(BIM) workflows

251 Pages·2017·13.56 MB·English

by  Margarida Barbosa

As-built building information modeling (BIM) workflows:
from point cloud data to BIM
Doutoramento em Arquitetura
Conservação e Restauro

Candidata:
Margarida de Carvalho Jerónimo Barbosa
Orientadores:
Prof. Doutor Luís Mateus (FA-ULisboa)
Prof. Doutor Victor Ferreira (FA-ULisboa)
Prof. Doutor ir.-arch. Pieter Pauwels (Universidade de Ghent)

Tese especialmente elaborada para a obtenção do grau de doutor
2018
1
As-built building information modeling (BIM) workflows: from point cloud data to BIM
2018

Presidente e vogal:
Doutor José Nuno Dinis Cabral Beirão,
Professor Auxiliar
Faculdade de Arquitetura da Universidade de Lisboa.

Vogais:
Doutor Carlos Nuno Lacerda Lopes,
Professor Auxiliar com Agregação
Faculdade de Arquitectura da Universidade do Porto;

Doutora Sara Eloy Cardoso Rodrigues,
Professora Auxiliar
ISCTE – Instituto Universitário de Lisboa;

Doutora Ana Paula Filipe Tomé,
Professora Auxiliar
Instituto Superior Técnico da Universidade de Lisboa;

Doutor Luís Miguel Cotrim Mateus,
Professor Auxiliar
Faculdade de Arquitetura da Universidade de Lisboa;

Doutor Nuno Filipe Santos de Castro Montenegro,
Professor Auxiliar Convidado
Faculdade de Arquitetura da Universidade de Lisboa.

Esta foi desenvolvida no âmbito do projecto ReabOp: “Optimização de fluxos de trabalho de documentação
em reabilitação de estruturas construídas”, da Faculdade de Arquitectura da Universidade Técnica de Lisboa e
do Instituto de Engenharia Mecânica (IDMEC), PTDC/ATP-AQI/5355/2012, financiado pela FCT/MEC, através
de fundos nacionais (PIDDAC).

ACKNOWLEDGEMENTS

I would like to express my deep gratitude to my advisors, Prof. Doctor Luis Mateus, Prof. Doctor Victor
Ferreira, and Prof. Doctor ir.-arch. Pieter Pauwels, who offered me the opportunity to pursue this
research. They provided generous support, decisive guidance and essential advice throughout my
research.

I gratefully acknowledge the funding received towards my PhD from the FCT/MEC. I wish to thank
various people for their contribution and support to this project; Prof. Doctor Amélia Loja (IDMEC),
Håvard Vasshaug (Snøhetta), Christine Grape (Grape Architects), Mariana Alves (Dark Arkitekter), Kelly
Cone (Clearedge3D), Silviu Stoian (The Beck Group), Pedro Cordeiro (FA-ULisboa), Ben Malone
(BIM.Technologies). I wish to acknowledge the help provided by: Tim Lowery (Clearedge3D) for sharing
an Edgewise Building study case; Brendan Nichols (Beck Group) for developing the solar study
described in Section 5.2.2; and Arne Bjelland (Hel Ved Arkitektur) for the development of the workflow
in Vitusapotek Volvat study. I am particularly grateful to Angie Mendez (A-lab), whose willingness to
provide me time to write the thesis has been very much appreciated.

I wish to thank the authors who kindly provided the copies of their papers or contributed figures to
this survey.

Finally, I would like to thank my family and friends who have been encouraging and supporting me
throughout my doctorate program. In particular my Mum for the unconditional support, my Dad, my
Sister and Håvard for helping in whatever way they could during this challenging period. None of this
would have been possible without them.

I would like to thank the following companies for their assistance with the collection of my data:

