Infrastructure Asset Management Research Articles

Towards an Integrated Approach to Infrastructure Damage Assessment in the Aftermath of Natural Hazards

The world has witnessed an alarmingly increasing number of serious natural hazards. In the aftermath of a hazard, relevant authorities/agencies face, among others, the challenging tasks of rapidly evaluating and assessing the damages to infrastructures and restoring their essential functionality and operation. The availability of reliable, high-quality structural and operational/maintenance data of a structure and its health, before and after a natural hazard, can be instrumental in the rapid assessment of a damaged structure. We collectively refer, in this paper, to the existing as-built and facility operational information about a structure or an infrastructure asset represented respectively in Building Information Modeling (BIM) and Infrastructure Asset Management (IAM) systems as Product Lifecycle Data (PLD). Arguably, PLD combined with other post-hazard condition assessment data can provide a more reliable and integrated solution for a rapid damage assessment of buildings and other critical infrastructures. Unfortunately, the application of PLD in this critical area has been unexplored in the literature, and the mapping between PLD and damage assessment methods is loosely investigated. In an effort to address this research gap, this paper provides a critical analysis of the most common structural damage assessment methods and explores the potential of combining them with PLD to provide more reliable, comprehensive, and integrated solution for damage assessment. Findings from this study could be useful for practitioners in selecting the most appropriate and effective methods to conduct damage and safety assessments of critical infrastructures. The study will also assist the further theoretical developments in the integration of PLD with different damage assessment methods.

Incorporating defect specific condition indicators in a bridge life cycle analysis

Bridges are critical assets for the safe, reliable and functional operation of transportation networks. Infrastructure asset managers are responsible for ensuring that these bridges adhere to rigorous safety standards using the finite resources available to transportation agencies. To facilitate strategy development and to present decisions to stakeholders, a life cycle analysis is commonly performed.Many bridge owners use stochastic models that are calibrated using condition records from visual examinations, however, condition records typically report bridge condition on a single condition scale. In this study, defect specific condition scales are utilised to implement multiple defect specific condition indicators in the modelling of deterioration. These additional indicators enable the modelling of the interactions between defects during deterioration. Moreover, the indicators are used in the modelling of different defect specific maintenance interventions providing the scope to quantitatively assess the effects of strategies that favour early intervention.A multiple defect deterioration model is presented as a dynamic Bayesian network, which is calibrated using records for metallic girders from railway bridges in the United Kingdom. A Petri net model is then used to perform a life cycle analysis, which incorporates a novel dynamic conditional approach for Petri net modelling to utilise the multiple condition indicators.

Strategies to promote collaborative governance regime in Indian rural road maintenance

PurposeEffective maintenance of rural roads is an essential aspect of public infrastructure delivery. However, governments failed to upkeep the built infrastructure. Accordingly, this study addresses this pressing issue by identifying attributes, skills and resources for asset maintenance. To do this, collaborative governance, a recent plausible alternative in the public policy literature, is used.Design/methodology/approachThe literature review proffered 29 strategies for operationalising collaborative governance principles. A questionnaire survey with the public sector representatives comprising top-level, mid-level and lower-level engineers was used to test the applicability of these strategies in rural infrastructure maintenance of India. The rated responses concerning strategies were subjected to exploratory factor analysis to determine the underlying structure for reducing the dimensions to make them practically operational.FindingsThe exploratory factor analysis showed that six dimensions play an essential role in initiating and promoting collaboration. This parsimonious framework suggests building a common collaborative framework, communicating vision and fostering communities, leadership, increasing the industry's capacity, transparency of power and responsibilities, and technical and financial resources. Thus, governments’ initiatives to build collaboration is most prominent in initiating and sustaining a successful collaboration.Practical implicationsThe practical strategies reinforced through this study can formalise self-initiated regimes or independently convened regimes to a federally directed regime well within the scope of the national programmes. Thus, findings primarily have considerable implications to emerging countries where reducing the unit costs to save the public exchequer from wastage and preventing assets from becoming dilapidate are essential.Originality/valuePublic sector practitioners often lack the essential skills and innovative thinking and thus offered new knowledge would transform the traditional practices in infrastructure maintenance. Theoretically, the present research advances the understanding of structures and processes for collaborative governance theory to non-contractual infrastructure asset management literature.

Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Abstract Analytical tools used in infrastructure asset management of urban water pipe networks are reliant on asset data. Traditionally, data required by analytical tools has not been collected by most water utilities because it has not been needed. The data that is collected might be characterised by low availability, integrity and consistency. A process is required to support water utilities in assessing the accuracy and completeness of their current data management approach and defining improvement pathways in relation to their objectives. This study proposes a framework to enable increased data-driven asset management in pipe networks. The theoretical basis of the framework was a literature review of data management for pipe network asset management and its link to the coherence of set objectives. A survey to identify the current state of data management practice and challenges of asset management implementation in five Swedish water utilities and three focus group workshops with the same utilities was carried out. The main findings of this research were that the quality of pipe network datasets and lack of interoperability between asset management tools are drivers for creating data silos between asset management levels, which may hinder the implementation of data-driven asset management. Furthermore, these findings formed the basis for the proposed conceptual framework. The suggested framework aims to support the selection, development and adoption of improvement pathways to enable increased data-driven asset management in municipal pipe networks. Results from a preliminary application of the proposed framework are also presented.

A risk-informed decision support tool for the strategic asset management of railway track infrastructure

The provision of safe, efficient, reliable and affordable railway transport requires the railway track infrastructure to be maintained to an appropriate condition. Given the constrained budgets under which the infrastructure is managed, maintenance needs to be predicted in advance of track failure, prioritized and identified risks and uncertainties need to be considered within the decision-making process. This paper describes a risk-informed approach that can be used to economically justify railway track infrastructure conditions by comparing on a life-cycle basis infrastructure maintenance costs, train operating costs, travel time costs, safety, social and environmental impacts. The approach represents a step-change for the railway industry as it will enable economic maintenance standards to be derived which considers the needs of the infrastructure operator, but also those of users, train operating companies and the environment. Further, the risk-informed capability of the tool enables asset managers to deal with uncertainties associated with forecasting costs and the effects of track maintenance, and unavailability of data. The Monte Carlo simulation technique and a Fuzzy reasoning approach are used to address safety data uncertainties through probabilistic risk assessment allied to expert opinion. The approach is illustrated using data from three routes on the UK mainline railway network. The results demonstrate that the approach can be used to support strategic and tactical levels of railway asset management to inform plausible design and maintenance strategies that realise the maximum benefit for the available budget.

Willingness to Pay for Improved Water Supply Services Based on Asset Management: A Contingent Valuation Study in South Korea

The pressure on water infrastructure has increased due to an increase in the number of aging water pipes. Aging pipes are prone to failure, causing significant financial losses and service disruptions. The increasing number of aged pipes and limited budget for pipe rehabilitation or replacement necessitates water infrastructure asset management to ensure sustainable water supply services. In this study, contingent valuation was used to estimate the willingness to pay (WTP) and value improved water supply services through the implementation of asset management. To estimate the WTP at the individual and county levels, we performed a nationwide survey including eight provinces and 24 counties/cities with distinct water supply service performances. At the individual level, the median WTP estimated using the double-bounded dichotomous choice model was 249.50 KRW/month (0.22 USD/month). The results showed that high-level satisfaction of customers with water supply services and positive price perception of water bills resulted in a high WTP. At the county level, decreasing water supply service performances were associated with a low WTP, indicating that proper interventions by local utilities are required to achieve sustainable water supply services. Our results provide a quantitative basis for decision-making in implementation of water infrastructure asset management.

