Tài liệu Computing in civil engineering 2017 sensing, simulation, and visualization

Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Computing in Civil Engineering 2017 Sensing, Simulation, and Visualization Selected Papers from the ASCE International Workshop on Computing in Civil Engineering 2017 Seattle, Washington June 25–27, 2017 Edited by Ken-Yu Lin, Ph.D.; Nora El-Gohary, Ph.D.; and Pingbo Tang, Ph.D., P.E. Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. COMPUTING IN CIVIL ENGINEERING 2017 SENSING, SIMULATION, AND VISUALIZATION SELECTED PAPERS FROM THE ASCE INTERNATIONAL WORKSHOP ON COMPUTING IN CIVIL ENGINEERING 2017 June 25–27, 2017 Seattle, Washington SPONSORED BY Computing Division of the American Society of Civil Engineers EDITED BY Ken-Yu Lin, Ph.D. Nora El-Gohary, Ph.D. Pingbo Tang, Ph.D., P.E. 1801 ALEXANDER BELL DRIVE RESTON, VIRGINIA 20191–4400 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Published by American Society of Civil Engineers 1801 Alexander Bell Drive Reston, Virginia, 20191-4382 www.asce.org/publications | ascelibrary.org Any statements expressed in these materials are those of the individual authors and do not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein. No reference made in this publication to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by ASCE. The materials are for general information only and do not represent a standard of ASCE, nor are they intended as a reference in purchase specifications, contracts, regulations, statutes, or any other legal document. ASCE makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor. The information contained in these materials should not be used without first securing competent advice with respect to its suitability for any general or specific application. Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents. ASCE and American Society of Civil Engineers—Registered in U.S. Patent and Trademark Office. Photocopies and permissions. Permission to photocopy or reproduce material from ASCE publications can be requested by sending an e-mail to [email protected] or by locating a title in ASCE's Civil Engineering Database (http://cedb.asce.org) or ASCE Library (http://ascelibrary.org) and using the “Permissions” link. Errata: Errata, if any, can be found at https://doi.org/10.1061/9780784480830 Copyright © 2017 by the American Society of Civil Engineers. All Rights Reserved. ISBN 978-0-7844-8083-0 (PDF) Manufactured in the United States of America. Computing in Civil Engineering 2017 iii Preface Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Welcome to Seattle, the Emerald City in Washington! The 2017 ASCE International Workshop on Computing in Civil Engineering (IWCCE) was held in Seattle from June 25-27, 2017. The workshop was hosted by the University of Washington with sponsorship from ASCE’s Computing Division. The workshop is the Computing Division’s major meeting event and is held biannually in the United States, with participation from scholars worldwide. The workshop has a long history of success and serves as a platform for sharing research innovation as well as valuable lessons. We introduced several pioneering changes this year, including the inaugural all-stakeholder meeting for the Computing Division. We had a strong and engaged Technical Committee which provided rigorous reviews for the abstracts and full papers, with each submission being reviewed by at least two members of our Technical Committee. The 2017 workshop, as a standalone event, received more than 300 abstracts, 184 full papers, and 32 extended abstracts for the poster and demonstration sessions. The participation from our growing community has set a record and a total of 162 full papers were accepted and included in the proceedings. Among these papers, Building Information Modeling and Civil Information Modeling formed the most popular technical interests while Energy, Sustainability and Resilience topped the list of application contexts. We would like to thank the Department of Construction Management at The University of Washington for its support of the workshop. We are also grateful for the guidance from the Computing Division’s Executive Committee and the assistance from ASCE. We hope that you enjoyed the technical sessions at the workshop and had a memorable and meaningful IWCCE experience in Seattle this year. Ken-Yu Lin, Ph.D. Chair, Organizing Committee, IWCCE 2017 Nora El-Gohary, Ph.D. Chair, Technical Committee, IWCCE 2017 Pingbo Tang, Ph.D., P.E. Vice Chair, Organizing Committee, IWCCE 2017 © ASCE Computing in Civil Engineering 2017 iv Acknowledgments Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Special thanks are due to the following individuals at the University of Washington for their continuous and tireless support throughout the organization of the workshop: Name Julie Angeley Mark Baratta Brian Vogt Zhenyu Zhang Title IWCCE Local Administrator