for Journals by Title or ISSN
for Articles by Keywords
  Subjects -> COMPUTER SCIENCE (Total: 2064 journals)
    - ANIMATION AND SIMULATION (31 journals)
    - ARTIFICIAL INTELLIGENCE (101 journals)
    - AUTOMATION AND ROBOTICS (105 journals)
    - COMPUTER ARCHITECTURE (10 journals)
    - COMPUTER ENGINEERING (11 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER PROGRAMMING (26 journals)
    - COMPUTER SCIENCE (1196 journals)
    - COMPUTER SECURITY (46 journals)
    - DATA BASE MANAGEMENT (14 journals)
    - DATA MINING (35 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (29 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (110 journals)
    - INTERNET (93 journals)
    - SOCIAL WEB (51 journals)
    - SOFTWARE (33 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1196 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 27)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 12)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 5)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 4)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 29)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Sciences     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 44)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 11)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 142)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 294)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 21)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 37)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 47)
British Journal of Educational Technology     Hybrid Journal   (Followers: 137)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 21)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 52)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 16)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 96)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 23)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 19)
Computer Physics Communications     Hybrid Journal   (Followers: 7)

        1 2 3 4 5 6 | Last

Journal Cover
Automation in Construction
Journal Prestige (SJR): 1.613
Citation Impact (citeScore): 5
Number of Followers: 6  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0926-5805
Published by Elsevier Homepage  [3162 journals]
  • Occupancy prediction through machine learning and data fusion of
           environmental sensing and Wi-Fi sensing in buildings
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Wei Wang, Jiayu Chen, Tianzhen Hong Occupancy information is crucial to building facility design, operation, and energy efficiency. Many studies propose the use of environmental sensors (such as carbon dioxide, air temperature, and relative humidity sensors) and radio-frequency sensors (Wi-Fi networks) to monitor, assess, and predict occupancy information for buildings. As many methods have been developed and a variety of sensory data sources are available, establishing a proper selection of model and data source is critical to the successful implementation of occupancy prediction systems. This study compared three popular machine learning algorithms, including k-nearest neighbors (kNN), support vector machine (SVM), and artificial neural network (ANN), combined with three data sources, including environmental data, Wi-Fi data, and fused data, to optimize the occupancy models' performance in various scenarios. Three error measurement metrics, the mean average error (MAE), mean average percentage error (MAPE), and root mean squared error (RMSE), have been employed to compare the models' accuracies. Examined with an on-site experiment, the results suggest that the ANN-based model with fused data has the best performance, while the SVM model is more suitable with Wi-Fi data. The results also indicate that, comparing with independent data sources, the fused data set does not necessarily improve model accuracy but shows a better robustness for occupancy prediction.
  • Automatic geometry measurement for curved ramps using inertial measurement
           unit and 3D LiDAR system
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Wenting Luo, Lin Li Although road geometry data can be automatically collected using instruments mounted on survey vehicle, measurement of curved ramp geometry is still of low effectiveness and accuracy due to manual or semi-automatic detection of PC (Point of Curvature)/PT (Point of Tangent) as well as influences of vehicle vibration and wandering. In this study a new method is presented for automatic measurement of ramp geometry in network level using IMU (Inertial Measurement Unit) and 3D LiDAR (Light Detection And Ranging) system. Firstly, horizontal alignment measurements are implemented: 1) an improved K-Mean clustering method and linear fitting method are integrated for automatic PC/PT station detection; 2) an algorithm is developed for automatic lane marking identification and localization for vehicle's trajectory calibration; 3) curve radius and length are measured based on roadway centerline. Subsequently, pavement slope is calibrated using IMU and transverse profiling data. Finally, nine segments are chosen from highway ramps as test bed, and validation tests are conducted using the field measurement. The test results show the average errors for curve detection and curve radius measurement are 5.89% and 1.99% respectively, and the P-value for longitudinal and cross slope measurement are 0.621 and 0.989 respectively, which indicate the proposed method is robust in ramp geometry measurement. The significant of the proposed method is three folds. First, it integrates and synchronizes the IMU and 3D LiDAR system in geometry measurement. Second, it solves the common problems of mobile survey on vehicle wandering and vibration. Third, it is of high accuracy and effectiveness, and can be used for roadway survey in network level.
  • Automatic recognition of asphalt pavement cracks using metaheuristic
           optimized edge detection algorithms and convolution neural network
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Hoang Nhat-Duc, Quoc-Lam Nguyen, Van-Duc Tran Crack detection is a crucial task in periodic pavement survey. This study establishes and compares the performance of two intelligent approaches for automatic recognition of pavement cracks. The first model relies on edge detection approaches of the Sobel and Canny algorithms. Since the implementation of the two edge detectors require the setting of threshold values, Differential Flower Pollination, as a metaheuristic, is employed to fine-tune the model parameters. The second model is constructed by the implementation of the Convolution Neural Network (CNN) – a deep learning algorithm. CNN has the advantage of performing the feature extraction and the prediction of crack/non-crack condition in an integrated and fully automated manner. Experimental results show that the model based on CNN achieves a good prediction performance of Classification Accuracy Rate (CAR) = 92.08%. This performance is significantly better than the method based on the edge detection algorithms (CAR = 79.99%). Accordingly, the proposed CNN based crack detection model is a promising alternative to support transportation agencies in the task of periodic pavement inspection.
  • Erratum to "Logic for ensuring the data exchange integrity of building
           information models [AUTCON 85 (2018) 249–262"]
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s):
  • LODOS - Going from BIM to CFD via CAD and model abstraction
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Stuart Porter, Tele Tan, Xiangyu Wang, Vishnu Pareek This paper looks at the challenge of performing Computational Fluid Dynamic simulations against models of real world environments and objects. The difficulty for these simulations is the effort required to render complex objects and environments, as well as the computational power required to solve them. To assist with the first problem, this paper presents a process for importing Building Information Models or 3D CAD models into ANSYS workbench, a popular CFD environment in industry. In order to address computational concerns, this paper also introduces and discusses a system, LODOS, designed to aid in importation and set-up of high complexity models by selectively reducing geometric complexity. This paper presents preliminary results from the use of this system to import two Building Information Models into ANSYS Workbench, showing the current strengths of the system, as well as discussing its current limitations.
  • Adaptive wavelet neural network for terrestrial laser scanner-based crack
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Yelda Turkan, Jonathan Hong, Simon Laflamme, Nisha Puri Objective, accurate, and fast assessment of civil infrastructure conditions is critical to timely assess safety risks. Current practices rely on visual observations and manual interpretation of reports and sketches prepared by inspectors in the field, which are labor intensive, subject to personal judgment and experience, and prone to error. Terrestrial laser scanners (TLS) are promising for automatically identifying structural condition indicators, as they are capable of providing coverage for large areas with accuracy at long ranges. Major challenges in using this technology are in storing significant amount of data and extracting appropriate features enabling condition assessment. This paper proposes a novel adaptive wavelet neural network (WNN)-based approach to compress data into a combination of low- and high-resolution surfaces, and automatically detect concrete cracks and other forms of damage. The adaptive WNN is designed to sequentially self-organize and self-adapt in order to construct an optimized representation. The architecture of the WNN is based on a single-layer neural network consisting of Mexican hat wavelet functions. The strategy is to first construct a low-resolution representation of the point cloud, then detect and localize anomalies, and finally construct a high-resolution representation around these anomalies to enhance their characterization. The approach was verified on four cracked concrete specimens. The experimental results show that the proposed approach was capable of fitting the point cloud, and of detecting and fitting the crack. The results demonstrated data compression of 99.4%, 72.2%, 92.4% and 78.9% for the four specimens when using low resolution fit for crack detection. For specimens 1, 2 and 3, 97.1%, 42.5% and 63.9% compression of data were obtained for crack localization, which is a significant improvement over previous TLS based crack detection and measurement approaches. Using the proposed method for crack detection would enable automatic and remote assessment of structural conditions. This would, in turn, result in reducing costs associated with infrastructure management, and improving the overall quality of our infrastructure by enhancing maintenance operations.
