Bile duct injury during laparoscopic cholecystectomy (LC) is rare and often happens due to misidentification. Experts recommend dissection during laparoscopic cholecystectomy occur lateral to the cystic artery lymph node (LN). The LN is classically identified as a single node overlying the cystic artery and lateral to the bile duct. It thus represents another important landmark during LC. We present the first patient, to our knowledge, with 3 LNs in the hepatobiliary triangle. The laparoscopic cholecystectomy and recovery were uneventful. The LN is an important anatomical marker during LC and the presence of multiple LNs does not impact on surgical technique.
In this work, we adopt the integration of the L-system fractal tree generation, 3D printed wind tunnel modeling, and computational fluid dynamics (CFD) simulation approach to model the wind effect on a single tree. We compare the agreement between CFD simulations and wind tunnel measurements of rigid branched structures resembling trees. First, fractal tree mesh models based on species growth and branching patterns are developed to represent tree species for wind–tree modeling. Subsequently, a scaled-down fractal tree is generated with 3D-printing and subjected to tunnel testing with load cell and particle image velocimetry measurement data under the wind speed of 10 m/s and 15 m/s. Finally, CFD based on Reynolds-Average Navier–Stokes (RANS) simulation with a full closure model and Large Eddy Simulation (LES) using appropriate momentum sink and turbulence source terms for the volumetric tree is carried out. We use both the volume-average porous media and the volume-splitting discretized zones (split number 10 × 10 × 10) to reproduce the momentum sink effect in the numerical simulation. Three tree species, namely, Peltophorum pterocarpum (yellow flame), Khaya senegalensis (African mahogany), and Hopea odorata (ironwood), are tested, and a reasonable agreement of drag force prediction and velocity profiles is obtained when comparing the CFD simulation results with wind tunnel data. The RANS modeled drag force results exhibit 20% of over-prediction, while the normalized velocity profiles display a good match of velocity decay at the tree leeward sides. On the other hand, LES produces much better results with only 3% discrepancy with the experimental results. A comparison of experimental results among the tree species is also carried out. Due to the actual random wind direction, tree slenderness representation, and structural flexibility issues, the current methodology still has the limitation for validation with urban on-site measurement. Nonetheless, this integrated approach is the first step in establishing modeling tool applicability to examine the effect of the forest structure and composition on wind loads.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.