Comparative study of Infrastructure Asset Management (IAM) between Papah irrigation areas in Indonesia and Cu-Chi irrigation areas in Vietnam

Infrastructure Asset Management (IAM) is implemented to overcome problems in the management of the agricultural sector. For example, in this study, the 2 research areas had similar problems, namely the poor water supply system in which the amount of water supplied did not match the initial design. To overcome this problem, IAM implementation in these two areas focuses on Integrated Water Resource Management. The objective of this implementation is that the ratio between the amount of water distributed and the one designed is close to 1 or the same. Based on the research results shown after implementing this IAM this problem was resolved. However, Cu-Chi Irrigation Area is still experiencing problems in the financial sector because the income from the sale of water supply is still far from the initial supply price. Whereas in Papah Irrigation Area this financial problem can be resolved with the implementation of the Irrigation Service Fee (ISF) and better management of the management company. Seeing this result, this ISF system can be applied to DI Cu-Chi to overcome the imbalance problem between the costs incurred for water supply and the revenue from the sale of the water.

Risk-Based Prioritization of Sewer Pipe Inspection from Infrastructure Asset Management Perspective

The escalating number of aging sewer pipes necessitates an infrastructure asset management approach to achieve an efficient budget allocation for maintenance. This study suggests a risk-based prioritization framework for sewer pipe inspection considering the predicted condition of sewer pipes and the criticality of the economic, social and environmental impacts associated with them. The results from both models can be used to evaluate the risk of sewer pipes by classification into risk groups. A risk matrix is used for the classification, and it divides the sewer pipes into five risk groups. The results of this study show an improvement in the accuracy of finding sewer pipes in a bad condition using this framework. The condition prediction model can successfully find sewer pipes with a bad condition with over 70% precision. High-risk sewer pipes are highlighted using the differences in the environmental features as well as in the physical features associated with other sewer pipes. Additionally, through the combination of both the condition and criticality of sewer pipes, the framework systemically prioritizes needed maintenance for sewer pipes with a very bad condition. This prioritization framework is expected to help the process of deciding which sewer pipes should be prioritized within a constrained budget.

Water Infrastructure Asset Management Is Evolving

Infrastructure Asset Management (IAM) is the process by which decisions are made and resources allocated to ensure organisational or societal assets continue to deliver, as required. IAM is an evolving field. We discuss this evolution and present our perspectives on the future direction of IAM. IAM was born as a response to the poor state of maintenance of infrastructure, largely due to lack of resources, and emphasizes the need to prioritize maintenance and renewal using risk-based approaches. The demands on IAM have also continued to evolve as asset systems have become more complex, with multifunctionality, adaptative capacity and nature-based infrastructure, all issues that IAM must now consider. These challenges underpin the changing context of Water Infrastructure Asset Management (WIAM) and the opportunity for WIAM to harness new technical developments from other IAM domains. WIAM will need to continue to evolve, responding to these challenges and take advantage of these opportunities through research and application in collaboration with a relevant education and capacity development agenda.

Metamodel-based state-dependent fragility modeling for Markovian sequential seismic damage assessment

Accurate characterization of seismic damage accumulation is crucial to reliable seismic risk assessment. Emerging research efforts have been devoted to state-dependent fragility modeling considering the impact of sequential earthquake excitations so as to better inform the management of structure and infrastructure assets. However, the current state-dependent fragility models largely rely on simple functional forms conditioned on only a scalar ground motion intensity measure (IM); fragility models are separately developed for different state-transition scenarios, without any joint modeling mechanism to preserve the multivariate nature among the different damage states; and the lack of parameterization further hinders these models from offering pertinent fragility estimates for structural portfolios with uncertain structural parameters. By leveraging advanced ground motion selection and machine learning techniques, this study proposes a novel metamodel-based state-dependent fragility modeling approach that offers superior parameterization and damage classification capability and can be seamlessly integrated into the Markovian sequential seismic damage assessment (SSDA) framework. The proposed fragility modeling approach features a systematic sequential dynamic analysis procedure that leverages efficient experimental design and hazard-consistent ground motion selection to sufficiently cover the feature space, and an artificial neural network (ANN) classification model conditioned on one-hot encoded initial damage states along with other earthquake and structure-related predictors. Based on generic inelastic single-degree-of-freedom (SDOF) systems with varying structural configurations, damage state classification performance of the proposed fragility model is thoroughly evaluated, and its applicability within the Markovian SSDA framework is elaborated and discussed.

