•A neural network is developed as a surrogate tool fed by a numerical dataset.•PSO utilizes monitoring data to estimate most probable rheological parameters.•The methodology is validated on two ...adjacent tunnels in karstic rock mass.•Numerical results agreed well with the long-term monitored settlements.
The continuous monitoring of long-term performance of tunnels constructed in soft rock masses shows that the rock mass deformations continue after construction, albeit at a rate that reduces with time. This is in contrast with NATM postulates which assume deformation stabilizes shortly after tunnel construction. This paper proposes the prediction of long-term vertical settlement performance of a tunnel in soft rock mass, through the inclusion of a Burger’s creep viscous-plastic constitutive law to model post-construction deformations. To overcome issues related to the complex characterization of this constitutive model, a neural network NetRHEO is developed and trained on a numerically obtained dataset. A particle swarm algorithm is then employed to estimate the most probable rheological parameter set, by utilizing the long-term in-situ monitoring data from several observation points on a real tunnel. The paper demonstrates the potential of the proposed methodology, using displacement measurements of two adjacent tunnels in karstic rock mass in Croatia. The complex interaction of a railway tunnel Brajdica and a road tunnel Pećine, conditioned by the character of the surrounding rock mass as well by the chronology of their construction, was evaluated to predict the future behavior of these tunnels.
Weather phenomena can result in severe impacts on railway infrastructure. In future, projected changes to the frequency and/or intensity of extreme weather events could change weather–infrastructure ...risk profiles. Infrastructure owners and operators need to manage current weather impacts and put in place adequate plans to anticipate and adapt to changes in future weather risks, or mitigate the impacts arising from those risks. The assessment of the risk posed to railway infrastructure from current and future weather is dependent on a good understanding of the constituent components of risk: hazard, vulnerability, and exposure. A good understanding of the baseline and projected future risk is needed in order to understand the potential benefits of various climate change adaptation actions. Traditional risk assessment methods need some modification in order to be applied to climate change timescales, for which decisions need to be made under deep uncertainty. This review paper highlights some key challenges for assessing the risk, including: managing uncertainties; understanding weather‐impact relationships and how they could change with climate change; assessing the costs of current and future weather impacts and the potential cost versus benefit of adaptation; and understanding practices and tools for adapting railway infrastructure. The literature reveals examples of progress and good practice in all these areas, providing scope for effective knowledge‐sharing—across the railway infrastructure and other sectors—in support of infrastructure resilience and adaptation.
This article is categorized under:
Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
Railway infrastructure is at risk from weather, and climate change could alter the future risk. Management of, and adaptation to, climate change is needed, if railways are to continue running safe, reliable, and efficient services in future.
This paper introduces a comprehensive framework for the development of optimal multi-year maintenance plans for a large number of bridges. A maintenance plan is said to be optimal when, within the ...given budget, a maximum number of bridges can be maintained in the best possible year, achieving maximum performance with minimum socio-economic impact. The framework incorporates heuristic rules, multi-attribute utility theory, discrete Markov chain process, and genetic algorithms to find an optimal balance between limited budgets and performance requirements. The applicability of the proposed framework is illustrated on an extensive case study of highway bridges. The framework enables asset owners to execute various planning scenarios under different budget and performance requirements, where each resulting plan is optimal. The focus of this study has mainly been on highway bridges, however the framework is general and can be applied to any other infrastructure asset type.
Aged earthworks constitute a major proportion of European rail infrastructures, the replacement and remediation of which poses a serious problem. Considering the scale of the networks involved, it is ...infeasible both in terms of track downtime and money to replace all of these assets. It is, therefore, imperative to develop a rational means of managing slope infrastructure to determine the best use of available resources and plan maintenance in order of criticality. To do so, it is necessary to not just consider the structural performance of the asset but also to consider the safety and security of its users, the socioeconomic impact of remediation/failure and the relative importance of the asset to the network. This paper addresses this by looking at maintenance planning on a network level using multi-attribute utility theory (MAUT). MAUT is a methodology that allows one to balance the priorities of different objectives in a harmonious fashion allowing for a holistic means of ranking assets and, subsequently, a rational means of investing in maintenance. In this situation, three different attributes are considered when examining the utility of different maintenance options, namely availability (the user cost), economy (the financial implications) and structural reliability (the structural performance and subsequent safety of the structure). The main impact of this paper is to showcase that network maintenance planning can be carried out proactively in a manner that is balanced against the needs of the organization.