IWCCE Local IT Lead IWCCE Local Web Consultant IWCCE Secretary A sincere appreciation goes to the Microsoft Corporation for providing the editors free access to Microsoft’s Academic Conference Management Service and for customizing the online platform for the workshop. The editors would also like to thank the following Technical Committee members for their assistance and effort with the paper review and selection process: Name Abbas Rashidi Albert Chen Ali Mostafavi Amin Hammad Amir Behzadan Andre Barbosa Andre Borrmann Atefeh Mohammadpour Auroop R. Ganguly Baabak Ashuri Behzad Esmaeili Bon-Gang Hwang Brenda McCabe Burcin Becerik Carl Haas Carlos Caldas Carol Menassa Changbum Ahn Chao Wang Chen Feng © ASCE Institution Georgia Southern University National Taiwan University Florida International University Concordia University Missouri State University Oregon State University The Technical University of Munich Indiana University-Purdue University Fort Wayne Northeastern University (United States) Georgia Institute of Technology University of Nebraska-Lincoln National University of Singapore University of Toronto University of Southern California University of Waterloo University of Texas at Austin University of Michigan University of Nebraska-Lincoln Louisiana State University Mitsubishi Electric Research Laboratories Computing in Civil Engineering 2017 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Chien-Cheng Chou Chimay Anumba Christian Koch David Lattanzi Dong Zhao Dulcy Abraham Ebrahim Karan Eduardo Santos Esin Ergen Fadi Castronovo Farrokh Jazizadeh Fei Dai Feng Li Fernanda Leite Frank Boukamp Frederic Bosche Guangbin Wang Hanbin Luo Hubo Cai Ian Smith Ioannis Brilakis Islam El-adaway Ivan Mutis Jack Cheng Jiansong Zhang Jiayu Chen Jie gong Jing Du Jinyue Zhang John Messner John Taylor Jun Yang Justin Ker-Wei Yeoh Koji Makanae Lu Zhang Lucio Soibelman Mani Golparvar-Fard Mario Berges Menghan Tsai Michael Olsen Ming Lu © ASCE v National Central University (Taiwan) University of Florida University of Nottingham George Mason University Michigan State University Purdue University Millersville University University of Sao Paulo Istanbul Technical University California State University East Bay Virginia Tech West Virginia University Research Institute of Highway (China) University of Texas at Austin Royal Melbourne Institute of Technology Heriot-Watt University Tongji University Huazhong University of Science and Technology Purdue University Ecole Polytechnique Federale (Switzerland) Cambridge University University of Tennessee Illinois Institute of Technology Hong Kong University of Science and Technology Western Michigan University City University of Hong Kong Rutgers University Texas A&M University Tianjin University Penn State University Georgia Tech Northwestern Polytechnical University (China) National University of Singapore Miyagi University Florida International University University of Southern California University of Illinois at Urbana-Champaign Carnegie Mellon University National Taiwan University Oregon State University University of Alberta Computing in Civil Engineering 2017 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Mounir El Asmar Nai-Wen Chi Nan Li Nipesh Pradhananga Nobuyoshi Yabuki Omar El-Anwar Oswald Chong Paul Goodrum Pin-Chao Liao Ray Issa Renate Fruchter Ren-Jye Dzeng Reza Akhavian Rishee Jain Robert Amor Rucheng Xiao Rui Liu Saiedeh Razavi Sanghoon Lee SangHyun Lee SangUk Han Semiha Ergan Seokho Chi Shang-Hsien Hsieh Sheryl Staub-French Steven Ayer Takashi Michikawa Tamer El-Diraby Timo Hartmann Walid Tizani Wen Xiong Xiangyu Wang Xianzhong Zhao Xiaowei Luo Xiaolong Xue Xuesong Liu Xuesong Shen Yelda Turkan Yimin Zhu Ying Zhou Yong Cho © ASCE vi Arizona State University National Taiwan University Tsinghua University Florida International University Osaka University Cairo University Arizona State University University of Colorado at Boulder Tsinghua University University of Florida Stanford University National Chiao-Tung University California State University East Bay Stanford University University of Auckland Tongji University University of Florida McMaster University University of Hong Kong University of Michigan University of Alberta New York University Seoul National University National Taiwan University University of British Columbia Arizona State University RIKEN University of Toronto Technical University of Berlin University of Nottingham Southeast University Curtin University Tongji University City University of Hong Kong Harbin Institute of Technology Carnegie Mellon University University of New South Wales Oregon State University Louisiana State University Huazhong University of Science and Technology Georgia Institute of Technology Computing in Civil Engineering 2017 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. 