662 papers
This study employs highly resolved simulations to evaluate the impact of injector spacing on a reacting hydrogen jet in a hot air cross-flow, revealing that intermediate-to-wide spacing (approximately eight diameters) offers the optimal design trade-off by balancing unburnt hydrogen throughput, wall heat transfer, and flow stability.
This paper presents a novel, fully automated marker-based registration method that achieves sub-voxel precision in aligning simultaneously acquired preclinical PET and MRI images, specifically addressing the challenges posed by a non-stationary PET detector with limited internal space.
This paper demonstrates that sequentially published energy data often fails to uphold privacy promises over time, as repeated annual releases allow for the inference of sensitive marginal group information through simple subtraction, necessitating a shift from auditing isolated files to evaluating the entire sequence using new metrics like "specification half-life."
This paper proposes PETAR, a predictive energy and trust-aware routing protocol that enhances energy efficiency, security, and network stability in wireless sensor networks for smart healthcare and urban monitoring by utilizing future energy forecasting and node trust evaluation to optimize cluster head selection and data transmission.
This study demonstrates that using repeated underwater blast loading, particularly triple explosions, significantly improves die filling and reduces material thinning in the explosive forming of 3 mm metallic plates compared to single-shot methods, as validated by both experimental results and CEL simulations.
This study proposes a multi-objective scheduling framework for highway PV-storage-charging microgrid clusters that integrates a spatiotemporal EV-load cascade model to account for dynamic travel behaviors, successfully generating a feasible Pareto frontier that minimizes both operating costs and carbon emissions while ensuring strict constraint compliance.
This study establishes a clear process-structure-anisotropy relationship by demonstrating that vacuum-assisted resin transfer molding (VARTM) generally enhances fiber volume fraction and stiffness-dominated behaviors in carbon, glass, and basalt fiber-reinforced polymer composites compared to hand layup, while significantly influencing multiaxial mechanical properties and anisotropy indices critical for optimizing lightweight automotive structures.
This paper presents a data-quality-aware hybrid deep learning framework that integrates advanced preprocessing techniques, an ensemble of machine learning models, and hyperparameter optimization to significantly improve the accuracy and robustness of drilling rate of penetration (ROP) prediction from noisy field measurements.
This paper presents a Wi-Fi sensing system that achieves accurate multi-target range detection through coherent processing of synchronized NDP packets while addressing privacy concerns by proposing methods to randomize training signals and weaken line-of-sight components.
This research proposes a novel approach that links soil pore size distribution to water flow dynamics, demonstrating that primary consolidation occurs in macropores while secondary consolidation arises from micropore flow, thereby enabling the prediction of total settlement without requiring long-term tests.