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Several workplace injuries and fatalities are annually reported in the construction industry, and various efforts have been made to ensure safety. However, the construction industry still has higher casualty rates than other industries, and a preemptive safety management system that considers the safety risk factors at the construction site is deemed a necessity. Therefore, this study proposed a model that can quantitatively evaluate the safety of construction workers. A total of 18 safety risk factors consisting of three groups was derived from disaster-case data through a literature review, and was consulted to experts based on a survey to verify the suitability. Based on the results from the survey, 13 safety risk factors were selected, and the weights for each factor were derived. Moreover, an Analytic Network Process was used to derive the weights. Afterwards, a safety risk scale for each factor was derived based on the utility function from the accident case data provided by Korea Occupational Safety and Health Agency and opinions provided by expert. Finally, a safety assessment index for construction workers was proposed by combining the derived weights and safety risk scales. Accordingly, this study facilitates identifying construction workers with a high probability of suffering accidents in advance. Therefore, this study can contribute to preventing accidents at the construction site by supporting customized safety management for workers in hazardous environments. [ABSTRACT FROM AUTHOR]

Recently, Simultaneous Localization and Mapping (SLAM) has been integrated into the development of AR systems. Using conventional SLAM adoption method to overlay a building information model (BIM) onto the image of a real scene on handheld device in a construction site will result in poor model overlaying accuracy owing to the relatively unique environment and monotonous texture of such environment. This paper proposes an adoption method of SLAM suitable for construction environment to improve positioning accuracy for the fitting of BIMs for the AR presentation. In addition, a AR system to visualize construction progress on-site is developed. It allows site personnel to input on-site work progress through an AR device, then compares the originally planned construction progress with the actual on-site progress, and presents BIM components using different colors in the AR mode to show whether work progress on each component is ahead or behind schedule intuitively. [ABSTRACT FROM AUTHOR]

The dispatching of ready-mixed concrete (RMC) is usually scheduled manually and difficult to meet the demand of construction sites. The inefficient dispatching plan causes concrete defects of discontinuous casting (cold joint formation) or long on-site queuing (concrete early hardening inside RMC truck). The RMC dispatching literature focus on optimizing the dispatching intervals to minimize RMC truck on-site queuing, system operation costs of RMC plant and construction sites, or tradeoff. The previous research methods include mixed-integer linear programming (MILP) and evolutionary algorithms. They have the limitations of providing optimal solutions or computation efficiency. This paper develops a Binary Linear programming with Sliding Time-Window (BLSTW) to overcome these limitations. The BLSTW model subtly determines the dispatch of RMC trucks through binary variables incorporated into sliding time window search approach. Two perspectives, from the RMC plant supplier and construction site demanders, are discussed respectively. Three case studies are conducted to verify the efficiency improvement of the developed model including one largescale example of 25 sites. The comparisons made with two cited results shows the superior of the developed model. [ABSTRACT FROM AUTHOR]

When constructing a tunnel using a shield Tunnel Boring Machine, segments are mainly used. Sealants are then installed at segments for waterproofing. Two types of sealants, a hydrophilic rubber waterstop and a rubber gasket, are mainly used. Sealants can be arranged in single or double layers in consideration of construction site conditions. In this study, waterproofing performance was experimentally evaluated based on the type of sealant and the number of layers. A total of five types of sealant installation methods were tested. Waterproofing performance tests were used to determine their relative waterproofing performances under the same experimental conditions. Results showed that the hydrophilic waterstop was relatively vulnerable to a gap and the gasket was relatively vulnerable to an offset. If double layers of sealants are to be arranged at the construction site, it is recommended to arrange double layers of different types of sealants rather than double layers of the same type of sealants. This study could be helpful for selecting the type of sealant and/or the number of arrays at a construction site. [ABSTRACT FROM AUTHOR]

Instrumentation during tunnel construction can be used as reference data to identify anomalies, find the causes, and develop countermeasures through data trend analysis in terms of the construction, maintenance, and management of tunnels. Therefore, obtaining reliable and accurate data is very important to prevent large accidents and minimize damage. However, measurement sensors used in the field often show abnormal data because of the noise caused by functional and environmental factors. Such data may be misinterpreted as actual data caused by accidents in the analysis process and lead to construction delays due to investigating the situation. Moreover, the accumulation of such data may also have negative effects on analyzing the trend of the entire measurement data. Therefore, this paper proposes data filter-based correction techniques to correct noisy measurement data so that it does not affect the trend of accumulated data. By applying data filters of various sizes through simulations, this paper also presents the appropriate data filter size by examining the performance by filter size and validates the data correction performance by applying the proposed techniques to accumulated actual data measured from a construction site. [ABSTRACT FROM AUTHOR]