In the current economic climate, it is crucial to optimize the use of all resources regarding railway infrastructure maintenance. In this paper, a multi-attribute decision support framework is ...applied to categorize railway embankments in order to prioritize maintenance activities. The paper describes a methodology to first determine the current condition of embankments using a combination of ground penetrating radar (GPR) surveys, visual inspection, and historical data about maintenance activities. These attributes are then used for the development of a multi-attribute utility theory model, which can be used as a support for decision making process for maintenance planning. The methodology is demonstrated for the categorization of 181 km of railway embankments in Croatia.
Durability of reinforced concrete is primarily influenced by the penetration of aggressive substances into concrete, which are degrading concrete and reinforcement. For structures in marine ...environment chlorides are the most critical environmental load, which are causing serious corrosion damages. Data collected during the survey of the Krk Bridge, a large reinforced concrete arch bridge structure located on the Adriatic coast, is used as documented reference in this research. The structure has been exposed to the marine environment for over 25 years. Based on collected materials data and the exposure conditions, the service life of this structure is estimated using three currently available prediction models, two deterministic models, the North American
Life
-
365
model and the Croatian
CHLODIF
model, and the
DuraCrete
probabilistic method. All these models are based on the chloride diffusion process, but with different detailing of the model parameters. The conclusion is an evaluation of the service life predictive ability of each of these three service life models.
In recent times, there has been an increase in transport infrastructure failure. This increase is due to aging infrastructure, increased number of extreme weather events caused by climate change, and ...increased traffic loading. Accordingly, the need for planned and unplanned maintenance interventions is rising. Associated costs do not only involve direct maintenance or reconstruction costs, but also secondary effects experienced by users of the transport network as well as the environment and society in general. Infrastructure managers require tools for accurate quantification of infrastructure resilience that will enable rational adaptation investment strategies, so as to maintain high level of safety of transport networks. Through the development of a Global Safety Framework, at the core of which is a Multi-modal Network Decision Support Tool, the SAFE-10-T project (Safety of Transport Infrastructure on the TEN-T Network) is providing integrated solutions to issues related to infrastructure safety and planning. The paper presents a reliability-based whole life cycle model developed within this project enabling strategic investment decisions that maximize safety, minimize disruption, and environmental impacts and allow for the best use of limited resources. The model is applied on a case study of a bridge in the Port of Rotterdam in the Netherlands.
Ultra-high-performance fiber-reinforced cement-based composite (UHPFRC) has been increasingly adopted for rehabilitation projects over the past two decades, proving itself as a reliable, ...cost-efficient and sustainable alternative against conventional methods. High compressive strength, low permeability and high ductility are some of the characteristics that render UHPFRC an excellent material for repairing existing aged infrastructure. UHPFRC is most commonly applied as a surface layer for strengthening and rehabilitating concrete structures such as bridge decks or building slabs. However, its implementation with steel structures has so far been limited. In this work, the UHPFRC strengthening of a steel bridge is investigated both in simulation as well as in the laboratory, by exploiting a real-world case study: the Buna Bridge. This Croatian riveted steel bridge, constructed in 1893, repaired in 1953, and decommissioned since 2010, was removed from its original location and transported to laboratory facilities for testing prior to and after rehabilitation via addition of UHPFRC slab. The testing campaign includes static and dynamic experiments featuring state-of-the-art monitoring systems such as embedded fiber optics, acoustic emission sensors and digital image correlation. The information obtained prior to rehabilitation serves for characterization of the actual condition of the structure and allows the design of the rehabilitation solution. The UHPFRC slab thickness was optimized to deliver optimal fatigue and ultimate capacity improvement at reasonable cost. Once the design was implemented, a second round of experiments was conducted in order to confirm the validity of the solution, with particular attention allocated to the interface between the steel substrate and the UHPFRC overlay, as the connection between both materials may result in a weak contact point. A detailed fatigue analysis, based on updated FEM models prior to and after strengthening, combined with the results of a reliability analysis prove the benefits of adoption of such a solution via the significant extension of the structural lifespan.
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