Guerra de Oliveira, Sara Filipa (2020) Sustainability of linear infrastructure domain-specific data sets in open BIM asset centric workflows. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Sustainability of linear infrastructure domain-specific data sets in open BIM asset centric workflows
Autori:
AutoreEmail
Guerra de Oliveira, Sara Filipasaraguerraoliveira@gmail.com
Data: 7 Marzo 2020
Numero di pagine: 64
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria Civile, Edile e Ambientale
Dottorato: Ingegneria dei sistemi civili
Ciclo di dottorato: 32
Coordinatore del Corso di dottorato:
nomeemail
Papola, Andreapapola@unina.it
Tutor:
nomeemail
Dell'Acqua, Gianluca[non definito]
Tibaut, Andrej[non definito]
Data: 7 Marzo 2020
Numero di pagine: 64
Parole chiave: Building Information Modelling (BIM), Linear infrastructure, Interoperability, Sustainability, Industry Foundation Classes (IFC), Big datasets
Settori scientifico-disciplinari del MIUR: Area 08 - Ingegneria civile e Architettura > ICAR/04 - Strade, ferrovie ed aeroporti
Depositato il: 19 Mar 2020 16:45
Ultima modifica: 05 Nov 2021 13:03
URI: http://www.fedoa.unina.it/id/eprint/13226

Abstract

The digitalization of linear infrastructure projects can be nowadays supported by workflows that improve not only the quality of the deliverables but also the efficiency of the way they are developed, cultivating communication between project participants. Technology, tools, equipment and procedures aid in accomplishing these objectives and the construction industry is becoming more and more digital-oriented and receptive to approaches as Building Information Modelling (BIM). Amongst the advantages of BIM implementation, one can count increased productivity, earlier exposure of project errors, earlier detection of omissions, communication procedures streamlined, project costs optimization and control, more informed scheduling, building simulation and analysis, and many others. However, since it is of recent adoption in the infrastructure field, to fully make the most of the listed benefits, there are still significant developments and adaptations to be made due to the nature of this sector. The infrastructure domain is vast, encompassing assets related to the economy and social domains of society. The focus of the present dissertation is on the transportation category, where linear infrastructures assets such as roads, railways and airport runways occupy an emphasized role. As networks of longitudinal structures with large territory interaction, their intervention area must be subject to multiple analysis at an earlier planning stage, before and beyond simple plano-altimetric decisions. They present a very specific nature, both structure and component-wise as related to the terminology and modelling methodology. Like any complex built asset, linear infrastructures are multidisciplinary (in terms of specialized areas and teams involved), and their projects present very particular challenges, namely the high dependence on existing structures, infrastructures and the surrounding environment. There is now no argument that BIM is and has to be applied and viewed as something beyond just the 3D model. Even though it can be considered as the central core of any project, the part that provides the most return to professionals in terms of investment has to be considered the organizational one related to data. The initial investment in training and resources is later compensated by the increased quality of project deliverables and especially improved control and management of the assets in their operation life. Project participants should encourage in an early stage the adoption and implementation of open standards, since if they remain connected to proprietary software the full potentialities of BIM will never be attained. One of the major demands when it comes to linear infrastructure projects is related to the organization of all the data associated and its conveyance between all project participants (interoperability of information) in a streamlined way. These projects encompass a great amount of information (big datasets) that originates from manifold sources, often not properly organized and stored, leading to lack of organization. The present dissertation focuses on a new methodology for sustainability of datasets, created since the early project stages up to the operation and maintenance, and how they can be gathered, accessed and retrieved in an open standardized manner. As part of the methodology a technical framework is proposed that connects big datasets to the digital BIM model of the asset. The development of these data connections contributes additionally to the sustainability of projects, minimizing paper-based deliverables, improving the communication between different teams involved (leading to better and timely decisions), aiding in cost savings and general improvement of all operation, maintenance and rehabilitation procedures and activities. Therefore, the main deliverable of the present dissertation is a methodology that proposes a technical framework consisting of different software applications that integrates domain-specific data, connecting and integrating open infrastructure BIM (IFC) models with big datasets through a relational database. The methodology also proposes a new BIM workflow that enables the integration of IFC 4.3 files, with collections of infrastructure domain-specific data (e.g. spreadsheet data, images, pdf documents). The proposed framework called InfraGOTdata can be regarded as an innovative Common Data Environment (CDE), which is a well-known concept for BIM workflows. The relational database InfraGOTdb is inherent to the IFC schema and upgraded to support big datasets coming from multiple static or dynamic sources. The user application InfraGOTapp enhances professional user experience, streamlining the integration of domain specific data, benefiting from a clear connection with data from multiple sources can be organized, referenced and queried according to the interests and needs of the professionals. Future developments of the presented work can extend it by integrating prediction models (e.g. performance-wise, climate changes impact analysis) and establishing the connection to technologies related to the smart city concept, where the Internet of Things (IoT) solutions further improve the efficiency and sustainability of the infrastructure assets’ management.

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