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Youngjib Ham Yunfeng Chen Zhenhua Zhu Zheng Yang Zhiliang Ma vii Florida International University Georgia Southern University Concordia University Stanford University Tsinghua University Finally, the editors would also like to thank the following Poster and Demonstration Organization Committee members for their help with the related review process: Name Cheng Zhang Hamid Abdirad Jiawei Chen Kadir Amasyali Kaijian Liu Lufan Wang Luming Shang Vamsi Sai Kalasapudi Xuan Lv Zhenyu Zhang © ASCE Institution Arizona State University University of Washington Arizona State University University of Illinois at Urbana-Champaign University of Illinois at Urbana-Champaign University of Illinois at Urbana-Champaign University of Washington Arizona State University University of Illinois at Urbana-Champaign University of Washington Computing in Civil Engineering 2017 viii Contents Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Design Management and Collaboration Simultaneous Data Exchange between BIM and VR for Collaborative Decision Making.......................................................................................................... 1 Jing Du, Zhengbo Zou, Yangming Shi, and Dong Zhao The Need for Taxonomies in the Ontological Approach for Interoperability of Heterogeneous Information Models ......................................... 9 Aaron M. Costin, Charles Eastman, and Raja R. A. Issa Hybridizing Topology Optimization and Evolutionary Computation to Support Computer-Aided Engineering Design .......................... 18 Achyuthan Jootoo and David Lattanzi Education When Is a Construction Educational Serious Game Too Serious? Striking a Balance between Engagement and Learning ...................................................... 26 Fadi Castronovo, Robert M. Leicht, and John I. Messner Learning Advanced Decision-Making Techniques and Technologies through a Collaborative Project .............................................................................. 35 Seokyon Hwang and Mahdi Safa ICT-Enabled Cross-Cultural Education in Sustainable Urbanization................ 43 Nan Li, Deland Chan, Kevin Hsu, Zhiyong Fu, and Quan Mao An Augmented Reality Environment for Students’ Learning of Steel Connection Behavior ................................................................................................ 51 Hazar Nicholas Dib and Nicoletta Adamo A New Learning Model, Guided Soft Classroom, Integrating MOOCs into Conventional Classrooms for University Students ................................................ 59 Yi-Fen Li, Ching-Mei Tseng, and Shih-Chung Kang Hybrid Real/Virtual Simulation in an Engineering Laboratory Course ............ 68 Yupeng Luo and Jeevjyot Chhabda © ASCE Computing in Civil Engineering 2017 ix Intelligent Sensing and Monitoring Automated Monitoring of the Utilization Rate of Onsite Construction Equipment ................................................................................................................. 74 Xiaoning Ren, Zhenhua Zhu, Chantale Germain, Roger Belair, and Zhi Chen Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. A Personalized HVAC Control Smartphone Application Framework for Improved Human Health and Well-Being ............................................................. 82 Da Li, Carol C. Menassa, and Vineet R. Kamat Automated Change Diagnosis of Single-Column-Pier Bridges Based on 3D Imagery Data ............................................................................................................. 91 Ying Shi, Wen Xiong, Vamsisai Kalasapudi, Chao Geng, Cheng Zhang, and Pingbo Tang Feasibility of Field Measurement of Construction Workers’ Valence Using a Wearable EEG Device ................................................................................ 99 Houtan Jebelli, Sungjoo Hwang, and SangHyun Lee Using Photometric Stereo Method in Evaluating the Volume of Potholes ........ 107 Peng-Yuan Chen and Shih-Chung Kang Comparison of Traditional Laser Scanning and Mobile Lidar Technology for AECO Applications ..................................................................... 113 Nathan Blinn and Raja R. A. Issa Mobile Asset Tracking for Dynamic 3D Crane Workspace Generation in Real Time ................................................................................................................. 122 Jingdao Chen, Yihai Fang, and Yong K. Cho A Smart Construction Object (SCO)-Enabled Proactive Data Management System for Construction Equipment Management ............................................. 130 Yuhan Niu, Weisheng Lu, Diandian Liu, Ke Chen, and Fan Xue Potential Use of Cyber-Physical Systems (CPS) for Planning and Operation of Mobile Cranes on Construction Sites............................................. 139 C. Kan, C. J. Anumba, and J. I. Messner Proactive Construction Project Controls via Predictive Visual Data Analytics .................................................................................................................. 