Construction and Building Materials, Год журнала: 2024, Номер 451, С. 138781 - 138781
Опубликована: Окт. 18, 2024
Язык: Английский
Construction and Building Materials, Год журнала: 2024, Номер 425, С. 135962 - 135962
Опубликована: Март 28, 2024
Язык: Английский
Процитировано
16
Sustainability, Год журнала: 2024, Номер 16(12), С. 4889 - 4889
Опубликована: Июнь 7, 2024
Underground infrastructure projects pose significant environmental risks due to resource consumption, ground stability issues, and potential ecological damage. This review explores sustainable practices for mitigating these impacts throughout the lifecycle of underground construction projects, focusing on recycling reusing excavated tunnel materials. systematically analyzed a wide array practices, including on-site reuse material as backfill, grouting, soil conditioning, concrete production. Off-site reuses explored are road bases, refilling works, value-added materials, like aggregates products, vegetation reclamation, landscaping. Opportunities recover repurpose components temporary support structures, known “false linings”, also reviewed. Furthermore, utilizing industrial wastes in works explored, such thermal insulation, fire protection, lining. Incorporating green materials energy-efficient methods areas lighting, lining discussed. Through comprehensive analysis numerous case studies, this demonstrates that with optimized planning, treatment techniques, end-use selection informed by characterization, can significantly reduce footprint infrastructure. However, certain approaches require further refinement standardization, particularly consistent assessment recycled properties development standardized guidelines their use various applications. These contribute broader sustainability goals reducing minimizing waste generation, promoting Achieving coordinated multi-stakeholder adoption, collaboration between contractors, suppliers, regulatory bodies, research institutions, is crucial maximizing impact accelerating transition towards more industry.
Язык: Английский
Процитировано
6
Sustainability, Год журнала: 2025, Номер 17(5), С. 2286 - 2286
Опубликована: Март 6, 2025
Effective tunnel construction and demolition (C&D) waste management is a critical issue in the context of sustainable development, C&D measures guided by 3R principles (Reduce, Reuse, Recycle) comply with circular economy. In this study, an extended theory planned behavior model based on existing literature was proposed to identify drivers managers’ intention implement effective measures; then, respondents were classified into four groups according personality traits explore effects profile heterogeneity relationships between psychological behaviors. The results show that all TPB constructs, policies, environmental concern are significant predictors manage properly. Then, considerable variance driving various across different witnessed. For positive temperate participants, subjective norms policies most factors. However, PBC stronger relationship conservative introverted participants’ intentions adopt measures. findings beneficial developing corresponding promote management.
Язык: Английский
Процитировано
0
Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Апрель 3, 2025
Abstract During the construction of TBM tunnels, a substantial quantity rock debris is generated, leading to significant land occupation and environmental pollution. Recycling into materials other resources emerges as viable solution these problems. To realize continuous classified storage disposal tunnel debris, this research explores four-level processing network, establishes an objective function for evaluating recycling value during tunneling, grades by calculating weight similarity their performance indicators (uniaxial compressive strength, content acicular flattened particles, mud content, crushing index) through TOPSIS method. Through correlation analysis, we identify five key characteristics, i.e. cutterhead torque, tool penetration, thrust, advancing rate, support shoe pump pressure, conduct real-time perception level debris. Leveraging comprehensive database that encompasses both tunneling parameters, models are constructed using different machine learning algorithms. After Bayesian hyperparameter optimization, based on CART, SVM, KNN, ANN demonstrate accuracies 67.5%, 80.0%, 82.5%, 83.8% respectively. Notably, optimization significantly enhances accuracy model. When applying optimized ANN-based grade model engineering, tested rate stands at 83.3%, demonstrating its effectiveness potential practical applications. This approach provides valuable guidance graded efficient helps alleviate pollution problem.
Язык: Английский
Процитировано
0
Construction and Building Materials, Год журнала: 2024, Номер 444, С. 137852 - 137852
Опубликована: Авг. 10, 2024
Язык: Английский
Процитировано
3
Journal of Building Engineering, Год журнала: 2024, Номер 98, С. 111068 - 111068
Опубликована: Окт. 15, 2024
Язык: Английский
Процитировано
2
Construction and Building Materials, Год журнала: 2024, Номер 451, С. 138781 - 138781
Опубликована: Окт. 18, 2024
Язык: Английский
Процитировано
1