Abstracts – Browse Results
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Akin, F D, Damci, A and Arditi, D (2024) Optimum finance-based scheduling. Journal of Construction Engineering and Management, 150(09).
Assaad, R H, Omran, A, Soliman, N and Assaf, G (2024) Prediction of the lateral pressure of self-consolidating concrete on construction formwork systems using machine-learning algorithms. Journal of Construction Engineering and Management, 150(09).
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-14509
- Abstract:
Construction firms face considerable challenges in relation to finding cost-effective formwork solutions to meet increased construction demands. Project stakeholders have relied on self-consolidating concrete (SCC) to speed up the construction time because SCC is highly fluid and has numerous advantages compared to traditional concrete. To withstand SCC's high fluidity, formwork systems should be robust. Although previous research has experimentally examined various characteristics of SCC, few research studies have used machine-learning algorithms to estimate or predict the lateral pressure exerted by SCC on formwork systems. Hence, this study addressed this knowledge gap by proposing a machine-learning approach to predict the lateral pressure of SCC on vertical formwork systems. First, laboratory tests were performed to collect data on lateral pressure measurements, material factors, placement conditions, and formwork characteristics affecting the SCC lateral pressure on formwork systems. Second, four supervised machine-learning algorithms were considered in this study: k-nearest neighbor (KNN), artificial neural network (ANN), decision tree (DT), and random forest (RF). Third, the hyperparameters of the machine-learning algorithms were tuned, and their performance metrics were compared. Fourth, the most accurate predictive machine-learning model was verified on an unseen testing set. The results showed that the RF machine-learning algorithm was the best model for predicting the lateral pressure of SCC on formwork systems, with a mean percentage error of 0.8%, a mean absolute percentage error of 4.29%, and a coefficient of determination R2 of 0.9548. This study adds to the construction engineering and management body of knowledge by developing a machine-learning predictive model that can be used to accurately assess the lateral pressure exerted by SCC on formwork, which helps to ensure safe design of formwork systems and economic construction operations in formwork-related activities.
Assaf, G and Assaad, R H (2024) Analyzing the critical success factors affecting project bundling performance of infrastructure projects. Journal of Construction Engineering and Management, 150(09).
Chammout, B, El-Adaway, I H, Abdul Nabi, M and Assaad, R H (2024) Price escalation in construction projects: Examining national and international contracts. Journal of Construction Engineering and Management, 150(09).
Dorignon, L, Oswald, D, Kempton, L, Boehme, T, Iyer-Raniga, U, Moore, T and Dalton, T (2024) Investigating residential building materials in a circular economy: An Australian perspective. Journal of Construction Engineering and Management, 150(09).
Görsch, C, Seppänen, O, Peltokorpi, A and Lavikka, R (2024) Unlocking productivity: Revealing waste and hidden disturbances impacting mep workers. Journal of Construction Engineering and Management, 150(09).
Gao, M Y, Han, J, Yang, Y, Tiong, R L K, Zhao, C and Han, C (2024) BIM-based and IoT-driven smart tracking for precast construction dynamic scheduling. Journal of Construction Engineering and Management, 150(09).
Jiang, Y, Yang, G, Li, H, Zhang, T and Khudhair, A (2024) Physics-informed knowledge-driven decision-making framework for holistic bridge maintenance. Journal of Construction Engineering and Management, 150(09).
Koo, H J, Kelly, D and Deman, D (2024) Risk assessment of the challenges in the adaptive reuse of historic buildings. Journal of Construction Engineering and Management, 150(09).
Namian, M, Nabil, F R, Al-Mhdawi, M K S, Kermanshachi, S S and Nnaji, C (2024) Postpandemic era: Investigating the impact of COVID-19 on construction workers' situational awareness. Journal of Construction Engineering and Management, 150(09).
Ning, X, Yang, Y, Liu, C and Han, Y (2024) Construction workers' unsafe behavior contagion under government-contractor dual influence. Journal of Construction Engineering and Management, 150(09).
Olugboyega, O (2024) Diverse forms of greed and self-interest that contribute to corruption among construction stakeholders. Journal of Construction Engineering and Management, 150(09).
Ouyang, Y and Luo, X (2024) Effects of physical fatigue on construction workers' visual search patterns during hazard identification. Journal of Construction Engineering and Management, 150(09).
Paneru, S, Suh, S, Seo, W and Rausch, C (2024) Evaluating the decarbonization potential of industrialized construction: A review of the current state, opportunities, and challenges. Journal of Construction Engineering and Management, 150(09).
Sadoughi, A, Kouhirostami, M, Kouhirostamkolaei, M, Qi, B and Costin, A (2024) Autonomous building design for manufacturing and assembly: A systematic review of design application, challenges, and opportunities. Journal of Construction Engineering and Management, 150(09).
Shahedi, F, Etemadfard, H, Omrani, F and Ghalehnovi, M (2024) Cost performance modeling for steel fabrication shops with machine learning algorithms. Journal of Construction Engineering and Management, 150(09).
Shuang, Q, Liu, X, Wang, Z and Xu, X (2024) Automatically categorizing construction accident narratives using the deep-learning model with a class-imbalance treatment technique. Journal of Construction Engineering and Management, 150(09).
Wang, R D, Zayed, T, Eltoukhy, A E E and Wu, H (2024) Integrated planning approach for optimizing tower crane and truck locations in modular integrated construction. Journal of Construction Engineering and Management, 150(09).
Wu, H, Chang, Y and Chen, Y (2024) Transitioning work arrangements in the construction industry: Changes in time-use patterns and individual greenhouse gas emissions. Journal of Construction Engineering and Management, 150(09).
Yang, J, Wu, Y and Li, D (2024) Block planning based on grid's topology for the dismantling of long-span spatial lattice structures. Journal of Construction Engineering and Management, 150(09).
Zhang, Y, Chang, R, Mao, W, Zuo, J, Liu, L and Han, Y (2024) Challenges of automating interior construction progress monitoring. Journal of Construction Engineering and Management, 150(09).
Zhang, Y, Liu, L, Song, Z, Zhao, Y and He, S (2024) Enhancing tunnel boring machine penetration rate predictions through particle swarm optimization and elman neural networks. Journal of Construction Engineering and Management, 150(09).