  • A real-time interaction platform for settlement control during shield
           tunnelling construction
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Xiongyao Xie, Qiang Wang, Isam Shahrour, Jun Li, Biao Zhou Settlement control has always been the first concern for all the participants of shield tunnelling construction when the shield machine passes through buildings, especially in urban areas. However, owing to insufficient information communication of the participants, abnormal settlement usually results, against which reasonable settlement control measures are difficult to take. Therefore, a real-time mobile interaction and coordinated management platform was designed and developed with the instant messaging (IM) tool. The key ingredients of the platform are timely auto-sending of monitoring data and information flow in the coordinated management mechanism. The platform can inform all participants timely of the settlement as well as the tunneling situation. With this platform, problems encountered during shield tunnelling construction can be solved by IM group discussion. The real-time interaction platform has been validated and verified in the project of Nanning metro line 1 crossing beneath Nanning railway station, which realized the settlement control goal of a maximum value of −4 mm.
  • Sensitivity analysis of structural health risk in operational tunnels
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Wenli Liu, Xianguo Wu, Limao Zhang, Yanyu Wang, Jiaying Teng During the operation of metro tunnels, structural performance could inevitably degrade due to the combined effects of the stochastic and disadvantageous environment. In order to reduce the randomness and uncertainty underlying the structural safety risk analysis in operational tunnels, this paper develops a novel hybrid approach to perform global sensitivity analysis. The deterministic and stochastic finite element (FE) model is used to develop the approximate relationship between input and output parameters with a high level of accuracy. Based on the simulated data from an FE model, a meta-model is constructed by a built Particle Swarm Optimization-Least Square Support Vector Machine (PSO-LSSVM) model. In this research, 10,000 groups of data are generated by the built PSO-LSSVM model, which provides data support for the global sensitivity analysis through Extended Fourier Amplitude Sensitivity Test (EFAST). The input variables with a high global sensitivity are identified as crucial variables which should be well controlled and managed during tunnel operation. A Hankou-Fanhu (H-F) tunnel section in the Wuhan metro system is utilized as a case study to verify the applicability of the proposed approach. Global sensitivity analysis enables the reduction of the epistemic uncertainty in tunnel structural safety management, providing insight into a better understanding of (1) the input-output causal relationships of the structural safety risk in operational tunnels, (2) the reduction of the epistemic uncertainty in project safety management of operational tunnels.
  • Terrestrial laser scanning harnessed for moisture detection in building
           materials – Problems and limitations
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Czesław Suchocki, Jacek Katzer Since the 1980s, Terrestrial laser scanning is successfully adopted in geodesy for contact-free measurements. Collecting dense point-clouds by using TLS is proven as increasingly useful in several other quasi-geodetic, structural, and civil engineering applications. In the study, the newest trend of harnessing TLS is discussed in association with assessing the properties of a scanned object as opposed to its geometrical location. The most promising area of the aforementioned application of TLS is moisture detection in buildings and structures. The present study involved a thorough research programme dedicated to this topic as described in previous publications. Different scanners utilizing visible green and infrared laser beam were harnessed in the research programme. Such aspects of scanning porous construction materials as roughness, colour and presence of water are analysed. Based on the experience, the possibilities and limitations of harnessing TLS for moisture detection in building materials are discussed in the study.
  • Drone-enabled bridge inspection methodology and application
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Junwon Seo, Luis Duque, Jim Wacker The field of Civil Engineering has lately gained increasing interest in Unmanned Aerial Vehicles (UAV), commonly referred to as drones. Due to an increase of deteriorating bridges according to the report released by the American Society of Civil Engineers (ASCE), a more efficient and cost-effective alternative for bridge inspection is required. The goal of this paper was to analyze the effectiveness of drones as supplemental bridge inspection tools. In pursuit of this goal, the selected bridge for inspection was a three-span glued-laminated timber girder with a composite concrete deck located near the city of Keystone in the state of South Dakota (SD). A drone, a Dà-Jiāng Innovations (DJI) Phantom 4, was utilized for this study. Also, an extensive literature review to gain knowledge on current bridge inspection techniques using drones was conducted. The findings from the literature review served as the basis for the development of a five-stage drone-enabled bridge inspection methodology. A field inspection utilizing the drone was performed following the stages of the methodology, and the findings were compared to current historical inspection reports provided by the SD Department of Transportation (SDDOT). Quantified data using the drone such as a spalled area of 0.18 m2, which is identical to the measurement provided by the SDDOT (0.3 m by 0.6 m), demonstrated the efficiency of the drone to inspect the bridge. This study detailed drone-enabled inspection principles and relevant considerations to obtain optimum data acquisition. The field investigation of the bridge demonstrated the image quality and damage identification capabilities of the drone to perform bridge inspection at a lower cost when compared to traditional methods.
  • Identification of latent legal knowledge in differing site condition (DSC)
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Tarek Mahfouz, Amr Kandil, Sukhrob Davlyatov Conflicts in construction projects have always been a major problem. Unless an alternate resolution mechanism is spelled out in the contract, these disputes are typically resolved in court, which might be time consuming and financially substantial. This paper represents a continuation in a research focused on creating robust methodologies for legal decision support within the construction industry. Consequently, this papers tackles the problem of automating the extraction of implicit knowledge about significant legal factors upon which verdicts of Differing Site Condition (DSC) litigations are based. To that end, the research methodology (1) utilized a set of 600 cases from the Federal Court of New York; (2) adopted 15 legal concepts that have been found to be statistically significant for DSC litigations; (3) implemented 4 weighing mechanism for data representation, namely Term Frequency, Logarithmic Term Frequency, Augmented Term Frequency, and Term Frequency Inverse Document Frequency; and (4) employed Machine Learning (ML) classifiers, namely Naïve Bayes, Decision Tree, and PART for the development of 12 prediction models. Among the finding of this study (1) ML classifiers present a suitable solution for the analyzed task; and (2) Naïve Bayes classifiers achieved the highest prediction accuracy of 88%.
  • Development of an automated optimizer for sustainable urban landscape
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Ossama A. Hosny, Elkhayam M. Dorra, Khaled A. Tarabieh, Khaled A. Nassar, Sherif Zahran, Mariam Amer, Ayman Ibrahim Current practice in selecting plants in the field of landscape design is based largely on aesthetic criteria, rather than cost and water consumption needs. This typically results in a design that neither minimizes the Life Cycle Cost (LCC) to the fullest nor optimizes the sustainability of water resources. This paper presents an Automated Optimizer for Sustainable Urban Landscape design (SEOUL) that supports landscape architects in overcoming the drawbacks of current practice. It consists of a database module that includes the list of plants from which the tool makes its selection, as well as an optimization model that uses dynamic programming to optimize the plant selection through minimizing initial cost and water needs. SEOUL is applied on selected case study projects in Egypt to demonstrate the functionality. It was validated by comparing SEOUL's results to those received from current practice through three actual projects. The results obtained shows a 44% and 33% savings in initial cost and water consumption respectively when using SEOUL versus traditional landscape design tools. In addition, the application's ergonomics was evaluated for ease of use, simplicity and efficiency for the end-users.
