1639 papers
This paper presents a Y-shaped inlet square-chamber micromixer with optimized arc-shaped obstacles that significantly enhances mixing efficiency under laminar flow by inducing transverse velocity and local vortices, achieving superior performance at a 0.95 mm obstacle width and 0.15 m/s inlet velocity.
This study validates the IEC 62364:2019 model for predicting hydro-abrasive erosion in Kaplan, Francis, and Pelton turbines by demonstrating its high accuracy and reliability through strong statistical correlation with observed field and experimental data.
This study utilizes a full factorial design and second-order polynomial regression to demonstrate that optimizing the extrusion ratio to 110% and layer thickness to 0.20 mm significantly enhances the tensile and flexural strength of FDM-printed PLA, providing a validated predictive framework for manufacturing high-performance clinical devices.
This study utilizes Python-based network analytics to map Italy's sports infrastructure, revealing significant spatial disparities between well-connected metropolitan corridors and underserved rural or mountainous regions, thereby advocating for hub-and-spoke planning to enhance equitable accessibility.
This paper proposes BLGSNet, a lightweight hybrid deep learning architecture combining multi-scale 1D convolutions and BiLSTM, which achieves robust and accurate photovoltaic fault detection under noisy conditions while being validated on both standard and experimental datasets and deployed on an edge device with a real-time decision-support system.
This study combines field data from over 1,800 buildings with nonlinear dynamic analyses to demonstrate that reducing design drift limits to 1.0% significantly decreases the risk of collapse and severe damage to both structural and nonstructural components without compromising drift capacity.
This paper proposes ASD-BOD, an unsupervised framework combining Robust Principal Component Analysis and weighted cophenetic correlation-based clustering to effectively detect vibroacoustic anomalies in high-variation hydraulic machinery during End-of-Line Testing, significantly improving detection performance without requiring product-specific re-tuning.
This study experimentally demonstrates that while Selective Laser Sintering (SLS) of pure Nylon 12 yields superior tensile strength and ductility compared to its glass-fibre-reinforced counterpart, the composite offers enhanced hardness and impact resistance, revealing a distinct strength–ductility trade-off driven by processing-induced defects and interfacial bonding limitations.
This paper presents a data-driven, two-stage automated pipeline that utilizes a Random Forest regression model to predict and optimize CNC machining parameters based on historical G-code data, thereby reducing reliance on expert knowledge and improving process consistency without requiring hardware modifications.
This study demonstrates that fused filament fabrication (FFF) of rectilinear-infilled carbon-fibre-reinforced polyamide (CFPA) composites yields materials with superior thermal stability, mechanical strength, and energy absorption, making them a promising candidate for lightweight, next-generation wind turbine blades.