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RISCrack Detection and Segmentation Using Deep Learning with 3D Reality Mesh Model for Quantitative Assessment and Integrated Visualization
Publisher: ASCE
Abstract: Crack detection has been an active research topic for civil infrastructure inspection. Over the last few years, many research efforts have focused on applying deep learning-based techniques to automatically detect cracks ...
Semantic Deep Learning Integrated with RGB Feature-Based Rule Optimization for Facility Surface Corrosion Detection and Evaluation
Publisher: ASCE
Abstract: Over the last few years, convolutional neural networks (CNNs) have been applied to detect corrosion in images. Unfortunately, the corrosion is detected in bounding boxes, without precisely segmenting the corrosion elements ...
Detecting and Geolocating City-Scale Soft-Story Buildings by Deep Machine Learning for Urban Seismic Resilience
Publisher: ASCE
Abstract: Seismic resilience is of great concern and vital importance for cities in earthquake zones. It is not only desirable but also mandatory for the cities to prepare an emergency response plan for possible seismic events. One ...
Daily Model Calibration with Water Loss Estimation and Localization Using Continuous Monitoring Data in Water Distribution Networks
Publisher: ASCE
Abstract: Due to the increasing deployment of sensors in water distribution networks (WDNs) for continuous monitoring, hydrodynamic data are readily available for engineers to improve the daily operations of WDNs. In collaboration ...
Generalized Acoustic Data Analysis Framework for Leakage Detection and Localization in Field Operational Water Distribution Networks
Publisher: ASCE
Abstract: Detecting and localizing leakages in underground water pipelines continue to be challenging in large-scale water distribution networks (WDNs) having a low density of acoustic sensors per unit pipeline. Many previous acoustic ...
Pressure-Based Demand Aggregation and Calibration of Normal and Abnormal Diurnal Patterns for Smart Water Grid in Near Real-Time
Publisher: ASCE
Abstract: An adequately calibrated hydraulic model is critically to the water distribution digital twin, which requires accurate representation of a water distribution network (WDN) in near real-time. It is thus imperative to construct ...
Near Real-Time Anomaly Event Localization by Pressure Drop Interpolation, Clustering, and Parallel Optimization of Hydraulic Model Calibration
Publisher: American Society of Civil Engineers
Abstract: Localization of anomaly events in near real-time (NRT) in water distribution networks is compelling but challenging for water utilities. This paper presents an integrated approach using both data-driven and hydraulic ...