  • Knowledge-based decision support system for prefabricated prefinished
           volumetric construction
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Bon-Gang Hwang, Ming Shan, Kit-Ying Looi As prefabricated prefinished volumetric construction (PPVC) has gained considerable attention worldwide in the past few years, decision-making for implementing PPVC becomes critical. As a result, this study aims to (1) identify the key decision-making factors (DMFs) for the adoption of PPVC, (2) propose a scoring approach that can assess the feasibility of using PPVC for a given project, and (3) develop a Knowledge-Based Decision Support System for Prefabricated Prefinished Volumetric Construction (KBDSS-PPVC) that can facilitate the decision-making for PPVC implementation. To achieve these goals, a comprehensive literature review and pilot interviews with industry experts were conducted first, followed by a structured questionnaire administered to 41 construction organizations in Singapore. Results of the questionnaire reported 19 DMFs of PPVC, which were then used to create the PPVC scoring approach. Subsequently, the KBDSS-PPVC was developed using the created PPVC scoring approach. Lastly, a panel of industry experts validated the developed KBDSS-PPVC, by utilizing the tool for their current construction projects. Validation results showed that the developed system could provide reliable recommendations for the industry practitioners on the decision-making of PPVC. Existing literature has seldom addressed the decision-making of PPVC, therefore, this study bridges the knowledge gap and contributes to the current body of knowledge. Furthermore, the developed KBDSS-PPVC would be useful to the industry practitioners as well, because it can help them achieve a better and easier decision-making of PPVC.
  • Electro-hydraulic velocity and position control based on independent
           metering valve control in mobile construction equipment
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Jianpeng Shi, Long Quan, Xiaogang Zhang, Xiaoyan Xiong Independent metering valve control system can overcome the shortcomings of the traditional four-side linkage valve controlled system, such as poor controllability and large energy consumption, especially under the overrunning load condition. Current researches mainly focus on the velocity, pressure and energy consumption characteristics of the hydraulic system. However, with the intelligent development of mobile machinery and the continuous improvement of work quality requirements, each actuator should not only meet the velocity and output force requirements, but also achieve high positioning accuracy. Therefore, according to the independent metering valve control system and pump-valve hybrid control principle, a velocity and position combined control strategy based on mode switching is proposed to control the boom and arm of hydraulic excavator. Then, a mechanical-hydraulic co-simulation model including the whole hydraulic excavator is established to verify the strategy, predict control characteristics and determine the controller parameters. Furthermore, a test prototype based on the above principle is established, and the boom and arm operating characteristics with the proposed strategy are tested and analyzed. The results show that the hydraulic cylinders can move smoothly along the expected trajectory under the premise of low energy consumption. The operate velocity fluctuation is small and the positioning error to the target position is about 1 mm. Due to the boom cylinder and arm cylinder in the research are separately typical two and four quadrants working actuators, the research work has universal significance to smooth, high-precision and low energy consumption automation operation of various types of mobile machineries.
  • Assessment of compliance of dimensional tolerances in concrete slabs using
           TLS data and the 2D continuous wavelet transform
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Nisha Puri, Enrique Valero, Yelda Turkan, Frédéric Bosché While several concrete waviness assessment methods are being developed to overcome the disadvantages of one assessment method over the other, the sparseness of measurements associated with each method prevents from achieving a better understanding of how elevations and undulations change across the surface. Assessing waviness over multiple one-dimensional (1D)-survey lines may not accurately reflect the actual condition or waviness of the entire floor. The methodology presented in this paper presents a compliance-checking algorithm for detecting elements where dimensions exceed specified tolerance. It also enables assessment of a concrete surface in two-dimensional (2D) domain using the synergy of Terrestrial Laser Scanning (TLS) and Continuous Wavelet Transform (CWT). 2D CWT analysis provides information not only about the periods of the surface undulation, but also the location of such undulations. The validity of the methodology is established by running a test on point clouds obtained from a warehouse project near Gresham, Oregon. A rigorous comparison between one of the existing floor waviness measurement methods, the waviness index method, and the proposed method is made. The results showed that the proposed methodology delivers accurate results that enable the localization of surface undulations of various characteristic periods. Furthermore, the proposed method is more efficient in terms of time taken for acquiring the measurements, and is, thus, more cost efficient.
  • Optimal logistics planning for modular construction using two-stage
           stochastic programming
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Pei-Yuan Hsu, Panagiotis Angeloudis, Marco Aurisicchio The construction sector is currently undergoing a shift from stick-built construction to modular building systems that take advantage of modern prefabrication techniques. Long established in-situ construction practices are thus being replaced by processes imported from the manufacturing sector, where component fabrication takes place within a factory environment. As a result of this transformation, current construction supply chains, which have focused on the delivery of raw materials to sites, are no longer apt and need to make way to new, strengthened, and time-critical logistics systems. The aim of this study is to establish a mathematical model for the optimisation of logistics processes in modular construction covering three tiers of operation: manufacturing, storage and assembly. Previous studies have indicated that construction site delays constitute the largest cause of schedule deviations. Using the model outlined in this paper we seek to determine how factory manufacturing and inventory management should react to variations in the demand on construction sites. A two-stage stochastic programming model is developed to capture all possible demand variations on site. The model is evaluated using a case study from the residential construction sector. The application shows that the model is effective and can serve as decision support to optimise modular construction logistics.
  • The study on the integrated control system for curtain wall building
           façade cleaning robot
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Yong-Seok Lee, Sang-Ho Kim, Myeong-Su Gil, Seung-Hoon Lee, Min-Sung Kang, Sung-Hoon Jang, Bo-Hyun Yu, Byung-Gab Ryu, Daehie Hong, Chang-Soo Han Recently, with a growing number of high-rise buildings in cities, interest in building facade maintenance is increasing. The existing method of cleaning the exterior walls of existing high-rise buildings depended on the methods by workers who used ropes, gondolas, and winch systems. Recently, however, BMU (building maintenance unit) has been developed and applied to resolve safety problems and boost work efficiency. In Germany, USA, France and other countries, various types of robot systems for building façade maintenance are being applied. In South Korea, façade cleaning robots attached with curtain walls are also being developed. In this paper, we propose an integrated control system for the stable control of robots with the building façade cleaning technology. The proposed control system can be divided into three stages such as preparation stage, cleaning stage, and return stage. Each independent robot system performs tasks such as cleaning, moving, and obstacle detection according to each stage. A wireless communication system for stable communication between robots was proposed and applied for controlling the robot system. The proposed integrated control system was applied to building façade cleaning robots and its efficiency was verified compared with existing high-rise building cleaning methods.
