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  Subjects -> ENGINEERING (Total: 2298 journals)
    - CHEMICAL ENGINEERING (192 journals)
    - CIVIL ENGINEERING (192 journals)
    - ELECTRICAL ENGINEERING (104 journals)
    - ENGINEERING (1209 journals)
    - ENGINEERING MECHANICS AND MATERIALS (385 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (69 journals)
    - MECHANICAL ENGINEERING (92 journals)

CIVIL ENGINEERING (192 journals)                     

Showing 1 - 192 of 192 Journals sorted alphabetically
ACI Structural Journal     Full-text available via subscription   (Followers: 17)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Structilia : Journal for the Physical and Development Sciences     Open Access   (Followers: 2)
Advances in Civil Engineering     Open Access   (Followers: 36)
Advances in Structural Engineering     Full-text available via subscription   (Followers: 28)
Agregat     Open Access  
Ambiente Construído     Open Access   (Followers: 1)
American Journal of Civil Engineering and Architecture     Open Access   (Followers: 31)
Architectural Engineering     Open Access   (Followers: 4)
Archives of Civil and Mechanical Engineering     Full-text available via subscription   (Followers: 1)
Archives of Civil Engineering     Open Access   (Followers: 10)
Archives of Hydro-Engineering and Environmental Mechanics     Open Access   (Followers: 2)
ATBU Journal of Environmental Technology     Open Access   (Followers: 4)
Australian Journal of Structural Engineering     Full-text available via subscription   (Followers: 6)
Baltic Journal of Road and Bridge Engineering     Full-text available via subscription   (Followers: 1)
BER : Building and Construction : Full Survey     Full-text available via subscription   (Followers: 10)
BER : Building Contractors' Survey     Full-text available via subscription   (Followers: 4)
BER : Building Sub-Contractors' Survey     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Building and Construction : An Executive Summary     Full-text available via subscription   (Followers: 4)
Bioinspired Materials     Open Access   (Followers: 5)
Bridge Structures : Assessment, Design and Construction     Hybrid Journal   (Followers: 16)
Building & Management     Open Access  
Building and Environment     Hybrid Journal   (Followers: 15)
Building Women     Full-text available via subscription  
Built Environment Project and Asset Management     Hybrid Journal   (Followers: 15)
Bulletin of Pridniprovsk State Academy of Civil Engineering and Architecture     Open Access   (Followers: 6)
Canadian Journal of Civil Engineering     Hybrid Journal   (Followers: 12)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Nondestructive Testing and Evaluation     Open Access   (Followers: 11)
Case Studies in Structural Engineering     Open Access   (Followers: 9)
Cement and Concrete Composites     Hybrid Journal   (Followers: 17)
Challenge Journal of Concrete Research Letters     Open Access   (Followers: 2)
Challenge Journal of Structural Mechanics     Open Access   (Followers: 5)
Change Over Time     Full-text available via subscription   (Followers: 2)
Civil and Environmental Engineering     Open Access   (Followers: 7)
Civil And Environmental Engineering Reports     Open Access   (Followers: 6)
Civil and Environmental Research     Open Access   (Followers: 19)
Civil Engineering = Siviele Ingenieurswese     Full-text available via subscription   (Followers: 4)
Civil Engineering and Architecture     Open Access   (Followers: 18)
Civil Engineering and Environmental Systems     Hybrid Journal   (Followers: 3)
Civil Engineering and Technology     Open Access   (Followers: 10)
Civil Engineering Dimension     Open Access   (Followers: 8)
Civil Engineering Infrastructures Journal     Open Access  
Cohesion and Structure     Full-text available via subscription   (Followers: 2)
Composite Structures     Hybrid Journal   (Followers: 268)
Computer-aided Civil and Infrastructure Engineering     Hybrid Journal   (Followers: 11)
Computers & Structures     Hybrid Journal   (Followers: 36)
Concrete Research Letters     Open Access   (Followers: 6)
Construction Economics and Building     Open Access   (Followers: 2)
Construction Engineering     Open Access   (Followers: 9)
Construction Management and Economics     Hybrid Journal   (Followers: 22)
Construction Science     Open Access   (Followers: 4)
Constructive Approximation     Hybrid Journal  
Curved and Layered Structures     Open Access   (Followers: 2)
DFI Journal : The Journal of the Deep Foundations Institute     Hybrid Journal   (Followers: 1)
Earthquake Engineering and Structural Dynamics     Hybrid Journal   (Followers: 17)
Enfoque UTE     Open Access   (Followers: 4)
Engineering Project Organization Journal     Hybrid Journal   (Followers: 7)
Engineering Structures     Hybrid Journal   (Followers: 13)
Engineering Structures and Technologies     Hybrid Journal   (Followers: 2)
Engineering, Construction and Architectural Management     Hybrid Journal   (Followers: 14)
Environmental Geotechnics     Hybrid Journal   (Followers: 5)
European Journal of Environmental and Civil Engineering     Hybrid Journal   (Followers: 9)
Fatigue & Fracture of Engineering Materials and Structures     Hybrid Journal   (Followers: 16)
Frattura ed Integrità Strutturale : Fracture and Structural Integrity     Open Access  
Frontiers in Built Environment     Open Access  
Frontiers of Structural and Civil Engineering     Hybrid Journal   (Followers: 6)
Geomaterials     Open Access   (Followers: 4)
Geosystem Engineering     Hybrid Journal   (Followers: 1)
Geotechnik     Hybrid Journal   (Followers: 3)
Géotechnique Letters     Hybrid Journal   (Followers: 7)
GISAP : Technical Sciences, Construction and Architecture     Open Access  
HBRC Journal     Open Access   (Followers: 2)
Hormigón y Acero     Full-text available via subscription  
HVAC&R Research     Hybrid Journal  
Indonesian Journal of Urban and Environmental Technology     Open Access  
Indoor and Built Environment     Hybrid Journal   (Followers: 2)
Infrastructure Asset Management     Hybrid Journal   (Followers: 2)
Infrastructures     Open Access  
Ingenio Magno     Open Access   (Followers: 1)
Insight - Non-Destructive Testing and Condition Monitoring     Full-text available via subscription   (Followers: 22)
International Journal for Service Learning in Engineering     Open Access  
International Journal of 3-D Information Modeling     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Structural Engineering     Open Access   (Followers: 16)
International Journal of Civil, Mechanical and Energy Science     Open Access   (Followers: 1)
International Journal of Concrete Structures and Materials     Open Access   (Followers: 14)
International Journal of Condition Monitoring     Full-text available via subscription   (Followers: 2)
International Journal of Construction Engineering and Management     Open Access   (Followers: 9)
International Journal of Geo-Engineering     Open Access   (Followers: 3)
International Journal of Geosynthetics and Ground Engineering     Full-text available via subscription   (Followers: 4)
International Journal of Masonry Research and Innovation     Hybrid Journal   (Followers: 1)
International Journal of Pavement Research and Technology     Open Access   (Followers: 6)
International Journal of Protective Structures     Hybrid Journal   (Followers: 6)
International Journal of Steel Structures     Hybrid Journal   (Followers: 2)
International Journal of Structural Engineering     Hybrid Journal   (Followers: 10)
