Changes to Subaqueous Delta Bathymetry Following a High River Flow Event, Wax Lake Delta, USA
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Knowledge of the flow patterns within distributary systems is key for understanding deltaic hydro- and morpho-dynamics, yet synoptic measurements of flow fields remain virtually nonexistent. As a means of overcoming this problem, a small number of studies have used biogenic surface films as synoptic flow tracers, under the assumption that biofilm streaklines are tangent to the local flow direction. Here we rigorously test this assumption and show that, despite flow patterns that change severely in space and time (over a range >270°), streaklines are relatively accurate synoptic flow tracers for the Wax Lake Delta, in Louisiana. When the incoming discharge was greater than 2400 m3/s with stable or falling tides, the streakline-derived flow direction departed from near bed flow direction measurements of 22.8° (root mean square). When the discharge was greater than 2400 m3/s and the tides were rising greater than 0.03 m/hr, they were accurate within 28.0°. Under conditions of discharge less than 2400 m3/s and tidal change less than a positive 0.03 m/hr, they were accurate within 33.3°, while during low discharge and rising tides they were accurate within 58.9°. Accuracy varied with distance from the delta, with proximal sites having greater precision. Our results demonstrate that a streakline-derived flow direction can characterize the spatiotemporal variability in the flow directions, but that the accuracy is significantly influenced by the hydrodynamic conditions and location within the network.
Particle erosion is an important process in both natural and manmade environments. For example, in natural environments particle or sediment erosion rates determine the course of rivers, depth of streams, and fate of deltas. The interplay between erosion rates and flow patterns can have dramatic impact on shorelines. Where hydrodynamic jet flows or rip currents change direction, sediments may accumulate or disperse altering the shape of coastlines and the ecosystems and economies that rely on them. In man-made systems, jet flows may be used to mobilize particles from surfaces or within industrial scale mixing tanks. For example, in the nuclear industry, impinging jet mixers may be used to mobilize and suspend sludges at the bottom of waste tanks. In each of these examples, the Shields diagram is useful to determine the conditions under which erosion occurs. This diagram plots the scaled critical shear stress for erosion as a function of the particle size as embedded in particle Reynolds numbers, Archimedes numbers, or their equivalents. Although the data, that carries a large spread, is largely in agreement with mathematical models, for the smallest particles, model predictions diverge from each other and from experimental data. Indeed, there is substantial uncertainty about the Shields diagrams at relatively small particle sizes and flow rates. Here we evaluate critical shear stresses for erosion under laminar jet flow. To date critical shear stresses for erosion, as embodied in Shields diagrams, have largely been developed for turbulent flow both experimental and mathematically. However, curves on the Shields diagrams diverge among various models at lower particle Reynolds numbers. Indeed, how critical shear stresses for erosion develop under fully laminar jet flow conditions (not simply laminar boundary layers under turbulent flow) remains unclear. Here we address this gap, which is particularly important for mobilization of the smallest particles. We find the Shields parameter to be inversely proportional to the particle Reynolds numbers under laminar jet flow conditions similar to turbulent conditions.
Abstract Estimates of nitrate loading to the Arctic Ocean are limited by the lack of field observations within deltas partly due to logistical constraints. To overcome this limitation, we use a remote sensing framework to estimate retention of nitrate in Arctic deltas. We achieve this by coupling hydrological and biogeochemical process models at the network scale for five major Arctic deltas. Binary masks of delta channels were used to simulate flow direction and magnitude through networks. Models were parameterized using historical and seasonal observations. Simulated nitrate retention ranged from 2.9% to 15% of the incoming load. Retention rates were largest during winter but smallest during spring conditions when increased discharges export large nitrate masses to the coast. Under future climate scenarios, retention rates fall by ∼1%–10%. Arctic deltas have an important effect on the magnitude of nitrate entering Arctic seas and the inclusion of processing in deltas can improve flux estimates.
Abstract. The abundance of global, remotely sensed surface water observations has accelerated efforts toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.
River deltas are home to large populations and can be composed of complex channel networks which convey flows of matter to the shoreline. Knowledge of flow within individual channels is needed to quantify the distribution of discharge across the delta, and thus its sustainability over time. Due to a lack of field measurements at the local channel scale, researchers leverage remote sensing data to estimate the partitioning of flow. We compare data from 15 river deltas to discharge partitioning estimates based on channel network graphs derived from remote sensing imagery. We quantify errors in the common width-based method and test alternative partitioning techniques to find that width-based discharge partitioning is universally applicable, suggesting that absent any site-specific information, discharge partitioning by average channel width is an appropriate approach. We also provide networks, streamflow measurements, and flux partitioning estimates for 28 delta networks as the Discharge In Distributary NeTworks (DIDNT) dataset.
