economy. Based on a risk analysis framework, a means of quantifying the level of risk will be established, firstly due to single land transport mode failures, and secondly for selected multi-mode-interdependent failure scenarios (e.g., failure of power stations result in failure of electrical train lines). In this study, methods will be developed to create an advanced risk assessment procedure, using a probabilistic based approach, to derive a measurable indicator of risk. The risk procedure will be benchmarked against case studies conducted on critical transport and operational tactical connections. The project outputs will contribute to the process of knowledge management used in the protection of Critical Infrastructure and will provide a basis for the development of decision support systems.
      258
  • Publication
    Calculation of the Dynamic Allowance for Railway Bridges from Direct Measurement
    In a traditional deterministic assessment, a dynamic amplification factor (DAF) is applied to the static loading in order to account for dynamics. The codified DAF values are appropriately conservative in order to consider the wide range of structures and load effects to which they are applied. In the current analysis, a site specific assessment dynamic ratio (ADR) is calculated from direct measurement on an 80 year old steel truss Railway Bridge. The ADR is defined as the ratio of characteristic total stress to the characteristic static stress. The application of ADR is a relatively new concept which has rarely been considered for railway bridges. An assessment performed on the bridge in question showed a decrease in the dynamic allowance when considering the site specific ADR, corresponding to a 26% decrease in calculated stress. The measurements available were also used to derive a robust stochastic model for dynamic allowance which considered the correlation between DAF and stress level. The developed model was applied to a probabilistic assessment and resulted in a 9% increase in reliability.
      444
  • Publication
    Non-Linear Response of Structures to Characteristic Loading Scenarios
    To assess the safety of an existing bridge, the traffic loads to which it may be subjected in its lifetime need to be accurately quantified. In this paper the 75 year characteristic maximum traffic load effects are found using a carefully calibrated traffic load simulation model. To generate the bridge loading scenarios, an extensive weigh in motion (WIM) database, from three different European countries, is used. Statistical distributions for vehicle weights, inter-vehicle gaps and other characteristics are derived from the measurements, and are used as the basis for Monte Carlo simulations of traffic representing many years. An advantage of this “long-run” simulation approach is that it provides information on typical extreme traffic loading scenarios. This makes possible a series of nonlinear finite element analyses of a reinforced concrete bridge to determine the response to typical characteristic maximum loadings.
      238
  • Publication
    Numerical Asessment of The Thermal Performance of Structural Precast Panels
    With the increasing cost of energy the need to provide energy efficient buildings continues to grow. In 2003 the EU introduced the Energy Performance of Buildings Directive and this was enforced by all member states by 2006. The need to continually improve thermal performance has lead to member states implementing their own national initiatives, and from next year the National Standards Authority of Ireland will specify that all certified sandwich panel products comply with the incoming building regulations. The incoming building regulations stipulate that all sandwich panels achieve a U-value of 0.15 W/m2K, a reduction from the current value of 0.25 W/m2K. This is a significant challenge and requires that there be no significant heat loss through the panel. This paper presents the results of a collaborative project with a sandwich panel manufacturer whereby the thermal performance of a number of concrete panels was assessed. Each sandwich panel contained an inner concrete wythe of 150mm thickness, a 120mm layer of phenolic foam insulation and a 90mm thick outer layer of concrete. For structural reasons it is necessary to use connectors between the inner and outer concrete wythes, but these connectors have the potential to allow heat loss. In this study 2 connector types were used: 1 manufactured using FRP, the other with stainless steel. A control (non-structural) panel was manufactured containing no connectors. The thermal performance of each panel was assessed through experimental hot-box testing to determine U-values. This was complemented by a series of images taken using a thermal camera to show areas of heat loss. In addition the U-values were also determined using a theoretical numerical approach and a thermal finite element analysis (using MSC Patran) was conducted to determine the heat flux through the panel. The results showed that the connector type has a significant influence on the thermal performance of the sandwich panels, and that those containing steel connectors were not capable of providing the required U-value. The relative performance of the various panel types was consistent between analysis methods, as the finite element, the numerical and experimental approaches were in agreement. In addition, the heat losses observed through the thermal imaging camera were consistent with the heat losses predicted by the finite element analysis. It is proposed then that the use of numerical and finite element approaches has a valuable role in the design of thermally efficient sandwich panels. The experimental testing required is time consuming and requires significant effort. The analysis approach described above will make the design process more efficient and facilitate the construction of energy efficient buildings.
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  • Publication
    Estimation of lifetime maximum distributions of bridge traffic load effects
    This paper considers the problem of assessing traffic loading on road bridges. A database of European WIM data is used to determine accurate annual maximum distributions of load effect. These in turn are used to find the probability of failure for a number of load effects. Using the probability of failure as the benchmark, traditional measures of safety – factor of safety and reliability index – are reviewed. Both are found to give inconsistent results, i.e., a given factor of safety or reliability index actually corresponds to a range of different probabilities of failure
      549
  • Publication
    Spatially Variable Assessment of Lifetime Maximum Load Effect Distribution in Bridges
    Bridge structures are key components of highway infrastructure and their safety is clearly of great importance. Safety assessment of highway bridges requires accurate prediction of the extreme load effects, taking account of spatial variability through the bridge width and length. This concept of spatial variability i s also known as random field analysis. Reliability - based bridge assessment permits the inclusion of uncertainty in all parameters and models associated with the deterioration process. Random field analysis takes account of the probability that two points n ear each other on a bridge will have correlated properties. This method incorporates spatial variability which results in a more accurate reliability assessm ent. This paper presents an integrated model for spatial reliability analysis of reinforced concre te bridges that considers both the bridge capacity and traffic load. A sophisticated simulation model of two - directional traffic is used to determine accurate annual maximum distributions of load effect. To generate the bridge loading scenarios, an extensi ve Weigh-in-Motion (WIM) database, from five European countries, is used. For this, statistical distributions for vehicle weights, inter - vehicle gaps and other characteristics are derived from the measurements, and are used as the basis for a Monte Carlo simulation of traffic. Results are presented for bidirectional traffic, with one lane in each direction, with a total flow of approximately 2000 trucks per day.
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