International Journal of Structural Integrity     Hybrid Journal   (Followers: 2)
International Journal of Structural Stability and Dynamics     Hybrid Journal   (Followers: 7)
International Journal of Sustainable Built Environment     Open Access   (Followers: 4)
International Journal of Sustainable Construction Engineering and Technology     Open Access   (Followers: 8)
International Journal on Pavement Engineering & Asphalt Technology     Open Access   (Followers: 7)
International Journal Sustainable Construction & Design     Open Access  
Journal of Bridge Engineering     Full-text available via subscription   (Followers: 15)
Journal of Building Engineering     Hybrid Journal   (Followers: 1)
Journal of Building Materials and Structures     Open Access   (Followers: 2)
Journal of Building Performance Simulation     Hybrid Journal   (Followers: 6)
Journal of Civil Engineering and Construction Technology     Open Access   (Followers: 12)
Journal of Civil Engineering and Management     Hybrid Journal   (Followers: 7)
Journal of Civil Engineering and Science     Open Access   (Followers: 8)
Journal of Civil Engineering Research     Open Access   (Followers: 6)
Journal of Civil Engineering, Science and Technology     Open Access  
Journal of Civil Society     Hybrid Journal   (Followers: 4)
Journal of Civil Structural Health Monitoring     Hybrid Journal   (Followers: 4)
Journal of Composites for Construction     Full-text available via subscription   (Followers: 13)
Journal of Computing in Civil Engineering     Full-text available via subscription   (Followers: 24)
Journal of Construction Engineering     Open Access   (Followers: 7)
Journal of Construction Engineering and Management     Full-text available via subscription   (Followers: 19)
Journal of Constructional Steel Research     Hybrid Journal   (Followers: 8)
Journal of Earth Sciences and Geotechnical Engineering     Open Access   (Followers: 4)
Journal of Fluids and Structures     Hybrid Journal   (Followers: 6)
Journal of Frontiers in Construction Engineering     Open Access   (Followers: 2)
Journal of Green Building     Full-text available via subscription   (Followers: 11)
Journal of Highway and Transportation Research and Development (English Edition)     Full-text available via subscription   (Followers: 14)
Journal of Infrastructure Systems     Full-text available via subscription   (Followers: 21)
Journal of Legal Affairs and Dispute Resolution in Engineering and Construction     Full-text available via subscription   (Followers: 5)
Journal of Marine Science and Engineering     Open Access   (Followers: 1)
Journal of Materials and Engineering Structures     Open Access   (Followers: 5)
Journal of Materials in Civil Engineering     Full-text available via subscription   (Followers: 10)
Journal of Nondestructive Evaluation     Hybrid Journal   (Followers: 11)
Journal of Performance of Constructed Facilities     Full-text available via subscription   (Followers: 4)
Journal of Pipeline Systems Engineering and Practice     Full-text available via subscription   (Followers: 7)
Journal of Rehabilitation in Civil Engineering     Open Access   (Followers: 3)
Journal of Solid Waste Technology and Management     Full-text available via subscription   (Followers: 1)
Journal of Structural Engineering     Full-text available via subscription   (Followers: 40)
Journal of Structural Fire Engineering     Full-text available via subscription   (Followers: 6)
Journal of Sustainable Architecture and Civil Engineering     Open Access   (Followers: 3)
Journal of Sustainable Design and Applied Research in Innovative Engineering of the Built Environment     Open Access   (Followers: 1)
Journal of the Civil Engineering Forum     Open Access  
Journal of the South African Institution of Civil Engineering     Open Access   (Followers: 4)
Journal of Water and Environmental Nanotechnology     Open Access  
Jurnal Spektran     Open Access   (Followers: 1)
Jurnal Teknik Sipil dan Perencanaan     Open Access   (Followers: 1)
Konstruksia     Open Access  
KSCE Journal of Civil Engineering     Hybrid Journal   (Followers: 2)
Latin American Journal of Solids and Structures     Open Access   (Followers: 4)
Materiales de Construcción     Open Access  
Mathematical Modelling in Civil Engineering     Open Access   (Followers: 3)
Nondestructive Testing And Evaluation     Hybrid Journal   (Followers: 17)
npj Materials Degradation     Open Access  
Obras y Proyectos     Open Access   (Followers: 1)
Open Journal of Civil Engineering     Open Access   (Followers: 7)
Photonics and Nanostructures - Fundamentals and Applications     Hybrid Journal   (Followers: 2)
Practice Periodical on Structural Design and Construction     Full-text available via subscription   (Followers: 4)
Proceedings of the Institution of Civil Engineers - Bridge Engineering     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Civil Engineers - Civil Engineering     Hybrid Journal   (Followers: 12)
Proceedings of the Institution of Civil Engineers - Management, Procurement and Law     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Civil Engineers - Municipal Engineer     Hybrid Journal   (Followers: 3)
Proceedings of the Institution of Civil Engineers - Structures and Buildings     Hybrid Journal   (Followers: 4)
Random Structures and Algorithms     Hybrid Journal   (Followers: 5)
Research in Nondestructive Evaluation     Hybrid Journal   (Followers: 7)
Revista IBRACON de Estruturas e Materiais     Open Access   (Followers: 1)
Road Materials and Pavement Design     Hybrid Journal   (Followers: 11)
Russian Journal of Nondestructive Testing     Hybrid Journal   (Followers: 6)
Science and Engineering of Composite Materials     Hybrid Journal   (Followers: 61)
Selected Scientific Papers - Journal of Civil Engineering     Open Access   (Followers: 3)
Slovak Journal of Civil Engineering     Open Access   (Followers: 2)
Soils and foundations     Full-text available via subscription   (Followers: 5)
Steel Construction - Design and Research     Hybrid Journal   (Followers: 3)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 10)
Structural Concrete     Hybrid Journal   (Followers: 11)
Structural Control and Health Monitoring     Hybrid Journal   (Followers: 9)
Structural Engineering International     Full-text available via subscription   (Followers: 12)
Structural Mechanics of Engineering Constructions and Buildings     Open Access  
Structural Safety     Hybrid Journal   (Followers: 7)
Structural Survey     Hybrid Journal  
Structure     Full-text available via subscription   (Followers: 23)
Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance     Hybrid Journal   (Followers: 13)
Structures     Hybrid Journal   (Followers: 1)
Study of Civil Engineering and Architecture     Open Access   (Followers: 9)
Superlattices and Microstructures     Hybrid Journal   (Followers: 2)
Surface Innovations     Hybrid Journal  
Technical Report Civil and Architectural Engineering     Open Access  
Teknik     Open Access  
The IES Journal Part A: Civil & Structural Engineering     Hybrid Journal   (Followers: 6)
The Structural Design of Tall and Special Buildings     Hybrid Journal   (Followers: 6)
Thin Films and Nanostructures     Full-text available via subscription   (Followers: 2)
Thin-Walled Structures     Hybrid Journal   (Followers: 4)
Transactions of the VŠB - Technical University of Ostrava. Construction Series     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Underground Space     Open Access  
Water Science & Technology     Partially Free   (Followers: 25)
Water Science and Technology : Water Supply     Partially Free   (Followers: 22)

