As industrial development and population growth continue, water pollution has become increasingly severe, particularly in rapidly industrializing regions like the area surrounding the Yopurga landfill. Ensuring water resource safety and environmental protection necessitates effective water quality monitoring and assessment. This paper explores the application of advanced machine learning technologies and the Water Quality Index (WQI) model as a comprehensive method for accurately assessing groundwater quality near the Yopurga landfill. The methodology involves selecting water quality indicators based on available data and the hydrochemical characteristics of the study area, comparing the performance of Decision Trees, Random Forest, and Xgboost algorithms in predicting water quality, and identifying the optimal algorithm to determine indicator weights. Indicators are scored using appropriate sub-index (SI) functions, and six different aggregation functions are compared to find the most suitable one. The study reveals that the Xgboost model surpasses Decision Trees and Random Forest models in water quality prediction. The top three indicator weights identified are pH, Manganese (Mn), and Nickel (Ni). The SWM model, with a 0% overestimation eclipsing rate and a 34% underestimation eclipsing rate, is chosen as the most appropriate WQI model for evaluating groundwater quality at the Yopurga landfill. According to the WQI results from the SWM aggregation function, the overall water quality in the area ranges from moderately polluted to slightly polluted. These assessment results provide a scientific basis for regional water environment protection.

The effect of aftershocks on the fragility of single-story masonry structures is investigated using probabilistic seismic demand analysis Finite element models of an unreinforced masonry (URM) structure and a confined masonry (CM) structure are established and their seismic response characteristics when subjected to mainshock, aftershock, and the mainshock-aftershock sequence are then comparatively investigated. The effects of aftershocks and the use of confining members on the seismic response are studied. Probabilistic seismic demand models of the structures are built, and fragility curves under various conditions are derived to investigate the effect of aftershocks on structural fragility. The maximum roof displacement and maximum inter-story drift ratio are lower in the confined masonry model than in the unreinforced masonry model; additionally, the probability of exceedance (PE) values of each damage limit state reduced, and those of the mainshock-damaged models subjected to aftershock significantly increase compared to those directly subjected to a same-intensity aftershock. The probability of severe damage or collapse compared with the mainshock-damaged CM model is greater than when each is subjected to a same intensity aftershock. The use of confining members benefits aftershock resistance and reduces the failure probability of the mainshock-damaged structure. The PE values significantly increase with the aftershock scaling factor δ. Therefore, the effect of aftershocks should be considered in the seismic design and analysis of masonry structures.

This paper presents a comprehensive assessment method of the fragility of low‐rise cold‐formed steel (CFS) framed wall structures subjected to wind hazards considering the fragility of both the main structure and the cladding system. The effects of wind directions on the fragility of CFS framed wall structures were also studied. For the main structure, the fragility curve is established using the maximum interstory drift ratio (ISDR_max) as the performance index for assessing the wind fragility of the structure. For the cladding system, the probabilistic models of the wind load and the cladding component resistance are established based on Monte Carlo simulation, and then methods for the fragility assessment of single cladding components and the cladding system under wind hazards considering the influence of the number and arrangement of the cladding components are proposed. The results indicated that, under strong wind, the cladding system may be damaged before the required wind resistance capacity of the main structure is exhausted. In particular, the roof sheathing is the most prone to damage, followed by the stud wall. That is, before the main structure is severely damaged or collapses, the cladding systems may be severely damaged, rendering the structure unusable. Therefore, the comprehensive assessment of the fragility of this type of structure subjected to wind hazard considering the fragility of both the main structure and the cladding system is more accurate. This study is of great significance for the improvement of the wind resistance performance of CFS structures and the popularization of this type of structure.

Lightweight steel structures are commonly used in industrial facilities due to their low weight, high strength, and excellent performance. The design of these structures for cold regions not only has to consider the effects of earthquakes but also the negative impact of snow loads. Industrial structures often have long spans, and the effects of uneven snow loads cannot be underestimated. However, relatively few studies have focused on the performance of lightweight steel structures under the influence of combined earthquake and non-uniform snow loads. Therefore, this study assessed the seismic fragility of a typical single-span, double-sloped lightweight steel factory under combined earthquake and non-uniform snow loads using incremental dynamic analysis. Non-uniform snow loads, as compared to uniform snow loads, substantially increase the structural displacement responses, thereby increasing the structural failure risk. The improved structural design developed in this study effectively decreases the impact of adverse loading scenarios and enhances the multi-hazard resilience of the structure. Accordingly, these results can serve as an important theoretical guide for enhancing the safety of lightweight steel structures subjected to multiple hazards in cold regions.