I
II
ACKNOWLEDGEMENTS
List of Acronyms XIII
English summary XVII
Resumo XXI
1 Introduction 1
1.1 As-built BIM 1
1.2. Research questions 3
1.3. Thesis outline 4
1.4. Thesis Dissemination 5
1.4.1. Publications 5
1.4.2. Presentations 5
2 Acquiring and Processing Building Data 7
2.1. The need for better documentation for interventions in existing buildings 8
2.2. Traditional methods for surveying 10
2.2.1. Robotic Total Station (RTS) 10
2.2.2 Computer-aided manual surveying (CAMS) 10
2.3. New technologies for surveying - 3D Surveys 11
2.3.1. Point clouds 12
2.3.2 Automatic Digital Photogrammetry (ADP) 15
2.3.3. Terrestrial Laser Scanning (TLS) 21
2.3.4. ADP and TLS comparison 25
2.4. Point cloud data outputs and limitations 27
2.4.1. Point clouds outputs 29
2.4.2. Point clouds limitation 35
2.5. Conclusion 37
3 Analyzing Building Data 39
3.1. Analysis of the building state through point cloud data 40
3.1.1. Radiometric information analysis 40
3.1.2. Deformation analysis information extraction 42
3.1.3. Analysis of infrared thermography information texturized into PCM 44
3.2. Analysis of building elements geometry based on point cloud data 44
3.3. Building Information Modeling (BIM) as a tool for analysing data 48
3.3.1. BIM definition 48
3.3.2. BIM history and current state of the art 49
3.3.3. BIM tools 53
3.3.4. Building Information Model as a tool to analyse data 57
3.3. Conclusion 68
4 Standards and BIM usage for existing building interventions 71
4.1 The benefits of standardized workflows in the construction of new buildings 72
III
4.2. BIM standards for new buildings 73
4.2.1 Data exchange requirements in BIM standards 74
4.2.2 Data modeling requirements in BIM standards 77
4.3. Toward collaborative workflows in interventions in existing buildings 79
4.4. Addressing challenges to improve usage of BIM for existing buildings 80
4.5. BIM for existing buildings 81
4.5.1 Documenting existing buildings using BIM software 81
4.5.2 Challenges and obstacles toward the application of BIM software 82
4.6. BIM standards for existing buildings interventions 89
4.6.1 The need for BIM standards for existing buildings intervention planning 89
4.6.2. An appropriately guided combination of automatic and manual techniques 90
4.6.3 Application of BIM standards for intervention planning in existing buildings 91
4.7. Conclusion 94
5 As-built BIM workflows 97
5.1. Handling uncertain data, objects and relations 100
5.1.1. Using Photogrammetric data 100
5.1.2. Using 360° panorama photos as complementing information for modeling 124
5.2. Handling high modeling/conversion effort 129
5.2.1 Building geometry analysis workflows 130
5.2.2. Combining automatic and manual techniques for workflow efficiency 168
5.3. Monitoring as-built information as a first step for the update and maintenance of information
in BIM 176
5.4. Conclusions 187
6 Guidelines 195
6.1. Guidelines for as-built BIM data exchange requirements 195
6.2. Guidelines for the as-built BIMs modeling standardization 196
6.2.1. Guidelines regarding data base for modeling 196
6.2.2.Guidelines regarding modeling process 198
7 Final Conclusions and Future Work 205
7.1. The different kinds of building data acquired 206
7.2. The different kinds of building data analysis processes 208
7.3. The use of standards and as-built BIM 209
7.4. As-built BIM workflows and guidelines for architectural offices 209
8 References 215