           

Journal Cover Computer-aided Civil and Infrastructure Engineering
  [SJR: 0.901]   [H-I: 51]   [11 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1093-9687 - ISSN (Online) 1467-8667
   Published by John Wiley and Sons Homepage  [1589 journals]
  • Modeling Relationship between Truck Fuel Consumption and Driving Behavior
           Using Data from Internet of Vehicles
    • Authors: Zhigang Xu; Tao Wei, Said Easa, Xiangmo Zhao, Xiaobo Qu
      Abstract: In this research, by taking advantage of dynamic fuel consumption–speed data from Internet of Vehicles, we develop two novel computational approaches to more accurately estimate truck fuel consumption. The first approach is on the basis of a novel index, named energy consumption index, which is to explicitly reflect the dynamic relationship between truck fuel consumption and truck drivers’ driving behaviors obtained from Internet of Vehicles. The second approach is based on a Generalized Regression Neural Network model to implicitly establish the same relationship. We further compare the two proposed models with three well-recognized existing models: vehicle specific power (VSP) model, Virginia Tech microscopic (VT-Micro) model, and Comprehensive Modal Emission Model (CMEM). According to our validations at both microscopic and macroscopic levels, the two proposed models have stronger performed in predicting fuel consumption in new routes. The models can be used to design more energy-efficient driving behaviors in the soon-to-come era of connected and automated vehicles.
      PubDate: 2018-01-19T09:15:44.706214-05:
      DOI: 10.1111/mice.12344
       
  • A Computer-Aided Model for the Simulation of Railway Ballast by Random
           Sequential Adsorption Process
    • Authors: Andrea Benedetto; Luca Bianchini Ciampoli, Maria Giulia Brancadoro, Amir M. Alani, Fabio Tosti
      Abstract: This article presents a computer-aided multistage methodology for the simulation of railway ballasts using the Random Sequential Adsorption (RSA – 2D domain) paradigm. The primary stage in this endeavor is the numerical generation of a synthetic sample by a “particle sizing and positioning” process followed by a “compaction” process. The synthetic samples of ballast are then visualized in the Computer-Aided Design (CAD) environment. The outcomes of the simulation are analyzed by comparison with the results of an experimental investigation carried out using a methacrylate container in which real samples of railway ballast are formed. A test of model reliability is carried out between the aggregates number and the grading curves of the synthetic sample and the real one. A validation is therefore performed using the ground-penetrating radar (GPR) nondestructive testing (NDT) method and the finite-difference time-domain (FDTD) simulation developed in a computer-aided environment. The results prove the viability and the applicability of the proposed modeling for the assessment of railway ballast conditions.
      PubDate: 2017-12-29T18:15:51.584987-05:
      DOI: 10.1111/mice.12342
       
  • Earth Dam Construction Simulation Considering Stochastic Rainfall Impact
    • Authors: Jun Zhang; Denghua Zhong, Binping Wu, Fei Lv, Bo Cui
      Abstract: Effective construction scheme planning is critical for schedule management, but heavy rain can affect construction processes. In previous studies, stochastic rainfall characteristics are often ignored, and their impact on macro- and microconstruction states are not depicted comprehensively. This research presents a construction simulation model to design reasonable construction schemes considering impact of stochastic rainfall. First, a rainfall model suitable for areas with heavy rainfall and uneven seasonal rainfall distribution is built. Then, multiaspect indicators are defined to intuitively quantify rainfall impact. Two case studies are conducted to evaluate applicability of the proposed method. Results demonstrate that the developed rainfall model aligns closely with observed data. Simulation findings reveal that if stochastic rainfall characteristics are ignored, the schedule and queuing probability of trucks will be underestimated, while machinery utilization will be overestimated. This research provides an effective simulation tool for determining adaptive measures to mitigate impacts of rainfall events.
      PubDate: 2017-12-15T05:56:55.16177-05:0
      DOI: 10.1111/mice.12337
       
  • Structural Displacement Measurement Using an Unmanned Aerial System
    • Authors: Hyungchul Yoon; Jaeho Shin, Billie F. Spencer
      Abstract: Vibration-based Structural Health Monitoring (SHM) is one of the most popular solutions to assess the safety of civil infrastructure. SHM applications all begin with measuring the dynamic response of structures, but displacement measurement has been limited by the difficulty in requiring a fixed reference point, high cost, and/or low accuracy. Recently, researchers have conducted studies on vision-based structural health monitoring, which provides noncontact and efficient measurement. However, these approaches have been limited to stationary cameras, which have the challenge of finding a location to deploy the cameras with appropriate line-of-sight, especially to monitor critical civil infrastructures such as bridges. The Unmanned Aerial System (UAS) can potentially overcome the limitation of finding optimal locations to deploy the camera, but existing vision-based displacement measurement methods rely on the assumption that the camera is stationary. The displacements obtained by such methods will be a relative displacement of a structure to the camera motion, not an absolute displacement. Therefore, this article presents a framework to achieve absolute displacement of a structure from a video taken from an UAS using the following phased approach. First, a target-free method is implemented to extract the relative structural displacement from the video. Next, the 6 degree-of-freedom camera motion (three translations and three rotations) is estimated by tracking the background feature points. Finally, the absolute structural displacement is recovered by combining the relative structural displacement and the camera motion. The performance of the proposed system has been validated in the laboratory using a commercial UAS. Displacement of a pinned-connected railroad truss bridge in Rockford, IL subjected to revenue-service traffic loading was reproduced on a hydraulic simulator, while the UAS was flown from a distance of 4.6 m (simulating the track clearance required by the Federal Railroad Administration), resulting in estimated displacements with an RMS error of 2.14 mm.
      PubDate: 2017-12-12T08:47:10.86329-05:0
      DOI: 10.1111/mice.12338
       
