This study, based on the context of rainstorm and flood disasters, explored the coupling, coordination, and decoupling between humans and the built environment. Combining the coupling coordination model with the Tapio decoupling model, the coupling situation in 16 prefecture-level cities in Anhui province from 2009 to 2020 was analyzed. A random forest method combined with recursive feature elimination was used to identify key driving factors. Constraint line extraction and elasticity analysis were used to determine the response and threshold of the coupling coordination to these driving factors. The results showed an overall upward trend in the coupling coordination of the 16 prefecture-level cities, and in most years, the decoupling between humans and the built environment exhibited varying degrees of coupling intensity. Using the decoupling index (DI) of 0.8 and 1.2 as classification thresholds, the vast majority of the sample exhibited a developmental decoupling pattern, with only a few cities exhibiting a decline-type decoupling pattern in a few years, which is generally consistent with the changing trend of the coupling coordination. GDP, urbanization rate, number of people with college or higher education per 100,000 people, economic losses from flooding, population affected by floods, length of drainage pipes, registered urban unemployment rate, and number of medical institutions are important drivers of changes in the coupling coordination degree. This study provides important insights into the relationship between people and the built environment in the context of heavy rain and flooding, and offers valuable reference and guidance for research and practice in related fields.

Valve internal leakage in thermal power stations exhibits a strong concealed nature. If it cannot be discovered and predicted of development trend in time, it will affect the safe and economical operation of plant equipment. This paper proposed an intelligent identification method for valve internal leakage that integrated an Improved Kepler Optimization Algorithm (IKOA) with Support Vector Regression (SVR). The Kepler Optimization Algorithm (KOA) was improved using the Sobol sequence and an adaptive Gaussian mutation strategy to achieve self-optimization of the key parameters in the SVR model. A multi-step sliding cross-validation method was employed to train the model, ultimately yielding the IKOA-SVR intelligent identification model for valve internal leakage quantification. Taking the main steam drain pipe valve as an example, a simulation case validation was carried out. The calculation example used Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and determination coefficient (R2) as performance evaluation metrics, and compared and analyzed the training and testing dataset using IKOA-SVR, KOA-SVR, Particle Swarm Optimization (PSO)-SVR, Random Search (RS)-SVR, Grid Search (GS)-SVR, and Bayesian Optimization (BO)-SVR methods, respectively. For the testing dataset, the MSE of IKOA-SVR is 0.65, RMSE is 0.81, MAE is 0.49, and MAPE is 0.0043, with the smallest values among the six methods. The R2 of IKOA-SVR is 0.9998, with the largest value among the six methods. It indicated that IKOA-SVR can effectively solve problems such as getting stuck in local optima and overfitting during the optimization process. An Out-Of-Distribution (OOD) test was conducted for two scenarios: noise injection and Region-Holdout. The identification performance of all six methods decreased, with IKOA-SVR showing the smallest performance decline. The results show that IKOA-SVR has the strongest generalization ability and robustness, the best effect in improving fitting ability, the smallest identification error, the highest identification accuracy, and results closer to the actual value. The method presented in this paper provides an effective approach to solve the problem of intelligent identification of valve internal leakage in thermal power station.

Icing modeling of drainage pipes of road slope in cold regions

Response characteristics and influence mechanism of lining structures under dual-indices blockage of longitudinal drainage pipe in karst tunnels

Detection and Effectiveness of Improved Drainage Pipe Defects–Based Semantic Segmentation Labeling Methods

Combining subsurface pipe drainage with organic fertilizer amelioration facilitated bacterial community succession and functional diversification in coastal saline-alkali soils

Innovations in modern building design encourage the integration of utility systems, such as rainwater drainage, into structural elements to improve space efficiency and aesthetics. This study aims to analyze the effect of embedding PVC (pralon) pipes as internal drainage channels on the strength and efficiency of reinforced concrete columns. A numerical analysis was carried out using the spColumn software on columns with dimensions of 350 × 600 mm, with variations in the number of 4-inch pipes (zero, one, two, and three). The results show that installing one, two, and three pipes gradually reduced the maximum compressive capacity of the column from 4100 kN to 3930 kN, 3790 kN, and 3650 kN, respectively. Despite this reduction, all column configurations were proven to be safe for sustaining the planned ultimate load of 368.72 kN. Interestingly, the structural–material efficiency of the column increased by up to 4.2% in the three-pipe configuration, as the reduction in concrete volume outweighed the decrease in capacity. It is concluded that the integration of PVC drainage pipes into columns offers a structurally safe, functional, and more material-efficient solution. These findings highlight the potential to reduce the need for external drainage channels, thereby improving spatial efficiency and lowering construction costs. Furthermore, integrating the drainage system into columns allows for cleaner, more minimalist façade designs without conventional piping interruptions, ultimately enhancing the aesthetic value and architectural competitiveness of the building.