IV
List of Figures
Figure 1.1- Schematic diagram of the Chapters subject sequence ......................................................................... 4
Figure 2.1- Schematic diagram of the Section 2 subject sequence ......................................................................... 7
Figure 2.2-ADP and TLS are subdivided into two main steps: the acquisition and the processing of the data .... 12
Figure 2.3 -Belém palace PCM: left image: each point clouds has one color;right image: PCM points colored by
RGB color. Source:image courtesy ArcHC_3D ....................................................................................................... 13
Figure 2.4 - Image of what is Point cloud file ........................................................................................................ 13
Figure 2.5 -Photogrammetric survey tools ............................................................................................................ 15
Figure 2.6- Convento de Cristo window Photogrammetry Survey-capture (ArcHC_3D survey). .......................... 16
Figure 2.7- Image on the left: VisualSFM software correlating 3d points and pixels; image on the right: diagram
of photos correlation. Source: Image courtesy ArcHC_3D. .................................................................................. 18
Figure 2.8 - Relative orientation of the cameras.Source: Image courtesy ArcHC_3D ........................................... 19
Figure 2.9- ADP dense point cloud. Source: Image courtesy ArcHC_3D ............................................................... 19
Figure 2.10 - A) Global view of the point cloud model, B) Detailed view, C) Detailed view where point density can
be observed. Source: Image courtesy ArcHC_3D .................................................................................................. 20
Figure 2.11- Aerial ADP survey through aerial photos of “Convento de Cristo” in Tomar. Source: Image courtesy
ArcHC_3D .............................................................................................................................................................. 20
Figure 2.12- A schematic diagram of a mirror-based triangulation measurement system, based in (English
Heritage 2011). ..................................................................................................................................................... 22
Figure 2.13- schematic diagram of the time-of-flight measurement system, based in (English Heritage 2011). . 22
Figure 2.14- Closed polygonal chain of point clouds (left) and oriented point clouds (right). ............................. 23
Figure 2.15 - Image of relative orientation of the TLS point clouds ...................................................................... 23
Figure 2.16 - Comparison of TLS model (left) with ADP model (center) with overlapping (right). Source: Image
courtesy Mateus et al ,(2012) ............................................................................................................................... 26
Figure 2.17- top: mesh production; bottom: NURBS surface ............................................................................... 28
Figure 2.18 - Possible connections between 2D and 3D data. .............................................................................. 28
Figure 2.19-PCM with intensity color.Source: image courtesy The Beck Group ................................................... 29
Figure 2.20- grayscale PCM ................................................................................................................................... 29
Figure 2.21- PCM colored with with RGB values. Source: image courtesy ArcHC_3D .......................................... 30
Figure 2.22 - PCM can have color ranges based on elevation values. Source: right bottom image, Google maps
.............................................................................................................................................................................. 30
Figure 2.23- PCM colored by normals ................................................................................................................... 31
Figure 2.24- PCM colored by point clouds single colo. Source:image courtesy ArcHC_3D .................................. 31
Figure 2.25 - Orthoimages - elevation on the left and section on the right .......................................................... 32
Figure 2.26 - Orthoimages - floorplan ................................................................................................................... 32
Figure 2.27- PCM section ...................................................................................................................................... 32
V
Figure 2.28- Process of obtaining a section merged with an ortho-image. Source: Image courtesy Mateus (2013)
.............................................................................................................................................................................. 33
Figure 2.29- Floorplan PCM section merged with an ortho-image. Source: Image courtesy Joäo Covas. ............ 33
Figure 2.30- Reflectance (laser wavelenght = 683nm) image of Valflores palace. Source: Image courtesy Mateus
(2012) .................................................................................................................................................................... 34
Figure 2.31 -top image: IR thermal image. Source: Image courtesy (Alba et al. 2011), with permission from CC BY
3.0 ; bottom image: IR thermal image projected in a point cloud. Source: Image courtesy (Wang et al., 2013),with
permission from ASCE ........................................................................................................................................... 35
Figure 3.1- schematic diagram of the Chapter 3 subjects summary ..................................................................... 39
Figure 3.2 - Presence of biological activity in a concrete wall. Source:image courtesy González-Jorge et al. (2012),
with permission from Elsevier ............................................................................................................................... 41
Figure 3.3- Chlorophyll identification through different spectral laser combination. Source: Image courtesy
Mateus (2012) ....................................................................................................................................................... 41
Figure 3.4- Wavebands that can be used to investigate layers of a painting. Image based in Rizzi et al. (2007) . 42
Figure 3.5 - Deformation analysis of a wall. Source: Image courtesy Mateus (2013) ........................................... 43
Figure 3.6 - Left: Bricks delamination analyses from TLS data; right: deformation of wall cladding panels analyses
through TLS Source: Image courtesy Al-Neshawy et al.( 2009) published under CC BY-SA 4.0 licence. ............... 43
Figure 3.7- 3D point cloud without color; 3D thermal point cloud colored by normalized temperature values.
Source: Image courtesy (Wang et al., 2013), with permission from ASCE ............................................................ 44
Figure 3.8 - Top images: vertical and horizontal sections; bottom image: floorplan ortho-images. Source: image
courtesy ArcHC_3D ............................................................................................................................................... 45
Figure 3.9- 2D CAD manually traced over ortho-image. Source: Image courtesy Mateus ( 2012). ...................... 45
Figure 3.10 - 3D elements generated from CAD drawings in Barbosa (2011) ...................................................... 46
Figure 3.11– First known workflow. Source: Image courtesy Chader (2008), with permission BY-NC. ................ 47
Figure 3.12 - Second known workflow. Source: Image courtesy Chader (2008), with permission BY-NC. ........... 47
Figure 3.13- Flux.io for collaboration and real-time feedback loop between architects and engineers. Source:
Image courtesy Håvard Vasshaug,from Snøhetta, presented in RTC2016 ........................................................... 55
Figure 3.14- Section of a building competition. Source: image courtesy Grape Architects .................................. 58
Figure 3.15- Floorplan of a building competition. Source: image courtesy Grape Architects .............................. 59
Figure 3.16 - Massing and area comparison between different design option studies. Source: Image courtesy
Håvard Vasshaug from DARK Arkitekter presented at RTC2015 .......................................................................... 60
Figure 3.17- Areas per type of housing. Different colors correspond to different house topologies. Source: image
courtesy Grape Architects ..................................................................................................................................... 60
Figure 3.18- Study of site orientation and relation with shade study. Source: Image courtesy Grape Architects 63
Figure 3.19 - Shade analysis inside the building. Source: Image courtesy Håvard Vasshaug from DARK Arkitekter
presented at RTC2015 ........................................................................................................................................... 64
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