A large amount of geotechnical investigation data is essential for the highly reliable design of geotechnical structure at a construction site. The number of geotechnical investigations, however, has been generally insufficient and spatially biased owing to economic and spatial-temporal limitations. In this study, a geotechnical three-dimensional spatial modeling was implemented using an optimized geostatistical interpolation approach at a bridge construction site in the south-central part of the Korean peninsula. The geotechnical investigation data were collected and standardized for the construction of a geo-database. For the site-specific stratification, a kriging-based integration of the geo-layers and the seismic velocity from a seismic refraction survey were applied. The value from a standard penetration test (SPT)-N of an uninvestigated location was predicted using parametric and nonparametric geostatistical methods. We accomplished three-dimensional spatial interpolations using ordinary kriging, a sequential Gaussian simulation with a normal score transformed dataset, and a sequential indicator simulation using the geodatabase. A leave-one-out cross validation was carried out to quantitatively evaluate the reliability of the three-dimensional modeling. Finally, a three-dimensional geotechnical spatial model assigned with subsurface stratification and SPT-N values was constructed using the sequential Gaussian simulation. [ABSTRACT FROM AUTHOR]

Collecting construction equipment information such as the site equipment enter and exit date-time, driver's name, type, and quantity is essential in construction management. Most construction projects use paper to record the equipment access history. However, manual recording is always labour-intensive and time-consuming. Therefore, this research aims to develop an assistant system, Site Equipment Management Assistant (SEMA), to automate the site equipment management processes. With the introduction of image recognition and multiple objects tracking technologies, the proposed system can extract equipment-related information from raw videos. SEMA is designed as a chatbot system that contains three major modules: data acquisition, information extraction, and information delivery. A deep learning-based model was first trained to automatically recognize and track construction equipment passing by the site monitor. Information such as equipment entering and exiting date-time, type, and quantity would be extracted and stored in a database. A chatbot interface was developed for users to obtain data from the database through an intuitive and easy-to-use interface. A system evaluation and usability test were conducted. The results showed that the system could effectively improve the construction equipment management process. SEMA can save 60.7% of users' operation time on obtaining related information. [ABSTRACT FROM AUTHOR]

The construction industry is introducing autonomous heavy equipment to overcome labor shortages and improve productivity. For autonomous heavy equipment to work on earthmoving at sites, the equipment needs to recognize and understand ground surface types. However, the ground surface types are manually inspected in practice, and related studies are lacking. To address this issue, the authors developed and tested models that automatically classify ground surface types from images acquired by an unmanned aerial vehicle using a deep learning-based multi-label classification method that applies Binary Relevance (BR) and Label Powerset (LP) methods with Residual Neural Network (ResNet) and Vision Transformer classification network (VIT). The model performances were comparatively evaluated through experiments conducted on actual construction sites. The results showed that the BR model with ResNet is the best model in terms of automated ground surface type identification during earthmoving. The results are expected to broaden the understanding of complex and expansive construction sites for autonomous vehicles and thus facilitate deployment of autonomous heavy equipment by helping them to understand working areas and any obstacles on construction sites quickly and effectively, which will reduce the cost and time needed for on-site ground surface management. [ABSTRACT FROM AUTHOR]

In this paper, the strategy of three scales was proposed to analyse strong stress distributions of key joints during the incremental launching construction. Firstly, the internal forces and reaction forces were obtained by the finite element method (FEM). Secondly, some key joints were separated from the whole structure. The displacements and boundary conditions of the separated joint were taken from the results of the FEM. Then the stress distributions of the separated joint were successfully obtained by using the FEM. Thirdly, the local stress concentration areas were separated from the key joint structure. The high stress distributions of the local stress concentration region were successfully obtained by using the extended boundary element method (XBEM). On the other hand, the stress of some joints were measured through mechanical test on the construction site. And calculation results of the FEM and XBEM were in good agreement with test results. A multi-scale method is developed to obtain the strong stress concentration during the construction of the super-spanned steel truss bridge accurately, which enables the safety of the construction. In addition, the present method can be further used to guide the design of super-tall building, super-spanned bridge, etc. [ABSTRACT FROM AUTHOR]

The construction of hydropower project is a complex management process, whose management covers the entire construction site. Building information modeling (BIM) + Web Geographic Information System (WebGIS) is an effective means to solve the management of the construction site and main structures. Industry foundation classes (IFC) is commonly used in architecture, engineering and construction (AEC) industry as a standard for BIM data exchange. However, as the components of hydropower projects have not been included in IFC standards, IFC needs to be extended in application. At the same time, WebGIS pays more attention to display whole scene and ignores the processing of high-precision models. There will be deficiencies in network transmission and browser rendering in WebGIS environment of elaborate BIM model. Therefore, the batched three dimensions (3D) Tiles data format, which uses Web Graphics Library (WebGL) as the standard for 3D model rendering, has been widely considered in recent years. At present, in the field of BIM and GIS fusion, the conversion of extended IFC to 3D Tiles data is still blank, and none of the current BIM modeling software has the ability to export the components of hydropower projects. This paper proposes an extended IFC export method based on Autodesk Revit and a data exchange from extended IFC to batched 3D Tiles. Finally, the effectiveness of this method is verified by a design modification case of roller compacted concrete (RCC) gravity dam. [ABSTRACT FROM AUTHOR]

