South Africa is facing significant water infrastructure investment challenges, both at the level of water resources and services. Principles for water use pricing, charges, tariffs and use are enshrined in South African legislation but implementation thereof is a major problem. The research paper addresses: 1) economic costs; 2) efficiencies; 3) investment challenges; and iv) the application and maximisation of economic tools. A total of 269 municipalities were sampled and the research exemplified that South Africa was losing ca. US$0.617 – 1.033 billion/annum to various inefficiencies: 1) water use under-pricing was ca. US$0.413 billion/annum. Water use charges and/or tariffs closer to cost-recovery levels would provide and ensure financial sustainability; 2) Return on capital investment inefficiencies contributed ca. US$0.926 billion/annum. Revenue far lower than asset value is illustrative of unsustainable revenue for investments; 3) non-revenue water (NRW) was 36.8% and ca. US$0.402 billion/annum. Investments in water infrastructure maintenance projects will minimise distribution losses; 4) the multipliers were varied and substantially high, viz. 3 – 27. This illustrates the extent and seriousness of prioritising the implementation of water conservation and demand management measures; and 5) The capital investment gap was estimated at US$2.258 billion/annum for the next ten (10) years (2019/20 – 2029/30). Under capital investments have serious downstream implications for socio-economic development and growth.
{"title":"Economic costs, efficiencies and challenges of investments in the provision of sustainable water infrastructure supply systems in South Africa","authors":"C. Ruiters, J. Amadi-Echendu","doi":"10.1680/jinam.21.00014","DOIUrl":"https://doi.org/10.1680/jinam.21.00014","url":null,"abstract":"South Africa is facing significant water infrastructure investment challenges, both at the level of water resources and services. Principles for water use pricing, charges, tariffs and use are enshrined in South African legislation but implementation thereof is a major problem. The research paper addresses: 1) economic costs; 2) efficiencies; 3) investment challenges; and iv) the application and maximisation of economic tools. A total of 269 municipalities were sampled and the research exemplified that South Africa was losing ca. US$0.617 – 1.033 billion/annum to various inefficiencies: 1) water use under-pricing was ca. US$0.413 billion/annum. Water use charges and/or tariffs closer to cost-recovery levels would provide and ensure financial sustainability; 2) Return on capital investment inefficiencies contributed ca. US$0.926 billion/annum. Revenue far lower than asset value is illustrative of unsustainable revenue for investments; 3) non-revenue water (NRW) was 36.8% and ca. US$0.402 billion/annum. Investments in water infrastructure maintenance projects will minimise distribution losses; 4) the multipliers were varied and substantially high, viz. 3 – 27. This illustrates the extent and seriousness of prioritising the implementation of water conservation and demand management measures; and 5) The capital investment gap was estimated at US$2.258 billion/annum for the next ten (10) years (2019/20 – 2029/30). Under capital investments have serious downstream implications for socio-economic development and growth.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"55 5 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83335160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Bouch, E. Shrimpton, Lewis O. Makana, Bryony Bowman, Christopher D F Rogers
Research has shown that value generation is an important factor when it comes to driving technological change. It follows that business models as narratives of value generation and capture have an important part to play as the end-goals in the change process. Research also suggests, however, that the understanding of when, why and how value accrues to stakeholders, and what value to create, appears to be lacking. This paper describes an objective and repeatable methodology for the identification of benefit and value-generating opportunities that can be used to aid business model creation. The methodology is demonstrated for the generic business of infrastructure asset management and discussed in more detail in the context of ‘Pipebots’, a current, scientific research project into the introduction of robotic and autonomous systems to the asset management of buried water and sewage pipe networks in the United Kingdom (UK). In conclusion the paper proposes that the methodology opens the door to a future where radical change in a given infrastructure system can lead to value capture across the wider system-of-systems.