An open-source and extensible platform for general infrastructure asset management system

Given the importance of maintaining infrastructure assets, asset management at both project- and network-levels has been the focus of hundreds of studies. Although these studies and previously developed asset management systems have pushed the boundaries of this field, these advances have been made separately without the ability to build upon one another. This paper puts forward the first open-source, extensible, freely accessible, and modular platform developed in Python, GIAMS, paving the way for researchers and practitioners to easily collaborate and contribute to future related research. Drawing upon related literature, this paper describes modules of GIAMS and illustrates their use with bridge components and models. One project-level lifecycle optimization and one network-level project-selection based on the Indiana, US, bridge network with more than 4600 bridges are provided to demonstrate the applicability of GIAMS. The modular and open-source nature of GIAMS makes it readily capable of further extension in a variety of asset management topics.

Multiple repair scheduling of Markovian deteriorated concrete structure

Choice of suitable repair method at proper time can extend lifetime of infrastructure and can reduce overall cost, saves revenue of the government. Maintenance optimization is the most cost-effective solution for infrastructure management system, used by bridge management system (BMS) of several countries. In this paper, deterioration of bridge deck by chloride diffusion is considered as a cause of failure. Monte Carlo simulation was used to develop transition probability matrix that was further used to predict future state through Markov process. This paper attempts to tabulate a schedule of multiple repair required by a Markov-deteriorated concrete structure. Challenges of incorporating different levels of cost and improvements to the facilities, imposed by the multiple repair at different age, were solved by the shortest path algorithm. Recursive equations, in excel solver platform, were used to update failure state of the facility to visualize the necessity of the repair actions. Sensitivity on unequal capacity of failure reduction and non-identical cost incurred by multiple repair methods are presented to estimate maintenance schedule. However, the model, described in this paper may be used as an efficient tool for infrastructure asset management.

Hydropower Sustainability Assessment Protocol (HSAP) Implementation in Indonesia : A mini-review

Sustainability is one of the principles in infrastructure asset management. In a hydropower project, Hydropower Sustainability Tools (HST) are needed in assessing sustainability principles into practice when developing new hydropower projects. International Hydropower Association (IHA) published guidelines consist of three documents; one of them is Hydropower Sustainability Assessment Protocol (HSAP). This study is a mini-review focusing on the implementation of HSAP in hydropower projects in Indonesia, including the Pelosika project in Southeast Sulawesi, the Ir. H. Juanda project, and the Bendung Perjaya project in South Sumatra. HSAP has its advantages and disadvantages, it covers a variation of topics widely, but the assessment is somewhat subjective, time-consuming, and cost-intensive. HSAP is relatively new in Indonesia; there are not many publications regarding this topic. Future studies are recommended to know more about its potential in increasing the sustainability of hydropower projects.

Levels of Uncertainty in Infrastructure Asset Management

The management of infrastructure assets is often challenged by uncertain factors such as changing weather trends and usage patterns. To reliably maintain the assets above a specified level of service, the extent of this uncertainty should be identified, and adequate methods for analyzing the risk factors should be implemented. The analysis of risk is well-defined in the field of strategic management. In the current study, four levels of uncertainty that are widely discussed in strategic management were used as a benchmark to determine the levels of uncertainty in infrastructure asset management. These levels range from known issues, to statistically predictable factors, to complete indeterminacy. The current methods of treating uncertainty in infrastructure asset management were reviewed to determine how they overlap with the four levels of uncertainty and whether or not asset managers handle this uncertainty in an optimal fashion. The current approaches in asset management were found to be primarily deterministic and probabilistic. A shortcoming was found in regard to the incorporation of risk analysis into asset management planning for large-scale networks. The researchers concluded that the level of uncertainty present in asset management at the network planning level can be best described as a range and addressed through the use of representative scenarios within that range.

