scholarly journals Biomediation of submarine sediment gravity flow dynamics

Geology ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 72-76 ◽  
Author(s):  
Melissa J. Craig ◽  
Jaco H. Baas ◽  
Kathryn J. Amos ◽  
Lorna J. Strachan ◽  
Andrew J. Manning ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Turbulent Flows ◽  
Extracellular Polymeric Substances ◽  
Flow Behavior ◽  
Laboratory Data ◽  
Deep Ocean ◽  
Unit Weight ◽  
Runout Distance ◽  
Sediment Gravity Flows ◽  
Gravity Flows

Abstract Sediment gravity flows are the primary process by which sediment and organic carbon are transported from the continental margin to the deep ocean. Up to 40% of the total marine organic carbon pool is represented by cohesive extracellular polymeric substances (EPS) produced by microorganisms. The effect of these polymers on sediment gravity flows has not been investigated, despite the economic and societal importance of these flows. We present the first EPS concentrations measured in deep-sea sediment, combined with novel laboratory data that offer insights into the modulation of the dynamics of clay-laden, physically cohesive sediment gravity flows by biological cohesion. We show that EPS can profoundly affect the character, evolution, and runout of sediment gravity flows and are as prevalent in deep oceans as in shallow seas. Transitional and laminar plug flows are more susceptible to EPS-induced changes in flow properties than turbulent flows. At relatively low concentrations, EPS markedly decrease the head velocity and runout distance of transitional flows. This biological cohesion is greater, per unit weight, than the physical cohesion of cohesive clay and may exert a stronger control on flow behavior. These results significantly improve our understanding of the effects of an unrealized biological component of sediment gravity flows. The implications are wide ranging and may influence predictive models of sediment gravity flows and advance our understanding about the ways in which these flows transport and bury organic carbon globally.

Benthic foraminiferal zonation in deep-water carbonate platform margin environments, northern Little Bahama Bank

1988 ◽  
Vol 62 (01) ◽  
pp. 1-8 ◽  
Author(s):  
Ronald E. Martin
Keyword(s):  
Deep Water ◽  
Benthic Foraminifera ◽  
Carbonate Platform ◽  
Sedimentary Facies ◽  
Depositional Environments ◽  
Near Surface ◽  
Sediment Gravity Flows ◽  
Gravity Flows ◽  
Platform Margin ◽  
Water Carbonate

The utility of benthic foraminifera in bathymetric interpretation of clastic depositional environments is well established. In contrast, bathymetric distribution of benthic foraminifera in deep-water carbonate environments has been largely neglected. Approximately 260 species and morphotypes of benthic foraminifera were identified from 12 piston core tops and grab samples collected along two traverses 25 km apart across the northern windward margin of Little Bahama Bank at depths of 275-1,135 m. Certain species and operational taxonomic groups of benthic foraminifera correspond to major near-surface sedimentary facies of the windward margin of Little Bahama Bank and serve as reliable depth indicators. Globocassidulina subglobosa, Cibicides rugosus, and Cibicides wuellerstorfi are all reliable depth indicators, being most abundant at depths >1,000 m, and are found in lower slope periplatform aprons, which are primarily comprised of sediment gravity flows. Reef-dwelling peneroplids and soritids (suborder Miliolina) and rotaliines (suborder Rotaliina) are most abundant at depths <300 m, reflecting downslope bottom transport in proximity to bank-margin reefs. Small miliolines, rosalinids, and discorbids are abundant in periplatform ooze at depths <300 m and are winnowed from the carbonate platform. Increased variation in assemblage diversity below 900 m reflects mixing of shallow- and deep-water species by sediment gravity flows.

scholarly journals Influence of biopolymers on the rheological properties of seafloor sediments and the runout behavior of submarine debris flows

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun Kameda ◽  
Hamada Yohei
Keyword(s):  
Rheological Properties ◽  
Debris Flows ◽  
Extracellular Polymeric Substances ◽  
Flow Behavior ◽  
Mass Movement ◽  
Rheological Parameters ◽  
Natural Environments ◽  
Natural Systems ◽  
Chemical Conditions ◽  
Seafloor Sediments