{"title":"Robotic autonomous asset management: benefit/value-based business model creation","authors":"C. Bouch, E. Shrimpton, Lewis O. Makana, Bryony Bowman, Christopher D F Rogers","doi":"10.1680/jinam.21.00022","DOIUrl":"https://doi.org/10.1680/jinam.21.00022","url":null,"abstract":"Research has shown that value generation is an important factor when it comes to driving technological change. It follows that business models as narratives of value generation and capture have an important part to play as the end-goals in the change process. Research also suggests, however, that the understanding of when, why and how value accrues to stakeholders, and what value to create, appears to be lacking. This paper describes an objective and repeatable methodology for the identification of benefit and value-generating opportunities that can be used to aid business model creation. The methodology is demonstrated for the generic business of infrastructure asset management and discussed in more detail in the context of ‘Pipebots’, a current, scientific research project into the introduction of robotic and autonomous systems to the asset management of buried water and sewage pipe networks in the United Kingdom (UK). In conclusion the paper proposes that the methodology opens the door to a future where radical change in a given infrastructure system can lead to value capture across the wider system-of-systems.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"28 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90092688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Obinna Akaa, Damien Douglas, David Arrowsmith, M. Darnell
The reinstatement of pavement markings after resurfacing will typically entail like-for-like remarking of the resealed road sections. However, there are cases where sections in between planned reseal (infills) may be left - untouched or are not required in the renewal contract irrespective of infill markings’ service life and condition. This gives room for poor marking continuity and reduction of the markings service level. As the asset management of long-life high-performance markings includes a duty of care around cost-effectively realising value from planned maintenance, there is the need to consider infills when reinstating long-life markings on resurfaced road sections. This paper presents a method to determine infill sites for cost-effective renewal to forestall returning to the same road in the future, thereby managing customer delay and realising cost savings without compromising road safety. The method considers tactical assessment merits and lifecycle costs to demonstrate its suitability to solve the problem. Various markings reinstatement cases were investigated where the results showed method applicability and highlighted sensitivities to remark length and installation time. The method supports the asset owner/manager to plan pavement markings renewals at the tactical/section level and could benefit from further studies that consider more complex scenarios, extended variables, and uncertainties.
{"title":"An asset management methodology for value-for-money reinstatement of pavement markings","authors":"Obinna Akaa, Damien Douglas, David Arrowsmith, M. Darnell","doi":"10.1680/jinam.21.00026","DOIUrl":"https://doi.org/10.1680/jinam.21.00026","url":null,"abstract":"The reinstatement of pavement markings after resurfacing will typically entail like-for-like remarking of the resealed road sections. However, there are cases where sections in between planned reseal (infills) may be left - untouched or are not required in the renewal contract irrespective of infill markings’ service life and condition. This gives room for poor marking continuity and reduction of the markings service level. As the asset management of long-life high-performance markings includes a duty of care around cost-effectively realising value from planned maintenance, there is the need to consider infills when reinstating long-life markings on resurfaced road sections. This paper presents a method to determine infill sites for cost-effective renewal to forestall returning to the same road in the future, thereby managing customer delay and realising cost savings without compromising road safety. The method considers tactical assessment merits and lifecycle costs to demonstrate its suitability to solve the problem. Various markings reinstatement cases were investigated where the results showed method applicability and highlighted sensitivities to remark length and installation time. The method supports the asset owner/manager to plan pavement markings renewals at the tactical/section level and could benefit from further studies that consider more complex scenarios, extended variables, and uncertainties.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"5 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79091657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Determining how infrastructure corridors are to be optimally designed and modified over time is challenging due to the considerable uncertainty associated with potential changes in mobility patterns. This is because of factors such as the dynamisms of urban areas and the potential of transitioning to autonomous vehicles. Although currently this future uncertainty is taken into consideration in decisions with respect to highway designs and modifications in a qualitative manner, there is potential benefit to using quantitative methods and explicitly considering how highways may be modified in the future as a function of the actual future that emerges. In this article, the use of a quantitative evaluation method using real options is explored to evaluate highway designs, considering uncertainties in future mobility patterns and management flexibility. The usefulness of the method is investigated on the fictive but realistic case study based on the completion of the A15 highway, in the canton of Zürich, Switzerland. The results of this exploratory work indicate significant value in the use of the proposed method to ensure that infrastructure networks are optimally prepared to support society in an unknown future, and it is expected that it can be used more extensively in future spatial planning.
{"title":"Evaluating highway designs considering uncertain mobility patterns and flexibility using real options","authors":"C. Martani, Steven Eberle, B. Adey","doi":"10.1680/jinam.21.00018","DOIUrl":"https://doi.org/10.1680/jinam.21.00018","url":null,"abstract":"Determining how infrastructure corridors are to be optimally designed and modified over time is challenging due to the considerable uncertainty associated with potential changes in mobility patterns. This is because of factors such as the dynamisms of urban areas and the potential of transitioning to autonomous vehicles. Although currently this future uncertainty is taken into consideration in decisions with respect to highway designs and modifications in a qualitative manner, there is potential benefit to using quantitative methods and explicitly considering how highways may be modified in the future as a function of the actual future that emerges. In this article, the use of a quantitative evaluation method using real options is explored to evaluate highway designs, considering uncertainties in future mobility patterns and management flexibility. The usefulness of the method is investigated on the fictive but realistic case study based on the completion of the A15 highway, in the canton of Zürich, Switzerland. The results of this exploratory work indicate significant value in the use of the proposed method to ensure that infrastructure networks are optimally prepared to support society in an unknown future, and it is expected that it can be used more extensively in future spatial planning.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"21 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86077556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The construction of highway projects is characterised by cost overruns and time delays, due to the estimation approach and inappropriate analytical tools to predict uncertainty. The study therefore developed a hybrid intelligent tool that models three sources of uncertainty in linear infrastructure projects: variability, correlation and disruptive events. The developed tool measures uncertainties’ effect on cost and time of projects, by combining classical and intelligence prediction techniques. The variabilities were modelled using probability distributions; the Copula technique modelled the correlations. The Markov processes simulated the occurrence of disruptive events. The Adaptive Neuro-Fuzzy Inference System was used to assess the size of impact of disruptive events on cost and time of activities. The total project cost and time were simulated by propagating the impact of the three sources of uncertainty in the Monte Carlo simulation environment. The developed uncertainty model was validated against the final cost and time of a highway project. The study found that the accumulated impact of the three sources of uncertainty significantly increased the construction cost and time of infrastructure projects. It concludes that the improvement in accuracy of cost and time estimation of highway projects depends on a combination of classical and intelligent prediction techniques.
