Decision-making in construction planning and scheduling is complex because of budget and resource constraints, uncertainty, and the dynamic nature of construction environments. A knowledge gap in the construction literature exists regarding decision-making frameworks with the ability to learn and propose an optimal set of solutions for construction scheduling problems, such as activity sequencing and

This paper presents findings of delamination detection using infrared thermography (IRT) in five in-service bridges using an unmanned aerial vehicle system. The authors have used semantically segmented IRT images to evaluate IRT's effectiveness in detection of deck delamination for the first time. Using an adaptive image processing-based model, sub-surface delaminations were detected by optimizing

As an indispensable transportation tool, tower cranes are widely used in construction sites. However, since the mass and volume of the transported goods become larger, most of the traditional control algorithms designed for Concentrated Payload Mass (CPM) are not sufficient for Distributed Payload Mass (DPM). One of the main differences between DPM and CPM is that the payload swing caused by the moment

The Architecture, Engineering, and Construction (AEC) industry is transitioning toward using cloud-based Common Data Environments (CDEs) with interlinked BIM models. A CDE that engages all stakeholders of the building's design, construction, and operation phases represents the outset of BIM maturity level 3. This article introduces a CDE called Virtual Commissioning (VC), capable of commissioning an

Current legislation focuses on reducing the operational carbon impact of buildings. However, the production of materials used in construction generates a considerable amount of carbon, known as embodied carbon, that accounts for a sizeable fraction of the environmental impact of a building during its lifecycle. We present a newly developed tool, pycab, which calculates the embodied carbon of a building

A spatial designer's search goal is sequentially updated during the spatial design exploration process. The design exploration process requires a proactive process that supports better-informed design decisions and refreshes the search direction to avoid being fixed; however, no study has been conducted to date. This paper describes a framework called CreativeSearch, which provides three types of guidance

Acquiring data and measuring positions should be predetermined for data acquisition experiments, while numerical simulation provides effective guidance. Because bulldozing involves multibody dynamics, soil mechanics and hydraulic control, a high-fidelity simulation approach should be developed to cover these fields. This paper proposes a RecurDyn-EDEM-AMESim co-simulation which accurately characterizes

The resource-constrained project scheduling problem (RCPSP) is one of the project scheduling problems which are widely used in construction and many industrial disciplines. The challenge of the problem is to design some appropriate search mechanism for finding solutions in feasible space. An improved genetic algorithm based on time window decomposition is proposed in this paper. Three derivation methods

Pavement subsurface distress endangers driving safety and road serviceability. Ground penetrating radar (GPR) can non-destructively provides high-resolution profiles of road. However, the automatic interpretation of radar signals remains challenging. This study proposed an automatic pavement subsurface distress detection method using traditional signal processing and deep learning. Firstly, a piecewise

The progress in information technology allows an innovative transformation of practices commonly involved in the engineering and construction field, especially in relation to the existing architectural heritage's control and management activities. The proposed methodology takes advantage of an integrated 3D metric survey as a basis for an HBIM (Historic Building Information Modelling) model to be exploited

Mark bars drawn on the surfaces of bolted joints are widely used to indicate the severity of loosening. The automatic and accurate determination of the loosening angle of mark bolted joints is a challenging issue that has not been investigated previously. This determination will release workers from heavy workloads. This study proposes an automated method for detecting the loosening angle of mark bolted

Deep learning techniques have the potential to provide versatile solutions for automated semantic segmentation of bridge point clouds, but previous studies were limited to small-scale bridge point clouds and focused on limited bridge component categories due to training sample scarcity. Additionally, no prior work considered the intrinsic data imbalance problem in the bridge dataset, with the points

Because of the high costs of ground-based pavement condition methods used to monitor pavement condition, transportation agencies often limit distress surveys to their major roads. As a result, the condition of local and ancillary roads remains unknown to decision-makers. This study addresses this gap by exploring the capabilities of publicly available Synthetic Aperture Radar (SAR) data to estimate

Building information models (BIMs) have been widely adopted in current construction projects to enhance the efficiency of facility maintenance operations. As-built BIMs can reflect the actual conditions of facilities and thus as-built BIM reconstruction has shown great significance in digital twin generation, building health monitoring, facility management and urban renewal. Laser scanners are capable

This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorporate geometry-based collision checks in trajectory planning. This research developed an algorithm that

BIM, gamification, and Virtual Reality applications are more often used to serve the interests of Design for Manufacture and Assembly (DfMA). This paper presents a comprehensive study to exploit these technologies' innovative approaches and capabilities. The study is specifically adopted to implement small and medium-size architectural and construction practices with a limited budget and time dedicated

The moving morphable component (MMC) method, an important engineering structural optimization algorithm, achieves a boundary evolution through the migration and superposition of a series of moving morphable display components, resulting in structural optimization. Instead of the original linear skeleton thickness quadratic variation component, an elliptical initial component is used for topology optimization

Comprehensive image datasets can benefit the construction industry in terms of serving as the basis for generating deep-learning-based object detection models and testing the performance of object detection algorithms, but building such datasets is complex and requires vast professional knowledge. This paper develops and publicly releases a new large-scale image dataset specifically collected and annotated

