1616 papers
This study develops a reduced-order nonlinear model incorporating delayed memory and friction dynamics to explain how TBM advance rates and cumulative rock weakening govern the transition between stable, delayed clustered, and impulsive instability regimes during metro tunnel excavation in jointed rock masses.
This paper presents an improved switched-inductor-capacitor Z-source inverter (ISLC-ZSI) that achieves enhanced boost capability with reduced voltage stress and continuous input current, validated through theoretical analysis, simulation, and experimental results for low-voltage renewable energy applications.
This paper demonstrates the feasibility of using a one-dimensional Convolutional Neural Network to accurately infer key dynamic rupture parameters from source time functions by training on a large-scale synthetic dataset, thereby providing a reproducible benchmark for machine learning applications in seismic inversion.
This study demonstrates that an optimized transcritical R744 heat pump system with a parallel gas-cooler layout and decentralized PI control offers a reliable, environmentally friendly, and energy-efficient thermal management solution for zero-emission electric ferries, outperforming standard R410A systems across a wide range of operating temperatures.
This study proposes an interpretable, physics-informed machine learning framework that combines XGBoost regression with a logarithmic transformation to derive a highly accurate and transparent power-law equation for predicting the punching shear strength of reinforced concrete flat slabs, significantly outperforming conventional ACI 318-19 provisions while maintaining practical usability for structural engineers.
This paper presents the development and empirical validation of the P2P-Ironing platform, a hybrid cyber-physical marketplace that successfully mitigates Web3 operational friction and stakeholder distrust through a decoupled architecture and hardware-integrated smart contracts, thereby demonstrating high software quality and user acceptance for decarbonizing maritime shore-to-ship power.
This paper presents a finite element analysis demonstrating that topology-optimized steel connectors manufactured via Wire-and-Arc Additive Manufacturing (WAAM) offer improved load transfer efficiency and design flexibility compared to conventional welded connections, despite exhibiting different stress gradients and localized plastic deformation.
This study demonstrates that a biodegradable Mg-Ag-Mn-Zr alloy exhibits excellent wear resistance and mechanical stability for orthopedic implants, with its tribological performance effectively characterized and predicted using statistical and machine learning models that identify applied load as the dominant factor influencing wear and friction.
This study presents an object-level framework utilizing bitemporal Google Earth imagery and a hybrid-trained YOLOv12n detector to automatically screen candidate building losses following the 2023 Türkiye earthquakes, demonstrating a scalable approach for preliminary post-disaster assessment that operates independently of auxiliary geospatial datasets like building footprints or LiDAR.
This paper proposes a dual-IRS-assisted NOMA system for underwater visible light communication, deriving closed-form performance metrics under turbulent channels modeled by the Exponential Generalized Gamma distribution and validating the approach through analytical and simulation results.