Simulations have shown that while semi-definite relaxations of AC optimal power flow (AC-OPF) on three-phase radial networks with only wye connections tend to be exact, the presence of delta connections seem to render them inexact. This paper shows that such inexactness originates from the non-uniqueness of relaxation solutions and numerical errors amplified by the non-uniqueness. This finding motivates two algorithms to recover the exact solution of AC-OPF in unbalanced distribution networks featuring both wye and delta connections. In simulations using IEEE 13, 37 and 123-bus systems, the proposed algorithms provide exact optimal solutions up to numerical precision.
The effect of plasma turbulence on the trajectories of dust particles is investigated for the first time. The dynamics of dust particles is computed using the ad-hoc developed Dust Injection Simulator code, using a 3D turbulent plasma background computed with the TOKAM3X code. As a result, the evolution of the particle trajectories is governed by the ion drag force, and the shape of the trajectory is set by the Stokes number $St\propto a_d/n_0$, with $a_d$ the dust radius and $n_0$ the density at the separatrix. The plasma turbulence is observed to scatter the dust particles, exhibiting a hyperdiffusive regime in all cases. The amplitude of the turbulent spread of the trajectories $\Delta r^2$ is shown to depend on the ratio $Ku/St$, with $Ku\propto u_{rms}$ the Kubo number and $u_{rms}$ the fluctuation level of the plasma flow. These results are compared with a simple analytical model, predicting $\Delta r^2\propto (Ku/St)^2t^3$, or $\Delta r^2\propto (u_{rms}n_0/a_d)^2t^3$. As the dust is heated by the plasma fluxes, thermionic emission sets the dust charge, originally negative, to slightly positive values. This results in a substantial reduction of the ion drag force through the suppression of its Coulomb scattering component. The dust grain inertia is then no longer negligible, and drives the transition from a hyperdiffusive regime towards a ballistic one.
The recently-developed ability to control phosphorous-doping of silicon at an atomic level using scanning tunneling microscopy, a technique known as atomic precision advanced manufacturing (APAM), has allowed us to tailor electronic devices with atomic precision, and thus has emerged as a way to explore new possibilities in Si electronics. In these applications, critical questions include where current flow is actually occurring in or near APAM structures as well as whether leakage currents are present. In general, detection and mapping of current flow in APAM structures are valuable diagnostic tools to obtain reliable devices in digital-enhanced applications. In this report, we used nitrogen-vacancy (NV) centers in diamond for wide-field magnetic imaging (with a few-mm field of view and micron-scale resolution) of magnetic fields from surface currents flowing in an APAM test device made of a P delta-doped layer on a Si substrate, a standard APAM witness material. We integrated a diamond having a surface NV ensemble with the device (patterned in two parallel mm-sized ribbons), then mapped the magnetic field from the DC current injected in the APAM device in a home-built NV wide-field microscope. The 2D magnetic field maps were used to reconstruct the surface current densities, allowing us to obtain information on current paths, device failures such as choke points where current flow is impeded, and current leakages outside the APAM-defined P-doped regions. Analysis on the current density reconstructed map showed a projected sensitivity of ~0.03 A m -1 , corresponding to a smallest-detectable current in the 200 μm wide APAM ribbon of ~6 μA. These results demonstrate the failure analysis capability of NV wide-field magnetometry for APAM materials, opening the possibility to investigate other cutting-edge microelectronic devices.
Human activities have increased nitrate export from rivers, degrading coastal water quality. At deltaic river mouths, the flow of water through wetlands increases nitrate removal, and the spatial organization of removal rates influences coastal water quality. To understand the spatial distribution of nitrate removal in a river-dominated delta, in this study we deployed 23 benthic chambers across ecogeomorphic zones with varying elevation, vegetation, and sediment properties in Wax Lake Delta (Louisiana, USA) in June 2018. Regression analyses indicate that normalized difference vegetation index is a useful predictor of summertime nitrate removal. Mass transfer velocity were approximately three times greater on a vegetated submerged levee (13 mm hr –1 ), where normalized difference vegetation index was greatest, compared to other locations (4.6 mm hr –1 ). Two methods were developed to upscale nitrate removal across the delta. The flooded-delta method integrates spatially explicit potential removal rates across submerged portions of the delta and suggests that intermediate elevations on the delta—including submerged levees—are responsible for 70% of potential nitrate removal despite covering only 33% of the flooded area. The channel network method treats the delta as a network of river channels and suggests that although secondary channels are more efficient than primary channels at removing received nitrate, primary channels collectively contribute more to overall removal because they convey more of the total nitrate load. The two upscaling methods predict similar rates of nitrate removal, equivalent to less than 4% of nitrate entering the delta. To protect coastal waters against high nitrate loads, management policies should aim to reduce upstream nutrient loads.
