The substitution of cement with coal gangue powder (CGP) offers significant potential for energy conservation, emission reduction, and environmental sustainability. To optimize the mechanical properties of coal gangue cement paste, a modified response surface methodology (RSM) model was developed, incorporating grinding parameters as independent variables and compressive strength as the response variable. The feasibility of the model was validated through coefficient estimation, variance analysis, and fitting statistics. The analysis revealed that milling speed was the most significant factor influencing the compressive strength at 20% substitution, while the ball-to-material ratio predominantly affected the strength at 50% substitution. An increase in milling speed was observed to significantly broaden the particle size distribution, with larger particles (15.14$\mathrm{\mu m}$ to 275.42$\mathrm{\mu m}$) serving primarily as micro-aggregates, and smaller particles (0.32$\mathrm{\mu m}$ to 15.14$\mathrm{\mu m}$) functioning as fillers within ultra-fine pores. Scanning Electron Microscopy (SEM) further corroborated these findings. Numerical optimization based on the RSM model identified optimal grinding parameters: a ball-to-material ratio of 1.40, a milling time of 0.843 hours, and a milling speed of 300 rpm. These parameters are recommended to achieve the target compressive strengths of 25 MPa at 20% CGP substitution and 10 MPa at 50% CGP substitution. This study provides a cost-effective and feasible approach for the utilization of coal gangue in cementitious materials, contributing to the advancement of sustainable construction practices.

Rainwater harvesting (RH) techniques, specifically the implementation of Bio-pore Infiltration Holes (BIH), have been investigated as cost-effective and practical methods for managing surface runoff and mitigating flood risks. This study aimed to evaluate the infiltration rates of BIH in secondary forest and agricultural moorland areas, providing a basis for sustainable soil and water conservation practices. A survey methodology was employed to assess infiltration rates using the Horton equation model applied to circular holes with a depth of 50 cm. Soil samples were collected from the vicinity of the BIH for analysis of physical properties at the Soil Science Laboratory, Faculty of Agriculture, Tadulako University. A 4-inch diameter PVC pipe, inserted 30 cm into the soil, was used to measure water infiltration, with water levels recorded up to 60 cm. The findings indicated that infiltration rates in both secondary forest and agricultural lands were moderate. The physical characteristics of the soil, including its texture and organic carbon content, were identified as suboptimal, which constrained the efficiency of waste absorption through the infiltration process. The soil texture in both land types was classified as sandy according to USDA standards, making it susceptible to erosion, which is directly related to the infiltration capacity and the potential for soil transport during erosion events. The carbon organic content was relatively low, at 2.50% in secondary forest land and 1.17% in agricultural land, indicating medium-level criteria for organic content. To enhance soil conservation and flood mitigation, it is recommended that efforts be made to increase organic material content through compost application and post-flood land rehabilitation. Expanding the use of BIH in high-risk flood areas is advocated to effectively reduce and control surface runoff.

To address the lack of clear formulae for calculating the circumferential stress in steel epoxy sleeve-reinforced pipelines under internal pressure, this study constructs a mechanical model based on the specific stress characteristics of these pipelines. Using stress solution methods and deformation compatibility relationships, theoretical formulas for circumferential stress in the pipeline layer, epoxy resin layer, and sleeve layer under internal pressure are derived. The theoretical formulas are validated through numerical simulations using ANSYS software, which includes models with and without flanges. The calculations were performed for common pipelines with outer diameters of 219mm, 660mm, and 1219mm. The results show that the discrepancies between theoretical and numerical solutions of circumferential stress in all layers of both model types are within 10%. Specifically, the circumferential stress in the pipeline layer of the flanged model is lower than that of the non-flanged model and also lower than the theoretical values. The error between the theoretical and numerical solutions for pipelines of different diameters does not exceed 10%, confirming the validity and applicability of the theoretical formulas. This suggests that using the simplified mechanical model for circumferential stress calculations ensures a conservative approach for the structural assessment of pipelines. The formulas provided herein can serve as a reference for the design and evaluation of steel epoxy sleeve-reinforced pipelines under internal pressure.