147 Jacob J. Lin and Mani Golparvar-Fard A Compact and Versatile Wireless Sensor Prototype for Affordable Intelligent Sensing and Monitoring in Smart Buildings ..................................... 155 Q. Huang, C. Mao, and Y. Chen © ASCE Computing in Civil Engineering 2017 x Vision-Based Activity Analysis Framework Considering Interactive Operation of Construction Equipment ................................................................. 162 Jinwoo Kim, Seokho Chi, and Bon-Gang Hwang Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Perspective-Based Image-to-BIM Alignment for Automated Visual Data Collection and Construction Performance Monitoring ...................................... 171 Khashayar Asadi Boroujeni and Kevin Han Towards Light Intensity Assisted Non-Intrusive Electricity Disaggregation......................................................................................................... 179 Jue Wang and Farrokh Jazizadeh Smart Tracking of Highway Construction Projects ............................................ 187 Nazila Roofigari Esfahan, Shuming Du, Chimay Anumba, and Saiedeh Razavi On the Scalability of an LED-Based Indoor Positioning System ....................... 196 Milad Afzalan and Farrokh Jazizadeh Modeling and Simulation Modeling the Effect of a Socio-Psychological Process on Construction Workers’ Safety Behavior ...................................................................................... 205 Byungjoo Choi and SangHyun Lee Uncertainty Analysis for Thermal Comfort Evaluation in Naturally Ventilated Buildings ............................................................................................... 213 Jianli Chen, Godfried Augenbroe, Qinpeng Wang, and Xinyi Song A Basic Study on the Evacuation Characteristics of High-Rise Building through Comparing Evacuation Experiment and Simulations—A Case Study in Korea ........................................................................................................ 221 Jaehong Kim, Yongwei Shan, Junho Choi, Phil Lewis, and Wonhwa Hong Imaging-to-Simulation Framework for Improving Disaster Preparedness of Construction Projects and Neighboring Communities ................................... 230 Youngjib Ham, Seung Jae Lee, and Arindam Gan Chowdhury Formulating the Minimum Network Clearance Time for Evacuation Problems .................................................................................................................. 238 Yu-Ting Hsu and Hsiang-Yin Chen Planning Rough-Grading Projects: CAT Handbook vs. RS Means .................. 246 Chaojue Yi and Ming Lu © ASCE Computing in Civil Engineering 2017 xi Integrating Activities Risk and Traffic Microsimulation Data for Temporal Risk Assessment in Construction Work Zones: A Proof of Concept ................. 254 Bharathwaj Sankaran, Jojo France-Mensah, and William J. O’Brien Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Building Accessibility Code Compliance Verification Using Game Simulations in Virtual Reality ............................................................................... 262 Abdulaziz Alghamdi, Mohammed Sulaiman, Abdullah Alghamdi, Mohammed Alhosan, Majid Mastali, and Jiansong Zhang Development of Real-Time Indoor Temperature Distribution Simulation: A Pilot Study ........................................................................................................... 271 Chanachok Chokwitthaya, Yimin Zhu, Suraj Talele, Caleb Traylor, and Yong Tao Stochastic Forecasting of Unknown Future Project Streams for Strategic Portfolio Planning ................................................................................................... 280 Alireza Shojaei and Ian Flood Agent-Based Simulation Framework for Supply Chain Management of Large-Scale Construction Projects ....................................................................... 289 Minhyuk Jung Multi-Asset Optimization of Roadways Asset Maintenance .............................. 297 Omidreza Shoghli and Jesus M. de la Garza Investigating the Impact of Human Risk Taking Tendency on the Likelihood of Struck-By Accidents in Construction Using Agent-Based Simulation ................................................................................................................ 306 Cenfei Sun, Seungjun Ahn, and Changbum Ahn Implementation Verification and Validation of 3D Structural Elements in a Numerical Tool for Nonlinear SSI Seismic Analysis .................................... 315 Floriana Petrone, Jenna Wong, David McCallen, and Frank McKenna Robust Outlier Detection and Normal Estimation in Noisy Infrastructure 3D Point Clouds ...................................................................................................... 323 Ali Khaloo and David Lattanzi Comparison Basis of Building Information Modeling Workflows for Energy Analysis ...................................................................................................... 