AbstractSubmarine debris flows are mass movement processes on the seafloor, and are geohazards for seafloor infrastructure such as pipelines, communication cables, and submarine structures. Understanding the generation and run-out behavior of submarine debris flows is thus critical for assessing the risk of such geohazards. The rheological properties of seafloor sediments are governed by factors including sediment composition, grain size, water content, and physico-chemical conditions. In addition, extracellular polymeric substances (EPS) generated by microorganisms can affect rheological properties in natural systems. Here we show that a small quantity of EPS (~ 0.1 wt%) can potentially increase slope stability and decrease the mobility of submarine debris flows by increasing the internal cohesion of seafloor sediment. Our experiments demonstrated that the flow behavior of sediment suspensions mixed with an analogue material of EPS (xanthan gum) can be described by a Herschel–Bulkley model, with the rheological parameters being modified progressively, but not monotonously, with increasing EPS content. Numerical modeling of debris flows demonstrated that the run-out distance markedly decreases if even 0.1 wt% of EPS is added. The addition of EPS can also enhance the resistivity of sediment to fluidization triggered by cyclic loading, by means of formation of an EPS network that binds sediment particles. These findings suggest that the presence of EPS in natural environments reduces the likelihood of submarine geohazards.

scholarly journals Sinking rates and ballast composition of particles in the Atlantic Ocean: implications for the organic carbon fluxes to the deep ocean

2009 ◽  
Vol 6 (1) ◽  
pp. 85-102 ◽  
Author(s):  
G. Fischer ◽  
G. Karakaş
Keyword(s):  
Organic Carbon ◽  
Atlantic Ocean ◽  
Sediment Trap ◽  
Carbon Flux ◽  
Coastal Upwelling ◽  
Production Systems ◽  
Deep Ocean ◽  
Biogeochemical Model ◽  
Carbonate Content ◽  
Organic Carbon Flux

Abstract. The flux of materials to the deep sea is dominated by larger, organic-rich particles with sinking rates varying between a few meters and several hundred meters per day. Mineral ballast may regulate the transfer of organic matter and other components by determining the sinking rates, e.g. via particle density. We calculated particle sinking rates from mass flux patterns and alkenone measurements applying the results of sediment trap experiments from the Atlantic Ocean. We have indication for higher particle sinking rates in carbonate-dominated production systems when considering both regional and seasonal data. During a summer coccolithophorid bloom in the Cape Blanc coastal upwelling off Mauritania, particle sinking rates reached almost 570 m per day, most probably due the fast sedimentation of densely packed zooplankton fecal pellets, which transport high amounts of organic carbon associated with coccoliths to the deep ocean despite rather low production. During the recurring winter-spring blooms off NW Africa and in opal-rich production systems of the Southern Ocean, sinking rates of larger particles, most probably diatom aggregates, showed a tendency to lower values. However, there is no straightforward relationship between carbonate content and particle sinking rates. This could be due to the unknown composition of carbonate and/or the influence of particle size and shape on sinking rates. It also remains noticeable that the highest sinking rates occurred in dust-rich ocean regions off NW Africa, but this issue deserves further detailed field and laboratory investigations. We obtained increasing sinking rates with depth. By using a seven-compartment biogeochemical model, it was shown that the deep ocean organic carbon flux at a mesotrophic sediment trap site off Cape Blanc can be captured fairly well using seasonal variable particle sinking rates. Our model provides a total organic carbon flux of 0.29 Tg per year down to 3000 m off the NW African upwelling region between 5 and 35° N. Simple parameterisations of remineralisation and sinking rates in such models, however, limit their capability in reproducing the flux variation in the water column.

scholarly journals Hidden cycle of dissolved organic carbon in the deep ocean

2014 ◽  
Vol 111 (47) ◽  
pp. 16706-16711 ◽  
Author(s):  
Christopher L. Follett ◽  
Daniel J. Repeta ◽  
Daniel H. Rothman ◽  
Li Xu ◽  
Chiara Santinelli
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Deep Ocean

A Three-Equation Eddy-Viscosity Model for Reynolds-Averaged Navier–Stokes Simulations of Transitional Flow

2008 ◽  
Vol 130 (12) ◽  
Author(s):  
D. Keith Walters ◽  
Davor Cokljat
Keyword(s):  
Boundary Layer ◽  
Turbulent Flows ◽  
Eddy Viscosity ◽  
Flow Behavior ◽  
Applied Pressure ◽  
Plate Boundary ◽  
Low Frequency ◽  
Transitional Flow ◽  
Test Cases ◽  
Eddy Viscosity Model

