Bridge Maintenance Activities Research Articles

A Reliability-Based Framework for Damage Accumulation Due to Multiple Earthquakes: A Case Study on Bridges

Damage accumulation due to multiple seismic impacts over time has a significant effect on the residual service life of the bridge. A reliability-based framework was developed to make decisions in bridge maintenance activities. The feature of the framework enables quantifying the time-dependent probability of failure of bridges due to the impact of multiple earthquakes and progressive deterioration. To estimate the reliability of the bridge systems, the probability of failure of the bridge was used. Two case studies were utilised to demonstrate how the method can be applied to the real world. Results show that the accumulated damage caused by multiple earthquakes and progressive deterioration significantly impact the remaining useful life of the bridge. Furthermore, the soil conditions predominantly influence the progressive deterioration and reduce the service life of the bridge. Overall, the proposed framework enables the sustainable decision-making process for bridge maintenance activities. The results reveal the necessity of including the combined impact in the bridge maintenance system and that there is a more than 40% increase in the probability of failure, due to the combined effect of progressive deterioration and earthquake impacts, compared to the impact only due to seismic loads for the considered case study bridge.

Estimation of structural response using convolutional neural network: application to the Suramadu bridge

PurposeStructural health monitoring (SHM) has gained significant attention due to its capability in providing support for efficient and optimal bridge maintenance activities. However, despite the promising potential, the effectiveness of SHM system might be hindered by unprecedented factors that impact the continuity of data collection. This research presents a framework utilising convolutional neural network (CNN) for estimating structural response using environmental variations.Design/methodology/approachThe CNN framework is validated using monitoring data from the Suramadu bridge monitoring system. Pre-processing is performed to transform the data into data frames, each containing a sequence of data. The data frames are divided into training, validation and testing sets. Both the training and validation sets are employed to train the CNN models while the testing set is utilised for evaluation by calculating error metrics such as mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE). Comparison with other machine learning approaches is performed to investigate the effectiveness of the CNN framework.FindingsThe CNN models are able to learn the trend of cable force sensor measurements with the ranges of MAE between 10.23 kN and 19.82 kN, MAPE between 0.434% and 0.536% and RMSE between 13.38 kN and 25.32 kN. In addition, the investigation discovers that the CNN-based model manages to outperform other machine learning models.Originality/valueThis work investigates, for the first time, how cable stress can be estimated using temperature variations. The study presents the first application of 1-D CNN regressor on data collected from a full-scale bridge. This work also evaluates the comparison between CNN regressor and other techniques, such as artificial neutral network (ANN) and linear regression, in estimating bridge cable stress, which has not been performed previously.

A strategy of quick hierarchization of road bridge maintenance activities

The control and maintenance of infrastructures is a crucial aspect for the sustainability and development of the economic and social activities of a country. The managing authorities, in order to preserve the efficiency and safety of the traffic flows, have to deal with a rather old infrastructure asset that is often in a non-optimal conservation state with an increasing degradation process induced by the increment of the traffic loads and by the environmental actions. The situation is exacerbated by the limited economic resources and reduced workforces at disposal with the consequence that an order of priority in the maintenance plain is anavoidable. This work provides a logical tool to define the hierarchy of the maintenance plain of the infrastructural heritage based on one hand on the structure state of conservation and on the other hand on the context in which the construction is integrated

DEVELOPMENT OF A COMPREHENSIVE PEDESTRIAN FOOTBRIDGE MANAGEMENT SYSTEM

The footbridges in rural areas have been crucial as the only mean to overcome the rural isolation and allow breaking the cycle of poverty by providing access to such development facilities like education opportunities, markets, medical clinics and other basic services. In Rwanda, under collaboration with Engineers without Borders from German, and International Non-Government Organization Bridge to Prosperity (B2P, some footbridges are already built. In line with the agreement with B2P around 355 bridges are also planned in 5 years. The key challenge is to optimally allocate resources in order to maintain this number of bridges, especially under the current financial constraints. The purpose of this paper was to investigate and propose a pedestrian footbridge management system for Rwanda (PFBMS) which should allow the efficient bridge management, through the analysis of condition data, determination of the ranking and priority of bridge maintenance activities, as well as evaluation of the alternatives of preservation or replacement. The methodology comprises of the use of interview and discussions with district engineers in charge of bridge management, local community using the constructed footbridges as well as bridge builders from B2P. Microsoft Excel analysis tool has been used to developing the deterioration model, and therefore the PFBM was proposed. It is concluded that this system can accurately predict optimal maintenance planning as well as bridge rating.