  • Construction automation: Research areas, industry concerns and suggestions
           for advancement
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Qian Chen, Borja García de Soto, Bryan T. Adey Construction automation has shown the potential to increase construction productivity after years of technical development and experimenting in its field. Exactly how, and the possible benefits and challenges of construction automation, though is unclear and missing from current research efforts. In order to better understand the comprehensive potential of construction automation for increasing construction productivity and the associated possible ramifications, an objective and data-driven review of the use of automation technologies in construction was done. The review was accomplished by using text mining methods on publically available written documents, covering a wide range of relevant data including scientific publications and social media. The text mining software VOS Viewer and RapidMiner Studio were used to determine the most promising areas of research through the analysis of scientific publications, and the main areas of concern of industry through the analysis of text on social media, respectively. These research areas and concerns are summarized in this paper, and based on them suggestions for industry are made to help advance the uptake of automation in construction.Graphical abstractUnlabelled Image
  • A dynamic approach for evacuees' distribution and optimal routing in
           hazardous environments
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Pawel Boguslawski, Lamine Mahdjoubi, Vadim Zverovich, Fodil Fadli In a complex built environment, the situation changes rapidly during an emergency event. Typically, available systems rely heavily on a static scenario in the calculation of safest routes for evacuation. In addition, egress route calculation and evacuation simulations are performed separately from path-finding for rescue teams. In this paper, we propose a state-of-the-art dynamic approach, which deals not only with a 3D environment, shape of spaces and hazard locations, but also with the dynamic distribution of occupants during evacuation. A database of densities and information about hazard influence are generated and used to calculate optimal paths for rescue teams. Three simulation scenarios were rigorously compared in this study, namely static with constant density values determined for subsequent stages of evacuation, semi-dynamic with densities representing an actual people distribution in a building during evacuation simulation, and dynamic with temporal distribution of evacuees stored in a database, and dynamically used in optimal path calculations. The findings revealed that static simulation is significantly different from semi-dynamic and dynamic simulations, and each type of simulation is better suited for the decision task at hand. These results have significant implications on achieving a rapid and safe evacuation of people during an emergency event.
  • Ergonomic posture recognition using 3D view-invariant features from single
           ordinary camera
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Hong Zhang, Xuzhong Yan, Heng Li Manual construction tasks are physically demanding, requiring prolonged awkward postures that can cause pain and injury. Person posture recognition (PPR) is essential in postural ergonomic hazard assessment. This paper proposed an ergonomic posture recognition method using 3D view-invariant features from a single 2D camera that is non-intrusive and widely installed on construction sites. Based on the detected 2D skeletons, view-invariant relative 3D joint position (R3DJP) and joint angle are extracted as classification features by employing a multi-stage convolutional nerual network (CNN) architecture, so that the learned classifier is not sensitive to camera viewpoints. Three posture classifiers regarding arms, back, and legs are trained, so that they can be simultaneously classified in one video frame. The posture recognition accuracies of three body parts are 98.6%, 99.5%, 99.8%, respectively. For generalization ability, the relevant accuracies are 94.9%, 93.9%, 94.6%, respectively. Both the classification accuracy and generalization ability of the method outperform previous vision-based methods in construction. The proposed method enables reliable and accurate postural ergonomic assessment for improving construction workers' safety and healthy.
  • Technology gaps in Human-Machine Interfaces for autonomous construction
    • Abstract: Publication date: October 2018Source: Automation in Construction, Volume 94Author(s): Jan Czarnowski, Adam Dąbrowski, Mateusz Maciaś, Jakub Główka, Józef Wrona This paper presents the results of a holistic research experiment on the identification of gaps in the current state-of-the-art that hamper the utilization of Unmanned Ground Vehicles (UGVs) in various construction scenarios. The challenge of developing infrastructure with the use of UGVs has common aspects in both civilian and military contexts. The aim of the presented work is to show the influence of UGV Operational Requirements (ORs) on technological aspects of autonomous operation and on UGV Human-Machine Interfaces (HMIs). The authors have based the presented approach on previous experiences in analyzing UGV operations in security and military contexts, where they are widely applied. First, gap identification methodology and UGV Operational Requirements (ORs) are described. Next, analyses of gaps in the area of UGV autonomous operation and gaps in the field of UGV Human-Machine Interfaces (HMIs) are presented. Finally, selected aspects of these gaps are highlighted along with conclusions concerning challenges to meet the requirements.
  • Greenhouse gas emission monitoring system for manufacturing prefabricated
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Xingyu Tao, Chao Mao, Fangyun Xie, Guiwen Liu, PengPeng Xu Excessive greenhouse gas (GHG) emissions from construction stage pose an obvious and emerging challenge. Most previous studies on emissions from the construction phase only focused on emission prediction in advance of the actual construction activities or on quantitative analysis after building construction. A system that enables builders to monitor emissions from construction activities in real time is still lacked, although GHG emission monitoring (GEM) and analysis are considered as the top activities that must be performed to minimize excessive environmental impacts. As an initial exploration, this paper proposes a GEM system based on Internet of things (IoT) technology to real-time monitor emissions when manufacturing prefabricated components. In this system, Radio Frequency Identification (RFID) sensors are adopted to identify the component ID, and the corresponding material usage data are extracted from a database that is preset in the GEM system. Laser sensors are installed in the components production line to measure the running time of equipment so that energy usage can be calculated in real time. In addition, a data service platform was developed to implement wireless data transmission from production line to computing platform, where the monitoring results are visually presented. A production line of real-life prefabricated components in China is adopted to demonstrate that the IoT-based monitoring system can acquire and analyze real-time carbon emission data from the manufacturing process. The results indicate that GEM system can facilitate project teams to timely control irregular emissions, identify potential emission risks and explore possible strategies for minimizing carbon emissions in the construction sector.
  • Tower cranes layout planning using agent-based simulation considering
           activity conflicts
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Ahmed Younes, Mohamed Marzouk The layout planning of tower cranes is a processes which defines the types, the quantities and the positions of tower cranes, has a significant impact on the overall productivity and cost effectiveness of construction projects. Previous research utilized either mathematical methods or visualization tools to find an optimal tower crane layout plan. However, such methods and tools are not adequate to evaluate the effect of conflict among tower cranes, in terms of time and cost calculations. Moreover, they do not assure the maximum efficiency of tower crane layout to fulfill the needs of crane-based executed activities. This paper presents an Agent Based Simulation (ABS) model to overcome the limitations of previous research. The proposed ABS model has the superiority of quantitatively assessing the effect of conflict on the overall time and costs of tower crane operations. It is capable of simulating tower cranes operations and interactions between different agents of the model. Furthermore, it calculates the time and the cost of tower crane's operation cycles, taking into account the potential conflicts among the working tower cranes. In addition, the proposed model is able to compare between several combinations of tower crane layouts to achieve the optimum solution that fulfills the requirements, with respect to the time or the cost. A case study has been provided to demonstrate the capabilities and contributions of the developed ABS model.
  • Performative design environment for kinetic photovoltaic architecture
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): P. Jayathissa, S. Caranovic, J. Hofer, Z. Nagy, A. Schlueter The design of complex architectural components such as kinetic architectural elements poses a challenge due to the multiple technological branches involved. This paper presents a performative design environment that combines the branches of structural and energy engineering, control, industrial design, and architecture. The methodology is applied in the context of the Adaptive Solar Facade, a kinetic photovoltaic shading system for the HiLo building in Duebendorf, Switzerland. The authors describe how the environment enables the user to design the form of the facade, get feedback on its structural strength, analyse the energetic performance of the interior space, conduct a daylighting analysis, render images, and produce fabrication plans for a rapid design process. With the parametric design environment, project meetings transform from information exchanges to design sessions where all stakeholders can collaboratively influence the design and see immediate results. What would normally take a month, was condensed to just a few hours. Ultimately, this paper extends the field of performative design by presenting a practical example where a system as complex as a kinetic photovoltaic envelope can be designed, prototyped, and fabricated by a small team of four designers.Graphical Graphical abstract for this article
  • Monitor-While-Drilling-based estimation of rock mass rating with
           computational intelligence: The case of tunnel excavation front
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): M. Galende-Hernández, M. Menéndez, M.J. Fuente, G.I. Sainz-Palmero The construction of tunnels has serious geomechanical uncertainties involving matters of both safety and budget. Nowadays, modern machinery gathers very useful information about the drilling process: the so-called Monitor While Drilling (MWD) data. So, one challenge is to provide support for the tunnel construction based on this on-site data.Here, an MWD based methodology to support tunnel construction is introduced: a Rock Mass Rating (RMR) estimation is provided by an MWD rocky based characterization of the excavation front and expert knowledge.Well-known machine learning (ML) and computational intelligence (CI) techniques are used. In addition, a collectible and “interpretable” base of knowledge is obtained, linking MWD characterized excavation fronts and RMR.The results from a real tunnel case show a good and serviceable performance: the accuracy of the RMR estimations is high, Errortest≅3%, using a generated knowledge base of 15 fuzzy rules, 3 linguistic variables and 3 linguistic terms.This proposal is, however, is open to new algorithms to reinforce its performance.
