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Credibly assessing the resilience of energy infrastructure in the face of natural disasters is a salient concern facing researchers, government officials, and community members. Here, we explore the influence of the spatial distribution of…
Energy conservation in buildings is a paramount concern to combat greenhouse gas emissions and combat climate change. The efficient management of room occupancy, involving actions like lighting control and climate adjustment, is a pivotal…
Surface water quality has a direct impact on public health, ecosystems, and agriculture, in addition to being an important indicator of the overall health of the environment. California's diverse climate, extensive coastline, and varied…
In this work, a revised formulation of Chance-Constrained (CC) Model Predictive Control (MPC) is presented. The focus of this work is on the mathematical formulation of the revised CC-MPC, and the reason behind the need for its revision.…
Wildfires pose a significant threat to ecosystems, wildlife, and human communities, leading to habitat destruction, pollutant emissions, and biodiversity loss. Accurate wildfire risk prediction is crucial for mitigating these impacts and…
The increasing recognition of the association between adverse human health conditions and many environmental substances as well as processes has led to the need to monitor them. An important problem that arises in environmental statistics…
To date, the prospect of using real-time hybrid simulation (RTHS) to study the effects of long-term or 'wear-and-tear' loads, such as exposure to harmful environmental conditions or fatigue, has remained underexplored. This study presents a…
To obtain the accurate transient states of the big scale natural gas pipeline networks under the bad data and non-zero mean noises conditions, a robust Kalman filter-based dynamic state estimation method is proposed using the linearized gas…
Natural gas pipeline leaks pose severe risks, leading to substantial economic losses and potential hazards to human safety. In this study, we develop an accurate model for the early prediction of pipeline leaks. To the best of our…
The quality of air is closely linked with the life quality of humans, plantations, and wildlife. It needs to be monitored and preserved continuously. Transportations, industries, construction sites, generators, fireworks, and waste burning…
This study presents a machine learning framework for forecasting short-term faults in industrial centrifugal pumps using real-time sensor data. The approach aims to predict {EarlyWarning} conditions 5, 15, and 30 minutes in advance based on…
Coating chambers create thin layers that improve the mechanical and optical surface properties in jewelry production using physical vapor deposition. In such a process, evaporated material condensates on the walls of such chambers and, over…
Municipal Solid Waste systems have important economic, social, and environmental impacts for society. Within the diverse stages of the Municipal Solid Waste reverse logistic chain, the waste bin location problem consists in properly…
We design statistical hypothesis tests for performing leak detection in water pipeline channels. By applying an appropriate model for signal propagation, we show that the detection problem becomes one of distinguishing signal from noise,…
Pavement deterioration modeling is important in providing information regarding the future state of the road network and in determining the needs of preventive maintenance or rehabilitation treatments. This research incorporated spatial…
Water infrastructure in the United States is beginning to show its age, particularly through water main breaks. Main breaks cause major disruptions in everyday life for residents and businesses. Water main failures in Syracuse, N.Y. (as in…
The safety and resilience of civil infrastructure systems are increasingly threatened by compounded risks from various hazard events and structural deterioration due to environmental stressors. This study presents a comprehensive…
The effectiveness of the machine learning methods for real-world tasks depends on the proper structure of the modeling pipeline. The proposed approach is aimed to automate the design of composite machine learning pipelines, which is…
Urban rivers provide a water environment that influences residential living. River surface monitoring has become crucial for making decisions about where to prioritize cleaning and when to automatically start the cleaning treatment. We…
The resilience of electric power grids is threatened by natural hazards. Climate-related hazards are becoming more frequent and intense due to climate change. Statistical analyses clearly demonstrate a rise in the number of incidents (power…