In the realm of engineering, the significance of minichannels has escalated, especially in micro-scale multiphase fluid dynamics. This study conducts an extensive numerical analysis of two-phase flow in minichannels, utilizing the level-set method coupled with COMSOL Multiphysics®. Focusing on the minutiae of the liquid-gas interface, the research employs a two-dimensional grid to solve the incompressible Navier-Stokes equations, thereby illuminating the complex formation of diverse flow patterns in minichannels. A critical aspect of this investigation is the exploration of various geometric configurations at the inlet, particularly the examination of serrated air and water inlet channels. The findings reveal that serrated air inlets, when designed internally, effectively mitigate the buoyancy force across diverse channel configurations, ensuring stable and predictable flow patterns. Conversely, the configuration of water inlets plays a less significant role in controlling this force, underscoring the paramount importance of air inlet design in achieving optimal flow regulation. These insights not only deepen the understanding of minichannel flow dynamics but also provide practical knowledge for enhancing the efficiency of micro-scale systems. The implications of this study extend to the design of more effective minichannel applications, such as cooling systems, heat sinks, and heat exchangers used as evaporators. Moreover, the research highlights the necessity of considering geometric factors in minichannel flow analyses and sets the stage for future advancements in this evolving domain of engineering.
This investigation explores the dynamics of logistics information traceability within the realm of e-commerce, emphasizing the simultaneous existence of diverse sales channels in the digital landscape. It adopts Stackelberg game theory to dissect multi-channel pricing strategies, underscoring the significance of consumer preferences pertaining to logistics information traceability and pricing structures. The study meticulously constructs a supply chain framework, predominantly supplier-driven, integrating both platform-based retail and direct sales channels. This framework serves as the basis for examining fluctuations in retail pricing and the aggregate profit margins under varying decision-making scenarios. It is revealed that platforms operating independently and opting for third-party logistics services for information traceability tend to achieve elevated traceability levels. In contrast, direct sales models managed by suppliers and utilizing e-commerce platform logistics services are associated with enhanced traceability. These insights contribute to a nuanced understanding of the strategic choices in e-commerce logistics, especially in the context of information traceability. This study's findings have broad implications for designing efficient logistics systems in the e-commerce sector, catering to the evolving demands of the digital economy.
Urban transportation systems, characterized by inherent uncertainty and ambiguity, present a formidable challenge in decision-making due to their complex interplay of factors. This complexity arises from dynamically shifting commuter behaviors, a diverse array of transit options, and variable traffic patterns. Such unpredictability hinders the formulation and implementation of effective strategies. Addressing this challenge necessitates innovative problem-solving methodologies capable of handling the nuanced uncertainties present in these systems. This study introduces the multidimensional neutrosophic fuzzy hypersoft set (MDNFHS) as a groundbreaking method for managing ambiguity in urban transportation planning. MDNFHS, emerging from the integration of neutrosophic fuzzy sets (NFSs) and hypersoft sets (HSs), uniquely encapsulates both the degrees of membership and non-membership. It is demonstrated that the tailored set-theoretic operations and distance measurements specific to MDNFHS enable enhanced manipulation and analysis, making it a potent tool in complex decision-making scenarios. The efficacy of MDNFHS in decision-making is exemplified through a compelling case study, showcasing its ability to offer clarity in situations marred by ambiguity. This novel approach is posited to revolutionize decision-making processes, offering a new level of certainty in environments traditionally dominated by uncertain elements.
When cutting the hard cortical bone layer, orthopedic robots are prone to cutting chatter and thermal damage due to force and heat. Accurately establishing a model of cortical bone milling force and assessing the milling force in suppressing cortical bone cutting chatter, reducing cutting thermal damage, and optimizing process parameters is of great significance. This study aims to deeply explore the issues of modeling and coefficient identification of the milling force model of the orthopedic robot ball-end milling cutter for cortical bone, and to establish a theoretical model related to the milling state for analyzing the stability of robot milling chatter. The milling force model of the orthopedic robot ball-end milling cutter was constructed using the micro-element method, and a milling coefficient identification model was established based on the average milling force model. The coefficients were identified using the least squares method, and the cortical bone milling force model for the orthopedic robot ball-end milling cutter was established and experimentally verified. The experimental results show that the milling force curve calculated is basically consistent with the actual measured curve in terms of values and trend, verifying the accuracy of the established milling force model, and providing a theoretical basis for the study of robot cortical bone milling chatter.
In the realm of ground transportation, high-speed maglev trains stand out due to their exceptional stability, rapid velocity, and environmental benefits, such as low pollution and noise. However, the aerodynamic challenges faced by these lightweight, high-velocity trains significantly impact their safety and comfort, making aerodynamics a critical aspect in their design. This research delves into the dynamic aerodynamic behavior of high-speed maglev trains in the presence of crosswinds. A simulation analysis was conducted on a simplified model of a three-car maglev train, with an established aerodynamic model for the train and track beam in crosswind scenarios. The study employed three-dimensional, steady-state, incompressible $N-S$ equations, complemented by a $k-\varepsilon$ dual-equation turbulence model. The finite volume method was utilized to assess the flow field structure around the train and the pressure distribution on its surface under varying combinations of train speed and wind velocity. The investigation summarized the patterns and trends in aerodynamic loads across diverse conditions. Results demonstrate that at a speed of 600 km/h, the tail car is subjected to the highest aerodynamic drag, while the head car bears the maximum lateral force and overturning moment. As crosswind speeds increase from 5 m/s to 20 m/s, the tail car exhibits the largest increment in drag, reaching 16.6 kN. The front car shows the most significant rise in lateral force and overturning moment, measured at 34.11 kN and 52.45 kN·m, respectively. It is observed that the behavior of aerodynamic forces at lower and medium speeds aligns fundamentally with the patterns noted at higher speeds.
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