  • EEG-based workers' stress recognition at construction sites
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Houtan Jebelli, Sungjoo Hwang, SangHyun Lee Taking into account that many construction workers suffer from excessive stress that adversely impacts their safety and health, early recognition of stress is an essential step toward stress management. In this regard, an electroencephalogram (EEG) has been widely applied to assess individuals' stress by analyzing brain waves in the clinical domains. With recent advancements in wearable EEG devices, EEG's ability can be extended to field workers, particularly by non-invasively assessing construction workers' stress. This study proposes a procedure to automatically recognize workers' stress in construction sites using EEG signals. Specifically, the authors collected construction field workers' EEG signals and preprocessed them to capture high-quality signals. Workers' salivary cortisol, a stress hormone, was also collected to label low or high-stress levels when they work at sites. Time and frequency domain features from EEG signals were calculated using fixed and sliding windowing approaches. Finally, the authors applied several supervised learning algorithms to recognize workers' stress while they are working at sites. The results showed that the fixed windowing approach and the Gaussian Support Vector Machine (SVM) yielded the highest classification accuracy of 80.32%, which is very promising given the similar accuracy of stress recognition in clinical domains where extricate and wired EEG devices were used and the subjects engage in minimal body movement. The results demonstrate that the proposed field stress recognition procedure can be used for the early detection of workers' stress, which can contribute to improving workers' safety, health, wellbeing, and productivity.
  • Evaluating performance of daylight-linked building controls during
           preliminary design
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Laura Bellia, Francesca Fragliasso Thanks to the spread of new light sources and of smart dynamic control systems, automation sector has begun to play a fundamental role in lighting design. In this regard, daylight-linked control systems (DLCSs) represent a particularly interesting research field, since they offer great opportunities both in obtaining energy savings and in improving visual comfort conditions. However, their use is not so spread, because of the difficulties in predicting their functioning during the design process and in evaluating their effective energetic and economic advantages: available technical solutions are so many that design choices can be very hard for specialists. To overcome these obstacles, a precise assessment methodology is needed. Given these premises, the goal of the paper is to show the effectiveness of new performance parameters (Daylight Integration Adequacy, Percentage Intrinsic Light Excess, Percentage Light Waste and Percentage Light Deficit) in order to evaluate DLCs performance and to underline which factors mostly affect their functioning.
  • A triangular mesh generator over free-form surfaces for architectural
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Qisheng Wang, Boqing Gao, Tierui Li, Hui Wu, Jianzhong Kan, Bo Hu Computer-aided design software enables the rapid conceptual creation of a curved surface geometry, whereas it is not a convenient task for engineers to create a discrete grid structure on a complex surface that meets architectural and aesthetic requirements. This emphasizes the importance of grid generating tools and methods. A new triangular mesh generator for the free-form curved surfaces of architectural structures is developed based on the mapping truss-like method. The mapping truss-like method builds a bidirectional mapping mechanism between 3D domain and 2D domain, generates meshes in 2D domain using constrained Delaunay triangulation, and relaxes the mesh iteratively with the planar mesh regarded as a plane truss structure. This generator can generate uniform meshes and adaptive meshes in harmony with the surface features by a relative edge size function for various free-form surfaces. The directional trend of the mesh is adjustable by rotating the initial node placement, and selected points can be fixed to mesh multi-surfaces. In addition, methods are proposed to counteract mapping distortion by adjusting the mesh-generating algorithm locally. Examples illustrate that the generator has wide adaptability, high automation and comprehensive control of resulting meshes. Thus, this paper presents a useful design tool for free-form surfaces of grid structures.
  • Modeling water flow on Façade
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Chul Woong Park, Jaeman Park, Naree Kim, Youngchul Kim This study aims to develop a novel method by which visually to simulate water flow paths on building façades. Rainwater runoff affects the designs of façades in terms of safety and aesthetics because runoff leaves dirt and stains on an aesthetic façade. The first step is to review flow simulation algorithms and identify its limitations in fluid visualization research on flow path simulations. The second step is to review an existing CFD program to identify its limitations, and then establish the goals of the newly proposed method. The third step is to identify the properties and behaviors of water on a surface, including basic fluid mechanics to establish the mechanical relationship between the water and the façade material. The fourth step involves an experiment with water flows to reveal their characteristics based on the literature. The fifth step is to develop an algorithm which visually simulates water flows on a building façade. As a result, “Rainflow01” and “Rainflow02” are developed based on the open-source Grasshopper component “Drainage Polysurface” and Rhino. Rainflow01 and Rainflow02, which work based on the angle variation and critical sliding angle of the water path, present an innovative approach for predictions of water paths over a façade.
  • Review of Unmanned Aerial System (UAS) applications in the built
           environment: Towards automated building inspection procedures using drones
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Tarek Rakha, Alice Gorodetsky Unmanned Aerial Systems (UAS – a.k.a. drones) have evolved over the past decade as both advanced military technology and off-the-shelf consumer devices. There is a gradual shift towards public use of drones, which presents opportunities for effective remote procedures that can disrupt a variety of built environment disciplines. UAS equipment with remote sensing gear present an opportunity for analysis and inspection of existing building stocks, where architects, engineers, building energy auditors as well as owners can document building performance, visualize heat transfer using infrared imaging and create digital models using 3D photogrammetry. This paper presents a comprehensive review of various literature that addresses this topic, followed by the identification of a standard procedures for operating a UAS for energy audit missions. The presented framework is then tested on the Syracuse University campus site based on the literature review to showcase: 1) pre-flight inspection procedure parameters and methodologies; 2) during-flight visually identified areas of thermal anomalies using a UAS equipped with Infrared (IR) cameras and; 3) 3D CAD modeling developed through data gathered using UAS. A discussion of the findings suggests refining procedure accuracy through further empirical experimentation, as well as study replication, as a step towards standardizing the automation of building envelope inspection.Graphical abstractUnlabelled Image
  • Linking radio-frequency identification to Building Information Modeling:
           Status quo, development trajectory and guidelines for practitioners
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Fan Xue, Ke Chen, Weisheng Lu, Yuhan Niu, G.Q. Huang The global construction industry has witnessed the prolific development of radio-frequency identification (RFID), building information modeling (BIM), and most recently, linkage of the two. However, comparatively little attention has been paid to understanding the status quo and development trajectory of such RFID-enabled BIM systems. In view of the proliferation of existing RFID, BIM, and information linkage, practitioners would benefit from guidelines for choosing systems so that their construction engineering and management (CEM) needs can be better met. Accordingly, the study described in this paper has two interconnected research aims: (1) to identify current patterns and development trends in RFID-enabled BIM systems; and (2) to develop guidelines for choosing appropriate solutions for different CEM scenarios. A review of 42 actual cases published in scholarly papers reveals that RFID, used to identify objects and improve real-time information visibility and traceability, is now increasingly linked to BIM as a central information platform. This study provides practitioners with five-step guidelines for linking RFID to BIM for various CEM needs. It also provides researchers with a point of departure for further exploration of approaches to enhancing the value of RFID, BIM, and the integration of one with the other.