This paper presents a modified oriented bounding box method and a compound control law for the developed intelligent demolition robot working safely and accurately in a high-radiation environment. Combining statics and kinematics, the modified oriented bounding box method is applied to predict the real-time and accurate collision detection of possible collisions. The Newton–Euler method is then adopted

Construction project is sensitive to material arrival delays, which can cause schedule delays and budget overruns. The prompt detection of construction material arrival delays is necessary to recover disrupted projects in time. This paper explores computer vision-based (CVB) mutually coupled detection and tracking of transport trucks for monitoring construction material arrival delays. Through the

Three-dimensional (3D) concrete printing is an advanced and promising construction method that shows great development potential in the field of construction engineering owing to its highly flexible and intelligent characteristics. The printing path design that is directly related to the 3D printing process is usually limited by the time-dependent rheological properties of concrete composites and the

The development of the disc cutter replacement manipulator requires an actuator with high power density and excellent positioning precision, typically, electro-hydrostatic actuator (EHA). However, the EHA is a pump-controlled hydraulic system that has a slower response in comparison with conventional centralized hydraulics. In this paper, a position-pressure feedback control (PPFC) method is proposed

This paper explores buildability quantification of randomly meshed 3D printed concrete objects by considering structural failure by elastic buckling. The newly proposed model considers the most relevant printing parameters, including time-dependent material behaviors, printing velocity, localized damage and influence of sequential printing process. The computational uniaxial compression tests were

The nontarget-based displacement measurement approaches that use structural features have been developed for the wider adoption of computer vision-based methods in real-world applications. However, nontarget-based approaches still require the target or known structural metric information to obtain the displacement. This study proposes a nontarget-based displacement measurement method using LiDAR combined

Due to ground loss and shallowly buried tunnels, there are serious safety problems in shield tunnel construction. To comprehensively describe the safety of shield tunnel construction, two safety control indices (ground settlement and segment floating) were applied to represent the two main aspects of construction safety (surrounding environment and tunnel structure). Here, a deep-learning method involving

In recent years, building information modeling and artificial intelligence of things (BIM-AIOTs) in the construction industry have gained much attention. Construction engineers and researchers learn about BIM-AIOT and increase their professional knowledge through internet searches. However, the large amount of information on the internet makes it difficult to find specific information. Although some

One of the most critical issues related to the current application of virtual reality during design appraisal is the inability to have a collaborative virtual environment where a group of geographically remote stakeholders can interact and communicate effectively in real-time. This paper addresses this shortcoming by proposing a collaborative furniture, fixture and equipment virtual environment (COFFEE)

Indoor environmental quality (IEQ) monitoring is an important basis of smart buildings to ensure human comfort and control energy systems. IEQ monitoring conventionally relies on a limited number of stationary sensors deployed at selected locations, which has little capacity to capture fine spatial characteristics due to the cost of infrastructure and maintenance. This paper describes a robot-based

To advance the scan-to-model process for steel girder bridges, this paper presents an automated approach for creating complete geometric models for the steel superstructure elements based on the segmentation results from Yan and Hajjar (2021). The key innovation is two-fold: 1) cross-frames are automatically partitioned into cross-frame members that need to be modeled separately; 2) a 3D occlusion

Hydraulic shovel is widely used in mining industry around the world for materials excavation and loading. The mechanical design of hydraulic shovel remains a challenging optimization problem. To address this issue, we establish the many-objective optimization model of a new type hydraulic shovel named TriRocker. An improved reference points-based many-objective differential evolution algorithm is proposed

Masonry arch bridges constitute the majority of the European bridge stock and feature a wide range of geometric characteristics. Due to a general lack of construction drawings, their geometry is difficult to parameterize. Laser scanning devices are commonly used to capture bridge geometry. However, this requires time-consuming segmentation of point clouds into their constituent components to extract

Agent-based modeling and simulation can help reveal the progress and information flow of construction and assess on-site construction strategies based on a bottom–up approach. Despite research on multiple decision agents in the construction process, questions regarding the on-site behavior of construction performers and their interaction with the site remain unanswered. This study aims to simulate

One of the target areas of concern with large-scale 3D printing (Additive Manufacturing (AM)) processes is the need to enhance the bond strength between adjacent printed layers. In this paper, the impact of three process parameters on interlayer bond strength in paste was investigated. Utilizing an alternative clay-based material in large-scale AM was considered in this research due to concerns about

Shell structures are widely used in architectural design and civil engineering. However, it remains challenging to simultaneously optimize their shape, thickness, and topology under various design constraints and construction requirements. This work presents a method for the shape–thickness–topology coupled optimization of shell structures. In this method, the shape of shells is described by the non-uniform

A novel projection-based learning method named UnrollingNet is developed to conduct a multi-label segmentation of various objects including seepage from 3D point clouds of tunnels. 3D laser scanning is first utilized to collect raw point clouds from the operating tunnels. An unrolling projection approach is created on the trimmed dataset to generate 2D representations. A U-net-based segmentation algorithm