There is growing interest in energy storage technologies due to the expansion of renewable energy sources that are inherently intermittent and the increasing frequency of extreme weather events that disturb the power grid. Power consumption in buildings makes up approximately 76% of all electricity usage on the grid and is primarily used for thermal applications such as space conditioning, hot water, and cooking. This makes thermal energy storage (TES) an ideal solution for many of these applications. Many TES technologies rely on latent energy storage, which utilizes the melting/solidification of phase change materials (PCM) to store energy. Typically, TES designs suffer from low power density due to their low inherent thermal conductivity. This limitation makes the deployment of TES in active applications difficult as the ease of access to energy is essential for effective use. Common routes for improving power density include high thermal conductivity additives or extended features such as fins that increase cost. This study presents an alternative approach to improving performance through increasing the overall surface area to volume ratio of the device, to increase the available area for convection to occur between the working fluid and PCM. In the study a commercial PCM was selected with a transition temperature ideal for space heating applications. The heat exchanger design utilizes a unique application of triply periodic minimal surfaces (TPMS) for macro-encapsulation of the PCM. The use of TPMS for heat exchangers has been growing in interest due to their high-surface area to volume ratios, which were previously unmanufacturable until the development of additive manufacturing. A modular system was designed and manufactured with a stereolithography resin printing system that is then backfilled with PCM. An experiment test set-up is designed to test the charge and discharge performance of the thermal storage using a conditioned air stream. The pressure drop of the design is tested across a variety of flow rates. When compared to existing experimental data within literature, there is excellent agreement based on the Reynolds number at similar hydraulic diameters. Several inlet temperatures are tested at consistent temperature differences from the phase change temperature for both charging and discharging. Additionally, the volumetric flow rate is varied for each temperature set point. It was found that increasing flow rate had diminishing returns in reducing the overall charge time of the TES. The temperature delta from the melting temperature was the primary contributor to the change in average heat flux with limited variation in average heat transfer rate between charging and discharging at similar inlet temperatures and flow rates. The TPMS heat exchanger design has a high air-side pressure drop but it provides high heat transfer rates. This helps maintain a high outlet temperature during discharge, which is important to thermal comfort applications. The design, manufacturing, and experimental characterization of the TES device will be presented as part of this study.
Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius $\delta$ goes to zero, and to the fractional Laplacian as $\delta$ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We also provide theoretical convergence rates with respect to $\delta$ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, $\delta$ and $\alpha$, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order $\alpha(y)$, which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as $\delta$. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.
As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.
River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).
Dihadron azimuthal correlations containing a high transverse momentum ($ p_{T} $) trigger particle are sensitive to the properties of the nuclear medium created at RHIC through the strong interactions occurring between the traversing parton and the medium, i.e. jet-quenching. Previous measurements revealed a strong modification to dihadron azimuthal correlations in Au+Au collisions with respect to p+p and d+Au collisions. The modification increases with the collision centrality, suggesting a path-length or energy density dependence to the jet-quenching effect. This paper reports STAR measurements of dihadron azimuthal correlations in mid-central (20%-60%) Au+Au collisions at $ \sqrt{s_{\rm{NN}}} = 200 $ GeV as a function of the trigger particle's azimuthal angle relative to the event plane, $ \phi_{s} = | \phi_{t}- \psi_{{\rm{EP}}}| $. The azimuthal correlation is studied as a function of both the trigger and associated particle $ p_{T} $. The subtractions of the combinatorial background and anisotropic flow, assuming Zero Yield At Minimum (ZYAM), are described. The correlation results are first discussed with subtraction of the even harmonic (elliptic and quadrangular) flow backgrounds. The away-side correlation is strongly modified, and the modification varies with $ \phi_{s} $, with a double-peak structure for out-of-plane trigger particles. The near-side ridge (long range pseudo-rapidity $ \Delta\eta $ correlation) appears to drop with increasing $ \phi_{s} $ while the jet-like component remains approximately constant. The correlation functions are further studied with the subtraction of odd harmonic triangular flow background arising from fluctuations. It is found that the triangular flow, while responsible for the majority of the amplitudes, is not sufficient to explain the $ \phi_{s} $-dependence of the ridge or the away-side double-peak structure. The dropping ridge with $ \phi_{s} $ could be attributed to a $ \phi_{s} $-dependent elliptic anisotropy; however, the physics mechanism of the ridge remains an open question. Even with a $ \phi_{s} $-dependent elliptic flow, the away-side correlation structure is robust. These results, with extensive systematic studies of the dihadron correlations as a function of $ \phi_{s} $, trigger and associated particle $ p_{T} $, and the pseudo-rapidity range $ \Delta\eta $, should provide stringent inputs to help understand the underlying physics mechanisms of jet-medium interactions in high energy nuclear collisions.