In order to effectively recycle Construction and Demolition, this study evaluates and quantifies the economic feasibility and emission of carbon dioxide for two recycling processes: on-site recycling process and process of a private recycling center. The results show that recycling costs were strongly influenced by the transport distance, the construction site conditions, and the amount of waste concrete to recycle, while emissions of carbon dioxide of the two recycling processes was mainly affected by the transport distance. On-site recycling process at the construction site cost only 63.8% as much and emitted only 33.6% as much carbon dioxide as the process at a private recycling center. Using sensitivity analysis, this study found that the unit recycling cost of on-site recycling process had little impact on the installation and dismantling costs of on-site recycling facilities when there was more than 10,000 metric tons of waste concrete to recycle. The process of a private recycling center emitted more carbon dioxide than on-site recycling process when the transport distance exceeded 10 km. [ABSTRACT FROM AUTHOR]

Managing a construction project is challenging because of cost, time, safety, and quality considerations. In the most projects, the cost of construction is one of the most critical aspect because material cost alone accounts for significant ratio of the total project. Therefore, the cost of construction materials should be controlled. In this study, we proposed the use of material requirements planning (MRP) to control the cost of construction materials. After determining the demand for the materials required for construction, we estimated both the quantity of materials required and time taken to deliver the materials to the construction site. Although economic order quantity models have been applied to analyze construction material costs, they do not accurately reflect concerns related to material cost. Therefore, we used the material supply chain model (construction logistics planning) to analyze material costs. To optimize MRP according to the current progress of a project, a novel approach combining the dragonfly algorithm (DA) and particle swarm optimization algorithm (PSO) was proposed. To verify the advanced searchability of the DA–PSO algorithm, the algorithm was compared with the gray wolf and the genetic algorithms. [ABSTRACT FROM AUTHOR]

Energy consumption and construction period in the construction process have been the focus of experts and researchers in the industry. Income by energy consumption and construction period is the long-term goal of industry managers. However, random events on the construction site are unpredictable, which have a random impact on energy consumption, construction period and its benefits. Therefore, a multi-objective stochastic optimization algorithm is designed to analyze the energy consumption, construction period and its benefits in the construction process, considering the random events. By introducing the idea of Lyapunov drift plus penalty, the construction process is simulated as a network transmission model, starting from the begin of the construction, and a series of construction sections are used as transmission. In this way, a virtual construction queue is constructed, Lyapunov quadratic function is defined, drift function is constructed, and the greedy objective function is punished to the minimum. Through the simulation process, the practicability of the algorithm is verified under the creation of several random events. The simulation accuracy and benefit value discrimination of the algorithm are higher comparing with the situation before optimization. [ABSTRACT FROM AUTHOR]

Location data of construction resources are important in understanding on the context of a construction site, yet most sites still rely on people's observations to localize their resources. Among then various localization technologies, radio frequency identification (RFID) is considered as a good solution. However, RFID either provides limited location data when fixed receivers are used, or it requires considerable manpower for scanning the tagged resources when hand-held receivers are used. These requirements result in inefficiency and impractical demands on time and cost, particularly in the case of complex or large-scale sites. This study attempted to overcome the limitations by proposing an integrated unmanned aerial vehicle-RFID (UAV-RFID) platform to replace the considerable manpower with the UAV and to enable identifying tags on a site. It applies deep learning algorithms to localize an RFID tag position within an acceptable range of accuracy, thereby demonstrating the feasibility of the integrated platform for construction resource localization. [ABSTRACT FROM AUTHOR]

Construction safety assessment is a major component of safety management in construction projects. However, thus far, most assessment studies have focused on either cross-sectional or longitudinal performance. This study aims to develop a proactive and preliminary safety assessment method using a fluid dynamics (FD) approach by integrating longitudinal contractor performance with cross-sectional safety conditions. To this end, an FD framework was first developed using three processes: (a) identifying the connections between FD principles and safety analogs, (b) incorporating the Darcy-Weisbach equation into the framework, and (c) modifying FD equations for construction safety assessment. Subsequently, two case studies were investigated, and the results obtained were compared and verified with one existing assessment results. The results indicate that the state of safety at a construction site incorporates both the occurrence of hazards and conservation of energy. Thus, the proposed FD approach can be used to preliminarily assess and predict safety conditions by combining safety-related measures with the dynamic characteristics of construction processes. The approach considers a comprehensive range of indicators and parameters, which enables the comparison of safety performance between projects or assessment periods by independently changing parameters. [ABSTRACT FROM AUTHOR]