  • Multi-point vibration measurement and mode magnification of civil
           structures using video-based motion processing
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Zhexiong Shang, Zhigang Shen Image-based vibration measurement has gained increased attentions in civil and construction communities. A recent video-based motion magnification method was developed to measure and visualize small structure motions. This new approach presents a potential for low-cost vibration measurement and mode shape identification. Pilot studies using this approach on simple rigid body structures were reported. Its validity on complex outdoor structures has not been investigated. In this study, a non-contact video-based approach for multi-point vibration measurement and mode magnification is introduced. The proposed approach can output a full-field vibration map that increases the efficiency of the current structural health monitoring (SHM) practice. The multi-point approach is developed based on the local phases which also fill the gap of the existing intensity-based multi-point vibration measurement. As an extension of the phase-based motion magnification, the multi-point measurement result is then integrated with the maximum likelihood estimation (MLE) to estimate the magnified frequency bands at each identified structure mode for operational deflection shape (ODS) visualization. This proposed method was tested in both indoor and outdoor environments for validation. The results show that using the developed method, mode frequencies and mode shapes of multiple points in complex structures can be simultaneously measured. And vibrations in each mode can be visualized separately after magnification.
  • UAV path planning method for digital terrain model reconstruction –
           A debris fan example
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Cheng-Hsuan Yang, Meng-Han Tsai, Shih-Chung Kang, Chi-Yao Hung This research develops an unmanned aerial vehicle (UAV) path-planning method that aims to ensure the required image overlap and optimize the flying routes when applying the UAV for digital terrain model's (DTM) reconstruction. To collect images on a terrain for image modeling, enough overlap between each collected image must be ensured. In addition, when planning the optimized flying routes for collecting images on a debris fan, the specifications of the debris fan and the limitations of the UAV should both be taken into consideration. The path planning method takes a debris fan as an example and refers to the specifications of a debris fan and the limitations of the UAV. The developed method can help the operators to ensure the image overlap through dividing the debris fan into cells by the UAV's maximum image collection distance interval. The near-optimized UAV flying paths are calculated though applying a modified ant colony optimization algorithm (ACO). The developed method is validated to be able to help operators to sufficiently use the limited UAV batteries and evaluate the efficiency of the image collection process. A site experiment was also conducted for validating the workability of the developed method. The result of the comparison shows that the path-planning method can reduce 18.5% of the image collection time. It also confirms that applying the method on an actual debris fan can guarantee the required image overlapping and generate a complete DTM without model breaking.
  • Decision framework for optimal installation of outriggers in tall
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Kang Zhou, Xiao-Wei Luo, Qiu-Sheng Li Installation sequence of outrigger system, an important structural component of high-rise buildings, is often determined simply based on engineers' experience, posing a threat to the structural safety and stability. This paper proposes a comprehensive decision framework for developing the optimal installation plan for the outrigger system, in which construction simulation and safety analysis of the overall structural system are well integrated. The proposed framework is applied to a super-tall building with a height of 600 m. First, the finite element method (FEM) model of the skyscraper used for construction simulation is validated by field measurements during Typhoon ‘Nida’. Based on the validated FEM model, the lower limits (earliest) for installing the outrigger system are obtained through the outrigger trusses' safety analysis for the service stage of the building, while the upper limits (latest) are determined through the analysis of structural stiffness and global stability for the construction stage. Thereupon, a rational plan is established for installing the outrigger system into the skyscraper, and the viability and efficiency of the proposed decision framework are examined by analyzing the construction simulation models. The outcomes of this study are expected to be of use and interest for structural engineers and researchers involved in construction management of installing outriggers into high-rise buildings, and therefore provide valuable implications for other similar projects.
  • Pose and trajectory control of shield tunneling machine in complicated
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Lintao Wang, Xu Yang, Guofang Gong, Jianan Du The present study is focused on developing a method for controlling the pose and trajectory of a shield tunneling machine (STM) applied in complicated stratum. Lacking method to determine target motions of thrust cylinders and suitable electro-hydraulic control system are major restrictions for the STM to realize automatic pose control. To overcome these bottlenecks, a mathematical method for determining the target motions of thrust cylinders is proposed based on kinematic analysis of the thrust mechanism. With this method, target motions of thrust cylinders when the STM excavates along any specific curves can be obtained and used as the input signal of the pose control system. A multi-cylinder control system is proposed based on master/slave control strategy to control the length of each kinematic chain in order to adjust the pose of the thrust mechanism. Experiments are carried out to evaluate the performances of this control system. The experimental results verify that the proposed pose control system is effective in controlling the pose and trajectory of the shield machine no matter it advances along a straight or a curved tunnel axis. Considering the complex loads during the experiments, the proposed system has great potential for applying in practical tunnel construction.
  • Utilizing IFC for shield segment assembly in underground tunneling
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Ying Zhou, Yu Wang, Lieyun Ding, Peter E.D. Love The shield method is a common approach used for subway tunnel excavation. A critical function of the shield method is the segment assembly process. It is, therefore, imperative to have access to information to be able to manage and control the performance of segment assembly during the construction process. However, an issue that hinders the capacity to undertake these tasks during construction is the inability of existing Building Information Modeling (BIM)-related software used to design tunnels to support information exchanges during a project's execution. The Industry Foundation Class (IFC) has evolved as an open and neutral data format to support information exchanges, but they are yet to be able to accommodate the segment assembly process. Considering the absence of such a data format, this research contributes to the extant literature through extending the IFC standard by treating the segment assembly shield used in construction as an ‘object’. It also proposes a new typesetting (i.e. positioning of segments) algorithm that can be used to automatically determine constraints. Moreover, the algorithm can define the design information that is required to enact data exchanges during construction. The newly developed IFC extensions are validated by demonstrating the successful transfer from a tunnel's parametric design models to the segment assembly system.
  • Proactive 2D model-based scan planning for existing buildings
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Meida Chen, Eyuphan Koc, Zhuoya Shi, Lucio Soibelman Creating a building information model (BIM) is known to be valuable during the life-cycle of a building. In most cases, a BIM of an existing building either does not exist or is out of date. For existing buildings, an as-is BIM is needed to leverage the technology towards building life-cycle objectives. To create an as-is BIM, field surveying is a necessary task in collecting current building related information. Terrestrial laser scanners have been widely accepted as field surveying instruments due to their high level of accuracy. However, laser scanning is a time-consuming and labor-intensive process. Site revisiting and reworking of the scanning process is generally unavoidable because of inappropriate data collection processes. In this context, creating a scan plan before going to a job-site can improve the data collection process. In this study, the authors have proposed a 2D proactive scan-planning framework that includes three modules: an information-gathering module, a preparation module, and a searching module. In addition, three search algorithms — a greedy best-first search algorithm, a greedy search algorithm with a backtracking process, and a simulated annealing algorithm — were compared based on 64 actual building site drawings to identify strength and limitations. The experimental results demonstrate that the greedy search algorithm with a backtracking process could be used to compute an initial scan plan and the simulated annealing algorithm could be used to further refine the initial scan plan. This paper will also introduce the results of a case study that deployed the proposed scan-planning framework. In the case study, the resulting 3D-point cloud that was generated based on the proposed framework was compared with the 3D point cloud created with data collected through a planned scanning process performed by a scan technician.