  • Damage Identification for Hysteretic Structures Using a Mode Decomposition
           Method
    • Authors: E. Poskus; G. W. Rodgers, C. Zhou, J. G. Chase
      Abstract: This article investigates structural health monitoring (SHM) of multidegree of freedom (MDOF) structures after major seismic or environmental events. A recently developed hysteresis loop analysis (HLA) SHM technique has performed robustly for single degree of freedom (SDOF) and single mode dominant MDOF structures. However, strong ground motions can trigger higher vibration modes, resulting in irregular hysteresis loops and making this otherwise robust identification difficult. This study presents a new filtering tool, enabling reconstruction of single mode dominant restoring force-displacement loops which can be readily used for HLA.The proposed filtering tool is based on a classic modal decomposition using optimized mode shape coefficients. The optimization process is carried out in a modal space and is based on decoupling frequency response spectra of interfering modes. Application of modal decomposition using the optimized mode shape coefficients allows for reconstruction of single-mode dominant hysteresis loops, which can be effectively identified using HLA. The proposed filtering tool is validated on the reconstruction of hysteresis loops on an experimental bridge pier test structure with notable contributions from at least two modes.The results show the method eliminates the influence of all higher modes that contain significant energy content and yields the reconstruction of “smooth” single mode dominant hysteresis loops. The resulting SHM analysis on the reconstructed experimental hysteresis loops identified degradation in the elastic stiffness profiles, indicating damage within the structure and matching prior published results based on physical inspection of damage. The overall method presented increases the breadth of potential application of the HLA method and can be readily generalized to a range of MDOF structures.
      PubDate: 2017-12-08T13:55:47.941068-05:
      DOI: 10.1111/mice.12317
       
  • Multicriteria Fuzzy Analysis for a GIS-Based Management of Earthquake
           Scenarios
    • Authors: Maria Grazia D'Urso; Daniele Masi, Giulio Zuccaro, Daniela Gregorio
      Abstract: Objective of this article is the formulation and the implementation of a decision-making model for the optimal management of emergencies. It is based on the accurate definition of possible scenarios resulting from prediction and prevention strategies and explicitly takes into account the subjectivity of the judgments of preference. To this end, a multicriteria decision model, based on fuzzy logic, has been implemented in a user-friendly geographical information system (GIS) platform so as to allow for the automation of choice processes between several alternatives for the spatial location of the investigated scenarios. In particular, we have analyzed the potentialities of the proposed approach in terms of seismic risk reduction, simplifying the decision process leading to the actions to be taken from directors and managers of coordination services. Due to the large number of variables involved in the decision process, it has been proposed a particularly flexible and streamlined method in which the damage scenarios, based on the vulnerability of the territory, have represented the input data to derive a vector of weights to be assigned to different decision alternatives. As an application of the proposed approach, the seismic damage scenario of a region of 400 km2, hit by the 2009 earthquake in L'Aquila (Italy), has been analyzed.
      PubDate: 2017-12-05T16:01:09.98342-05:0
      DOI: 10.1111/mice.12335
       
  • 3D Object Classification Using Geometric Features and Pairwise
           Relationships
    • Authors: Ling Ma; Rafael Sacks, Uri Kattel, Tanya Bloch
      Abstract: Object classification is a key differentiator of building information modeling (BIM) from three-dimensional (3D) computer-aided design (CAD). Incorrect object classification impedes the full exploitation of BIM models. Models prepared using domain-specific software cannot ensure correct object classification when transferred to other domains, and research on reconstruction of BIM models using spatial survey has not proved a full capability to classify objects. This research proposed an integrated approach to object classification that applied domain experts’ knowledge of shape features and pairwise relationships of 3D objects to effectively classify objects using a tailored matching algorithm. Among its contributions: the algorithms implemented for shape and spatial feature identification could process various complex 3D geometry; the method devised for compilation of the knowledge base considered both rigor and confidence of the inference; the algorithm for matching provides mathematical measurement of the object classification results. The integrated approach has been applied to classify 3D bridge objects in two models: a model prepared using incorrect object types and a model manually reconstructed using point cloud data. All these objects were successfully classified.
      PubDate: 2017-11-29T19:45:36.580051-05:
      DOI: 10.1111/mice.12336
       
  • Efficient Infrastructure Restoration Strategies Using the Recovery
           Operator
    • Authors: Andrés D. González; Airlie Chapman, Leonardo Dueñas-Osorio, Mehran Mesbahi, Raissa M. D'Souza
      Abstract: Infrastructure systems are critical for society's resilience, government operation, and overall defense. Thereby, it is imperative to develop informative and computationally efficient analysis methods for infrastructure systems, which reveal system vulnerabilities and recoverability. To capture practical constraints in systems analyses, various layers of complexity play a role, including limited element capacities, restoration resources, and the presence of interdependence among systems. High-fidelity modeling such as mixed integer programming and physics-based modeling can often be computationally expensive, making time-sensitive analyses challenging. Furthermore, the complexity of recovery solutions can reduce analysis transparency. An alternative, presented in this work, is a reduced-order representation, dubbed a recovery operator, of a high-fidelity time-dependent recovery model of a system of interdependent networks. The form of the operator is assumed to be a time-invariant linear dynamic model apt for infrastructure restoration. The recovery operator is generated by applying system identification techniques to numerous disaster and recovery scenarios. The proposed compact representation provides simple yet powerful information regarding systemic recovery dynamics, and enables generating fast suboptimal recovery policies in time-critical applications.
      PubDate: 2017-11-28T08:36:11.357927-05:
      DOI: 10.1111/mice.12314
       