332 Pelin Gultekin-Bicer, Issa J. Ramaji, and Chimay J. Anumba Robotics and Automation Automatic Barcode Extraction for Efficient Large-Scale Inventory Management ............................................................................................................ 340 Lichao Xu, Vineet R. Kamat, and Carol C. Menassa © ASCE Computing in Civil Engineering 2017 xii Roles, Benefits, and Challenges of Using UAVs for Indoor Smart Construction Applications ..................................................................................... 349 B. Y. McCabe, H. Hamledari, A. Shahi, P. Zangeneh, and E. Rezazadeh Azar Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Application of Assistive Wearable Robotics to Alleviate Construction Workforce Shortage: Challenges and Opportunities .......................................... 358 Chao Wang, Laura Ikuma, Jan Hondzinski, and Marcio de Queiroz Virtual Reality and Augmented Reality High-Fidelity Visualization of Fire following Earthquake ................................. 366 Xinzheng Lu, Xiang Zeng, Zhen Xu, and Qingle Cheng Quantifying Human Experience in Interior Architectural Spaces .................... 373 A. Radwan and S. Ergan Application of Immersive Virtual Environment (IVE) in Occupant Energy-Use Behavior Studies Using Physiological Responses............................ 381 Sanaz Saeidi, Adam Lowe, Neil Johannsen, and Yimin Zhu The Impact of Lighting Simulation Discrepancies on Human Visual Perception and Energy Behavior Simulations in Immersive Virtual Environment ............................................................................................................ 390 Chanachok Chokwitthaya, Sanaz Saeidi, Yimin Zhu, and Robert Kooima Interactive Highway Construction Simulation Using Game Engine and Virtual Reality for Education and Training Purpose ..................... 399 Majid Mastli and Jiansong Zhang Development of Immersive Personalized Training Environment for Construction Workers ............................................................................................ 407 Idris Jeelani, Kevin Han, and Alex Albert © ASCE Computing in Civil Engineering 2017 Simultaneous Data Exchange between BIM and VR for Collaborative Decision Making Jing Du, Ph.D.1; Zhengbo Zou2; Yangming Shi3; and Dong Zhao, Ph.D.4 1 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Assistant Professor, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77843 (corresponding author). E-mail: [email protected] 2 Ph.D. Student, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77843. E-mail: [email protected] 3 Ph.D. Student, Dept. of Construction Science, Texas A&M Univ., College Station, TX 77843. E-mail: [email protected] 4 Assistant Professor, School of Planning, Design and Construction, Michigan State Univ., East Lansing, MI 48824. E-mail: [email protected] Abstract Virtual reality (VR) has attracted increasing attention of the architecture, engineering, construction and facility management (AEC/FM) industry in recent years. VR has the potential to improve workflow efficiency through enhanced common understanding. However, the current workflow, which usually contains manually converting design files to VR application, is quite cumbersome and usually, inefficient. The lack of automated and efficient data exchange approach and protocol could potentially cause designers and other users to abandon VR after the first few design cycles. In this paper, we introduce a BIM-VR real-time data exchange system. The system is based on an innovative Cloud-based BIM metadata interpretation and communication method. With the function of allowing users to update BIM model changes in VR headsets automatically and simultaneously, the system achieves high user stickiness and reduces the complexity of workflow. We tested the system in a variety of design change scenarios including changing object dimensions and changing object types. Results confirmed the usability and efficiency. Keywords: BIM, Virtual reality, Information latency, Metadata, Cloud computing. INTRODUCTION & LITERATURE REVIEW BIM has gained its popularity in the AEC/FM industry in the past decades (Bernstein et al. 2012). With increasing number of use cases during design, construction and operation phases, BIM shows its potential in the whole life cycle management of a building asset (Grilo and Jardim-Goncalves 2010). BIM could be used as a 3D visualization platform for built or not yet built buildings (Shiratuddin and Thabet 2011). The ability of demonstrating an intuitive model among different stakeholders, especially those without a background in the AEC industry, has great potential of facilitating the communication and bring up awareness of problems during design phases (Shiratuddin and Thabet 2011). © ASCE 1 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Computing in Civil Engineering 2017 The combination