Infrastructure Asset Management: Referees 2020

<i>Infrastructure Asset Management</i>: Referees 2020

Fundamental References: Infrastructure Asset and Renewable Energy [Book Review

This book provides detailed highlights of infrastructure asset management issues. The author points out that infrastructure asset management can be expressed as a combination of managerial, financial, economic, and engineering concepts applied to physical assets. Infrastructure asset management is a wide field that covers different expertise areas. It includes the whole lifecycle of an asset: design, construction, commission, operation, maintenance, modification, decommissioning, and disposal. There are budget constraints, which result in the need for a strategy for asset management. The electric power system is a massive infrastructure to manage the supply of electricity from generation to consumption. The electric power system is undergoing a major reconstruction, which is captured in the concept of a smart grid. The main drivers are higher reliability, climate change, and customer participation in sustainable energy. This book provides readers with knowledge of the terminology and theory used. It provides different analysis tools and examples to use for electric power system applications. The book focuses on energy infrastructure asset management. It shows systematic techniques, such as reliability- centered maintenance (RCM) and reliability-centered asset maintenance (RCAM). These are used to achieve infrastructure asset management strategies. The RCM method focuses on maintenance plans’ reliability aspects. Maintenance and reliability are large costs not only as maintenance tasks but also as production and breakdowns costs. Breakdown consequences affect the environment and/or personal safety. The RCAM method combines RCM with maintenance-optimization techniques. Merging these approaches provides an instrument for maintenance strategy assessment and comparisons. The author eloquently presents that new technology developments provide enhanced solutions for asset management. One new general trend is control and operation with phasor measurement units located in transmission grids or with smart meters placed at consumer sites to enable the integration of distributed resources with distributed energy-use control.

Developing Pavement Marking Management Systems: A Theoretical Model Framework Based on the Experiences of the US Transportation Agencies

Pavement markings are essential elements of transportation infrastructure with critical impacts on safety and mobility. They provide road users with the necessary information to adjust driving behavior or make calculated decisions about commuting. The visibility of pavement markings for drivers can be the boundary between a safe trip and a disastrous accident. Consequently, transportation agencies at the local or national levels allocate sizeable budgets to upkeep the pavement markings under their jurisdiction. Infrastructure asset management systems (IAMS) are often biased toward high-capital-cost assets such as pavements and bridges, not providing structured asset management (AM) plans for low-cost assets such as pavement markings. However, recent advances in transportation asset management (TAM) have promoted an integrated approach involving the pavement marking management system (PMMS). A PMMS brings all data items and processes under a comprehensive AM plan and enables managing pavement markings more efficiently. Pavement marking operations depend on location, conditions, and AM policies, highly diversifying the pavement marking management practices among agencies and making it difficult to create a holistic image of the system. Most of the available resources for pavement marking management focus on practices instead of strategies. Therefore, there is a lack of comprehensive guidelines and model frameworks for developing PMMS. This study utilizes the existing body of knowledge to build a guideline for developing and implementing PMMS. First, by adapting the core AM concepts to pavement marking management, a model framework for PMMS is created, and the building blocks and elements of the framework are introduced. Then, the caveats and practical points in PMMS implementation are discussed based on the US transportation agencies’ experiences and the relevant literature. This guideline is aspired to facilitate PMMS development for the agencies and pave the way for future pavement marking management tools and databases.

