{"title":"An Industry Survey on the use of Graphene-Reinforced Concrete for Self-Sensing Applications","authors":"I. Papanikolaou, A. Al-Tabbaa, M. Goisis","doi":"10.1680/ICSIC.64669.613","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.613","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"60 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":"122800769","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}
In the paradigm of the Smart City, cities are embracing new digital technologies and data innovation to redefine their relationship to citizens and enterprise. Increasingly, cities are developing visions, strategies, and related digital masterplans and action groups with which to coordinate these efforts. The European Horizon 2020 funded OrganiCity project explored a new model for providing access to all citizens to collaboratively develop and test their ideas for managing and improving the urban environment using data. The people centred and data driven approach of the OrganiCity project developed an Experimentation as a Service (EaaS) model across 13 cities and with 43 experiments. In this paper, we describe the 4 key service pillars that emerged through designing a platform to enable experimentation and the associated engagement practices required to facilitate testing in a city. The service pillars are: systematic experimentation, co-creation, federated ethics & privacy, and management of liability & Intellectual Property Rights. The EaaS approach provided a low-risk service blueprint for city authorities to democratically source, test and support scaling-up innovative solutions to their city challenges. Analysis of experimenter’s projects highlighted the importance of shared infrastructure for reducing the barrier to entry for accessing the digital tools, but more importantly highlighted the investment required, and value of, the human resources required to facilitate the process of experimentation.
{"title":"Organicity: Lessons from an Experimentation as a Service Model for Digital Civic Innovation","authors":"D. Wilson, Shane J. McLoughlin, M. Brynskov","doi":"10.1680/ICSIC.64669.195","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.195","url":null,"abstract":"In the paradigm of the Smart City, cities are embracing new digital technologies and data innovation to redefine their relationship to citizens and enterprise. Increasingly, cities are developing visions, strategies, and related digital masterplans and action groups with which to coordinate these efforts. The European Horizon 2020 funded OrganiCity project explored a new model for providing access to all citizens to collaboratively develop and test their ideas for managing and improving the urban environment using data. The people centred and data driven approach of the OrganiCity project developed an Experimentation as a Service (EaaS) model across 13 cities and with 43 experiments. In this paper, we describe the 4 key service pillars that emerged through designing a platform to enable experimentation and the associated engagement practices required to facilitate testing in a city. The service pillars are: systematic experimentation, co-creation, federated ethics & privacy, and management of liability & Intellectual Property Rights. The EaaS approach provided a low-risk service blueprint for city authorities to democratically source, test and support scaling-up innovative solutions to their city challenges. Analysis of experimenter’s projects highlighted the importance of shared infrastructure for reducing the barrier to entry for accessing the digital tools, but more importantly highlighted the investment required, and value of, the human resources required to facilitate the process of experimentation.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"319 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":"116647191","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}
Nowadays, the dramatic growth of global population and the rapid development of urbanization are the main reasons of a continuously increasing demand for thousands of architecture, engineering and construction (AEC) projects particularly in China, which is the largest AEC market in the world. However, along with that come severe challenges of high energy consumptions, massive resource wastes and serious productivity decline to the traditional AEC industry in China. Therefore, a technological concept named pre-fabricated construction is being highly embraced in recent years to help solve these challenges and meanwhile realize "Lean Construction" which is mentioned in the sustainable development of urbanization. This concept is proposed for decades, but its implementation in practice is facing technical barriers including lack of efficient management patterns, inefficient collaborations of stakeholders, outdated means of information collection and processing. To overcome these barriers and narrow the gap between the concept and practice, an emerging digital technology called Building Information Modelling (BIM) is suggested to accelerate the digitalization of AEC industrial management pattern and the implementation of efficient pre-fabricated construction. This paper aims to introduce an innovative framework for a digital management system that integrates the concept of five-dimensional (5D) BIM with the technique of radio frequency identification devices (RFID). This BIM-based system is developed in order to realize efficient management from off-site pre-fabrication stage to on-site assembly phase for pre-fabricated construction projects in China. It is also expected that 5D BIM can provide modeling, schedule simulation, and cost estimation to maximize the value of information flow for improving the productivity of pre-fabricated construction process.