of BIM and game engines provides intuitive and realistic 3D models for better human interaction with the building due to the powerful 3D and physics engines residing in the modern game engines (Mól et al. 2008). Building visualization could even be achieved in unprecedented ways, such as, creating highly credible surroundings, visualizing sensor data intuitively and creating lifelike avatars for user interactions (Park and Kim 2013; Rüppel and Schatz 2011). Evidence shows that interactive building models improved by game engines has the benefit of enhancing user experience and user communication during various phases in a building project (Yan et al. 2011). With the rapid improvement in technology industry, the usage of virtual reality (VR) is finding its way in AEC/FM industry. Integrated with game engine and BIM, VR applications are developed for facilitating design, visualization, management and communication . The participation of technology giants such as Google, Facebook and Microsoft, only helps to bring down the cost of VR technology, and spread VR headsets to more users around the globe. Researches on various VR technology use cases in AEC industry have been conducted, and showed positive results on improving the quality of the entire AEC/FM industry workflows (Fernandes et al. 2006; Kasireddy et al. 2016; Messner et al. 2003; Park and Kim 2013; Rekapalli and Martinez 2007; Zielinski et al. 2015). However, with the complexity of the game engine development, VR integration and still under power VR hardware, users in AEC industry could find various problems in the BIM to VR workflow. For example, missing information, slow response and difficulties when integrating building information more than just geometry (Kasireddy et al. 2016). Therefore, this research aims to develop a framework to effectively exchange information between VR application and BIM design software. We will test the framework by experimenting information exchange in a toy example first, then examine it in a real-world project. BVRS: BIM-VR REAL-TIME SYNCHRONIZATION Given the great potentials of BIM-VR applications in the AEC/FM areas, there is a pressing need to address the data synchronization issue between BIM and VR databases. We propose a BIMVR real-time synchronization system, or BVRS to tackle this issue. BVRS builds upon the metadata of BIM databases, and establishes an innovative Cloud-based workflow to automate the real-time transfer of metadata between BIM and VR game engine. The remainder of this section will introduce the details of BVRS. Overall Architecture of BVRS As illustrated in Fig. 1, BVRS consists of four major components: BIM software, Cloud servers and database, game engine, and VR applications. BIM provides the project model. In our pilot study, we use Revit as the BIM platform so that architects and engineers can work in their most comfortable environment. Cloud servers and database provide an online calculating and storing space. Real time updates can be achieved by pushing and retrieving information from and to servers. Functions like building walk around, BIM information extraction, and model refreshing can be developed within the game engine development kit, for example, Unity3D. VR applications are the user end of BVRS system. Users interact with building models using a © ASCE 2 Computing in Civil Engineering 2017 3 controller or simply by using “gaze to select”. To achieve the functions mentioned in BVRS system, three main steps are needed: gather metadata from BIM; transfer metadata via cloud server; develop in game engine. Revit Game Engine Metadata VR HeadSets Data • • • • Creator Element ID Cost Code File Size... • • Object Data Cost Data... • • • • Object Data IFC Geometry Material Manufacture Model... Logic (Controller) Oculus Rift Start YES Upload&Transfer Request Response Cloud Database & Server Cloud Database Element ID Cloud Server ElementID > maxID PropertyID = 0 ElementID += 1 Publish YES Proxy Server Composed Response NO ObjectData[PropertyID] Change API NO YES Destroy Object[ElementID] Protocal Application Server Request Create Object[ElementID] with updated property Response } …… …… { "Position": [ 3.00, 2.00, 1.00 ], "Material": "Steel", "Manufacture": Best Steel Co., "Model": null, } Web Browsers Standalone Apps PropertyID > maxID { 000000 …… …… 999999 Google Cardboard NO Object Data "Position": [ 1.00, 2.00, 3.00 ], "Material": "Concrete", "Manufacture": Best Concrete Co., "Model": null, Samsung Gear VR ElementID = 0 API Data Request Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Element ID PropertyID += 1 Fig.1 Architecture of BVRS Step 1: Gather Metadata in BIM First, metadata from BIM models has to be collected and preserved. To match individual objects from BIM software, such as Revit, to their metadata, identifications (IDs) must be deployed, such as Global Unique Identifier (GUID) (Jeong et al. 2009), Unique ID (Kull 2012) and Element ID (Liu et al. 2015). The IDs are used in two parts of the BVRS system. First, IDs are used to match objects to objects’ properties, such as material, dimension and manufacture. Second, IDs are used to match objects in Revit to corresponding objects on the cloud database and the corresponding objects in game engines. ID is an important part of BVRS system. It simply plays a role as a key to all objects information. For example, during the process of transferring projects model from Revit to Unity © ASCE Computing in Civil Engineering 2017 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. 