1641 papers
This paper proposes a robust multi-objective optimization approach using the NSGA-II algorithm to determine the optimal 3D part orientation in fused deposition modeling by balancing support area, build time, surface robustness, and surface quality under uncertainty.
This paper utilizes the Operational Transfer Path Analysis (OTPA) method to identify key vibration characteristics and transmission paths in metro trains, revealing that wheel polygonization and track irregularities primarily transmit vibrations through specific bogie components to the car body, thereby providing a foundation for structural optimization and vibration reduction.
This review article synthesizes existing research to demonstrate how specific apartment building façade features—categorized into geometry, surface properties, add-on elements, and neighborhood quality—can mitigate Urban Noise Island effects on occupants' perceptual reactions, thereby reducing reliance on air conditioning and lowering overall energy consumption.
This study demonstrates that while sunflower oil-based MQL significantly improves surface finish during prolonged milling of Ti6Al4V ELI, the addition of MoS₂ nanoparticles primarily enhances tool preservation by suppressing built-up edge and delamination rather than further reducing surface roughness.
This paper presents a deterministic, slice-supervised method using differentiable 3D Gaussian ellipsoids for one-to-one digital rock reconstruction, demonstrating that while the approach achieves macroscopic permeability fidelity comparable to the original volume, it often fails to preserve detailed pore morphology and that high pixel-level image similarity does not guarantee accurate transport property reproduction.
This study combines experimental testing and a novel 3D XFEM-CZM numerical model to demonstrate that single-stepped-lap joints (SSLJ) with 2.0 mm substrate thickness outperform conventional single-lap joints (SLJ) by 11.15% in ultimate load due to reduced secondary bending, while increasing substrate thickness to 4.0 mm negatively impacts strength for both configurations.
This paper presents a deep learning-driven multi-objective optimization framework that outperforms classical power-law models in predicting surface finish and tool wear for CNC dry turning, successfully identifying a superior Pareto front and robust operating parameters through NSGA-III and TOPSIS analysis.
This paper proposes a novel streamline-based surrogate optimization algorithm that integrates injection/production efficiency metrics with advanced sampling strategies to efficiently and reliably optimize well controls in heterogeneous waterflooding reservoirs, thereby significantly improving oil recovery and economic benefits while overcoming the limitations of traditional streamline and pure surrogate methods.
This study demonstrates that in the sparse NO₂ monitoring network of Buenos Aires, complex machine learning models offer only marginal and operationally limited improvements over classical methods at short horizons, with no added value at longer timeframes, suggesting that transparent, causally rigorous evaluation is often more valuable than algorithmic complexity under data-constrained conditions.
This preliminary study suggests that contact-triggered thermal feedback from a multi-point haptic ring system may enhance spatial presence and experienced realism in virtual reality, although the findings require further validation due to marginal statistical significance and the lack of evidence for superiority over uniform thermal feedback.