{"title":"Modelling uncertainty of cost and time in highway projects","authors":"A. Moghayedi","doi":"10.1680/jinam.21.00004","DOIUrl":"https://doi.org/10.1680/jinam.21.00004","url":null,"abstract":"The construction of highway projects is characterised by cost overruns and time delays, due to the estimation approach and inappropriate analytical tools to predict uncertainty. The study therefore developed a hybrid intelligent tool that models three sources of uncertainty in linear infrastructure projects: variability, correlation and disruptive events. The developed tool measures uncertainties’ effect on cost and time of projects, by combining classical and intelligence prediction techniques. The variabilities were modelled using probability distributions; the Copula technique modelled the correlations. The Markov processes simulated the occurrence of disruptive events. The Adaptive Neuro-Fuzzy Inference System was used to assess the size of impact of disruptive events on cost and time of activities. The total project cost and time were simulated by propagating the impact of the three sources of uncertainty in the Monte Carlo simulation environment. The developed uncertainty model was validated against the final cost and time of a highway project. The study found that the accumulated impact of the three sources of uncertainty significantly increased the construction cost and time of infrastructure projects. It concludes that the improvement in accuracy of cost and time estimation of highway projects depends on a combination of classical and intelligent prediction techniques.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"6 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89588278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saviz Moghtadernejad, G. Huber, Jürgen Hackl, B. Adey
A significant portion of railway network income is spent on the maintenance and restoration of the railway infrastructure to ensure that the networks continue to provide the expected level of service. The execution of the interventions – that is, when and where to perform maintenance or restoration activities, depends on how the state of the infrastructure assets changes over time. Such information helps ensure that appropriate interventions are selected to reduce the deterioration speed and to maximise the effect of the expenditure on monitoring, maintenance, repair and renewal of the assets. Presently, there is an explosion of effort in the investigation and use of data-driven methods to estimate deterioration curves. However, real-world time history data normally includes measurement of errors and discrepancies that should not be neglected. These errors include missing information, discrepancies in input data and changes in the condition rating scheme. This paper provides solutions for addressing these issues using machine learning algorithms, estimates the deterioration curves for railway supporting structures using Markov models and discusses the results.
{"title":"Data-driven estimation of deterioration curves: a railway supporting structures case study","authors":"Saviz Moghtadernejad, G. Huber, Jürgen Hackl, B. Adey","doi":"10.1680/jinam.21.00006","DOIUrl":"https://doi.org/10.1680/jinam.21.00006","url":null,"abstract":"A significant portion of railway network income is spent on the maintenance and restoration of the railway infrastructure to ensure that the networks continue to provide the expected level of service. The execution of the interventions – that is, when and where to perform maintenance or restoration activities, depends on how the state of the infrastructure assets changes over time. Such information helps ensure that appropriate interventions are selected to reduce the deterioration speed and to maximise the effect of the expenditure on monitoring, maintenance, repair and renewal of the assets. Presently, there is an explosion of effort in the investigation and use of data-driven methods to estimate deterioration curves. However, real-world time history data normally includes measurement of errors and discrepancies that should not be neglected. These errors include missing information, discrepancies in input data and changes in the condition rating scheme. This paper provides solutions for addressing these issues using machine learning algorithms, estimates the deterioration curves for railway supporting structures using Markov models and discusses the results.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"73 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74396682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Penstocks have been used in the water industry for flow control since the Victorian expansion and consolidation of clean and waste water networks. However, the Victorians were the first to use grey cast iron (GCI) castings to manufacture large scale penstocks. Most of these ageing assets are still in operation, however engineering assessments are necessary to determine a structure’s fitness-for-service. Even today, penstocks in the sewer system tend to be made from GCI, due to ease of manufacturing, resistance to corrosion and cost. One characteristic property of grey cast iron is the graphite flake structure in the material, contributing to its low toughness, inconsistency in material strength and brittle behaviour, despite exhibiting slight hardening properties. Finite element analysis (FEA), is a numerical method which allows the analysis of complex structures by splitting it into finite parts and solving them with a computer processor. Despite the versatility of FEA, appropriate considerations and assumptions are necessary due to the difficulty to obtain data from inspection and unique material behaviour of GCI. The article shows concerns for an analysis of GCI penstocks using FEA, which extends into the application of fracture mechanics approaches for defect assessments.