Sustainability of bridge maintenance

Bridge maintenance activities are important to consider within sustainable development due to the cost and environmental impact associated with various maintenance activities. Comparisons have been made between different bridge structural forms, based on materials, components and construction method, but less information is available on bridge maintenance activities to help decide a sustainable structural form. Typical maintenance aspects of the predominant forms of bridge structure (i.e. concrete, steel and masonry bridges) were considered in this study to reveal their sustainability in terms of materials, energy, transportation, human health and ecosystems. The results indicate that concrete and steel bridge maintenance activities have an average impact of 42% and 46% compared with 12% for masonry bridge maintenance activities. It is concluded that the component parts of concrete and steel bridges should be revised as they play an integral role in the selection of maintenance options.

Using genetic algorithms for long-term planning of network of bridges

Bridge maintenance activities are often budgeted, scheduled and conducted for networks of bridges with different ages, types and conditions, which can make bridge network maintenance management challenging. In this study, we propose an improved maintenance planning model based on genetic algorithm for a network of bridges to bring a long-term perspective to the lifespan of bridges. To test the applicability and efficiency of the model, it is applied to a network of 100 bridges in one of the south-western provinces of Iran. The results of the model implementation show considerable potential for improvement over the currently adopted model for bridge maintenance planning.

Probabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repair.

Railway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.

Prioritization of bridges for maintenance planning using data envelopment analysis

Resources—especially funds allotted—for the maintenance of bridges, are generally scanty. Thus, it becomes difficult to select bridges for maintenance from among several competing bridges to ensure their safety and serviceability to the desired level. A bridge health index is considered a reasonably accurate depiction of the condition of a bridge and hence is the basis for most of the decisions on fund allocation. However, it still remains to be seen whether such a decision-making tool results in an efficient fund allocation. From data collected on Indian bridges, it is observed that fund allocation based on bridge condition is not always judicious. Rather, a number of factors affect the final decision on fund allocation. Hence, an alternative approach of data envelopment analysis (DEA) has been used for scoring the efficiency of 14 bridges selected for the study. Depending on the availability of data, this method can take into account other factors besides the bridge health index that influence decisions on maintenance planning. The variables selected for the DEA are: bridge health index, deck area of the bridge, maintenance cost of the bridge, and the age of the bridge. The allocation of funds for the maintenance of bridges based on DEA has proved to be comparatively more efficient. This has been illustrated with the help of a numerical example. The proposed method would enable bridge authorities to formulate better strategies for planning and executing bridge maintenance activities in a cost-effective manner.

Waterway transitions at US bridges

Stream and river management projects are implemented to improve water quality, stream function, aquatic habitat and aesthetics, and provide mitigation for road construction. In contrast, bridge maintenance activities are undertaken to convey water, sediment and debris beneath bridges at high flows. Road crossings can have a significant influence on local hydraulics and sediment transport, resulting in an altered flow pattern that can cause backwater, increased erosion, debris and sediment deposition and channel instability. Thus, managing rivers and streams that include one or more road crossings requires some knowledge of the flow hydraulics over a range of flows in order to create a smooth, stable transition through the bridge opening. In-stream structures, such as vanes and weirs, can help to transition flow, sediment and debris through a bridge opening. The use of these in-stream structures at road crossings, and scenarios for planning projects where road crossings intercept the project reach, are presented.

GA-based algorithm for selecting optimal repair and rehabilitation methods for reinforced concrete (RC) bridge decks

Korean government agencies manage bridge structures at the network level using a Bridge Management System (BMS). One of the most important functions of the BMS is to provide the agencies with an effective decision making tool for managing bridges. Especially, it is very important for the BMS to assist in prioritizing routine maintenance, repair, rehabilitation, and replacement activities to optimize the given constrained budgets. This paper suggests an algorithm for the BMS to prioritize bridge maintenance activities at the network level and to show its implementation. The selection of maintenance activities can be modeled as a multi-objective combinatorial optimization problem. A genetic algorithm is used to solve it. Using bridge decks as an example, the application of genetic algorithms is demonstrated and the feasibility of the suggested methodology is examined through some numerical case studies.