Existing global river networks underpin a wide range of hydrological applications but do not represent channels with divergent river flows (bifurcations, multi‐threaded channels, canals), as these features defy the convergent flow assumption that elevation‐derived networks (e.g., HydroSHEDS, MERIT Hydro) are based on. Yet, bifurcations are important features of the global river drainage system, especially on large floodplains and river deltas, and are also often found in densely populated regions. Here we developed the first raster and vector‐based Global RIver Topology that not only represents the tributaries of the global drainage network but also the distributaries, including multi‐threaded rivers, canals and deltas. We achieve this by merging a 30 m Landsat‐based river mask with elevation‐generated streams to ensure a homogeneous drainage density outside of the river mask for rivers narrower than approximately 30 m. Crucially, we employ the new 30 m digital terrain model, FABDEM, based on TanDEM‐X, which shows greater accuracy over the traditionally used SRTM derivatives. After vectorization and pruning, directionality is assigned by a series of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, comparison with existing networks, and randomized manual checks. The new network represents 19.6 million km of streams and rivers with drainage areas greater than 50 km 2 and includes 67,495 bifurcations. With the advent of hyper‐resolution modeling and artificial intelligence, GRIT is expected to greatly improve the accuracy of many river‐based applications such as flood forecasting, water availability and quality simulations, or riverine habitat mapping.
Radial electric fields up to ~4 kV m –1 are observed in the boundary between the private flux region (PFR) and the scrape-off layer (SOL) driving E × B drifts between the inner and outer targets at speeds up to 2.8 km s –1 in the Tokamak à configuration variable divertor. The resulting E × B fluxes, located in a narrow region ($\Delta {\rho _\Psi } < 0.012$ in normalized radius or $\Delta $ R – R sep <4 mm mapped to the outer midplane) are equivalent to around 20% of the total heat and particle flux to the divertor targets (inner + outer). At the peak E r , the E × B poloidal transport is equivalent to parallel flows with M ∥ ~ 3. In the snowflake divertor with a second X-point in the outer SOL, the drifts in the PFR-SOL boundary were equivalent to around 30% of the total heat and particle flux to the divertor targets and cover a region ~50% wider than in the single null ($\Delta {\rho _\Psi }$ ~ 0.018, $\Delta $R – R sep ~ 6 mm). Furthermore, the location of the PFR-SOL boundary drift shifts radially in the E ∥ × B direction when reversing the toroidal field direction. Peaks in density and electron pressure have been identified near the primary X-point along with large gradients in density, temperature, and potential, the latter resulting in a local electric field ~2.7 kV m –1 which drives a drift (1.9 km s –1 ) upwards towards the closed flux surfaces. Floating potential (V f ) magnitudes up to 75 V (~2 kT e ) were measured, indicating that V f and parallel currents should not be neglected when estimating plasma potential.
This report completes Milestone M2.2.2 - ZrH pellet fabricated with controlled hydride loading: ZrH1.5±0.1 single phase pellets fabricated with controlled and thermally stable hydride loading. Hydrogen content to be quantified and single-phase confirmed by X-ray diffraction. In this milestone, we report the successful fabrication of delta-phase zirconium hydride pellets using the ORNL bulk metal hydriding system. The successful deployment of zirconium hydride moderator in advanced reactors requires development of a consistent and affordable production pathway along with implementation of a hydrogen retention solution throughout the reactor life. Fabrication of delta-phase zirconium hydride is challenging since the absorption of a large amount of hydrogen into alpha-zirconium induces significant volume expansion and the present hydrogen concentration gradient results in cracking. A fully programmable hydriding system with continuous hydrogen partial pressure and flow control to facilitate processing of massive metal hydride has been developed at ORNL. In this report, the working principle of the hydriding system will be introduced. Characterization of the produced zirconium hydride includes X-ray powder diffraction to identify the present phases and X-ray Computed Tomography to visualize the internal microstructure (including cracks). The results indicate that single delta-phase zirconium hydride pellets with various sizes have been successfully produced.