Multi-objective model for optimizing railway infrastructure asset renewal

Trabalho inspirado num problema real da empresa Infraestruturas de Portugal, EP.A multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.info:eu-repo/semantics/publishedVersio

Highway filter drains maintenance management

Across a large part of the UK highways network the carriageway and pavement foundations are drained by Highway Filter Drains (HFDs). A HFD is a linear trench constructed either at the pavement edge or central reserve, fitted with a porous carrier pipe at the base and backfilled with an initially highly porous aggregate material. This arrangement enables the swift removal of surface runoff and subsurface water from the pavement system minimising road user hazards and eliminating risk of structural damage to the pavement sub-base. The highly porous backfill filters throughout its operational life fines washed from the pavement wearing course or adjacent land. HFDs have been found to be prone to collecting near the basal sections (pipe) or surface layers contaminants or detritus that causes the filter media to gradually block. The process has been defined as HFD clogging and it has been found to lead to reduced drainage capacity and potentially severe drop of serviceability. O&M contractual agreements for DBFO projects usually propose in-service and handback requirements for all assets included in the concession portfolio. Different performance thresholds are thus prescribed for pavements, structures, ancillary assets or street lighting. Similar definitions can be retrieved for drainage assets in such agreements, and these include HFDs. Performance metrics are defined though in a generic language and residual life (a key indicator for major assets that usually drives long-term maintenance planning) is prescribed without indicative means to evaluate such a parameter. Most of pavement maintenance is carried out nowadays using proactive management thinking and engineered assessment of benefits and costs of alternative strategies (what-if scenarios). Such a proactive regime is founded upon data driven processes and asset specific ageing / renewal understanding. Within the spectrum of road management, maintenance Life Cycle Costs are usually generated and updated on an annual basis using inventory and condition data linked to a Decision Support Tool (DST). This enables the assessment and optimisation of investment requirements and projection of deterioration and of treatment impacts aligned to continuous monitoring of asset performance. Following this paradigm shift in infrastructure management, a similar structured methodology to optimise HFD maintenance planning is desired and is introduced in this thesis. The work presented enables the identification of proactive maintenance drivers and potential routes in applying a systemised HFD appraisal and monitoring system. An evaluation of Asset Management prerequisites is thus discussed linked to an overview of strategic requirements to establish such a proactive approach. The thesis identifies condition assessment protocols and focuses on developing the means to evaluate deteriorated characteristics of in service drains using destructive and non-destructive techniques. A probabilistic HFD ageing / renewal model is also proposed using Markov chains. This builds upon existing deterioration understanding and links back to current treatment options and impacts. A filter drain decision support toolkit is lastly developed to support maintenance planning and strategy generation

A Methodology to Determine Non-Fixed Performance Based Thresholds for Infrastructure Rehabilitation Scheduling

In an era of increasing demand and loading, aging infrastructure, and funding shortfalls, infrastructure agencies continue to seek cost-effective solutions to persistent and pervasive questions regarding the upkeep of their physical assets. One such question is the appropriateness of the current fixed condition thresholds used at several agencies for rehabilitation timing purposes, whether there is the possibility of having flexible rather than fixed thresholds, and determining what these thresholds should be. A related question is how these flexible thresholds may vary, depending on the objectives of the decision maker, the relative weight of agency and user costs, and the form of expression of the life-cycle cost associated with the candidate rehabilitation schedules. Fortunately, a number of past researchers have developed inputs that are valuable for addressing this issue. Also, there exists data from in-service infrastructure that could be used to test the hypotheses regarding the sensitivity of the optimal schedules

Incorporating pavement deterioration uncertainty into pavement management optimization

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Pavement Engineering on 2022, available online: https://www.tandfonline.com/doi/full/10.1080/10298436.2020.1837827[EN] Pavement management systems can be used to efficiently allocate limited maintenance budgets to better align with pavement deterioration. However, pavement deterioration is subject to uncertain factors that complicate the prediction of future pavement conditions accurately, entailing differences in the optimum maintenance strategy. This paper addresses this challenge by introducing a method to aid local engineers in optimising the scheduling of maintenance activities under uncertain pavement deterioration conditions. Markov chains are used to simulate the variability of life-cycle performance. Moreover, a multi-objective optimisation of an urban network is carried out to find the maintenance programme that minimises the mean life-cycle cost, maximises the mean user benefit, and minimises the standard deviation of life-cycle cost. This third objective enables the optimisation routine to minimise the possibility of unintentionally increasing the life-cycle cost due to system variability. This approach results in a reduction of the life-cycle cost variability by up to 62%, provides pavement strategies that benefit road users as a result of better pavement conditions, and reduces the risk of resorting to costly future maintenance activities.This work was supported by the Spanish Ministry of Science and Innovation with the European Regional Development Fund (grants BIA2017-85098-R and RTC-2017-6148-7).García-Segura, T.; Montalbán-Domingo, L.; Llopis-Castelló, D.; Lepech, MD.; Sanz-Benlloch, MA.; Pellicer, E. (2022). Incorporating pavement deterioration uncertainty into pavement management optimization. International Journal of Pavement Engineering. 23(6):2062-2073. https://doi.org/10.1080/10298436.2020.18378272062207323

Guidelines for data collection and monitoring for asset management of New Zealand road bridges