Correction: Methods to monitor the defects of the drainage pipe network: a review

This research aims to give a general view of a thorough analysis of the while building road embankments on soft ground and suggests a course for future development Roadbed construction is an important part of the road project, and the quality of the subgrade is directly related to the quality of the entire road project. The subgrade works include the subgrade itself, related earth (stone), small bridges and culverts along the line, retaining walls, shoulders, slopes, drainage pipes, and other projects. Depending on whether the roadbed is located in a cut or in an embankment, it has its own specific aspects and a different structure. There is a discussion of frequently employed soft-ground improvement methods. In many parts of the world, particularly along deltas and coastal regions, there exist thick deposits of soft ground, such as soft marine and estuary clay. These soils have bad geotechnical characteristics, such as a high natural moisture content that is almost liquid, a high compressibility, and low shear strength. Embankments on such soft terrain, which are frequently used for highway building, are frequently impacted by edge stability and long-term settlement. The approaches, findings, and historical cases that contribute to the stability of the road embankment are examined. The research demonstrates that the construction of the road embankment is complicated by settlement, slope stability, and soil-bearing capacity. Geometric data is also discovered to be a crucial element in embankment design. This study's findings can be utilized to create design guidance systems, numerical modeling, and to provide an overview and background knowledge to other researchers who are conducting or plan to conduct research in this area. Understanding the behavior of these components is essential for producing a successful embankment. Finally, research directions for the future are related to artificial intelligence-based predictions of the elements that influence the stability of road embankments.

Rapid urbanization and frequent extreme events have made urban flooding a growing threat to residents. This issue is acute in old urban districts, where extremely limited land resources, outdated standards and poor infrastructure have led to inadequate drainage and uneven pipe settlement, heightening flood risk. This study applies InfoWorks ICM Ultimate (version 21.0.284) to simulate flooding in a typical old urban district for six return periods. A risk assessment was carried out, flood causes were analyzed, and mitigation strategies were evaluated to reduce inundation and cost. Results show that all combined schemes outperform single-measure solutions. Among them, the green roof combined with pipe optimization scheme eliminated high-risk and medium-risk areas, while reducing low-risk areas by over 78.23%. It also lowered the ponding depth at key waterlogging points by 70%, significantly improving the flood risk profile. The permeable pavement combined with pipe optimization scheme achieved similar results, reducing low-risk areas by 77.42% and completely eliminating ponding at key locations, although at a 50.8% higher cost. This study underscores the unique contribution of cost-considered gray-green infrastructure retrofitting in old urban areas characterized by land scarcity and aging pipeline networks. It provides a quantitative basis and optimization strategies for refined modeling and multi-strategy management of urban waterlogging in such regions, offering valuable references for other cities facing similar challenges. The findings hold significant implications for urban flood control planning and hydrological research, serving as an important resource for urban planners engaged in flood risk management and researchers in urban hydrology and stormwater management.

This project aims to develop a system that detects home floods using IoT, alerting residents to evacuate. In Malaysia, flooding is a common occurrence that causes damage to homes and often affects homeowners. There is a risk of electrical appliances or wires getting damaged, which raise the risk of electrocution. A flooded manhole causes the sewage/drain pipes to overflow with wastewater. This flows back into the homes, causing an increased danger of airborne diseases. Hence, a prototype monitoring and alerting system is designed and simulated in a home setting using Arduino UNO and ultrasonic sensors to mitigate floods in homes. This system alerts the residents audibly and visually to evacuate when flooding occurs. As a precaution, the electricity breaker is automatically switched off, and a solenoid valve placed in the drainage pipes, is closed to prevent worst-case scenarios. Information from the device is displayed in an app called FloodA. This system provides a clear visualisation of water levels through a mobile app interface. A notification is sent out when the flooding becomes severe, as an extra means of alerting the users. This reduces the flood risk faced by the residents. This research aligns with sustainable goals 11 (Sustainable Cities and Communities) and 13 (Climate Action).

