Effect of reactive fumes suppressant DOPO on the chemical composition and performance of asphalt DOI

Shangheng Zeng,

Shi Xu, Tianwei Zhang

et al.

Construction and Building Materials, Journal Year: 2024, Volume and Issue: 443, P. 137693 - 137693

Published: Aug. 5, 2024

Language: Английский

Low-carbon high-strength engineered geopolymer composites (HS-EGC) with full-volume fly ash precursor: Role of silica modulus DOI Creative Commons
Ling-Yu Xu, Jian-Cong Lao, Lan-Ping Qian

et al.

Journal of CO2 Utilization, Journal Year: 2024, Volume and Issue: 88, P. 102948 - 102948

Published: Oct. 1, 2024

Language: Английский

Citations

31
Life cycle assessment of carbon emissions for cross-sea tunnel: A case study of Shenzhen-Zhongshan Bridge and Tunnel in China DOI Creative Commons
Huanyu Wu, Wenwen Zhou, Zhikang Bao

et al.

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 21, P. e03502 - e03502

Published: July 9, 2024

Due to significant population concentration and capital influx in Guangdong-Hong Kong-Macao Greater Bay Area, the construction of cross-sea tunnels with consumption various resources materials, has been frequently witnessed. However, there is a lack knowledge regarding how carbon emissions transportation infrastructure are generated across its life-cycle stages. This study proposes life cycle assessment (LCA) approach for quantifying exploring reduction potentials case world-renowned tunnel project Area. The results find that this contributes approximately 849 kilotons CO2eq an emission intensity 1.1 per meter. materialization stage largest contributor (474.9 CO2eq), followed by service (248.3 CO2eq, accounting 29.2 %). Some raw materials can be offset using recycled materials. discarded concrete, block, stone, sand, occupying over 90 % total waste weight could achieve 93.5 potentially. It provides opportunity reveal engineering details world-class super complex infrastructure. makes one first attempts quantify infrastructure, which enriches foundational dataset environmental impact emerging field. findings provide scientific references formulating targeted low-carbon strategies different

Language: Английский

Citations

9
Targeted and Highly Effective Technique for Healing the Aggregate-Asphalt Interface DOI
Dong Lu, Xi Jiang, Zhen Leng

et al.

Colloids and Surfaces A Physicochemical and Engineering Aspects, Journal Year: 2025, Volume and Issue: unknown, P. 136165 - 136165

Published: Jan. 1, 2025

Language: Английский

Citations

1
Steel slag aggregate property improvement in cold mixed asphalt mixtures through surface modification treatment DOI
Xiaowei Zhou,

Zhenjun Wang,

Haoyan Guo

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 477, P. 143889 - 143889

Published: Oct. 1, 2024

Language: Английский

Citations

5
The Evaluation and Prediction of Flame Retardancy of Asphalt Mixture Based on PCA-RBF Neural Network Model DOI Open Access
Peng Yin, Haowu Wang, Yangwei Tan

et al.

Materials, Journal Year: 2024, Volume and Issue: 17(13), P. 3298 - 3298

Published: July 4, 2024

Warm mix flame retardant asphalt mixture can reduce the energy dissipation and harmful gas emissions during pavement construction, as well mitigate adverse effects of road fires. For this, this paper studies design performance a modified with combination warm agent retardant, retardancy are evaluated. Additionally, prediction model based on radial basis function (RBF) neural network is established. On basis, principal components analysis (PCA) used to analyze most significant evaluation indicators affecting retardancy, finally, three-dimensional finite element developed loading structure. The results show that compared virgin mixture, shows reduction in mixing compaction temperatures by approximately 12 °C. high-temperature improved, while low-temperature moisture stability slightly decrease, but its significantly enhanced. RBF revealed established has high accuracy, allowing for precise retardancy. Finally, PCA identified combustion time effect displacements fire were lower than all directions under loading.

Language: Английский

Citations

4
Comparative study on the prediction of the unconfined compressive strength of the one-part geopolymer stabilized soil by using different hybrid machine learning models DOI Creative Commons
Qinyi Chen,

Guo Hu,

Jun Wu

et al.

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 21, P. e03439 - e03439

Published: July 26, 2024

With the development of green, low-carbon, and sustainable economic systems, issues high pollution energy consumption in construction materials have become increasingly prominent. This study focuses on adopting one-part geopolymer (OPG) soil stabilization for underground engineering, which exhibits environmental low-carbon advantages. The unconfined compressive strength (UCS) serves as a crucial parameter assessing stabilized soil's performance. However, it is necessary to conduct large number experiments, inducing costs time consumption. In this study, one multiple linear regression model, Decision Tree (DT) five ensemble machine learning (ML) models (i.e. Random Forest [RF], Extra [ET], Gradient Boosting [GB], [GBDT], Extreme [XGBoost]), hybrid those single with Particle Swarm Optimization (PSO) PSO-RF, PSO-ET, PSO-GB, PSO-GBDT, PSO-XGBoost) were adopted compared achieve better prediction UCS OPG-stabilized soil. Furthermore, interpretable method including SHAP PDP (1D 2D), was employed investigate precise mechanisms by input parameters influenced output label. results revealed that model delivered lowest accuracy, PSO-XGBoost PSO-ET exhibited best performance R2 value 0.9964 0.9928, respectively. addition, Curing exerted most significant impact UCS, followed FA/GGBFS, Molarity, Water/Binder, NaOH/Precursor. Compared method, offered more intuitive approach reveal relationship between inputs output. outcome shed new light application ML engineering.

Language: Английский

Citations

4
Inhibitory effects of surface modified solid acid synergistic warm-mixed flame retardant on asphalt combustion behavior DOI
Mengkai Sun,

Zhaoyi He,

Yifei Wu

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 465, P. 140266 - 140266

Published: Feb. 1, 2025

Language: Английский

Citations

0
Investigation of macroscopic and microscopic void characteristics' effects on flame-retardant performance of porous asphalt mixtures for tunnel pavement DOI

Xiaoguang Xie,

Wenhui Zhang, Ke Xu

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 472, P. 140962 - 140962

Published: March 24, 2025

Language: Английский

Citations

0
Multi-objective optimization and performance investigation of surface modification synergistic warm-mixed flame retardant asphalt DOI
Mengkai Sun, Qing Guo,

Zhaoyi He

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 473, P. 141021 - 141021

Published: April 1, 2025

Language: Английский

Citations

0
Enhancing Mechanical Properties and Crack Resistance of High-strength SHCC/ECC for Durable Transportation through Ethylene-Vinyl Acetate Polymer Modification DOI Creative Commons
Yanlin Huo,

Tianan Liu,

Dong Lu

et al.

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: unknown, P. e03878 - e03878

Published: Oct. 1, 2024

Language: Английский

Citations

3