Publisher PD

Use of Petri Nets to Manage Civil Engineering Infrastructures

Over the last years there has been a shift, in the most developed countries, in investment and efforts within the construction sector. On the one hand, these countries have built infrastructures able to respond to current needs over the last decades, reducing the need for investments in new infrastructures now and in the near future. On the other hand, most of the infrastructures present clear signs of deterioration, making it fundamental to invest correctly in their recovery. The ageing of infrastructure together with the scarce budgets available for maintenance and rehabilitation are the main reasons for the development of decision support tools, as a mean to maximize the impact of investments. The objective of the present work is to develop a methodology for optimizing maintenance strategies, considering the available information on infrastructure degradation and the impact of maintenance in economic terms and loss of functionality, making possible the implementation of a management system transversal to different types of civil engineering infrastructures. The methodology used in the deterioration model is based on the concept of timed Petri nets. The maintenance model was built from the deterioration model, including the inspection, maintenance and renewal processes. The optimization of maintenance is performed through genetic algorithms. The deterioration and maintenance model was applied to components of two types of infrastructure: bridges (pre-stressed concrete decks and bearings) and buildings (ceramic claddings). The complete management system was used to analyse a section of a road network. All examples are based on Portuguese data

A multi-objective differential evolutionary algorithm for optimal sustainable pavement maintenance plan at the network level

Sustainable highway pavement maintenance is important for achieving sustainability in the transportation sector. Because the three aspects included in sustainability metrics (environment, economy, and society) often contradict each other, maximising the sustainability performance of highway pavements is difficult, especially at the network level. This study developed a novel multi-objective heuristic algorithm to formulate sustainable highway pavement network maintenance plans considering carbon emissions (CE), life cycle agency cost (LCAC), and pavement long-term performance (LTP). The proposed algorithm is a new variant of multi-objective differential evolution (MODE) that incorporates self-adaptive parameter control and hybrid mutation strategies embedded in its framework (MOSHDE). Three state-of-the-art multi-objective heuristics, namely, the non-dominated sorting genetic algorithm II(NSGA-II), classic MODE, and multi-objective particle swarm optimisation (MOPSO), as well as the proposed MOSHDE, were applied to an existing highway pavement network in China for performance evaluation. Compared with other heuristic algorithms, the proposed self-adaptive parameter control strategy enables the automatic adjustment of the control parameters, avoiding the time-consuming process of selecting them and enhancing the robustness and applicability of differential evolution. The hybrid mutation strategy uses both exploration and exploitation operators for the mutation operations, thus leveraging both global and local searches. The results of the numerical experiment demonstrate that MOSHDE outperforms the other tested heuristics in terms of efficiency and quality and diversity of the obtained approximate Pareto set. The optimal solutions obtained by the proposed method correspond to a proactive maintenance policy, as opposed to the reactive maintenance policy commonly adopted in current practice. In addition, these solutions are more cost-effective and environmentally friendly and can provide better pavement performance to highway users over the project life cycle. Therefore, the proposed MOSHDE may help practitioners in the transportation sector make their highway infrastructure more sustainable

A life-cycle approach for managing road infrastructures in developing countries based on Asset Management

Road infrastructures are very important to economic activity, especially in developing countries where they play an essential role in marketing agricultural products and providing access to health, education, and other services. While economic growth and the investments in road transport have increased heavily in developing countries, the public sector responsible for their life-cycle planning, management and maintenance is struggling to make the necessary reforms to keep up with the pace. The main objective of this dissertation is to understand the patterns that influence the strategic planning of road infrastructures and the successful implementation of the practices of asset management in the regulatory environment and structure of the responsible authorities in the developing countries. These patterns (external drivers), different in each country, if not researched and understood correctly, may affect the outcome of the results for the upcoming decades and jeopardize the entire implementation of asset management processes within the organizational structures of the developing countries. It reviews and analyzes the National regulatory environment and practices in Top Asset management countries (Canada, Australia, New Zealand, Uk, USA) and current social and political situation in the western Balkans region (developing countries region), which is influencing the successful management of primary infrastructures in this region. A significant Case study from Albania (Highway Durres- Kukes - Morine, a segment of European route 7 between Albania and Serbia), is introduced and actual physical Conditions, value, and performance of the highway are taken in consideration. Description of Problems this highway experiences because of lack of life-cycle planning and management are presented and how the mismanagement of the assets on a strategic level leads to tangible problems on the technical level. Transport impacts on the highway in terms of displacement, traffic flows, and forecast, historical traffic data are analyzed in order to analyze capacity/demand patterns and future demand, the influence it has on Road asset management and relate this with different strategies of maintenance

A Microeconomic Perspective to Infrastructure Renewal Decisions

Under the prevailing financial constraints and rapid infrastructure deterioration, funding decisions for renewal (rehabilitation) projects have become large challenges for engineers and economists alike. However, existing prioritization and ranking methods suffer from serious drawbacks of not considering multi-year and multi funding scenarios. Moreover, optimization efforts in the literature employ sophisticated mechanisms without providing a structured strategy or justification behind the funding solution. To overcome these drawbacks and to arrive at optimum and economically justifiable infrastructure funding decisions, this research provides a decision support system by adopting well-established concepts from the science of Microeconomics that relate to Consumer Theory and Behavioural Economics. The new decision support system has been developed with two components: (1) an enhanced benefit-cost analysis (EBCA) heuristic approach that arrives at optimum decisions by targeting equilibrium among the different renewal expenditure categories, using the equal marginal utility per dollar concept; and (2) a visual what-if analysis inspired by the indifference maps concept to study the sensitivity of decisions under different budget levels. The developed decision support system has been validated through a number of case studies including a case study were different categories of assets (pavements, bridges) are co-located. The results proved the capability of the system to arrive at optimum funding decisions supported with economic justification. Using the behavioural economic concept of “Loss-aversion”, this research also compared the strategy of minimizing loss against the typical strategy of maximizing gain in the infrastructure funding decisions. In essence, this research is aiming at improving this crucial infrastructure funding problem by integrating the two worlds of microeconomics and asset management. Such integration will help provide optimum funding decisions, increase the credibility of funding methods to the public, and justify the spending of tax payer’s money on infrastructure rehabilitation projects