{"title":"FEA on Grey Cast Iron Assets: A Case Study on Penstocks in the Waste Water System","authors":"W. Khor, J. Farrow, M. Mulheron, D. Jesson","doi":"10.1680/jinam.21.00019","DOIUrl":"https://doi.org/10.1680/jinam.21.00019","url":null,"abstract":"Penstocks have been used in the water industry for flow control since the Victorian expansion and consolidation of clean and waste water networks. However, the Victorians were the first to use grey cast iron (GCI) castings to manufacture large scale penstocks. Most of these ageing assets are still in operation, however engineering assessments are necessary to determine a structure’s fitness-for-service. Even today, penstocks in the sewer system tend to be made from GCI, due to ease of manufacturing, resistance to corrosion and cost. One characteristic property of grey cast iron is the graphite flake structure in the material, contributing to its low toughness, inconsistency in material strength and brittle behaviour, despite exhibiting slight hardening properties. Finite element analysis (FEA), is a numerical method which allows the analysis of complex structures by splitting it into finite parts and solving them with a computer processor. Despite the versatility of FEA, appropriate considerations and assumptions are necessary due to the difficulty to obtain data from inspection and unique material behaviour of GCI. The article shows concerns for an analysis of GCI penstocks using FEA, which extends into the application of fracture mechanics approaches for defect assessments.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"383 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78014418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bridge management professionals need effective tools to help guide the decision-making process and maintain quality infrastructure in a region. A new binary response is herein defined by categorizing bridges as at-risk and not at-risk, based on the existing overall bridge condition scores. Fitting binary logistic regression model for the response, the probability of a bridge being at-risk is expressed in terms of the primary bridge factors age, load, types of construction material and structural design, and conditions of the deck, superstructure, and substructure. These estimated probabilities multiplied by specified consequence values are used to introduce the risk classes and their ranks. Employing the method for training and validating sets of sizes 13,540 and 3,385 in 2017, and 13,481 and 3,370 in 2018 data in National Bridge Inventory (NBI) Indiana, a statistically significant model is established containing age, load, conditions of both superstructure and substructure. Moreover, at-risk bridges are identified from Indiana NBI data in both years and for a subset from Connecticut in 2017. The novel bridge-ranking tool prioritizes bridges for maintenance purposes such as replacing or repairing and hence efficiently guides the management in the decision-making process for capital expenditures, and perhaps, for predicting the missing overall bridge condition.
{"title":"Binary Logistic Regression Approach for Decision Making in Bridge Management","authors":"U. Wijesuriya, Adam G. Tennant","doi":"10.1680/jinam.21.00011","DOIUrl":"https://doi.org/10.1680/jinam.21.00011","url":null,"abstract":"Bridge management professionals need effective tools to help guide the decision-making process and maintain quality infrastructure in a region. A new binary response is herein defined by categorizing bridges as at-risk and not at-risk, based on the existing overall bridge condition scores. Fitting binary logistic regression model for the response, the probability of a bridge being at-risk is expressed in terms of the primary bridge factors age, load, types of construction material and structural design, and conditions of the deck, superstructure, and substructure. These estimated probabilities multiplied by specified consequence values are used to introduce the risk classes and their ranks. Employing the method for training and validating sets of sizes 13,540 and 3,385 in 2017, and 13,481 and 3,370 in 2018 data in National Bridge Inventory (NBI) Indiana, a statistically significant model is established containing age, load, conditions of both superstructure and substructure. Moreover, at-risk bridges are identified from Indiana NBI data in both years and for a subset from Connecticut in 2017. The novel bridge-ranking tool prioritizes bridges for maintenance purposes such as replacing or repairing and hence efficiently guides the management in the decision-making process for capital expenditures, and perhaps, for predicting the missing overall bridge condition.","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"PP 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84605600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Climate-Resilient Road Infrastructure in Coastal Areas Subjected to Cyclones and Associated Floods","authors":"U. Sahoo, S. R. Dash, C. S. Sahu","doi":"10.1680/jinam.21.00010","DOIUrl":"https://doi.org/10.1680/jinam.21.00010","url":null,"abstract":"","PeriodicalId":43387,"journal":{"name":"Infrastructure Asset Management","volume":"13 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90533882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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