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Abstract Shrimps locomote through water using five pairs of appendages known as pleopods, which beat in a coordinated metachronal motion. Each pleopods consists of two membranous rami, a medial endopod and lateral exopod whose edges are lined with fine hair-like setae. Because of their close spacing and density, the setae act as an impermeable membrane. During swimming, each pleopod executes a power stroke, propelling water backward, followed by a recovery stroke to reset its position. During the power stroke, the exopods, endopods, and setae spread out, forming a propulsor with a larger area. In contrast, the rami close and overlap during the recovery stroke, reducing the effective area. In this study, we simulate natural shrimp swimming based on high-speed recordings under Reynolds number (Re) of 1980, using an in-house computational fluid dynamics (CFD) solver. We compared a model based on a natural swimming shrimp with a model with pleopod area fixed at the maximum area. Our results reveal that the model incorporating spread-out motion achieves a notable reduction of 49.84% in cycle-averaged hydrodynamic power while sacrificing only 23% of cycle-averaged thrust when compared to the fixed-pleopod area model. Furthermore, the effect of spread-out motion decreases the cost of transportation by 41.72% through reducing body drag by 12%. Additionally, our analysis observed the presence of a high-speed zone behind the second pleopod during stroke motion, particularly near the tangent plane of the lowest tip trajectory, and a low-speed zone in front of that pleopods. 

Abstract Under-ice eddies are prevalent in the major circulation system in the western Arctic Ocean, the Beaufort Gyre. Theoretical studies hypothesize that the eddy-driven overturning and the ice-ocean drag are crucial mechanisms of the gyre equilibration in response to atmospheric winds. However, due to severe weather conditions and limitations of remote sensing instruments, there are only sparse eddy observations in the ice-covered Arctic Ocean. Hence, the evolution of the under-ice eddy field, its impact on the gyre variability, and their mutual response to the ongoing Arctic warming remain uncertain. Here, we infer the characteristics of the under-ice eddy field by establishing its tight connection to the angular velocities of isolated spinning sea ice floes in marginal ice zones. Using over two decades of satellite observations of marginal ice zones in the western Arctic Ocean, we identified and tracked thousands of floes and used idealized eddy modeling to infer the interannual evolution of the eddy energetics underneath the ice. We find that the eddy field is strongly correlated to the strength of the Beaufort Gyre on interannual timescales, which provides the major observational evidence consistent with the hypothesis of the gyre equilibration by eddies. The inferred trends over the past two decades signify that the gyre and its eddy field have been intensifying as the sea ice cover has been declining. Our results imply that with continuing sea ice decline, the eddy field and the Beaufort Gyre will keep intensifying and leading to enhanced transport of freshwater and biogeochemical tracers. 

Abstract. We introduce a time-dependent, one-dimensional model ofearly diagenesis that we term RADI, an acronym accounting for the mainprocesses included in the model: chemical reactions, advection, molecularand bio-diffusion, and bio-irrigation. RADI is targeted for study ofdeep-sea sediments, in particular those containing calcium carbonates(CaCO3). RADI combines CaCO3 dissolution driven by organic matterdegradation with a diffusive boundary layer and integrates state-of-the-artparameterizations of CaCO3 dissolution kinetics in seawater, thusserving as a link between mechanistic surface reaction modeling andglobal-scale biogeochemical models. RADI also includes CaCO3precipitation, providing a continuum between CaCO3 dissolution andprecipitation. RADI integrates components rather than individual chemicalspecies for accessibility and is straightforward to compare againstmeasurements. RADI is the first diagenetic model implemented in Julia, ahigh-performance programming language that is free and open source, and itis also available in MATLAB/GNU Octave. Here, we first describe thescientific background behind RADI and its implementations. Following this, we evaluateits performance in three selected locations and explore other potentialapplications, such as the influence of tides and seasonality on earlydiagenesis in the deep ocean. RADI is a powerful tool to study thetime-transient and steady-state response of the sedimentary system toenvironmental perturbation, such as deep-sea mining, deoxygenation, oracidification events.