Maintaining safety and serviceability of concrete bridges in Croatia

This paper discusses the management, maintenance and repair of Croatian bridges. Unfortunately, activities related to bridge maintenance are not carried out regularly, but on an ‘as-needed’ basis with inspection and testing undertaken only when structural damage becomes self-evident. Poor in-service performance and condition of existing bridges in Croatia led to the conclusion that the currently employed approach to solving bridge maintenance issues is not satisfactory, and should be improved. The framework for more efficient bridge management in terms of the bridge management system named HRMOS exists. Unfortunately, the introduction of HRMOS did not ensure that the activities related to bridge maintenance are carried out regularly nor according to the prescribed procedures. To illustrate the grave consequences of neglecting bridge maintenance activities, several case studies are discussed, including world-renowned structures such as the Krk bridges. These clearly show that if we choose to act only when ...

Time-Dependent Bridge Network Reliability: Novel Approach

A novel reliability-based approach to evaluating the overall performance of a bridge network and to assessing the reliability importance of individual bridges to the bridge network is presented. The new concepts of the time-dependent bridge network reliability and bridge reliability importance factor (RIF) are introduced. A bridge network is regarded as an assembly of nodes, points, and links. The bridge network reliability is formulated in terms of connectivity between the origin and destination locations. However, this formulation can be extended to include traffic capacity and impacts of bridge maintenance activities on economy, environment, and society. Reliability importance factor is defined as the sensitivity of the bridge network reliability to changes in individual bridge system reliability. This clearly represents the reliability importance of individual bridges in the network. Based on a bridge network topology, a series-parallel path model is created to compute the bridge network reliability using network theories and techniques. This novel approach is illustrated on a group of fourteen existing bridges of different material and structural types located in Colorado. This study provides the basis of a network-level bridge management system where lifetime reliability and life-cycle costs are the key considerations for optimal bridge maintenance strategies.

Areas of Uncertainty in Bridge Management: Framework for Research

Bridge maintenance activities, from inspection and assessment to fund allocation and execution of the work, involve many uncertainties. If the predictably increasing future requirements for bridge maintenance are to be met in a cost-effective manner, these uncertainties must be identified and reduced as much as possible. Past research in bridge engineering has mostly concentrated on the engineering aspects of the activities. Many countries are now conducting considerable research and development efforts to produce better materials, innovative forms of construction, improved inspection and monitoring techniques, and better evaluation procedures and criteria. Now is the time to examine the uncertainties found in bridge management. To address these deficiencies, it is necessary to determine the focus of future research. Clearly, the level of resources that is used in different areas of research should reflect the accuracy that is warranted by the end use. On the basis of experiences gained from bridge management as well as from similar activities in the field of offshore structures, the areas of uncertainty, such as method sophistication, operator expertise, and human and sampling errors, are identified. In addition, a possible methodology is outlined that could provide bridge authorities, researchers, and industry with an overview of the currently perceived problems and their relative importance so that resources could be used in a cost-effective manner. The process of breaking down management into component activities by the use of flow diagrams and the representation of individual uncertainties through probabilistic distribution are also presented.

New Developments in Bridge Management Methodology

Currently available bridge management systems (BMSs) are broadly based on two principles: firstly, the bridge maintenance needs are directly related to the condition states of the structures and, secondly, the justification for any proposed work is that it will cost more later if the work is not carried out now. However, contrary to the first assumption, experience gained from the UK Highways Agency’s bridge maintenance activities shows that the major part of the work depends on the load carrying capacity (or structural adequacy) of the structures rather than on their conditions alone. This paper describes the principles and basic steps of a new bridge maintenance bidding and bid prioritisation procedure being developed by the Highways Agency for implementing in the near future.

Optimal Long‐Term Scheduling of Bridge Deck Replacement and Rehabilitation

The paper presents a (0-1) binary decision model to determine optimal long-term deck replacement or rehabilitation schedules for a system of independent bridges. The model is applicable to multiple decks and is driven by over-all long-term cost considerations. Maintenane activites are scheduled based on the current condition and future deterioration of each deck. An example is presnted using 3 bridges in North Carolina and a piecewise linear deterioration function. Possible extensions using nonlinear deterioration functions and additional rehabilitation alternatives are discussed. The study results show that the model can be used by engineers as an aid in the long-term scheduling of bridge maintenance activities.