Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction最新文献_第5页

Briefing: PLEXUS – Priming Laboratory Experiments on infrastructure and Urban Systems 简报:PLEXUS -基础设施和城市系统的启动实验室实验

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-05-11 DOI: 10.1680/jsmic.21.00017

Christopher D F Rogers

{"title":"Briefing: PLEXUS – Priming Laboratory Experiments on infrastructure and Urban Systems","authors":"Christopher D F Rogers","doi":"10.1680/jsmic.21.00017","DOIUrl":"https://doi.org/10.1680/jsmic.21.00017","url":null,"abstract":"The UK Collaboratorium for Research on Infrastructure and Cities (UKCRIC) is, with a capital investment of £138 m from the UK Government and matched funding from its 15 collaborating partner universities, creating world-class city observatory, modelling & simulation and physical laboratory facilities. This briefing aims to introduce UKCRIC’s formulation, capabilities and core thinking, before describing a programme of work that has linked the eleven laboratory facilities. PLEXUS has focussed on three important technical challenges—intense physical interdependency of urban infrastructure systems, harvesting energy from buried infrastructure systems and accelerated deterioration of infrastructure materials due to extreme loading—as well as a study of how the large, multi-disciplinary research team progressed towards transdisciplinary working. The background context of UKCRIC, its approach to collaborative research and how this has shaped the PLEXUS research programme provides the starting point to this narrative. Thereafter the underpinning thinking and justification for the four strands of PLEXUS’ research are described. Finally, the briefing draws these strands together into a proposition for the research, development and implementation of a new generation of transport bridges building on the research reported in this special issue.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126446573","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}

引用次数: 2

Recognition of temporary vertical objects in large high-quality point clouds of construction sites 建筑工地大质量点云中临时垂直物体的识别

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-05-09 DOI: 10.1680/jsmic.21.00033

M. A. Vega, A. Braun, F. Noichl, A. Borrmann, H. Bauer, D. Wohlfeld

{"title":"Recognition of temporary vertical objects in large high-quality point clouds of construction sites","authors":"M. A. Vega, A. Braun, F. Noichl, A. Borrmann, H. Bauer, D. Wohlfeld","doi":"10.1680/jsmic.21.00033","DOIUrl":"https://doi.org/10.1680/jsmic.21.00033","url":null,"abstract":"Although adherence to project schedule is the most critical performance metric among project owners, still 53 % of typical construction projects exhibit schedule delays. While construction progress monitoring is key to allow effective project management, it is still a largely manual, error prone and inefficient process. To contribute to more efficient construction progress monitoring, this research proposes a method to automatically detect the most common temporary object classes in large-scale laser scanner point clouds of construction sites. Finding the position of these objects in the point cloud can help determine the current state of construction progress and verify compliance with safety regulations. The proposed workflow includes a combination of several techniques: image processing over vertical projections of point clouds, finding patterns in 3D detected contours, and performing checks over vertical cross-sections with deep learning methods. After applying and testing the method on three real-world point clouds and testing with three object categories (cranes, scaffolds, and formwork), the results reveal that our technique achieves rates above 88 % for precision and recall and outstanding computational performance. These metrics demonstrate the method’s capability to support the automatic 3D object detection in point clouds of construction sites.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132117599","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}

引用次数: 0

The potential for heat recovery and thermal energy storage in the UK using buried infrastructure 英国利用地埋基础设施进行热回收和热能储存的潜力

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-04-14 DOI: 10.1680/jsmic.21.00018

F. Loveridge, A. Schellart, S. Rees, R. Stirling, D. Taborda, S. Tait, L. Alibardi, G. Biscontin, P. Shepley, I. Shafagh, W. Shepherd, A. Yildiz, B. Jefferson