3D, which is a commonly used process (Dalton and Parfitt 2013; Du et al. 2016), the Element IDs are preserved, and later can be found as part of the name of corresponding objects in game engines. For example, a cabinet, after transferred into a game engine, might have a name like “Base Cabinet-Double Door & 2 Drawer 33 [974236]”. The six-digit number, “[974236]”, is the Element ID of this cabinet. Step 2: Transfer and Store Metadata via a Cloud Server Real-time updates require Revit constantly sending updated information to a shared database, such as a cloud server. Once the object changed and stored locally, such as saved in a Revit project, updated information should be pushed to the cloud database. The updated information then would be received and stored in the cloud database. The basic functions of the cloud server and database include: listening to requests; judging validity of requests; identifying the changed objects; and committing the updated information. The web server in BVRS monitors user requests, such as http requests from a Revit plugin. Once receiving a request, the web server determines if the request is valid. If so, send the request to the application server. If not, discard the request and continue to listen to other requests. Application server then examine the requested ID. If the ID was valid, further examine the requested property of the object with the correct ID. If the property was also valid, the database would update properties according to the user’s request. The cloud server and database simply only keep records of the projects’ information, so that VR applications can pull the stored information and adjust their models accordingly. Step 3: Develop in Game Engine To build a VR application with real-time BIM data updating function, four major parts are developed, including: model transfer and refinement; user interface design; cloud server connections and player functions development. First, model transfer is to bring the developed model from BIM software to game engine for further development. One major challenge is model refinement, which includes enriching the model and reducing lagging at run time. Enriching the model can be done in the game engine by creating new materials and attaching them to the corresponding objects. Note that newly created materials should have the same names as their old counterparts, so that the objects’ property information remains intact. Reduce lagging at run time can be achieved by utilizing the same texture for objects with same materials and deploy built-in improvement functions, such as Occlusion Culling in Unity3D (Unity Documentation 2016). Second, user interface of the VR application should be developed according to the VR device. For example, if the VR device is a Google Cardboard, due to the lack of buttons of that platform, developers should keep in mind that a proper user interface might include a large amount of “gazing to select”. If the VR device is Oculus Rift or similar computer powered VR devices, user interface and interactions can be much more complex. For example, mouse and arrow keys on keyboard can be used as navigation tools. Other input devices can also be attached to a computer, such as a Bluetooth controller. With a Bluetooth controller, user interactions can be developed by © ASCE 4 Computing in Civil Engineering 2017 5 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. mimickin ng commonlly seen gamees on gamin ng consoles. If the VR deevice is a high-end dediicated VR head dset like HTC C Vive, or Oculus O Rift with Touchh, the user innterface desiign should uutilize controllers provided by those platforms. Fo or example, HTC Vive controller ccan be usedd as a handle to o pick up and d relocate ob bjects in VR scenes. Third, BVRS is heaavily relied on the cloud server andd database. The VR appplication crreates requests for the cloud d server everry few secon nds, and receeives updateed informatioon from the ccloud ormation, su uch as objecct’s propertiies, is indeeed changed,, VR appliccation database.. If the info should find f the updated objecct by ID, then t update the properrties accordding to the new informatiion. Finally, users of VR applicatio ons control the movem ment of their avatars tthrough a pplayer controller. Basic fun nctions of a player