1593 papers
This study utilizes Taguchi-based drilling experiments and machine learning algorithms to demonstrate that feed rate is the dominant factor affecting thrust force and torque in Wood Plastic Composite drilling, with the Random Forest model emerging as the most accurate predictor for optimizing process parameters to minimize these forces.
This study designs, numerically optimizes, and fabricates a bio-inspired bouligand-structured bone scaffold composed of 90% hydroxyapatite, 9.9% barium titanate, and 0.1% graphene with 70% infill, demonstrating its potential to achieve an optimal balance of mechanical strength, piezoelectricity, and permeability for bone tissue engineering applications.
This documentary and comparative-analytical study synthesizes existing literature on 3D-printed auxetic resonant metamaterials to develop a comprehensive technology-transfer roadmap for adapting South Africa's deep-mining seismic experience to mitigate shock waves in Peru's tunnels, while identifying critical low-frequency attenuation gaps for future prototype development.
This paper proposes a distributed optimization-based framework for the coordinated planning of transmission and energy storage in multi-regional power systems, which effectively reduces total annual costs and improves renewable energy accommodation compared to independent or single-component planning strategies.
This study utilizes a 3D Computational Fluid Dynamics reconstruction with the rhoCentralFoam solver to analyze the 2025 Ezeiza explosion, demonstrating that local wave-structure interactions like channeling and refocusing, rather than simple stand-off distance, were the primary drivers of the observed structural damage and twisting.
This paper presents a probabilistic reliability assessment of a Cessna 172 main wing spar under uncertain aerodynamic and harmonic loads using Monte Carlo simulation, revealing that resonance significantly impacts failure probability and identifying the second and third vibration modes as the most critical excitation bands.
This study establishes a rigorous verification and statistical validation workflow for mesh-based A356 aluminum gravity casting simulations, demonstrating that a converged finite-volume model accurately predicts filling and solidification behaviors while confirming pouring temperature as the dominant factor influencing porosity through quantitative correlation with experimental Density Index measurements.
This paper proposes a reliability-gated GRU-based secure control framework that effectively detects false data injection attacks and compensates for corrupted sensor measurements in nonlinear floating offshore wind turbines, significantly improving rotor speed and power regulation accuracy while maintaining platform stability.
This study introduces a physics-guided transfer learning framework based on a stochastic differential equation network that leverages radiative transfer simulations and collocated MODIS-CALIPSO data to achieve high-accuracy, uncertainty-quantified discrimination of clouds, dust aerosols, and bright surfaces in passive satellite remote sensing, significantly outperforming existing benchmark methods.
This study experimentally compares two refrigerant-side heat recovery strategies in a packaged air-conditioning unit, demonstrating that both open-loop steady-state and closed-loop transient configurations effectively utilize waste heat to produce domestic hot water while significantly improving overall system efficiency and cooling performance.