{"title":"The potential for heat recovery and thermal energy storage in the UK using buried infrastructure","authors":"F. Loveridge, A. Schellart, S. Rees, R. Stirling, D. Taborda, S. Tait, L. Alibardi, G. Biscontin, P. Shepley, I. Shafagh, W. Shepherd, A. Yildiz, B. Jefferson","doi":"10.1680/jsmic.21.00018","DOIUrl":"https://doi.org/10.1680/jsmic.21.00018","url":null,"abstract":"Dispersed space heating alone accounts for 40% of UK energy use and 20% of CO2 emissions. Tackling heating and building cooling demands is therefore critical to achieve net zero ambitions in the UK. The most energy efficient way to decarbonise heating and cooling is through the use of ground source heat pumps and district heating technology. However, capital costs are often high, sometimes prohibitively so. To reduce investment costs, it is proposed to use buried infrastructure as sources and stores of thermal energy. Barriers to this innovative approach include lack of knowledge about the actual net amount of recoverable energy, and impacts on the primary function of any buried infrastructure, as well as the need for new investment and governance strategies integrated across the energy and infrastructure sectors. Additional opportunities from thermal utilisation in buried infrastructure include the potential mitigation of damaging biological and/or chemical processes that may occur. This paper presents a first assessment of the scale of the opportunity for thermal energy recovery and storage linked to new and existing buried infrastructure, along with strategic measures to help reduce barriers and start the UK on the journey to achieving of its infrastructure energy potential.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127839214","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}

引用次数: 4

CityGML model generation using parametric interpolations 使用参数插值生成CityGML模型

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-04-04 DOI: 10.1680/jsmic.21.00015

A. Malhotra, Simon Raming, Maximilian Schildt, J. Frisch, Christoph van Treeck

引用次数: 0

Automating excavator productivity measurement using deep learning 使用深度学习自动化挖掘机生产率测量

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-04-04 DOI: 10.1680/jsmic.21.00031

Elham Mahamedi, K. Rogage, Omar Doukari, M. Kassem

引用次数: 4

Comparison of in-situ and InSAR monitoring for the assessment of bridge thermal expansion 现场监测与InSAR监测在桥梁热膨胀评估中的比较

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-03-29 DOI: 10.1680/jsmic.21.00008

Sivasakthy Selvakumaran, Z. Sadeghi, Matthew Collings, C. Rossi, T. Wright, A. Hooper

{"title":"Comparison of in-situ and InSAR monitoring for the assessment of bridge thermal expansion","authors":"Sivasakthy Selvakumaran, Z. Sadeghi, Matthew Collings, C. Rossi, T. Wright, A. Hooper","doi":"10.1680/jsmic.21.00008","DOIUrl":"https://doi.org/10.1680/jsmic.21.00008","url":null,"abstract":"Asset owners responsible for the management and maintenance of bridges value the collection of data which can be processed into useful information to inform decisions about future management of structures. Installing, powering and receiving data from sensors is not always convenient or possible, but satellite monitoring may provide the ability to measure bridge movements and thus provide an indication of potential problems for asset owners to take action on. This study presents the results of satellite monitoring of the Hammersmith Flyover, London, using the Interferometric Synthetic Aperture Radar (InSAR) technique. Sentinel-1 (free) and COSMO-SkyMed (commercial) satellite radar data was processed to provide millimetre-scale measurements of the Flyover and surrounding region and validated with in-situ sensor measurements. A method was developed for selecting and comparing InSAR measurements with in-situ displacement and temperature measurements, making use of bridge geometrical and structural modelling information. The results compare in-situ sensor measurements with remote InSAR measurements and show the suitability of such measurements in measuring thermal expansion for some (but not all) bridge assets. The proposed techniques, illustrated with the case study of Hammersmith Flyover, will enable asset owners to collect regular measurements of bridge movements to complement and add value to current inspection methods and potentially give early warning to defective bridge bearings.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131114005","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}

引用次数: 1

Identifying the most suitable machine learning approach for a road digital twin; a systematic literature review 为道路数字孪生识别最合适的机器学习方法;系统的文献综述

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-03-28 DOI: 10.1680/jsmic.22.00003

Kun Chen, Mehran Eskandari Torbaghan, Mingjie Chu, Long Zhang, Alvaro Garcia-Hernández

{"title":"Identifying the most suitable machine learning approach for a road digital twin; a systematic literature review","authors":"Kun Chen, Mehran Eskandari Torbaghan, Mingjie Chu, Long Zhang, Alvaro Garcia-Hernández","doi":"10.1680/jsmic.22.00003","DOIUrl":"https://doi.org/10.1680/jsmic.22.00003","url":null,"abstract":"Road infrastructure systems have been suffering from ineffective maintenance strategies, exaggerated by budget restrictions. A more holistic road asset management approach enhanced by data-informed decision making through effective condition assessment, distress detection, future condition predictions can significantly enhance maintenance planning, prolonging asset life. Recent technology innovations such as Digital Twins have great potentials to enable the needed approach for road condition predictions and a proactive asset management. To this end, machine learning techniques have also demonstrated convincing capabilities in solving engineering problems. However, none of them has been considered specifically within digital twins context. There is therefore a need to review and identify appropriate approaches for the usage of machine learning techniques within road digital twins. This paper provides a systematic literature review of machine learning algorithms used for road condition predictions and discusses findings within the road digital twin framework. The results show that existing machine learning approaches are to some extent, suitable and mature to stipulate successful road digital twin development. Moreover, the review whilst identifying gaps in the literature, indicates several considerations and recommendations required on the journey to road digital twins, and suggests multiple future research directions based on the review summaries of machine learning capabilities.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128349539","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}

