The condition and deterioration of a railway track over time has a major influence on its maintenance demands, service life and consequently its life cycle costs. Railway track condition is currently assessed on the basis of manual inspections, wayside equipment and measurements performed by a measurement car. This paper deals with combining the advantages of above assessment technologies, allowing continuous and permanent measurements for the entire network. On the one hand, we use Distributed Acoustic Sensing, a methodology relying on the effect of Rayleigh backscattering. This technology uses fibre optic cables, which are already installed in cable troughs alongside railway tracks and used for telecommunication or signalling. On the other hand, fractal analysis of vertical track geometry allows for a componentspecific condition evaluation, i.e. distinguishing the root cause of an irregularity in track geometry. Correlating both methodologies should show whether or not/to what and to what extent this innovative methodology of using fibre optic cables is applicable for assessing the component specific condition of a railway track. The proposed combination of both methodologies paves the way for real time condition assessment of railway track.
{"title":"Fibre Optic Sensing as Innovative Tool for Evaluating Railway Track Condition?","authors":"Ivan Vidovic, M. Landgraf","doi":"10.1680/ICSIC.64669.107","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.107","url":null,"abstract":"The condition and deterioration of a railway track over time has a major influence on its maintenance demands, service life and consequently its life cycle costs. Railway track condition is currently assessed on the basis of manual inspections, wayside equipment and measurements performed by a measurement car. This paper deals with combining the advantages of above assessment technologies, allowing continuous and permanent measurements for the entire network. On the one hand, we use Distributed Acoustic Sensing, a methodology relying on the effect of Rayleigh backscattering. This technology uses fibre optic cables, which are already installed in cable troughs alongside railway tracks and used for telecommunication or signalling. On the other hand, fractal analysis of vertical track geometry allows for a componentspecific condition evaluation, i.e. distinguishing the root cause of an irregularity in track geometry. Correlating both methodologies should show whether or not/to what and to what extent this innovative methodology of using fibre optic cables is applicable for assessing the component specific condition of a railway track. The proposed combination of both methodologies paves the way for real time condition assessment of railway track.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133035115","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}
D. Xu, H. Chong, I. Main, M. Mineter, R. Bold, M. Forde, C. Gair, P. Madden, E. Angus, C. Ho
{"title":"Using Statistical Models and Machine Learning Techniques to Process Big Data from the Forth Road Bridge","authors":"D. Xu, H. Chong, I. Main, M. Mineter, R. Bold, M. Forde, C. Gair, P. Madden, E. Angus, C. Ho","doi":"10.1680/ICSIC.64669.411","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.411","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116684883","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. Chen, H. Seo, Y. Zhao, B. Chen, J. W. Kim, Y. Choi, M. Bang
{"title":"Pavement Damage Detection System Using Big Data Analysis of Multiple Sensor","authors":"C. Chen, H. Seo, Y. Zhao, B. Chen, J. W. Kim, Y. Choi, M. Bang","doi":"10.1680/ICSIC.64669.559","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.559","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129789299","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}
E. O’Dwyer, Indranil Pan, Indranil Pan, S. Izquierdo, S. Gibbons, N. Shah
Energy demand growth and the rapid rate of technological change in an urban context are already having an impact on our energy systems. Considering global ambitions to reduce carbon emissions and minimise the rate and impacts of climate change, this demand will need to be met with energy from low carbon sources. Increased electrification of heat and transport networks is anticipated, however, the crosssectoral impacts of different interventions in these systems must be better understood to prevent gains in one system leading to losses in another while ensuring financial benefits for producers and consumers. As such, evaluating the impacts of specific interventions can be a challenge, with analyses typically focussed on individual systems. In this paper, a simulation environment is developed to capture the behaviour of interconnected heat, power and transport networks in an urban environment to act as a ‘digital twin’ for the energy systems of a district or city. The modelling environment illustrated here is based on the smart city interventions in Greenwich (London), with model validation carried out using real data measurements. Building retrofit and heat electrification interventions are demonstrated in terms of costs, energy consumption and CO2 emissions, considering constraints on power and thermal systems.
