2594 papers
This study demonstrates that Magnetic Abrasive Jet Machining (MAJM), supported by CFD simulations and SEM image analysis, effectively improves the inner surface quality of G14 biopsy needles, identifying inflow velocity as the dominant factor for erosion rate and 500 rpm as the optimal rotation speed for achieving homogeneous surface processing.
This study establishes optimal forced oxidation ignition parameters for Fengyu bituminous coal through lab-scale experiments and develops a validated coupled heat-mass transfer model to enhance the success rate and operational control of deep drilling-based underground coal gasification.
This study isolates single-channel LoRaWAN performance under worst-case pure ALOHA conditions to identify a critical scalability threshold of 50–60 nodes where packet delivery sharply degrades, revealing that confirmed transmission modes offer initial reliability gains but ultimately incur prohibitive energy costs and reduced performance at high densities, while node mobility proves negligible in collision-dominated regimes.
This study demonstrates that femtosecond laser-textured uncoated cemented carbide inserts significantly improve the wet machining performance of wrought aluminium alloys by drastically reducing flank wear, lowering cutting forces, and modifying chip formation compared to conventional tools.
This study evaluates various cryogenic cooling strategies for grinding AISI 4140H steel and finds that while in-process CO2 cooling shows promise, conventional oil-based cooling ultimately yields superior surface integrity and process stability compared to all tested cryogenic methods.
This study proposes and evaluates a synergistic oil–gas–geothermal integration in Nigerian refineries, where co-produced brine and flue gas drive site-specific Organic Rankine Cycles to achieve net power outputs of 170–200 kW, exergy efficiencies of 11–13%, and CO₂ reductions of 16.9–21.1% with a 3.9–4.7 year payback, while highlighting source–fluid temperature mismatch as the primary design constraint.
This paper proposes Bandwidth-Aware Constraint Scheduling (BACS) and its observability-aware variant (BACS+), which optimize the transmission of inter-robot constraints over duty-cycle-limited LoRa links by prioritizing candidates based on predicted server-side trust and information density, thereby significantly reducing map-alignment errors compared to traditional trust-weighted fusion and random ordering.
This paper presents the first monolithically integrated silicon photonic processor that achieves fully analog, end-to-end online training with real-time adaptability by implementing an on-chip multiplexed gradient descent algorithm, enabling simultaneous inference and dynamic learning under varying environmental conditions.
This critical review evaluates Thermodynamic Rarity, Exergy Cost Analysis, and Statistical Entropy Analysis to enhance Life Cycle Assessment by identifying chemical exergy as the most robust metric for capturing geological scarcity and chemical associations, while highlighting Exergy Cost Analysis principles as essential for defining system boundaries and allocating co-product burdens in resource-oriented assessments.
This paper proposes and experimentally validates a variable-field look-up-table strategy for six-phase electrically excited synchronous motors that utilizes nonlinear flux-linkage maps to generate optimal current references, thereby significantly minimizing copper losses and ensuring fault-tolerant operation under single open-phase faults.