Recent observations of global warming phenomena have necessitated the evaluation of the service performance of asphalt pavements, which is substantially influenced by surface temperature levels. This study employed twelve distinct machine learning algorithms—K-neighbors, linear regression, multi-layer perceptron, lasso, ridge, support vector regression, decision tree, AdaBoost, random forest, extra tree, gradient boosting, and XGBoost—to predict the surface temperature of asphalt pavements. Data were sourced from the Road Weather Information System of Iowa State University, comprising 12,581 data points including air temperature, dew point temperature, wind speed, wind direction, wind gust, and pavement sensor temperature. These data were segmented into training (80%) and testing (20%) datasets. Analysis of model outcomes indicated that the Extra Tree algorithm was superior, exhibiting the highest R$^2$ value of 0.95, whereas the Support Vector Regression algorithm recorded the lowest, with an R$^2$ value of 0.70. Furthermore, Shapley Additive Explanations were utilized to interpret model results, providing insights into the contributions of various predictors to model outcomes. The findings affirm that machine learning algorithms are effective for predicting asphalt pavement surface temperatures, thereby supporting pavement management systems in adapting to changing environmental conditions.

Pile foundations, as one of the main foundation forms for bridges and offshore wind power structures, are prone to scour pits around them under the long-term action of water flow, leading to a decrease in bearing capacity. Traditional pile foundation scour prevention measures, such as the construction of protective jetties and riprap protection, are cumbersome and ineffective. Considering the inevitable generation of a large amount of spoil in engineering construction, by optimizing the performance of cement-stabilized soil, it is expected to use the discarded spoil for pile foundation scour management. Aiming at the underwater anti-dispersive cement-stabilized soil based on kaolin, 67 sets of single-factor rotation experiments were carried out to study the effects of changes in the addition of anti-dispersive agents ethylene-vinyl acetate copolymer (EVA), hydroxypropyl methylcellulose (HPMC) from 0‰ to 1‰, cement content from 8% to 14%, and water content from 1.4 to 2 times the liquid limit on the anti-dispersion performance, fluidity, and 7d and 28d unconfined compressive strength of the cement soil. The results show that the anti-dispersive agent HPMC can maximize the anti-dispersion performance of the cement soil, with the addition increased from 0‰ to 1‰, the anti-dispersion performance of the cement soil increased by 76.1%, but the fluidity decreased by 54.0%, and the strength of the 28d age cement soil increased by about 52.9%. Anti-dispersive agents can be added to quickly improve the anti-dispersion performance of the cement soil in pile foundation scour management, but attention should also be paid to its weakening effect on the fluidity of the cement soil; the increase in water content has the greatest impact on the fluidity of the cement soil, with the water content increased from 1.4 times the liquid limit to twice the liquid limit, the fluidity increased by 80.3%; the cement content increased from 8% to 14%, the unconfined compressive strength of the cement soil increased by more than double, and the anti-dispersion performance increased by 26.8%. Based on the experimental results, the recommended mix ratio of kaolin-based cement soil for pile foundation scour repair is: 0.75‰ EVA addition, 1.6 times the liquid limit water content, 10% cement content.

In response to the escalating pressures of urbanization and population growth on the ecosystems and flood risks in Bor County, Jonglei State, South Sudan, this study proposes the implementation of Sustainable Urban Drainage Systems (SUDS) as a resilience-building measure. Through the design of open drainage channels featuring non-uniform flow, inclusive of main and sub-channels alongside infiltration wells, the research aims at mitigating flooding, enhancing water quality, and fostering sustainable development within the region. The necessity for managing substantial runoff volumes has been identified, with a decade of rainfall data employed to accommodate annual variability. The evaluation of SUDS techniques to mitigate flooding entails a customized design approach, integrating cost estimation with flood mitigation strategies and the assessment of short- and long-term co-benefits. Hydrological analysis of ten years of rainfall data facilitated the sizing of channels for storm events ranging from 2 to 5 years, with precipitation intensities between 73.82 and 93.08 mm/day, resulting in the planning of open trapezoidal channels with dimensions to support 5 $m^3/s$ flows. Moreover, infiltration wells, with diameters of 2–3 meters and depths of 3-5 meters, have demonstrated potential in reducing runoff volumes by up to 70% in a 0.5-hectare modelled area. The incorporation of drop structures aims to control slopes ranging from 6-15% in channels, thereby preventing erosion for flows up to 20 $m^3/s$. The adaptability of SUDS approaches, commonly applied in developed nations, to the tropical environment of Bor is scrutinized, highlighting the necessity for localized adaptation due to data limitations and modelling simplifications. The potential barriers posed by capital costs underscore the importance of a life cycle analysis. The success of SUDS implementation in Bor County is contingent upon community engagement, ensuring acceptance and ownership. It is recommended that low-cost, simplistic pilot projects, focusing initially on rain gardens and permeable pavements, precede large-scale implementation. Through strategic planning, SUDS hold the potential to enhance climate resilience in the expanding community of Bor County. An integrated technical analysis provides actionable solutions for flood mitigation, advocating for further monitoring and community-driven initiatives to transition SUDS from concept to reality.