  • Computer vision aided inspection on falling prevention measures for
           steeplejacks in an aerial environment
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Qi Fang, Heng Li, Xiaochun Luo, Lieyun Ding, Hanbin Luo, Chengqian Li Falling from height accidents are a major cause of fatalities on construction sites. Despite a lot of research conducted on the enhancement of safety training and removal of hazardous areas, falling accidents remain a major threat for steeplejacks. According to NOISH FACE reports, 75.1% of the fall from height decedents didn't use the Personal Fall Arrest Systems (PFAS), which shows insufficient supervision of the use of Personal Protective Equipment (PPE) by steeplejacks. Few scholars consider PFAS an important measure to prevent falls and the existing studies on PPE inspections showed that they were unsuitable for the scenarios faced by steeplejacks. This paper proposes an automated inspection method to check PPEs' usage by steeplejacks who are ready for aerial work beside exterior walls. An aerial operation scenario understanding method is proposed, which makes the inspection a preventative control measure and highly robust to noise. A deep-learning based occlusion mitigation method for PPE checking is introduced. We tested the performance of our method under various conditions and the experimental results demonstrate the reliability and robustness of our method to inspect falling prevention measures for steeplejacks and can help facilitate safety supervision.
  • Modeling space preferences for accurate occupancy prediction during the
           design phase
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Seung Hyun Cha, Koen Steemers, Tae Wan Kim The accurate prediction of occupancy during the design phase of a building helps architects to improve space efficiency by eliminating the possible under-utilization and over-crowding of space during the design use phase. However, existing models exhibit limited accuracy in occupancy prediction. A major reason for this limitation is that spatial-choice behavior is ignored or oversimplified. We therefore developed a space-preference model to explain spatial-choice behavior, with a particular focus on individual work-related activities. For this purpose, we conducted a discrete-choice experiment: 2048 observations of spatial choices were collected, and a conditional logit model was used to model space preferences. The application of the space-preference model was illustrated by two case examples, with which the merits of the model were highlighted. It was then validated in a predictive success test and a case study. The model will help architects to assess potential over-crowding and under-utilization of space according to different design options.
  • Cloud asset-enabled integrated IoT platform for lean prefabricated
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Gangyan Xu, Ming Li, Chun-Hsien Chen, Yongchang Wei Prefabricated construction has become increasingly popular over the recent years, given its benefits including higher construction speed, lower cost, and improved quality. To facilitate the operations of prefabricated construction, various technologies have in parallel been introduced. However, due to its project-based feature and the involvement of numerous Small and Medium Enterprises (SMEs), the adoption of information technologies is insufficient and varies between SMEs, thereby hindering the improvement of the efficiency of prefabricated construction. Considering these issues and aiming at realizing lean prefabricated construction, this paper proposes an integrated cloud-based Internet of Things (IoT) platform through exploiting the concept of cloud asset. Its operation model has also been worked out to enable SMEs to adopt IoT technologies economically and flexibly. Besides, to make the platform compatible and scalable on managing diverse physical assets in different companies and scenarios, a unified cloud asset data model is proposed. Furthermore, an IoT service-sharing module is developed to support different levels of service-sharing on the platform. Finally, a real-life prefabricated construction project in Hong Kong and several lab-based LEGO construction models are adopted to verify the feasibility and effectiveness of the proposed platform.
  • Knowledge dynamics-integrated map as a blueprint for system development:
           Applications to safety risk management in Wuhan metro project
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Chao Dong, Fan Wang, Heng Li, Lieyun Ding, Hanbin Luo Safety has always been a persistent problem in the construction industry, particularly for tunnel construction projects due to the inherent uncertainty in geotechnical conditions and the complexity of the tunnel construction process. Literatures and practices highlight the importance of safety knowledge to the construction safety. However, safety knowledge is not always provided in a convenient and timely manner. This paper develops a Knowledge-dynamics Integrated Map (KIM) to visualize safety knowledge flow in tunnel construction safety risk management. The KIM highlights the what, the who, and the why of knowledge flow by portraying its dynamics associated to the working processes. With the use of KIM, the safety knowledge flow barriers are identified so that knowledge flow facilitators can be designed. The KIM has been applied in Wuhan metro project as a blueprint for systematically developing effective safety knowledge management systems.
  • Automated performance measurement for 3D building modeling decisions
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Saman Yarmohammadi, Daniel Castro-Lacouture Building information modeling (BIM) is instrumental in documenting design, enhancing customer experience, and improving product functionality in capital projects. However, high-quality building models do not happen by accident, but rather because of a managed process that involves several participants from different disciplines and backgrounds. Throughout this process, the different priorities of design modelers often result in conflicts that can negatively impact project outcomes. To prevent such unwanted outcomes from occurring, the modeling process needs to be effectively managed. This effective management requires an ability to closely monitor the modeling process and correctly measure the modelers' performance. Nevertheless, existing methods of performance monitoring in building design practices lack an objective measurement system to quantify modeling progress. The widespread utilization of BIM tools presents a unique opportunity to retrieve granular design process data and conduct accurate performance measurements. This research improves upon previous efforts by presenting a novel application programming interface (API)-enabled approach to (a) automatically collect detailed model development data directly from BIM software packages in real-time, and (b) efficiently calculate several modeling performance measures during schematic and design development phases of building projects. These indicators can be used to properly arrange modeling teams in the quest for high-quality building models. The specific objectives of this study to examine the feasibility of a proposed automated design performance measurement framework, and to identify optimal modeling team configurations using empirical performance information. A passive data recording approach allows for the real-time capture of comprehensive user interface (UI) interaction and model element modification events. The proposed framework is implemented as an Autodesk Revit plugin. Next, an experiment is conducted to capture data using the developed Revit plugin. Experiment participants' individual production rates are estimated to establish the validity of the proposed approach to identify the optimal design team configuration. The presented approach uses the earliest due date (EDD) sequencing rule in combination with the critical path method (CPM) to calculate the maximum lateness for different design team arrangements.
  • Automated tower crane planning: leveraging 4-dimensional BIM and
           rule-based checking
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Yuanshen Ji, Fernanda Leite Reviewing tower crane plans in the pre-construction phase is an iterative process and one that is in need of an approach that improves its effectiveness and efficiency. This study proposes a framework that integrates 4D modeling and rule-based checking for reviewing tower crane plans. A template of crane-specific rules that are based on prevailing tower crane design standards in the United States was developed. This framework is capable of automating the review process and identifying potential spatial and capacity conflicts based on design models and construction schedules. This work presents a prototype system to which crane-specific rules are applied in a rule-checking platform that uses a 4D model as input. In the validation tests, the system's effectiveness is demonstrated by its high recall rates. Efficiency is achieved through diminishing manual interventions. The proposed approach also gives rise to an automated tower crane-planning process, reducing the need for manual input. Higher efficiency allows users to review more alternatives consistently when compared with the manual approach.