An eddy-viscosity turbulence model employing three additional transport equations is presented and applied to a number of transitional flow test cases. The model is based on the k-ω framework and represents a substantial refinement to a transition-sensitive model that has been previously documented in the open literature. The third transport equation is included to predict the magnitude of low-frequency velocity fluctuations in the pretransitional boundary layer that have been identified as the precursors to transition. The closure of model terms is based on a phenomenological (i.e., physics-based) rather than a purely empirical approach and the rationale for the forms of these terms is discussed. The model has been implemented into a commercial computational fluid dynamics code and applied to a number of relevant test cases, including flat plate boundary layers with and without applied pressure gradients, as well as a variety of airfoil test cases with different geometries, Reynolds numbers, freestream turbulence conditions, and angles of attack. The test cases demonstrate the ability of the model to successfully reproduce transitional flow behavior with a reasonable degree of accuracy, particularly in comparison with commonly used models that exhibit no capability of predicting laminar-to-turbulent boundary layer development. While it is impossible to resolve all of the complex features of transitional and turbulent flows with a relatively simple Reynolds-averaged modeling approach, the results shown here demonstrate that the new model can provide a useful and practical tool for engineers addressing the simulation and prediction of transitional flow behavior in fluid systems.

Study on Laminar Turbulent Transition in Square Arrayed Rod Bundles

2021 ◽  
Author(s):  
Carolina S. B. Dutra ◽  
Elia Merzari
Keyword(s):  
Turbulent Flows ◽  
Flow Behavior ◽  
Spectral Element ◽  
Linear Instability ◽  
Rod Bundles ◽  
Rod Bundle ◽  
Turbulent Transition ◽  
Spatio Temporal ◽  
The Stability ◽  
Laminar Turbulent Transition

Abstract The study of coolant flow behavior in rod bundles is of relevance to the design of nuclear reactors. Although laminar and turbulent flows have been researched extensively, there are still gaps in understanding the process of laminar-turbulent transition. Such a process may involve the formation of a gap vortex street as the consequence of a related linear instability. In the present work, a parametric study was performed to analyze the spatially developing turbulence in a simplified geometry setting. The geometry includes two square arrayed rod bundle subchannels with periodic boundary conditions in the cross-section. The pitch-to-diameter ratios range from 1.05 to 1.20, and the length of the domain was selected to be 100 diameters. No-slip condition at the wall, and inlet-outlet configuration were employed. Then, to investigate the stability of the flow, the Reynolds number was varied from 250 to 3000. The simulations were carried out using the spectral-element code Nek5000, with a Direct Numerical Simulation (DNS) approach. Data were analyzed to examine this Spatio-temporal developing instability. In particular, we evaluate the location of onset and spatial growth of the instability.

Using new observations and Machine Learning to improve organic sinking processes in the PlankTOM global ocean biogeochemical model 

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Lionel Guidi ◽  
Jean-Olivier Irisson
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Deep Ocean ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Carbon Export ◽  
Mixing Depth ◽  
Chl A ◽  
Biogeochemical Models

<p>A lot of effort has been put in the representation of surface ecosystem processes in global carbon cycle models, in particular through the grouping of organisms into Plankton Functional Types (PFTs) which have specific influences on the carbon cycle. In contrast, the transfer of ecosystem dynamics into carbon export to the deep ocean has received much less attention, so that changes in the representation of the PFTs do not necessarily translate into changes in sinking of particulate matter. Models constrain the air-sea CO<sub>2</sub> flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO<sub>2</sub> emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO<sub>2 </sub>can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO<sub>2</sub> fluxes, and on the amount of CO<sub>2</sub> emissions that remain in the atmosphere.</p><p>In this work we focus on the representation of organic matter sinking in global biogeochemical models, using the PlankTOM model in its latest version representing 12 PFTs. We develop and test a methodology that will enable the systematic use of new observations to constrain sinking processes in the model. The approach is based on a Neural Network (NN) and is applied to the PlankTOM model output to test its ability to reconstruction small and large particulate organic carbon with a limited number of observations. We test the information content of geographical variables (location, depth, time of year), physical conditions (temperature, mixing depth, nutrients), and ecosystem information (CHL a, PFTs). These predictors are used in the NN to test their influence on the model-generation of organic particles and the robustness of the results. We show preliminary results using the NN approach with real plankton and particle size distribution observations from the Underwater Vision Profiler (UVP) and plankton diversity data from Tara Oceans expeditions and discuss limitations.</p>

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