  • Autonomous Structural Visual Inspection Using Region-Based Deep Learning
           for Detecting Multiple Damage Types
    • Authors: Young-Jin Cha; Wooram Choi, Gahyun Suh, Sadegh Mahmoudkhani, Oral Büyüköztürk
      Abstract: Computer vision-based techniques were developed to overcome the limitations of visual inspection by trained human resources and to detect structural damage in images remotely, but most methods detect only specific types of damage, such as concrete or steel cracks. To provide quasi real-time simultaneous detection of multiple types of damages, a Faster Region-based Convolutional Neural Network (Faster R-CNN)-based structural visual inspection method is proposed. To realize this, a database including 2,366 images (with 500 × 375 pixels) labeled for five types of damages—concrete crack, steel corrosion with two levels (medium and high), bolt corrosion, and steel delamination—is developed. Then, the architecture of the Faster R-CNN is modified, trained, validated, and tested using this database. Results show 90.6%, 83.4%, 82.1%, 98.1%, and 84.7% average precision (AP) ratings for the five damage types, respectively, with a mean AP of 87.8%. The robustness of the trained Faster R-CNN is evaluated and demonstrated using 11 new 6,000 × 4,000-pixel images taken of different structures. Its performance is also compared to that of the traditional CNN-based method. Considering that the proposed method provides a remarkably fast test speed (0.03 seconds per image with 500 × 375 resolution), a framework for quasi real-time damage detection on video using the trained networks is developed.
      PubDate: 2017-11-28T08:27:25.798867-05:
      DOI: 10.1111/mice.12334
       
  • Spatial and Temporal Quantification of Community Resilience: Gotham City
           under Attack
    • Authors: Hussam Mahmoud; Akshat Chulahwat
      Abstract: Mitigating the impact of disasters on communities requires not only a deep understanding of the essential features of infrastructure, social, and economical components that make a community resilient; but also the development of mathematical models that can seamlessly integrate these features. This article lays the foundation for an integrative model that captures interaction between these components. The underlying fundamentals of the proposed model hinges on the principle of a damped harmonic oscillator by assuming the behavior of a community in response to a hazard is equivalent to the response of a vibrating mass of finite stiffness and damping. We implemented the dynamic model by developing a novel finite element formulation capable of quantifying resilience both temporally and spatially. We then used the developed model to devise a suitable hazard-agnostic definition of community resilience. This was realized through a set of demonstration and logical verification tests conducted on Gotham City, the fictional city of the infamous character, Batman. It was observed that the model can be used to identify sensitive and vulnerable areas in a community, provide a spatial and temporal quantification of community resilience, and accommodate various types of hazards such as physical disruptions, economic downtimes, and even social disorders.
      PubDate: 2017-11-28T08:26:09.29557-05:0
      DOI: 10.1111/mice.12318
       
  • On the Value of Monitoring Information for the Structural Integrity and
           Risk Management
    • Authors: Sebastian Thöns
      Abstract: This article introduces an approach and framework for the quantification of the value of structural health monitoring (SHM) in the context of the structural risk and integrity management for systems. The quantification of the value of SHM builds upon the Bayesian decision and utility theory, which facilitates the assessment of the value of information associated with SHM. The principal approach for the quantification of the value of SHM is formulated by modeling the fundamental decision of performing SHM or not in conjunction with their expected utilities. The expected utilities are calculated accounting for the probabilistic performance of a system in conjunction with the associated structural integrity and risk management actions throughout the life cycle, the associated benefits, structural risks, and costs and when performing SHM, the SHM information, their probabilistic outcomes, and costs. The calculation of the expected utilities necessitates a comprehensive and rigorous modeling, which is introduced close to the original formulations and for which analysis characteristics and simplifications are described and derived. The framework provides the basis for the optimization of the structural risk and integrity management based on utility gains including or excluding SHM and inspection information. Studies of fatigue deteriorating structural systems and their characteristics (1) provide decision support for the performance of SHM, (2) explicate the influence of the structural component and system characteristics on the value of SHM, and (3) demonstrate how an integral optimization of SHM and inspection strategies for an efficient structural risk and integrity management can be performed.
      PubDate: 2017-11-21T08:20:56.867261-05:
      DOI: 10.1111/mice.12332
       
  • Introduction
    • Authors: James L. Beck; Oreste S. Bursi, Masahiro Kurata
      PubDate: 2017-11-15T10:51:06.072465-05:
      DOI: 10.1111/mice.12333
       
  • Structural Damage Detection with Automatic Feature-Extraction through Deep
           Learning
    • Authors: Yi-zhou Lin; Zhen-hua Nie, Hong-wei Ma
      Abstract: Structural damage detection is still a challenging problem owing to the difficulty of extracting damage-sensitive and noise-robust features from structure response. This article presents a novel damage detection approach to automatically extract features from low-level sensor data through deep learning. A deep convolutional neural network is designed to learn features and identify damage locations, leading to an excellent localization accuracy on both noise-free and noisy data set, in contrast to another detector using wavelet packet component energy as the input feature. Visualization of the features learned by hidden layers in the network is implemented to get a physical insight into how the network works. It is found the learned features evolve with the depth from rough filters to the concept of vibration mode, implying the good performance results from its ability to learn essential characteristics behind the data.
      PubDate: 2017-11-10T12:01:02.785431-05:
      DOI: 10.1111/mice.12313
       
  • Pavement Crack Width Measurement Based on Laplace's Equation for
           Continuity and Unambiguity
    • Authors: Wenjuan Wang; Allen Zhang, Kelvin C. P. Wang, Andrew F. Braham, Shi Qiu
      Abstract: Crack is one of the most important pavement condition indicators that are immediately relevant to water ingress and pavement deterioration. In practices of pavement management, crack width has been extensively referenced by highway agencies to determine pavement crack severity. Accurate measurement of pavement crack width is meaningful for highway agencies in understanding the mechanism of crack formation, and in predicting crack propagation. This article presents a new automatic method for measuring crack width using the binary crack map images. The proposed method introduces a new crack width definition and formulates it using the Laplace's Equation so that crack width can be continuously and unambiguously measured. Two algorithms, including the crack blob extraction algorithm and the crack boundary extraction algorithm, are developed to implement the proposed formulation in an automated fashion. Experimental tests using both synthetic data and field data are conducted to demonstrate the accuracy and reliability of the proposed method. A case study on crack width propagation is also performed to demonstrate the practical capacity of the proposed method. The results of the experimental tests and the outcome of the case study have demonstrated that the proposed method, together with the existing crack map extraction algorithms, provides a promising means for consistent and unambiguous crack width measurement supporting automated pavement condition evaluation.
      PubDate: 2017-11-08T06:26:20.555768-05:
      DOI: 10.1111/mice.12319
       