{"title":"Modelling and Evaluation of Multi-Vector Energy Networks in Smart Cities","authors":"E. O’Dwyer, Indranil Pan, Indranil Pan, S. Izquierdo, S. Gibbons, N. Shah","doi":"10.1680/ICSIC.64669.161","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.161","url":null,"abstract":"Energy demand growth and the rapid rate of technological change in an urban context are already having an impact on our energy systems. Considering global ambitions to reduce carbon emissions and minimise the rate and impacts of climate change, this demand will need to be met with energy from low carbon sources. Increased electrification of heat and transport networks is anticipated, however, the crosssectoral impacts of different interventions in these systems must be better understood to prevent gains in one system leading to losses in another while ensuring financial benefits for producers and consumers. As such, evaluating the impacts of specific interventions can be a challenge, with analyses typically focussed on individual systems. In this paper, a simulation environment is developed to capture the behaviour of interconnected heat, power and transport networks in an urban environment to act as a ‘digital twin’ for the energy systems of a district or city. The modelling environment illustrated here is based on the smart city interventions in Greenwich (London), with model validation carried out using real data measurements. Building retrofit and heat electrification interventions are demonstrated in terms of costs, energy consumption and CO2 emissions, considering constraints on power and thermal systems.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121633879","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":"Evaluating the Deterioration of Geotechnical Infrastructure Assets Using Performance Curves","authors":"K. Briggs, T. Dijkstra, S. Glendinning","doi":"10.1680/ICSIC.64669.429","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.429","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131940241","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 condition of masonry arch bridges is predominantly monitored with manual visual inspection. This process has been found to be subjective, relying on an inspection engineer’s interpretation of the condition of the structure. This paper initially presents a workflow that has been developed that can be used by a future automated bridge monitoring system to determine underlying faults in a bridge and suggest appropriate remedial action based on a set of detectable symptoms. This workflow has been used to identify the main classes of defects that an automated visual detection system for masonry should be capable of detecting. Subsequently, a convolutional neural network is used to classify these identified defect classes from images of masonry. As the mortar joints in the masonry are more distinctive than the defects being sought, their effect on the performance of an automated defect classifier is investigated. Compared to classifying all the regions of the masonry with a single classifier, it is found that where the mortar and brick regions have been classified separately, defect and defect free areas of the masonry have been predicted both with more confidence and with better accuracy.
{"title":"Automated Defect Detection For Masonry Arch Bridges","authors":"D. Brackenbury, I. Brilakis, M. DeJong","doi":"10.1680/ICSIC.64669.003","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.003","url":null,"abstract":"The condition of masonry arch bridges is predominantly monitored with manual visual inspection. This process has been found to be subjective, relying on an inspection engineer’s interpretation of the condition of the structure. This paper initially presents a workflow that has been developed that can be used by a future automated bridge monitoring system to determine underlying faults in a bridge and suggest appropriate remedial action based on a set of detectable symptoms. This workflow has been used to identify the main classes of defects that an automated visual detection system for masonry should be capable of detecting. Subsequently, a convolutional neural network is used to classify these identified defect classes from images of masonry. As the mortar joints in the masonry are more distinctive than the defects being sought, their effect on the performance of an automated defect classifier is investigated. Compared to classifying all the regions of the masonry with a single classifier, it is found that where the mortar and brick regions have been classified separately, defect and defect free areas of the masonry have been predicted both with more confidence and with better accuracy.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121224294","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":"Instrumentation and Monitoring of a Concrete Jacking Pipe","authors":"B. M. Phillips, R. Royston, B. Sheil, B. Byrne","doi":"10.1680/ICSIC.64669.457","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.457","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126266269","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}
V. Macchiarulo, G. Giardina, P. Milillo, J. Martí, Juan Sánchez, M. DeJong
{"title":"Settlement-Induced Building Damage Assessment Using MT-Insar Data for the Crossrail Case Study in London","authors":"V. Macchiarulo, G. Giardina, P. Milillo, J. Martí, Juan Sánchez, M. DeJong","doi":"10.1680/ICSIC.64669.721","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.721","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134055908","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}
Building Information Modelling (BIM) involves the exchange of models and information between stakeholders and within collaborating teams. This information is prone to contractual, legal, security and system issues amongst others. The existing practices aim to address a digital concept such as BIM with solutions from the paper world – contracts and other documents, which do not solve the problem completely. A recent advancement in database management – Blockchain Technology (BCT) aims to provide a new stream of solutions to industries across various sectors. BCT is a system of recording a database that stores information chronologically and distributes a copy of it over a network of computers that maintain its authenticity and security collectively. This paper first reviews the literature on the issues of information exchange in a BIM workflow and next explores the concept of BCT and its connection with BIM. The literature indicates that BCT shows high potential for solving challenges during the design phase of the project by clarifying liabilities, increasing the reliability of information and enhancing the security of information flow. Its ability to incorporate self-executing contracts enable many more applications around ownership and payments. Finally, the paper discusses a few of its challenges with scalability, user acceptance amongst others.
