JULY 11, 2023 Journal Article Analyzing At-Scale Distribution Grid Response to Extreme Temperatures ( Read More )
JULY 11, 2023 Conference Paper FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix ( Read More )
JULY 11, 2023 Journal Article Distributed Ledger Technology for Fault Tolerant Distribution Grid Operations ( Read More )
JULY 7, 2023 Journal Article Enabling Site-Specific Well Leakage Risk Estimation During Geologic Carbon Sequestration Using a Modular Deep-Learning-Based Wellbore Leakage Model ( Read More )
JULY 7, 2023 Conference Paper Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles ( Read More )
JULY 7, 2023 Conference Paper Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training ( Read More )
JULY 7, 2023 Journal Article Preventative studies should begin now for detecting AI-generated microscopy images ( Read More )
JULY 1, 2023 Report Limitations in Advanced Measurement Systems: An Overview for Power Systems ( Read More )
JUNE 30, 2023 Journal Article A Multifidelity Deep Operator Network Approach to Closure for Multiscale Systems ( Read More )
JUNE 29, 2023 Report Smart Contract Architectures and Templates for Blockchain-based Energy Markets (V1.0) ( Read More )
JUNE 29, 2023 Report High Value Opportunities to Advance Automation in Electric Grid Control Rooms ( Read More )
JUNE 29, 2023 Report Valuing Demand Flexibility During a Grid Disturbance: A Granular Approach to Resilience Valuation ( Read More )
JUNE 28, 2023 Journal Article CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems ( Read More )
JUNE 23, 2023 Conference Paper Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts ( Read More )
JUNE 23, 2023 Journal Article Sensitivity of the pseudo-global warming method under flood conditions: A case study from the Northeastern U.S. ( Read More )
JUNE 23, 2023 Conference Paper Leveraging High-Fidelity Datasets for Machine Learning-based Anomaly Detection in Smart Grids ( Read More )