1616 papers
This paper proposes an AI-driven framework that integrates GIS, weather data, and distance relay measurements with modified Long Short-Term Memory (LSTM) neural networks to classify overhead line faults with 83.4% accuracy, thereby enhancing Transmission System Operator asset management and energy system reliability.
This method article proposes a low-emission, AI-driven digital-twin framework integrating composite binders, machine-learning forecasting, and remote sensing to enable scalable co-solidification of multi-contaminant sediments in Peruvian Andean rivers and lagoons ahead of anticipated El Niño events, drawing on documented Chinese remediation practices while identifying pilot-scale validation as the critical next step.
This paper presents a microscopic panoramic imaging system that utilizes visual servoing to control pan-tilt movement and employs image stitching techniques to generate high-resolution panoramic views (15488 × 15456) from low-resolution (640 × 480) inputs, thereby overcoming the limited field of view inherent in traditional microscopy.
This paper proposes a fairness-constrained potential game mechanism for decentralized microgrid energy trading that embeds capacity-weighted fairness regularization into prosumer utility functions to guarantee Nash equilibrium existence and convergence while effectively protecting disadvantaged participants through an adjustable efficiency-fairness tradeoff.
This paper introduces an uncertainty-aware, closed-loop computational framework that maps SEM profiles to electrical responses by propagating boundary distributions through coupled process and device TCAD simulations, thereby improving electrical prediction accuracy and annotation efficiency compared to conventional hard-boundary calibration.
This paper proposes a bi-level optimization model that simultaneously determines the optimal sizing of PV and ESS systems within the Milad Tower Complex microgrid by integrating load management and carbon trading mechanisms to minimize costs, maximize profits, and enhance grid stability.
This study employs a fixed-seed Monte Carlo analysis to demonstrate that rated load alone is insufficient for ensuring the overturning stability of compact construction vehicles with crane booms, revealing that factors like wind, slope, and deck mass critically influence safety margins and necessitate specific azimuth restrictions or design modifications for longer-reach configurations.
This paper presents a theoretical analysis of a 10 nm gate-all-around carbon nanotube field-effect transistor functionalized with various biomolecules, demonstrating that glucose- and biotin-modified devices significantly reduce OFF currents while a hemoglobin-fragment-modified device achieves superior ON currents and sensitivity, thereby establishing a high-performance, label-free platform for next-generation implantable biosensors.
This study investigates the insulation failure and partial discharge mechanisms of biaxially oriented polypropylene (BOPP) films under complex electro-thermal stresses simulating ultra-high-voltage converter station conditions, revealing that superimposed harmonics and elevated temperatures generally degrade breakdown and partial discharge inception strengths while altering discharge patterns.
This study presents a unified, physics-based framework for modeling fracture capillary pressure and relative permeability using a single interpretable aperture parameter, eliminating the need for empirical fitting while offering a robust, simulator-ready alternative to traditional oversimplified assumptions and costly experiments.