{"title":"Leveraging Blockchain Technology in a BIM Workflow: A Literature Review","authors":"A. S. E. Pradeep, T. Yiu, R. Amor","doi":"10.1680/ICSIC.64669.371","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.371","url":null,"abstract":"Building Information Modelling (BIM) involves the exchange of models and information between stakeholders and within collaborating teams. This information is prone to contractual, legal, security and system issues amongst others. The existing practices aim to address a digital concept such as BIM with solutions from the paper world – contracts and other documents, which do not solve the problem completely. A recent advancement in database management – Blockchain Technology (BCT) aims to provide a new stream of solutions to industries across various sectors. BCT is a system of recording a database that stores information chronologically and distributes a copy of it over a network of computers that maintain its authenticity and security collectively. This paper first reviews the literature on the issues of information exchange in a BIM workflow and next explores the concept of BCT and its connection with BIM. The literature indicates that BCT shows high potential for solving challenges during the design phase of the project by clarifying liabilities, increasing the reliability of information and enhancing the security of information flow. Its ability to incorporate self-executing contracts enable many more applications around ownership and payments. Finally, the paper discusses a few of its challenges with scalability, user acceptance amongst others.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114647628","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}
Eirini Konstantinou, A. Parlikad, Alex Wong, Charlotte Broom
Maintenance task prioritization is essential for allocating resources. It is estimated that almost 1/3 of the maintenance cost is wasted to unnecessary activities. Task prioritization is based on risk assessment that takes into account the probability of failure and the criticality of asset (or consequence of failure). The criticality analysis is defined by the asset owner based on several parameters, among them safety, downtime cost, productivity, whilst the probability of failure is determined based on deterioration models, regular manual inspections, or sensors. The criticality of assets varies significantly between organizations, due to differences between their key performance indicators and maintenance objectives. Currently, the quantitative evaluation of the criticality of assets is a very complicated procedure for organisations. It depends on elaborate weighted score methods and extensive data collection efforts. However, the data required are not always available. This paper proposes an innovative method that exploits the advances in mobile communications, social networking, Internet of Things and machine learning to address this shortcoming. This approach brings building elements and assets online using asset tags with an online ‘asset profile’ linked to it. Users of assets are able to scan these tags using a mobile phone app to not only see the information about those assets, but also enter ‘comments’ describing issues and problems on the profiles. Natural language processing (NLP) is then applied to these c omments to estimate the criticality of assets. The proposed method is validated with historical data provided by the Estate Management, of the University of Cambridge.
{"title":"Prioritization of Responsive Maintenance Tasks via Machine Learning-based Inference","authors":"Eirini Konstantinou, A. Parlikad, Alex Wong, Charlotte Broom","doi":"10.1680/ICSIC.64669.061","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.061","url":null,"abstract":"Maintenance task prioritization is essential for allocating resources. It is estimated that almost 1/3 of the maintenance cost is wasted to unnecessary activities. Task prioritization is based on risk assessment that takes into account the probability of failure and the criticality of asset (or consequence of failure). The criticality analysis is defined by the asset owner based on several parameters, among them safety, downtime cost, productivity, whilst the probability of failure is determined based on deterioration models, regular manual inspections, or sensors. The criticality of assets varies significantly between organizations, due to differences between their key performance indicators and maintenance objectives. Currently, the quantitative evaluation of the criticality of assets is a very complicated procedure for organisations. It depends on elaborate weighted score methods and extensive data collection efforts. However, the data required are not always available. This paper proposes an innovative method that exploits the advances in mobile communications, social networking, Internet of Things and machine learning to address this shortcoming. This approach brings building elements and assets online using asset tags with an online ‘asset profile’ linked to it. Users of assets are able to scan these tags using a mobile phone app to not only see the information about those assets, but also enter ‘comments’ describing issues and problems on the profiles. Natural language processing (NLP) is then applied to these c omments to estimate the criticality of assets. The proposed method is validated with historical data provided by the Estate Management, of the University of Cambridge.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116447150","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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