引用次数: 2

Assessment of wind speed and spatial mapping across the Indian subcontinent 印度次大陆的风速评估和空间制图

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-03-17 DOI: 10.1680/jsmic.21.00010

Tamal Ghosh, Arjun Sil

{"title":"Assessment of wind speed and spatial mapping across the Indian subcontinent","authors":"Tamal Ghosh, Arjun Sil","doi":"10.1680/jsmic.21.00010","DOIUrl":"https://doi.org/10.1680/jsmic.21.00010","url":null,"abstract":"Site specific assessment of wind speed becomes essential to analyze the susceptibility of any slender structure. With the increasing number of occurrences of extreme wind events in the Indian subcontinent, a quantitative measure of wind hazard based on recent developments becomes the need of the hour for India. The Indian standard (IS-875-part III) is a national code for reference to the basic wind speed in India essentially for infrastructural planning and design of midrise to tall structures and the specified basic wind speeds in the code are computed based on 50 years return period by Gumbel probability distribution. However, recent cyclones reported extreme wind events already exceeded the specified value in the code. The Gumbel distribution (Type I ) is applied in the present study by method of moments (MOM) on the long term wind data (yearly maxima) considering the last few decades (40 years) available for forecasting wind speed at different return periods. The AD (Anderson darling) test results are also accommodated to establish the accuracy of the tail behavior of the statistical distribution used, where the p-value is found to be less than 0.05. Further, in the present study, site specific basic wind speed map is also proposed considering latest event data. Indeed, based on the present study, 100 years return period for basic wind speed is recommended instead of 50 years to ensure enhanced structural safety and serviceability during its design life.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121096319","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}

引用次数: 0

Smart Infrastructure and Construction: Referees 2021 智能基础设施和建设:裁判员2021

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-03-01 DOI: 10.1680/jsmic.2022.175.1.57

引用次数: 0

Internet of Things application for smart construction assets 物联网应用于智慧建筑资产

Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction Pub Date : 2022-02-28 DOI: 10.1680/jsmic.21.00022

Thomas M. Brennan, Joseph E Jesson, A. Deese, Efrain Rodriguez, Andrew J. Bechtel

{"title":"Internet of Things application for smart construction assets","authors":"Thomas M. Brennan, Joseph E Jesson, A. Deese, Efrain Rodriguez, Andrew J. Bechtel","doi":"10.1680/jsmic.21.00022","DOIUrl":"https://doi.org/10.1680/jsmic.21.00022","url":null,"abstract":"Internet of Things (IoT) devices allows data to be efficiently communicated using low power to a central server to report location, movement, temperature, and environmental attributes. With improvements in device connectivity distance, improved link margins, reductions in IoT hardware platform costs, and the availability of higher-capacity batteries, non-powered temporary construction equipment (e.g., concrete barriers) can become smart and trackable. For this study, a Long Range (LoRa) sensor platform is connected through an IoT Low Power Wide-Area Network (LPWAN) to test the feasibility of tracking construction equipment related to transportation. The signal strength relative to distance is analyzed along with the RF signal attenuation of signal strength through construction materials. The preliminary results show that a commercially available LoRa sensor, with an omni-directional antenna operating on an LPWAN can transmit up to 1,310 meters at-grade. It is expected that these types of sensor platforms can be applied to other types of non-powered construction equipment to introduce smart functionalities. From the study, it was determined that it is feasible to deploy a LoRa–based sensor network to track non-powered temporary construction equipment. The study also demonstrated that a cost-effective Polyvinyl Chloride (PVC) housing could be effective after 300 freeze-thaw cycles.","PeriodicalId":371248,"journal":{"name":"Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133776496","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}

引用次数: 0