  • Automating and scaling personalized safety training using eye-tracking
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Idris Jeelani, Kevin Han, Alex Albert Research has shown that a large proportion of hazards remain unrecognized, which expose construction workers to unanticipated safety risks. Recent studies have also found that a strong correlation exists between viewing patterns of workers, captured using eye-tracking devices, and their hazard recognition performance. Therefore, it is important to analyze the viewing patterns of workers to gain a better understanding of their hazard recognition performance. From the training standpoint, scan paths and attention maps, generated using eye-tracking technology, can be used effectively to provide personalized and focused feedback to workers. Such feedback is used to communicate the search process deficiency to workers in order to trigger self-reflection and subsequently improve their hazard recognition performance. This paper proposes a computer vision-based method that tracks workers on a construction site and automatically locates their fixation points, collected using a wearable eye-tracker, on a 3D point cloud. This data is then used to analyze their viewing behavior and compute their attention distribution. The presented case studies validate the proposed method.Graphical abstractUnlabelled Image
  • Project selection and scheduling for phase-able projects with
           interdependencies among phases
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Ali Shafahi, Ali Haghani This research proposes a model for project selection and scheduling when some of the projects in the available pool of projects can be implemented in phases. We present a mixed integer programming (MIP) model that maximizes the Net Present Value (NPV) of future investments in situations where temporal budget limitations and reinvestment strategies exist. The MIP reveals the optimal phasing solution. It models the Interdependencies among different phases of a project and also takes the foundation/infrastructure requirements for development of future phases into consideration. To solve large-size problems, we present a solution method that initially reduces the problem size. Then, a two-step heuristic is presented that in the first step adds projects to the pool of selected projects one by one based on a favorability measure and in the second step, eliminates some phases of the chosen projects with some probability. The performance of the heuristic is illustrated through five small-size and four large-size examples. We perform sensitivity analysis by altering various parameters that affect the heuristic's performance such as different favorability measures, and different initial available budgets. The results are favorable for the preprocessing step and solution heuristic. On small-size scenarios, the heuristic can find the optimal solution from the MIP in almost all cases. Furthermore, on large-size scenarios, the heuristic finds solutions within approximately 100 s that are better than the ones found by solving the MIP given a 10,000 s time limit.
  • Digital construction: From point solutions to IoT ecosystem
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Roy Woodhead, Paul Stephenson, Denise Morrey This paper takes a longitudinal view of literature to explain the current period as disruptive technology drives an evolutionary adaptation of the construction industry in a historical socio-technological process. The authors argue the way Internet of Things (IoT) solutions are conceived as singularly focused “point solutions” undermine future opportunities. An evolutionary view is overlooked because extant literature describes technology in a particular epoch. An ecosystem perspective needs to influence IT strategy as an emerging “digital layer” transcends a smart city and continues to function long after a traditional construction project completes. We describe innovation as a succession of transformational waves in an evolutionary process that is currently manifesting as “Industry 4.0” and changing expectations for the construction industry. The paper concludes by listing emerging trends and warns existing UK construction companies must understand the transformational process they are in and learn how to adapt with a stronger drive for R&D.
  • Automatic building information model reconstruction in high-density urban
           areas: Augmenting multi-source data with architectural knowledge
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Ke Chen, Weisheng Lu, Fan Xue, Pingbo Tang, Ling Hin Li Many studies have been conducted to create building information models (BIMs) or city information models (CIMs) as the digital infrastructure to support various smart city programs. However, automatic generation of such models for high-density (HD) urban areas remains a challenge owing to (a) complex topographic conditions and noisy data irrelevant to the buildings, and (b) exponentially growing computational complexity when the task is reconstructing hundreds of buildings at an urban scale. This paper develops a method - multi-Source recTification of gEometric Primitives (mSTEP) - for automatic reconstruction of BIMs in HD urban areas. By retrieving building base, height, and footprint geodata from topographic maps, level of detail 1 (LoD1) BIMs representing buildings with flat roof configuration were first constructed. Geometric primitives were then detected from LiDAR point clouds and rectified using architectural knowledge about building geometries (e.g. a rooftop object would normally be in parallel with the outer edge of the roof). Finally, the rectified primitives were used to refine the LoD1 BIMs to LoD2, which show detailed geometric features of roofs and rooftop objects. A total of 1361 buildings located in a four square kilometer area of Hong Kong Island were selected as the subjects for this study. The evaluation results show that mSTEP is an efficient BIM reconstruction method that can significantly improve the level of automation and decrease the computation time. mSTEP is also well applicable to point clouds of various densities. The research is thus of profound significance; other cities and districts around the world can easily adopt mSTEP to reconstruct their own BIMs/CIMs to support their smart city programs.
  • Distributed and interoperable simulation for comprehensive disaster
           response management in facilities
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Minji Choi, Richmond Starbuck, Seulbi Lee, Sungjoo Hwang, SangHyun Lee, Moonseo Park, Hyun-Soo Lee Disaster-related simulations can be helpful for conducting various analysis on damage evaluations and response operations in damaged facilities. However, no single simulation can solve all the functional needs for complex disaster situations due to diverse disasters, damage types, and response efforts. To address these issues, the authors have developed a distributed simulation platform for a comprehensive analysis of facility damage and response operations, which can be flexibly applied to diverse disaster situations. The High Level Architecture is adopted to synchronize different federates such as simulation models and incoming data streams within an interoperable simulation environment. The developed simulation platform includes five different disaster-related federates such as the Fire Dynamics Simulator, USGS earthquake data feeds, OpenSees structure response simulation, evacuation simulation, and restoration simulation. The accuracy of interactions among different federates was confirmed with the case simulations of a facility fire evacuation and an earthquake restoration situation. The developed platform provides a flexible and interoperable distributed simulation environment for comprehensive disaster response management of unexpected disaster situations while promoting reusability and future extendibility of existing and newly-added disaster-related simulations.
  • Additive manufacturing technology and its implementation in construction
           as an eco-innovative solution
    • Abstract: Publication date: September 2018Source: Automation in Construction, Volume 93Author(s): Seyed Hamidreza Ghaffar, Jorge Corker, Mizi Fan Additive manufacturing (AM) of construction materials has been one of the emerging advanced technologies that aim to minimise the supply chain in the construction industry through autonomous production of building components directly from digital models without human intervention and complicated formworks. However, technical challenges needs to be addressed for the industrial implementation of AM, e.g. materials formulation standardization, and interfacial bonding quality between the deposited layers amongst others. AM as one of the most highlighted key enabling technologies has the potential to create disruptive solutions, the key for its successful implementation is multidisciplinary effort in synergy involving materials science, architecture/design, computation, and robotics. There are crucial links between the material design formulations and the printing system for the manufacturing of the complex 3D geometries. Understanding and optimising the mix design for fresh rheology of materials and sufficient adhesion/cohesion of interface can allow the incorporation of complexity in the geometry.Graphical abstractThe relationship of systematic parameters for large-scale AM implementation in construction.Unlabelled Image
  • Logic for ensuring the data exchange integrity of building information
    • Abstract: Publication date: Available online 9 July 2018Source: Automation in ConstructionAuthor(s): Yong-Cheol Lee, Charles M. Eastman, Wawan Solihin Industry domains require distinct data and structures of building information models developed and tailored for their disciplines. To seamlessly exchange the building information models, Industry Foundation Classes (IFC), which is one of neutral formats, has been broadly used in the architecture, engineering and construction, and facility management industries. Model view definition (MVD), which is one of the IFC sub-schemas used by domain experts and BIM software vendors, consists of IFC-mapped data exchange requirements of each domain and helps software vendors develop IFC import and export features that allow project participants share and exchange BIM model information. Because of the heterogeneous translation processes and structures of IFC interfaces according to model views, their validation is imperative to ensure the integrity of BIM data and maintain a consistent data exchange environment. To accomplish this objective, this paper suggests the new approach to evaluating BIM data in accordance with diverse requirements of MVD. Since MVD entails various types of data exchange specifications, this research study examines their embedded checking rule types and categorizes corresponding implementation scenarios. In addition, this paper involves rule logic and IfcDoc-based BIM data validation developed based on the logical rule compositions of identified rules types and checking scenarios. This approach is expected to support sharing consistent BIM data sets and confirming the quality of received data pertaining to a syntax and semantics of a targeted model view.
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-