  • Prediction of Bus Travel Time Using Random Forests Based on Near Neighbors
    • Authors: Bin Yu; Huaizhu Wang, Wenxuan Shan, Baozhen Yao
      Abstract: The prediction of bus arrival time is important for passengers who want to determine their departure time and reduce anxiety at bus stops that lack timetables. The random forests based on the near neighbor (RFNN) method is proposed in this article to predict bus travel time, which has been calibrated and validated with real-world data. A case study with two bus routes is conducted, and the proposed RFNN is compared with four methods: linear regression (LR), k-nearest neighbors (KNN), support vector machine (SVM), and classic random forest (RF). The results indicate that the proposed model achieves high accuracy. That is, one bus route has the results of 13.65 mean absolute error (MAE), 6.90% mean absolute percentage error (MAPE), 26.37 root mean squared error (RMSE) and 13.77 (MAE), 7.58% (MAPE), 29.01 (RMSE), respectively. RFNN has a longer computation time of 44,301 seconds for a data set with 14,182 data. The proposed method can be optimized by the technology of parallel computing and can be applied to real-time prediction.
      PubDate: 2017-11-01T11:25:59.366567-05:
      DOI: 10.1111/mice.12315
       
  • A Viscoelastic Model for the Long-Term Deflection of Segmental Prestressed
           Box Girders
    • Authors: Angela Beltempo; Oreste S. Bursi, Carlo Cappello, Daniele Zonta, Massimiliano Zingales
      Abstract: Most of segmental prestressed concrete box girders exhibit excessive multidecade deflections unforeseeable by past and current design codes. To investigate such a behavior, mainly caused by creep and shrinkage phenomena, an effective finite element (FE) formulation is presented in this article. This formulation is developed by invoking the stationarity of an energetic principle for linear viscoelastic problems and relies on the Bazant creep constitutive law. A case study representative of segmental prestressed concrete box girders susceptible to creep is also analyzed in the article, that is, the Colle Isarco viaduct. Its FE model, based on the aforementioned energetic formulation, was successfully validated through the comparison with monitoring field data. As a result, the proposed 1D FE model can effectively reproduce the past behavior of the viaduct and predict its future behavior with a reasonable run time, which represents a decisive factor for the model implementation in a decision support system.
      PubDate: 2017-10-25T08:51:36.721574-05:
      DOI: 10.1111/mice.12311
       
  • Entropy-Based Optimal Sensor Placement for Model Identification of
           Periodic Structures Endowed with Bolted Joints
    • Authors: Tao Yin; Ka-Veng Yuen, Heung-Fai Lam, Hong-ping Zhu
      Abstract: The number of sensors and the corresponding locations are very important for the information content obtained from the measured data, which is a recognized challenging problem for large-scale structural systems. This article pays special attention to the sensor placement issues on a large-scale periodically articulated structure representing typical pipelines to extract the most information from measured data for the purpose of model identification. The minimal model parameter estimation uncertainties quantified by the information entropy (IE) measure is taken as the optimality criterion for sensors placement. By utilizing the inherent periodicity property of this type of structure together with the Bloch theorem, a novel tailor-made modeling approach is proposed and the computational cost required for dynamic analysis to form the IE with respect to the entire periodic structure can be dramatically reduced regardless of the number of contained periodic units. In addition, to avoid the error of dynamic modeling induced by conventional finite element method based on static shape function, the spectral element method, a highly accurate dynamic modeling method, is employed for modeling the periodic unit. Moreover, a novel discrete optimization method is developed, which is very efficient in terms of the number of function evaluations. The proposed methodology is demonstrated by both numerical and laboratory experiments conducted for a bolt-connected periodic beam model.
      PubDate: 2017-10-25T08:46:31.077998-05:
      DOI: 10.1111/mice.12309
       
  • A Bayesian Probabilistic Approach for Acoustic Emission-Based Rail
           Condition Assessment
    • Authors: Junfang Wang; Xiao-Zhou Liu, Yi-Qing Ni
      Abstract: The investigation described in this article aims at developing a Bayesian-based approach for probabilistic assessment of rail health condition using acoustic emission monitoring data. It comprises the following three phases: (i) formulation of a frequency-domain structural health index (SHI), via a linear transformation method, tailored to damage-sensitive frequency bandwidth; (ii) establishment of data-driven reference models, using Bayesian regression about the real and imaginary parts of the SHI derived with monitoring data from the intact rail; and (iii) quantitative evaluation of discrimination between the new observations representative of current rail health condition and the baseline model predictions in terms of Bayes factor. If the deviation of the new observations from the predictions is within an acceptable tolerance, no damage is flagged, and the new data are further used to update and refine the reference models. If the observations deviate substantially from the model predictions in a probabilistic sense, damage is signaled, damage severity is quantified, and damage location determined. The proposed approach is examined by using field monitoring data acquired from an instrumented railway turnout, and the coincidence between the assessment results and the actual health conditions demonstrates its effectiveness in damage detection, localization, and quantification.
      PubDate: 2017-10-23T07:51:26.677354-05:
      DOI: 10.1111/mice.12316
       
  • Vision-Based Natural Frequency Identification Using Laser Speckle Imaging
           and Parallel Computing
    • Authors: KyeongTaek Park; Marco Torbol, Sehwan Kim
      Abstract: This study focuses on the identification of the natural frequencies of structures through the analysis of the speckle pattern that a laser creates and a camera records. The laser pointer spreads its light over a target area on the structure and creates the speckle pattern. The ambient vibrations affect the pattern and a camera records the changes. The stream of images is fed into a graphics processing unit (GPU). The developed parallel code includes different algorithms: the speckle contrast image (SCI), the speckle flow imaging (SFI), and an innovative application of k-means clustering that uses the geometrical centroid of each cluster as virtual sensors. The tracking of the centroid in time domain through the images creates a vibration signal. The signals from different clusters are processed together to extract the natural frequencies of the structure. This study applies the proposed method to different sample structures both in laboratory and in the field to demonstrate how the obtained signals are reliable and easy to handle. The GPU technology enhances the performance of the entire method and allows the achievement of real-time processing. All these features create an inexpensive, portable, and efficient tool to inspect any structure or its components.
      PubDate: 2017-10-17T08:08:02.169288-05:
      DOI: 10.1111/mice.12312
       