ІННОВАЦІЙНО-ЛЮДСЬКИЙ ПОТЕНЦІАЛ У МЕНЕДЖМЕНТІ БУДІВЕЛЬНОЇ ГАЛУЗІ

During the operation of infrastructure assets excessive action of transport and natural vibrations, water-heat and low-temperature fluctuations, soil leaching leads to undesirable changes in the current criteria of their safety, premature technical wear of surfaces, cracks, irregularities, subsidence, increased seismic fluctuations and floods. sustainability of infrastructure assets. Taking into account the above negative trends, the article analyzes the positive and negative factors of the impact of innovation – human capital on management in the construction industry. Innovative – human capital of labor resources in the context of global digitalization requires constant professional development, human ability to effective research and innovation, it emphasizes the importance of updating educational programs in the global context and the principles of sustainable development. Therefore in the specified conditions harmonization of university business – education in the field of processes and technologies of management in building construction is a priority. In general, the strategies, technologies and processes of corporate management of infrastructure assets operating in the latest global conditions are actively used in such projects as interdisciplinary cooperation and partnership of stakeholders, including universities; city, departments for infrastructure asset management; international corporations; transfer of intellectual capital, exponential training of the young generation and transprofessionalization of the working population; "green" clean cities; protection and preservation / preservation of cultural heritage; design and operation of "smart" road systems; digital infrastructure; conservation / preservation of the marine ecosystem; rehabilitation / rejuvenation of existing funds. It is expected that the results of research should contribute to the real provision of quality management in the construction industry, innovative technologies and processes of urban management, planning, development, reconstruction and operation of settlements and regions to meet the needs of the population and business – production.

A resource allocation framework for predisaster resilience management of interdependent infrastructure networks

PurposeResource allocation is essential to infrastructure management. The purpose of this study is to develop a methodological framework for resource allocation that takes interdependencies among infrastructure systems into consideration to minimize the overall impact of infrastructure network disruptions due to extreme events.Design/methodology/approachTaking advantage of agent-based modeling techniques, the proposed methodology estimates the interdependent effects of a given infrastructure failure which are then used to optimize resource allocation such that the network-level resilience is maximized.FindingsThe findings of the study show that allocating resources with the proposed methodology, where optimal infrastructure reinforcement interventions are implemented, can improve the resilience of infrastructure networks with respect to both direct and interdependent risks of extreme events. These findings are also verified by the results of two case studies.Practical implicationsAs the two case studies have shown, the proposed methodological framework can be applied to the resource allocation process in asset management practices.Social implicationsThe proposed methodology improves the resilience of the infrastructure network, which can alleviate the social and economic impact of extreme events on communities.Originality/valueCapitalizing on the combination of agent-based modeling and simulation-based optimization techniques, this study fulfills a critical gap in infrastructure asset management by incorporating infrastructure interdependence and resilience concepts into the resource allocation process.

Maturity Improvements in Flood Protection Asset Management across the North Sea Region

North Sea Region countries depend heavily on flood protection infrastructure, such as dikes, dams, sluices and flood gates. Knowledge on where, when and how much to invest to ensure functioning is of crucial importance for asset owners and operators. This requires asset management approaches that are adaptable, respond to feedback and function within various contexts. The FAIR (Flood defense infrastructure Asset management &amp; Investment in Renovation, adaptation, optimisation and maintenance) project has developed a unique framework to ensure that asset management processes are adaptive, comprehensive and make effective connections across strategic, tactical and operational contexts. The framework has for the first time informed an assessment of maturity of five flood protection asset management organisations in the North Sea Region, using a seven-factor maturity assessment model. This paper describes the self-assessment process and the self-reported maturity changes during the project. Maturity assessments were undertaken on two occasions, at the start of the project, and again toward the end. This has revealed how the baseline level of maturity for each organisation developed over the course of the three-year project. The observed maturity changes indicate that adopting the FAIR framework has added value in improving current approaches to asset management.