Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 111466 - 111466
Published: Dec. 1, 2024
Language: Английский
Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 111466 - 111466
Published: Dec. 1, 2024
Language: Английский
Construction and Building Materials, Journal Year: 2024, Volume and Issue: 421, P. 135586 - 135586
Published: March 1, 2024
Language: Английский
Citations
18Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 86, P. 108792 - 108792
Published: Feb. 17, 2024
Language: Английский
Citations
16Buildings, Journal Year: 2024, Volume and Issue: 14(4), P. 907 - 907
Published: March 27, 2024
To overcome limitations inherent in existing mechanical performance prediction models for pervious concrete, including material constraints, limited applicability, and inadequate accuracy, this study employs a deep learning approach to construct Convolutional Neural Network (CNN) model with three convolutional modules. The primary objective of the is precisely predict 28-day compressive strength concrete. Eight input variables, encompassing coarse fine aggregate content, water admixture cement fly ash silica fume were selected model. dataset utilized both training testing consists 111 sample sets. ensure model’s coverage within practical range concrete enhance its robustness real-world applications, an additional 12 sets experimental data incorporated testing. research findings indicate that, comparison conventional machine method Backpropagation (BP) neural networks, developed CNN paper demonstrates higher coefficient determination, reaching 0.938, on test dataset. mean absolute percentage error 9.13%, signifying that proposed exhibits notable accuracy universality predicting regardless materials used preparation.
Language: Английский
Citations
3Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 11 - 34
Published: Jan. 1, 2025
Language: Английский
Citations
0Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112069 - 112069
Published: Feb. 1, 2025
Language: Английский
Citations
0Engineering Construction & Architectural Management, Journal Year: 2025, Volume and Issue: unknown
Published: March 17, 2025
Purpose The building industry generates around ten billion tons of construction and demolition waste (CDW) annually worldwide, posing both financial burdens on contractors significant environmental hazards. Embracing a circular economy (CE) approach emerges as promising strategy for sustainably managing the vast volumes CDW. However, sustainable performance many attempts in CDW circulation is still questioned need to be justified. This study transcends traditional reviews by adopting systematic literature review, focusing central question: “What’s contribution 3R principle its sustainability performance?” Design/methodology/approach methodological framework encompasses searching, screening quality assessment, culminating selection 177 articles bibliometric integrative analysis. Comparative assessments were conducted major reduction strategies, reuse materials, recycling rates other strategies. process was also discussed well modern advanced tools used design such information model (BIM), AI geographic systems (GIS). Findings analysis reveals evolution selected publications year, country research hotspots. Through analysis, explored principles adopted circulation, including reduction, recycling, methods across key global economies. There notable disparity volume addressing compared recycling. In comparison economic circulations, social has received less attention. Moreover, ventured into prospective trajectories, exploring future themes adoption “zero-waste” industry, promotion higher-level material circularity, institutional network among stakeholders practice, new holistic Originality/value Few this field have focused circulation. comprehensive not only contributes valuable insights current state within CE paradigm but directs attention toward critical avenues area.
Language: Английский
Citations
0Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(14), P. 20814 - 20852
Published: Feb. 24, 2024
Language: Английский
Citations
3Materials, Journal Year: 2024, Volume and Issue: 17(7), P. 1479 - 1479
Published: March 24, 2024
The impacts of various aggregate particle sizes and cement contents on the internal structure pervious concrete were investigated. Accordingly, test blocks with different dissected photographed. Subsequently, captured images processed using ImageJ software (1.53i) to analyze profiles identify mesoscopic parameters concrete. This study discusses relationship between microscopic macroscopic factors based experimental results. It also fits functional equations linking permeability coefficient pore parameters, matrix compressive strength. results indicated that, as size increased, diameter whereas total area width decreased. resulted in a low high strength block. Increasing content reduced porosity increased matrix. Consequently, decreased, block increased.
Language: Английский
Citations
1Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 135, P. 103652 - 103652
Published: June 5, 2024
Language: Английский
Citations
1Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 144382 - 144382
Published: Dec. 1, 2024
Language: Английский
Citations
1