  • On-Line Vehicle Routing Problems for Carbon Emissions Reduction
    • Authors: Tsai-Yun Liao
      Abstract: This paper proposes formulations and a hybrid meta-heuristic algorithm to solve the on-line vehicle routing problem (VRP) for minimizing costs related to economics and emissions. The on-line VRP considers real-time demands. Vehicle emissions are affected by travel speed and vehicle load. A hybrid meta-heuristic algorithm GA-Tabu is designed to solve the on-line VRP and a solution framework using DynaTAIWAN simulation is implemented. The numerical results show CO2 can be reduced by combining the emission factors into the objective function. Also, the route updates for on-line demands are analyzed and the performance measures of the on-line VRP are investigated by using various on-line demands.
      PubDate: 2017-10-13T06:27:23.455894-05:
      DOI: 10.1111/mice.12308
       
  • Modal Identification for High-Rise Building Structures Using Orthogonality
           of Filtered Response Vectors
    • Authors: Doyoung Kim; Byung Kwan Oh, Hyo Seon Park, Hak Bo Shim, Jiyoung Kim
      Abstract: The modal parameters of civil structures (natural frequency, mode shape, and mode damping ratio) are used for structural health monitoring (SHM), damage detection, and updating the finite element model. Long-term measurement has been necessary to conduct operational modal analysis (OMA) under various loading conditions, requiring hundreds of thousands of discrete data points for estimating the modal parameters. This article proposes an efficient output-only OMA technique in the form of filtered response vector (frv)-based modal identification, which does not need complex signal processing and matrix operations such as singular value decomposition (SVD) and lower upper (LU) factorization, thus overcoming the main drawback of the existing OMA technique. The developed OMA technique also simplifies parameters such as window or averaging, which should be designed for signal processing by the OMA operator, under well-separated frequencies and loading conditions excited by white noise. Using a simulation model and a 4-story steel frame specimen, the accuracy and applicability were verified by comparing the dynamic properties obtained by the proposed technique and traditional frequency-domain decomposition (FDD). In addition, the applicability and efficiency of the method were verified by applying the developed OMA to measured data, obtained through a field test on a 55-story, 214-m-tall high-rise building.
      PubDate: 2017-10-13T06:27:03.746379-05:
      DOI: 10.1111/mice.12310
       
  • Scalable Structural Modal Identification Using Dynamic Sensor Network Data
           with STRIDEX
    • Authors: Thomas J. Matarazzo; Shamim N. Pakzad
      Abstract: This article uses the formulation of the structural identification using expectation maximization (STRIDE) algorithm for compatibility with the truncated physical model (TPM) to enable scalable, output-only modal identification using dynamic sensor network (DSN) data. The DSN data class is an adaptable and efficient technique for storing measurements from a very large number of sensing nodes, which is the case in mobile sensor networks and BIGDATA problems. In this article, the STRIDEX output-only identification algorithm is proposed for the stochastic TPM to estimate structural modal properties (frequencies, damping ratios, and mode shapes) directly from DSN data. The spatial information produced by this novel algorithm, called STRIDEX (“X” for extended), is scalable, as demonstrated in a strategy to construct high-resolution mode shapes from a single DSN data set using a series of independent identification runs. The ability to extract detailed structural system information from DSN data in a computationally scalable framework is a step toward mobile infrastructure informatics in a large urban setting. The performance of the STRIDEX algorithm is demonstrated, using the simulated response of a 5,000 DOF structure, and experimentally, using measurements from two mobile sensor cars, which scanned about 8,000 points on a beam specimen in the laboratory. In the experimental results, a mobile sensor is shown to provide over 120 times more mode shape points than a fixed sensor.
      PubDate: 2017-10-09T07:53:15.812908-05:
      DOI: 10.1111/mice.12298
       
  • Two Methods to Calibrate the Total Travel Demand and Variability for a
           Regional Traffic Network
    • Authors: Tao Wen; Lauren Gardner, Vinayak Dixit, S. Travis Waller, Chen Cai, Fang Chen
      Abstract: This article proposes a novel methodology that uses the bi-level programming formulation to calibrate the expected total demand and the corresponding demand variability of traffic networks. In the bi-level formulation the upper-level is either a new maximum likelihood estimation method or a least squares method and the lower-level is the strategic user equilibrium assignment model (StrUE) which accounts for the day-to-day demand volatility. The maximum likelihood method proposed in this article has the ability to utilize information from day-to-day observed link flows to provide a unique estimation of the total demand distribution, whereas the least squares method is capable of capturing link flow variations. The lower-level StrUE model can take the total demand distribution as input, and output a set of link flow distributions which can then be compared to the link-level observations. The mathematical proof demonstrates the convexity of the model, and the sensitivity to the prediction error is analytically derived. Numerical analysis is conducted to illustrate the efficiency and sensitivity of the proposed model. Some possible future research is discussed in the conclusion.
      PubDate: 2017-10-02T03:40:35.179999-05:
      DOI: 10.1111/mice.12278
       
  • A Stereo-Matching Technique for Recovering 3D Information from Underwater
           Inspection Imagery
    • Authors: Michael O'Byrne; Vikram Pakrashi, Franck Schoefs, Bidisha Ghosh
      Abstract: Underwater inspections stand to gain from using stereo imaging systems to collect three-dimensional measurements. Although many stereo-matching algorithms have been devised to solve the correspondence problem, that is, find the same points in multiple images, these algorithms often perform poorly when applied to images of underwater scenes due to the poor visibility and the complex underwater light field. This article presents a new stereo-matching algorithm, called PaLPaBEL (Pyramidal Loopy Propagated BELief) that is designed to operate on challenging imagery. At its core, PaLPaBEL is a semiglobal method based on a loopy belief propagation message passing algorithm applied on a Markov random field. A pyramidal scheme is adopted that enables wide disparity ranges and high-resolution images to be handled efficiently. For performance evaluation, PaLPaBEL is applied to underwater stereo images captured under various visibility conditions in a laboratory setting, and to synthetic imagery created in a virtual underwater environment. The technique is also demonstrated on stereo images obtained from a real-world inspection. The successful results indicate that PaLPaBEL is well suited for underwater application and has value as a tool for the cost-effective inspection of marine structures.
      PubDate: 2017-09-22T08:51:01.786864-05:
      DOI: 10.1111/mice.12307
       
