Article
Construction & Building Technology
Kyungjae Lee, Hyunwoo Lim
Summary: Building energy code updates induce correlations among building parameters, which can affect data analysis. This study investigates the impact of these correlations through sensitivity analysis and Principal Component Analysis (PCA).
JOURNAL OF BUILDING ENGINEERING
(2024)
Article
Construction & Building Technology
Seong-Yong Cheon, Hye-Jin Cho, Jae-Weon Jeong
Summary: A dedicated outdoor air system (DOAS) assisted by an isothermal dehumidifier and an indirect evaporative cooler is proposed, and its energy-saving potential is evaluated based on detailed simulations. The results indicate that despite the free cooling operation by the indirect evaporative cooler, the proposed system consumes 10% more operating energy due to the low coefficient of performance (COP) of the isothermal dehumidifier. Improvements in the COP of the isothermal dehumidifier are required for comparable energy performance.
JOURNAL OF BUILDING ENGINEERING
(2024)
Article
Construction & Building Technology
Xiaochen Ma, Wenchao Shi, Hongxing Yang
Summary: The actual wetting factor of the plate surface and the movement of spray droplets are important factors in the performance of indirect evaporative cooling (IEC) systems. A 3D computational fluid dynamics (CFD) model that considers these factors is proposed in this study. The model accurately predicts the performance of IEC systems and provides insights for further improvement.
JOURNAL OF BUILDING ENGINEERING
(2024)
Review
Construction & Building Technology
Zhen Zhu, Yuliang Chen, Huiqin Wu, Peihuan Ye
Summary: This study investigated the shear capacity of solid-web H-shaped steel reinforced concrete (HSRC) columns under combined torque. Seven HSRC columns were tested, and the influence of different parameters on the shear capacity was analyzed. The results showed that the addition of H-shaped steel improved the shear capacity, while increasing the axial compression ratio increased the shear capacity. However, increasing the torsion bend ratio and shear span ratio decreased the shear capacity.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2024)
Article
Construction & Building Technology
Peng Jiang, Benchao Liu, Yuting Tang, Zhengyu Liu, Yonghao Pang
Summary: This study introduces a novel deep learning-based electrical method that jointly inverses resistivity and chargeability to estimate water-bearing structures and water volume. Compared with traditional linear inversion methods, the proposed method demonstrates superiority in locating and delineating anomalous bodies, reducing solution multiplicity.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Ding Mao, Peng Wang, Yi-Ping Fang, Long Ni
Summary: This study analyzes the structure, function, operation, and failure characteristics of district heating networks (DHNs) and proposes vulnerability analysis methods. The effectiveness of these methods is validated through application to a DHN in a Chinese city. The study finds that the heat source connectivity efficiency loss rate effectively characterizes topological and functional vulnerability. It also reveals that controllable DHNs have higher functional vulnerability under large area failure scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Yongxin Su, Tao Zhang, Mengyao Xu, Mao Tan, Yuzhou Zhang, Rui Wang, Ling Wang
Summary: This study proposes an optimization method for household integrated demand response (HIDR) by combining rough knowledge and a dueling deep Q-network (DDQN), aiming to address uncertainties in a household multi-energy system (HMES). The simulation results demonstrate that the proposed method outperforms rule-based methods and DDQN in terms of energy cost savings.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Tianyao Liu, Xudong Qian, Wei Wang, Yiyi Chen
Summary: This article translates the ductile tearing process of welded joints made from circular hollow sections into the load resistance and strain levels, providing an interface between fracture-mechanics based assessments and engineering analysis and monitoring.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2024)
Article
Construction & Building Technology
Mamdouh Al-Ghzawi, Khaled El-Rayes
Summary: This paper presents a machine learning methodology for quantifying the impact of alternative construction phasing plans on air traffic operations. The methodology includes developing multiple models, comparing their performance and prediction accuracy, and efficiently evaluating the impact of different construction phasing plans on airport operations, providing support for planners.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Emanuel Martinez Villanueva, Pablo Martinez, Rafiq Ahmad
Summary: This study proposes a generative process planning algorithm for machining cross laminated timber (CLT) in robotic environments, enabling automatic interpretation of CLT panel geometries and guiding robots for machining, providing manufacturing results from geometric information at the design stage.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Sima Abolghasemi, Nicholas E. Wierschem, Mark D. Denavit
Summary: Structures susceptible to soft story mechanisms are particularly vulnerable to earthquakes. The strongback has been proposed as a way to prevent soft story mechanisms, but its impact on structural performance considering vertical stiffness irregularities and different arrangements of energy dissipation devices is unclear. This study investigates the effects of strongback on a small-scale four-story elastic structure with varying stiffness irregularities and damper arrangements. The results show that the strongback significantly reduces maximum story drift and makes the structural performance insensitive to damper position and distribution.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2024)
Article
Construction & Building Technology
Tran-Van Han, Jeong MoonSook, YongNam Kim, Dongkyu Lee, Nguyen-Vu Luat, Kihak Lee
Summary: This paper presents a new approach for steel modular structures, incorporating the S-CN connector and rectangular hollow section (RHS) steel members. The mechanical behavior of S-CN connectors and their application in beam-column connections under compressive loading are studied numerically and validated experimentally.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Shuying Wang, Zihao Zhou, Xiangcou Zheng, Jiazheng Zhong, Tengyue Zheng, Changhao Qi
Summary: A real-time assessment and monitoring approach based on laser scanning technology and point cloud data analysis was proposed to address the hysteresis in assessing the workability of conditioned soils and the inefficiency in estimating the soil volume flow rate in tunnelling practice. The approach was successfully applied in identifying the workability of conditioned soil and its discharge rate in the EPB shield tunnelling project.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Shangshang Shen, Dan Yan, Xiaojie Liu
Summary: This study developed a comprehensive theoretical framework for evaluating, diagnosing, and optimizing multi-functional urban agriculture. The framework was applied in Xiamen, China to identify the obstacles that impede its coordinated development and propose optimized modes for its development. Results showed that urban agriculture in Xiamen exhibits sound social function, moderate economic function, and poor ecological function.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Jingzhe Li, Qihan Shen, Jingfeng Wang, Fengqin Wang, Guoqiang Li
Summary: This study investigates the effectiveness of externally bonding carbon-FRP for strengthening concrete-filled steel tube short columns with void defects. It proposes strength prediction formulas and provides insights into the strengthening mechanisms.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2024)
Article
Construction & Building Technology
Peigen Li, Bin Zhou, Chuan Wang, Guizhang Hu, Yong Yan, Rongxin Guo, Haiting Xia
Summary: This paper introduces a method for detecting pavement defects using convolutional neural networks. The method acquires grey and depth image data and preprocesses them. Two network structures, classic U-shaped and double-headed structures, are developed to accommodate the characteristics of the image data. Attention modules are integrated to enhance defect detection accuracy. The proposed method achieves significant improvement in detection accuracy and proves effective in focusing on pavement defect areas.
AUTOMATION IN CONSTRUCTION
(2024)