Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

Where the bridge is

Memoir excerpt

Virtual prototyping for planning bridge construction

4D simulation, building information modeling, virtual construction, computer simulation and virtual prototyping are emerging topics in the building construction industry. These techniques not only relate to the buildings themselves, but can also be applied to other forms of construction, including bridges. Since bridge construction is a complex process involving multiple types of plant and equipment, applying such virtual methods benefits the understanding of all parties in construction practice. This paper describes the relationship between temporary platforms, plant and equipment resources and a proposed-built model in the construction planning and use of Virtual Prototyping Simulation (VPS) to implement different construction scenarios in order to help planners identify an optimal construction plan. A case study demonstrates the use of VPS integrated with temporary platform design and plant and equipment-resource allocation to generate different construction scenarios.

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.

Modeling as a bridge between real world problems and school mathematics

This article argues for an interdisciplinary approach to mathematical problem solving at the elementary school, one that draws upon the engineering domain. A modeling approach, using engineering model eliciting activities, might provide a rich source of meaningful situations that capitalize on and extend students’ existing mathematical learning. The study reports on the developments of 48 twelve-year old students who worked on the Bridge Design activity. Results revealed that young students, even before formal instruction, have the capacity to deal with complex interdisciplinary problems. A number of students created quite appropriate models by developing the necessary mathematical constructs to solve the problem. Students’ difficulties in mathematizing the problem, and in revising and documenting their models are presented and analysed, followed by a discussion on the appropriateness of a modeling approach as a means for introducing complex problems to elementary school students.

Synthetic rating system for railway bridge management

Railway bridges deteriorate with age. Factors such as environmental effects on different materials of a bridge, variation of loads, fatigue, etc will reduce the remaining life of bridges. Bridges are currently rated individually for maintenance and repair actions according to the structural conditions of their elements. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. Current simplified but practical rating methods are not based on an accurate structural condition assessment system. On the other hand, the sophisticated but more accurate methods are only used for a single bridge or particular types of bridges. It is therefore necessary to develop a practical and accurate system which will be capable of rating a network of railway bridges. This paper introduces a new method for rating a network of bridges based on their current and future structural conditions. The method identifies typical bridges representing a group of railway bridges. The most crucial agents will be determined and categorized to criticality and vulnerability factors. Classification based on structural configuration, loading, and critical deterioration factors will be conducted. Finally a rating method for a network of railway bridges that takes into account the effects of damaged structural components due to variations in loading and environmental conditions on the integrity of the whole structure will be proposed. The outcome of this research is expected to significantly improve the rating methods for railway bridges by considering the unique characteristics of different factors and incorporating the correlation between them.

Synthetic rating system for railway bridge management

Railway bridges deteriorate with age. Factors such as environmental effects on different materials of a bridge, variation of loads, fatigue, etc. will reduce the remaining life of bridges. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. Current simplified but practical methods of rating a network of bridges are not based on an accurate structural condition assessment system. On the other hand, the sophisticated but more accurate methods are only used for a single bridge or particular types of bridges. It is therefore necessary to develop a practical and accurate system, which will be capable of rating a network of railway bridges. This article introduces a new method to rate a network of bridges based on their current and future structural conditions. The method identifies typical bridges representing a group of railway bridges. The most crucial agents will be determined and categorized to criticality and vulnerability factors. Classification based on structural configuration, loading, and critical deterioration factors will be conducted. Finally a rating method for a network of railway bridges that takes into account the effects of damaged structural components due to variations in loading and environmental conditions on the integrity of the whole structure will be proposed. The outcome of this article is expected to significantly improve the rating methods for railway bridges by considering the unique characteristics of different factors and incorporating the correlation among them.

A bridge over troubling waters : a snapshot of teacher graduates' perceptions of their ongoing professional learning needs

For graduating teachers, the bridging period between formal teacher preparation and joining the profession is a time of high anxiety and great excitement. While this transition influences efficacy, job satisfaction, career length and future teaching quality, it is widely recognized to be inconsistent, poorly planned and resourced and largely unsupported (DEST, 2002; Herrington & Herrington, 2004). In Australia, the transition to teaching remains largely a school-based affair. However, individual schools may not have the resources to support a comprehensive and cohesive transition program. This paper discusses a pilot university program of extended teacher preparation. It reports on the perceived professional learning needs of a group of graduates as they transition to teaching. The key findings indicate that these graduates are seeking ongoing support as they develop confidence in their canonical skills of teaching. We argue that university-based programs are one way of providing professional learning and support for beginning teachers.

Alternative structural design strategies for bridge decks in low traffic volume roads

This research is part of a major project with a stimulus that rose from the need to manage a large number of ageing bridges in low traffic volume roads (LTVR) in Australia. The project investigated, designed and consequently constructed, involved replacing an ageing super-structure of a 10m span bridge with a disused Flat-bed Rail Wagon (FRW). This research, therefore, is developed on the premises that the FRW can be adopted as the main structural system for the bridges in LTVR network. The main focus of this research is to present two alternate deck wearing systems (DWS) as part of the design of the FRW as road bridge deck conforming to AS5100 (2004). The bare FRW structural components were first examined for their adequacy (ultimate and serviceability) in resisting the critical loads specified in AS5100(2004). Two options of DWSs were evaluated and their effects on the FRW examined. The first option involved usage of timber DWS; the idea of this option was to use all the primary and secondary members of the FRW in load sharing and to provide additional members where weaknesses in the original members arose. The second option involved usage of reinforced concrete DWS with only the primary members of the FRW sharing the AS5100 (2004) loading. This option inherently minimised the risk associated with any uncertainty of the secondary members to their structural adequacy. This thesis reports the design phases of both options with conclusions of the selection of the ideal option for better structural performance, ease of construction and cost. The comparison carried out here focuses on the distribution of the traffic load by the FRW as a superstructure. Advantages and disadvantages highlighting cost comparisons and ease of constructability of the two systems are also included.

A method of extracting switching loss from a high efficiency MOSFET based half bridge converter

The measurement of losses in high efficiency / high power converters is difficult. Measuring the losses directly from the difference between the input and output power results in large errors. Calorimetric methods are usually used to bypass this issue but introduce different problems, such as, long measurement times, limited power loss measurement range and/or large set up cost. In this paper the total losses of a converter are measured directly and switching losses are exacted. The measurements can be taken with only three multimeters and a current probe and a standard bench power supply. After acquiring two or three power loss versus output current sweeps, a series of curve fitting processes are applied and the switching losses extracted.

Timed Probabilistic Automaton : a bridge between Raven and Song Scope for automatic species recognition

Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.