  • A Strategic User Equilibrium for Independently Distributed
           Origin-Destination Demands
    • Authors: Tao Wen; Chen Cai, Lauren Gardner, Vinayak Dixit, S. Travis Waller, Fang Chen
      Abstract: This article proposes an extension of the strategic user equilibrium proposed by Waller and colleagues and Dixit and colleagues. The proposed model relaxes the assumption of proportional Origin-Destination (O-D) demand, as it accounts for users’ strategic link choice under independently distributed O-D demands. The convexity of the mathematical formulation is proved when each O-D demand is assumed to follow a Poisson distribution independently; link flow distributions and users’ strategic link choice are also proved to be unique. Network performance measures are given analytically. A numerical analysis is conducted on the Sioux Falls network. A Monte Carlo method is used to simulate network performance measures, which are then compared to the results computed from the analytical expression. It is illustrated that the model is capable of accounting for demand volatility while maintaining computation efficiency.
      PubDate: 2017-09-06T09:32:06.66437-05:0
      DOI: 10.1111/mice.12292
       
  • Modeling the Proactive Driving Behavior of Connected Vehicles: A
           Cell-Based Simulation Approach
    • Authors: Feng Zhu; Satish V. Ukkusuri
      Abstract: Connected vehicles are able to proactively change speed to adapt to the prevailing traffic condition. Even in the mixed traffic environment, connected vehicles may function as leading vehicles, hence influencing the driving pattern of following nonconnected vehicles. This article proposes a cell-based simulation approach to model the proactive driving behavior of connected vehicles. First, a state variable of connected vehicles is introduced to track the trajectory of connected vehicles. Then the exit flow of cells containing connected vehicles is adjusted to simulate the proactive driving behavior, such that the traffic light is green when the connected vehicle arrives at the signalized intersection. The second part of the article conducts numerical tests to examine the effect of the proactive driving behavior of connected vehicles. Extensive test results consistently show that the presence of connected vehicles contributes significantly to the smoothing of traffic flow and vehicular emission reductions in the network.
      PubDate: 2017-09-05T09:26:19.526498-05:
      DOI: 10.1111/mice.12289
       
  • Blind Modal Identification in Frequency Domain Using Independent Component
           Analysis for High Damping Structures with Classical Damping
    • Authors: Xiao-Jun Yao; Ting-Hua Yi, Chunxu Qu, Hong-Nan Li
      Abstract: Output-only modal identification methods are practical for large-scale engineering. Recently, independent component analysis (ICA) which is one of the most popular techniques of blind source separation (BSS) has been used for output-only modal identification to directly separate the modal responses and mode shapes from vibration responses. However, this method is only accurate for undamped or lightly damped structures. To improve the performance of ICA for high damping structures, this article presents an extended ICA-based method called ICA-F, which establishes a BSS model in frequency domain. First, the basic idea of BSS and ICA applied in modal identification is introduced in detail. The free vibration responses and the correlation functions of ambient responses can be cast into the frequency-domain BSS framework just by mapping the time history responses to frequency domain through fast Fourier transform (FFT). Then, an ICA-based method in frequency domain called ICA-F is proposed to accurately extract mode shapes and modal responses for both light and high damping structures. A simulated 3 degree of freedom mass-spring system and a 4-story simulated benchmark model developed by the IASC-ASCE Task Group in Health Monitoring are employed to verify the effectiveness of the proposed method. The results show that the proposed method can perform accurate modal identification for both light and high damping structures. Finally, the IASC-ASCE experimental benchmark structure is also utilized to illustrate the proposed method applied to practical structure.
      PubDate: 2017-09-05T04:56:59.424358-05:
      DOI: 10.1111/mice.12303
       
  • Variable Neighborhood Search for Multistage Train Classification at
           Strategic Planning Level
    • Authors: Ivan Belošević; Miloš Ivić
      Abstract: Considerations on influences and interrelations between structural design and functional planning are imperative for raising the cost and operational effectiveness of marshaling yards in the context of managing wagonload services. This article focuses on multistage train classification, which rearranges a set of wagons from inbound trains to create a set of multigroup outbound trains in a proper form. Previous papers on the subject of multistage train classification were limited to considerations on the optimal classification schedule addressing the number of sorting steps as a primary objective. In contrast, this article proposes a model for overall optimization of the classification schedule and sidings layout, simultaneously addressing the number of sorting steps and the total number of wagon movements in the objective function. The model is created on a binary integer programming formulation. A Variable Neighborhood Search (VNS) heuristic is developed due to the computational complexity of the problem. Numerical experiments validate the formulated model and demonstrate the efficiency of the VNS meta-heuristic approach.
      PubDate: 2017-08-30T10:40:56.004656-05:
      DOI: 10.1111/mice.12304
       
  • Scheduling Optimization of Linear Schedule with Constraint Programming
    • Authors: Yuanjie Tang; Rengkui Liu, Futian Wang, Quanxin Sun, Amr A. Kandil
      Abstract: In recent decades, construction project scheduling optimization has received extensive attention from the research community. However, the most commonly used scheduling approach, the critical path method, is often inapplicable to transportation-type linear projects. Recently, the linear scheduling method (LSM) has demonstrated many advantages for such projects and has become a popular research subject. As a relatively novel scheduling method, LSM requires further improvement, as there are restrictions associated with the scheduling/optimization of linear projects. By analyzing results from previous studies, we propose a unique three-element mode, a description method for LSM's logical relationships and constraints system. An LSM-based scheduling optimization model based on constraint satisfaction problems and constraint programming is then proposed that could be used in classical scheduling optimization problems with flexibility, practicability, and solution superiority. The proposed model is verified using three practical transportation construction projects. Verification under six optimization scenarios demonstrates the advantages of our approach.
      PubDate: 2017-08-04T16:21:57.210595-05:
      DOI: 10.1111/mice.12277
       
  • Issue Information - TOC
    • Pages: 989 - 990
      PubDate: 2017-12-14T11:33:00.303946-05:
      DOI: 10.1111/mice.12339
       
  • Contents of Volume 32
    • Pages: 1085 - 1088
      PubDate: 2017-12-14T11:33:00.366473-05:
      DOI: 10.1111/mice.12340
       
  • Author Index to Volume 32
    • Pages: 1089 - 1090
      PubDate: 2017-12-14T11:33:02.978568-05:
      DOI: 10.1111/mice.12341
       
 
 
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