Despite the popularity of image-based classification techniques in identifying building materials and elements in building and construction sites, the real feasibility of it accommodating the needs of operation and maintenance (O&M) inspection-repair processes in the real project scale is still awaiting testing due to the vast number of project assets, hundreds of asset categories, and requirements

This paper combined data-driven modeling and optimal control for performance enhancement of earth pressure balance tunnel boring machine (EPBM). Two coupled processes, EPBM advance rate (AR) and cutterhead rotation torque, are modeled using support vector regression (SVR). An optimal control framework was formulated to maximize the AR, solved with particle swarm algorithm. Using the Seattle N125 project

Dynamical responses of vibratory compaction are the basis for extracting compaction indexes in intelligent compaction (IC) technology. However, dynamical response characteristics and its variation mechanisms have not been sufficiently investigated. In this study, a vibratory compaction model was built utilizing finite element (FE) method to observe the characteristics, and nonlinear system theory was

High accuracy 3D surface information is required for many construction robotics tasks such as automated cement polishing or robotic plaster spraying. However, consumer-grade depth cameras currently found in the market are not accurate enough for these tasks where millimeter (mm)-level accuracy is required. This paper presents SL Sensor, a structured light sensing solution capable of producing high

Transportation of prefabricated modules is a critical process in modular construction and can cause additional stresses which may damage individual modules, leading to additional costs and time during the installation and operational phase if damaged parts are not timely restored or replaced. Therefore, utilizing a tracking and condition monitoring system is useful for modular building manufacturers

Current defect detection studies in the industrial fields mainly adopt supervised strategies, which require large amounts of annotated defective samples to achieve superior results. However, it is hard to meet such large-scale data requirements in the actual industrial scenarios where defects commonly exhibit intensive scarcity and huge intraclass variation. To address the above limitations, we propose

Due to the complex working environment, limited vision, and complicated crane operations, the crane operator faces two major problems when constructing with a crane: safety and working efficiency. Every year, numerous accidents occur, the majority of which are the result of the crane operator's inability to acknowledge hidden hazards. Some of these accidents can be effectively avoided through a comprehensive

Conventional soil–cement columns fail to fully consider the layered structure of foundation soil, resulting in cement waste. Owing to the concealment of the installation site, soil–cement mixing column installation is labor-intensive, and its quality is considerably affected by the skills and experience of the laborers and operators. In this study, soil–cement mixing column installation technology

Automated investigation of concrete defects has attracted attention with well-developed computer vision techniques. However, most studies in defect reconstruction mainly focus on identifying and measuring defects on a two-dimensional surface. Few progresses have been made to explore the 3D reconstruction of concrete defects. This study describes an affordable optical laser triangulation system fusing

Detecting contractual risk information from construction specifications is crucial to succeeding in construction projects. This paper describes clause classification using the Bidirectional Encoder Representations from Transformers (BERT) method in natural language processing. Seven risk categories are determined from a literature review, including payment, temporal, procedure, safety, role and responsibility

The quality of 3D models of existing buildings reconstructed from point clouds is strongly related to the segmentation process used to detect structural elements. A new wall detection method in the indoor point clouds of buildings is presented in this study. The point clouds are segmented into horizontal layers, and a concept of continuous segments in a 2D grid representation is used to extract the

Vehicle-related ground occlusion is a common problem in MLS data. This study aims to design a detection and reconstruction method of static vehicle-related ground occlusion for MLS data. Ground extraction and vehicle segmentation are performed on the input point cloud data in advance. Then an α-shape boundary based on the prior vehicle geometry is designed to split non-ground empty area and ground

Elastic gridshells (EGS) offer a cost-effective and rapid way to construct lightweight structures. This paper focuses on bundlable EGS, gridshells which may be deployed from a compact slender state, thus allowing for off-site fabrication. Some bundlable EGS have the additional property of being self-shaping, an aspect that simplifies considerably the erection phase. Despite recent research interest

Digital Twins (DTs) are forecasted to be used in two-thirds of large industrial companies in the next decade. In the Architecture, Engineering and Construction (AEC) sector, their actual application is still largely at the prototype stage. Industry and academia are currently reconciling many competing definitions and unclear processes for developing DTs. There is a compelling need to establish DTs

In this paper, a machine process to repair cracks in asphalt pavements by filling them with hot bitumen is demonstrated for the first time. We have characterized the quality of these fillings. Furthermore, the paper examines how the filling speed, temperature, bitumen type, crack width, crack irregularity, and the flow of hot bitumen affect the crack filling quality by the machine. In the laboratory

Detecting visual relationships among construction resources plays a pivotal role in understanding complex construction scenes and performing vision-based site monitoring and digitalization. Despite extensive efforts, the propagation effects of different resource-to-resource interactions were overlooked and thus, it is still challenging to precisely detect entangled and intertwined visual relationships

Technology adoption is pivotal for the productivity growth in construction industry. This research paper attempts to fill this gap by addressing the following research objectives. First, the predictor factors stimulating project managers' adoption of construction automation innovations are rigorously analyzed using a mixed approach combining a systematic literature review, a knowledgeable panel, and