{"title":"Development of 5D BIM-Based Management System for Pre-Fabricated Construction in China","authors":"C. Chen, Cml Tang, Y. Jin","doi":"10.1680/ICSIC.64669.215","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.215","url":null,"abstract":"Nowadays, the dramatic growth of global population and the rapid development of urbanization are the main reasons of a continuously increasing demand for thousands of architecture, engineering and construction (AEC) projects particularly in China, which is the largest AEC market in the world. However, along with that come severe challenges of high energy consumptions, massive resource wastes and serious productivity decline to the traditional AEC industry in China. Therefore, a technological concept named pre-fabricated construction is being highly embraced in recent years to help solve these challenges and meanwhile realize \"Lean Construction\" which is mentioned in the sustainable development of urbanization. This concept is proposed for decades, but its implementation in practice is facing technical barriers including lack of efficient management patterns, inefficient collaborations of stakeholders, outdated means of information collection and processing. To overcome these barriers and narrow the gap between the concept and practice, an emerging digital technology called Building Information Modelling (BIM) is suggested to accelerate the digitalization of AEC industrial management pattern and the implementation of efficient pre-fabricated construction. This paper aims to introduce an innovative framework for a digital management system that integrates the concept of five-dimensional (5D) BIM with the technique of radio frequency identification devices (RFID). This BIM-based system is developed in order to realize efficient management from off-site pre-fabrication stage to on-site assembly phase for pre-fabricated construction projects in China. It is also expected that 5D BIM can provide modeling, schedule simulation, and cost estimation to maximize the value of information flow for improving the productivity of pre-fabricated construction process.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"8 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":"132795016","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}
Pub Date : 2019-01-01DOI: 10.3929/ETHZ-B-000354717
M. Esders, B. Adey, C. Martani
{"title":"Evaluating Initial Building Designs Considering Possible Future Changes: The Example of the New Pet Centre of the University Hospital of Zurich","authors":"M. Esders, B. Adey, C. Martani","doi":"10.3929/ETHZ-B-000354717","DOIUrl":"https://doi.org/10.3929/ETHZ-B-000354717","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"9 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":"128073100","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":"Developing a City-Level Digital Twin –Propositions and a Case Study","authors":"L. Wan, T. Nochta, J. Schooling","doi":"10.1680/icsic.64669.187","DOIUrl":"https://doi.org/10.1680/icsic.64669.187","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"20 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":"114526143","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":"Evaluation of a Railway Bridge Using Distributed and Discrete Strain Sensors","authors":"C. Barker, N. Hoult, H. Le, V. Tolikonda","doi":"10.1680/ICSIC.64669.533","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.533","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"71 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":"116292688","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":"Monitoring of Retaining Structures on an Open Excavation Site with 3D Laser Scanning","authors":"H. Seo, Y. Zhao, J. Wang","doi":"10.1680/ICSIC.64669.665","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.665","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"5 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":"115397970","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":"Tunnelling Under A Heritage Structure: Distributed Sensing Data and Cracked Equivalent Beam Models","authors":"S. Acikgoz, A. Franza, M. DeJong, R. Mair","doi":"10.1680/ICSIC.64669.675","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.675","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"12 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":"127526981","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}
Andrea Maroni, E. Tubaldi, J. Douglas, Neil M. Ferguson, D. Val, H. McDonald, S. Lothian, A. Chisholm, O. Riches, D. Walker, Euan Greenoak, Christopher Green, D. Zonta
Scour is the leading cause of bridge failures worldwide. In the United States, 22 bridges fail every year, whereas in the UK scour contributed significantly to the 138 bridge collapses recorded in the last century. In Scotland, there are around 2,000 bridges susceptible to scour. Scour assessments are currently based on visual inspections, which are expensive, time-consuming, and the information collected is qualitative. However, monitoring an entire infrastructure network against scour is not economically feasible. A way to overcome this limitation is to install monitoring systems at critical locations, and then extend the pieces of information gained to the entire asset through a probabilistic approach. This paper proposes a Decision Support System (DSS) for bridge scour management that exploits information from a limited number of scour monitoring systems to achieve a more confined estimate of the scour risk for a bridge network. A Bayesian network (BN) is used to describe conditional dependencies among the involved random variables. The BN allows estimating, and updating, the scour depth distributions using information from monitoring of scour depth and river flow characteristics. Data collected by the monitoring system and BN's outcomes are then used to inform a decision model and thus support transport agencies’ decision frameworks. A case study consisting of several road bridges in Scotland is considered to demonstrate the functioning of the DSS. The BN is found to estimate accurately the scour depth at unmonitored bridges, and the decision model provides higher values of scour thresholds compared to the ones implicitly chosen by the transport agencies.
{"title":"Managing Bridge Scour Risk Using Structural Health Monitoring","authors":"Andrea Maroni, E. Tubaldi, J. Douglas, Neil M. Ferguson, D. Val, H. McDonald, S. Lothian, A. Chisholm, O. Riches, D. Walker, Euan Greenoak, Christopher Green, D. Zonta","doi":"10.1680/ICSIC.64669.077","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.077","url":null,"abstract":"Scour is the leading cause of bridge failures worldwide. In the United States, 22 bridges fail every year, whereas in the UK scour contributed significantly to the 138 bridge collapses recorded in the last century. In Scotland, there are around 2,000 bridges susceptible to scour. Scour assessments are currently based on visual inspections, which are expensive, time-consuming, and the information collected is qualitative. However, monitoring an entire infrastructure network against scour is not economically feasible. A way to overcome this limitation is to install monitoring systems at critical locations, and then extend the pieces of information gained to the entire asset through a probabilistic approach. This paper proposes a Decision Support System (DSS) for bridge scour management that exploits information from a limited number of scour monitoring systems to achieve a more confined estimate of the scour risk for a bridge network. A Bayesian network (BN) is used to describe conditional dependencies among the involved random variables. The BN allows estimating, and updating, the scour depth distributions using information from monitoring of scour depth and river flow characteristics. Data collected by the monitoring system and BN's outcomes are then used to inform a decision model and thus support transport agencies’ decision frameworks. A case study consisting of several road bridges in Scotland is considered to demonstrate the functioning of the DSS. The BN is found to estimate accurately the scour depth at unmonitored bridges, and the decision model provides higher values of scour thresholds compared to the ones implicitly chosen by the transport agencies.","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"28 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":"125426359","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":"A Personalized Safety Training System for Construction Workers","authors":"S. Xu, Q. Ni, Mengge Zhang, M. Li","doi":"10.1680/ICSIC.64669.321","DOIUrl":"https://doi.org/10.1680/ICSIC.64669.321","url":null,"abstract":"","PeriodicalId":205150,"journal":{"name":"International Conference on Smart Infrastructure and Construction 2019 (ICSIC)","volume":"117 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":"124306873","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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