The UC Berkeley Center for Smart Infrastructure (CSI) hosted a visit by the American Water Works Association (AWWA) and EBMUD on April 17, 2025. David LaFrance, CEO of AWWA, interviewed CSI director Kenichi Soga about the role of research to… Read More »AWWA and EBMUD visit CSI Lab
A new paper introduces a comprehensive approach to evaluate the effects of earthquakes on transportation systems, focusing on bridge fragility, traffic disruptions, and economic losses. By integrating image-based bridge fragility models with regional-scale traffic simulations, the method provides a fine-grained… Read More »Granular framework for modeling the capacity loss and recovery of regional transportation networks under seismic hazards: A case study on the Port of Los Angeles
Researchers have conducted a comprehensive study to assess the performance of large-diameter segmented pipelines under transverse loading, focusing on vulnerabilities in connection joints during natural hazard events like earthquakes. Using a 4-point bending test on a 48-inch HDSS ductile iron… Read More »Assessment of Large-Diameter Ductile Iron Pipeline Joint to Transverse Loading using Distributed Fiber Optic Sensing
Researchers have developed innovative stabilization strategies for modeling incompressible fluid flow using the Material Point Method (MPM). The proposed mixed implicit MPM formulation employs a monolithic displacement–pressure approach inspired by Finite Element Methods (FEM), bypassing the need for free-surface detection… Read More »Stabilized mixed material point method for incompressible fluid flow analysis
A new study highlights the potential downsides of fuel-sensitive eco-routing, a strategy designed to reduce traffic-related environmental impacts. While eco-routing prioritizes fuel-efficient routes over faster highways, simulations for the San Francisco Bay Area and Tokyo reveal that it can increase… Read More »Spatial system perspective of understanding “fuel-sensitive routes” using regional-scale case studies
A novel crack analysis method improves the capabilities of Brillouin scattering-based distributed fiber optic sensing (Brillouin-DFOS) for structural health monitoring. Traditional Brillouin-DFOS systems struggle to detect highly localized strain from sub-millimeter cracks due to their decimeter-scale spatial resolution. The proposed… Read More »Distributed fiber optic strain sensing for crack detection with Brillouin shift spectrum back analysis
A new modification to the virtual stress boundary (VSB) method enhances the Material Point Method (MPM), a popular tool for simulating large deformations. The hybrid Eulerian–Lagrangian nature of MPM often leads to challenges in applying nonconforming boundary conditions, such as… Read More »The virtual stress boundary method to impose nonconforming Neumann boundary conditions in the material point method
Researchers have developed a fast and accurate model to improve Aquifer Thermal Energy Storage (ATES) systems in buildings, helping to balance seasonal energy demand and supply. The model uses temperature response functions and machine learning to predict thermal changes in… Read More »Machine-learning-assisted long-term G functions for bidirectional aquifer thermal energy storage system operation
CSI Researchers have successfully demonstrated the application of fiber optic strain sensing for structural health monitoring (SHM) of offshore wind turbines. In a full-scale test on UC Berkeley’s shaking table, two Distributed Fiber Optic Sensing (DFOS) technologies—Optical Frequency-Domain Reflectometry (OFDR)… Read More »Structural health monitoring of offshore wind turbines using distributed acoustic sensing (DAS)
CSI Researchers have developed a groundbreaking surrogate model to identify critical bridges in traffic networks during earthquakes, significantly accelerating seismic risk assessments. The model eliminates the need for time-intensive traffic simulations by using Markov random walk and random forest techniques,… Read More »Surrogate modeling for identifying critical bridges in traffic networks under earthquake conditions