p contro oller shouldd include: waalking in sceene; moving head and turniing body; po ointing at objjects interest users and uupdating thee model in reeal time. Waalking and turniing can be acccomplished d by reading the user inpuut from inpuut devices, liike a joystickk of a controller or the arro ow keys on keyboards. k Pointing P andd updating ccan be triggeered by dediicated buttons on o keyboardss or controlleers. TEST CASE Overview w We impllemented BV VRS to an existing bu uilding modeel, Francis Hall, home of Construuction Science Department D at Texas A& &M University. It shouuld be noted that due to the large siize of the Fran ncis Hall BIM B model, although all model ccomponentss are presennted in thee VR environm ment, only paart of the mo odel is synch hronized on oour Cloud seerver. Scenario o 1: Changin ng Object Tyype In the fiirst experim ment scenario o, we tested d if BVRS can update object typee changes inn VR headsets in real timee. One user changed thee type of a cchair in Revit, as shownn in Fig.2 (aa) and (b). Otheer users werre able to th he see the ch hange in theeir Oculus R Rift DK2 heeadsets. Nettwork delays may m be experienced by the users. Due D to the ddifficulty off measuring an everchannging network speed, the network delay y was not measured in thhis experimeent. (a) Th he chair type before chan nge in Revit © ASCE (b) T The chair typpe after channge in Revit Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. Computing in Civil Engineering 2017 (c) The view v of the chair c in VR before b chang ge 6 (d) Thee view of thee chair in VR R after changge Fig g. 2 Synchron nizing objecct type changges of a chairr via BVRS Scenario o 2: Changin ng Object Diimensions Our seco ond experiment scenario o tested dimeension channges. As illustrated in Fiig.3 (a), onee user can chan nge the heigh ht of a cabineet from 2’6”” to 3’6” in R Revit. Meanw while, other users can seee the changes in i Oculus Riift headsets, as illustrated in Fig.3 (cc) and (d). (e) Abou ut to change the height of o a cabinet in i Revit (f) Thhe height of the cabinet w was changedd (g) Th he view of th he cabinet in VR before change (h) T The view of the cabinet in VR after change Fig. 3 Synchronizing dimenssional changes of a cabinnet via BVR RS © ASCE Computing in Civil Engineering 2017 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19. Copyright ASCE. For personal use only; all rights reserved. DISCUSSION AND CONCLUSIONS In this paper, we introduced a real-time BIM-VR data synchronization system called BVRS (BIM-VR Real-time Synchronization) that updates BIM design changes in VR headsets automatically and simultaneously. BVRS builds on a metadata interpretation and communication protocol with a cross-platform Cloud infrastructure. Our prototype version of BVRS includes a Revit plugin that gathers BIM metadata on a regular basis, a Cloud server that organizes and transfers metadata based on the objects’ element ID stored in the Revit file, and a game engine that displays changes in VR headsets such as Oculus Rift DK2. BVRS also supports multiple users in the same model for enhanced interpersonal communication. Our test case shows that real-time synchronization of BIM data in VR devices is possible for different scenarios. Our future research agenda will focus on improving BVRS efficiency for complex models, such as those with many MEP objects. In our test case (not shown in this paper), we found that if a BIM model contains a large number of interdependent objects, the speed of BIM-VR data synchronization is affected. An explanation is that BVRS needs to dynamically monitor changes of every object in a BIM model. When the number of BIM objects are too large, the search/scanning process will consume much computing resource and eventually slows down the synchronization. The use of IDs as search key seems not be the most efficient approach. Other tree-based search algorithms (Kanal and Kumar 2012) will be examined to improve search efficiency. Another direction of this research is to evaluate if BVRS can help improve AEC/FM workflow efficiency through an enhanced common understanding among key parties. We will perform human-subject experiments to compare the productivity and quality of design change coordination meetings between teams using BVRS and those using conventional approach. Reference Bernstein, H. M., Jones, S. A., Russo, M., Laquidara-Carr, D., Taylor, W., Ramos, J., Healy, M., Lorenz, A., Fujishima, H., and Fitch, E. (2012). "The business value of BIM in North America." 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Search in artificial intelligence, Springer Science & Business Media. Kasireddy, V., Zou, Z., Akinci, B., and Rosenberry, J. "Evaluation and Comparison of Different Virtual Reality Environments towards Supporting Tasks Done on a Virtual Construction Site." Proc., Construction Research Congress 2016, 2371-2381. © ASCE 7