Dual-Stress aging of UV-CIPP composites: Microbial and mechanical degradation mechanisms in corrosive environments.

In the Nordic countries, some peatlands have been drained and cultivated with grass for animal husbandry. However, there is a challenge for agronomy due to high water content and poor trafficability, while improved drainage can lead to peat degradation. On the Norwegian west coast, we studied the effects of conventional pipe drainage and peat inversion, as a new drainage method to find improved solutions for farming while minimising peat degradation. In the peat inversion method, mineral soil excavated from below the peat is used to form a 0.5–1 m layer on top of peat. Peat inversion was carried out in a 3.5 ha field which was earlier drained with subsurface pipes, while the adjacent 2.7 ha field remained with subsurface pipes placed at 8 m spacing and 1.3 m deep. On adjacent grass-cultivated peatlands we compared water table (WT), volumetric water content (VWC), soil temperature and dry matter yield (DMY) over the period 2014–2019. The mean WT was lower (p < 0.001) in the inverted field, at -93 ± 62 cm compared to -53 ± 40 cm in the pipe-drained field. In the inverted field, soils were drier and frost was observed earlier and lasted longer due to the presence of the mineral topsoil. The mean VWC at 0–5 cm depth in the pipe-drained field was 47.4 ± 16.9 % v/v, which was higher (p < 0.001) than in the inverted field where the values were 28.6 ± 10.4 and 30.9 ± 10.7 % v/v, depending on mineral soil thickness. However, there was no difference (p = 0.775) in mean soil temperature at 0–5 cm depth between inverted and pipe-drained fields. There was a significant difference (p < 0.001) between DMY data collected from 2015 to 2018 in the inverted field (11.6 ± 2.32 t ha -1 yr -1 ) and the pipe-drained field (10.4 ± 1.22 t ha -1 yr -1 ) as well as a significant interaction between rainfall and drainage type (p < 0.001). Our study indicates that peat inversion lowers the WT and VWC and increases DMY. These findings provide a first estimate on the effects of this alternative drainage option for peatland agriculture in parts of western Norway receiving high precipitation.

Enhanced removal of thioethers from stormwater pipe overflows by coagulation and oxidation treatment: Removal performance, reaction kinetics, and ecotoxicity.

Methods to monitor the defects of the drainage pipe network: a review

Ground penetrating radar (GPR), known as a powerful geophysical technique, can detect underground artificial objects in urban environments. The shape of reflected or diffracted signals in GPR data slices can exhibit their locations in 2D/3D space. Continuous wavelet transform is effectively applied in locating and highlighting anomalies in geophysical methods, such as data earthquake analysis, seismic exploration, and gravity studies, by analyzing energy spectra in the time - frequency domain. This study presents a novel approach to GPR data interpretation that integrates continuous wavelet transform with traditional processing techniques. This workflow was applied to both modelled and field data sets. In the modelled case, a circular pipe with an electrical permittivity different from its surroundings was successfully recognized in the time - frequency domain after applying continuous wavelet transform. For the real case, two 2D GPR profiles were conducted to investigate an elongated underground drainage pipe on Nguyen Van Cu Street in District 5, Ho Chi Minh City, Vietnam. 3D representation of the continuous wavelet transform output for the real data demonstrated the presence of the anomaly, characterized by strong energy amplitudes linked with reflection and diffraction events.

Hydrochemical inspection of landslide drainage structures reveals high risk for scaling processes.

A framework for creating sustainable rainwater harvesting and reuse strategies for urban landscape irrigation in a changing climate.

New Classification of Drainage Pipe Defects Based on Computer Vision and Database Building and Effect Analysis

As urban underground drainage networks age, various internal defects gradually develop in pipelines, compromising their operational efficiency. Consequently, condition assessment of drainage systems has become essential for municipal authorities. However, manual inspection methods remain prevalent due to inefficiency and subjectivity, often leading to misjudgments. To address these challenges, researchers have integrated pipeline detection technologies with machine learning and deep learning frameworks, achieving automated and efficient defect identification. This paper systematically reviews existing methodologies and research achievements in drainage pipeline defect recognition, providing a comprehensive overview of current approaches.