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At least 523 records · Page 29

The evolution equations for Taylor vortices in the small gap limit

The centrifugal instability of the viscous fluid flow between concentric circular cylinders in the small gap limit is considered. The amplitude of the Taylor vortex is allowed to depend on a slow time variable, a slow axial variable, and the polar angle. It is shown that the amplitude of the vortex cannot in general be described by a single amplitude equation. However, if the axial variations are periodic a single amplitude equation can be derived. In the absence of any slow axial variations it is shown that a Taylor vortex remains stable to wavy vortex perturbations. Furthermore, in this situation, stable nonaxisymmetric modes can occur but do not bifurcate from the Taylor vortex state. The stability of these modes is shown to be governed by a modified form of the Eckhaus criterion.

Hall, P.↗

Evolution equations for Taylor vortices in the small-gap limit

The centrifugal instability of the viscous fluid flow between concentric circular cylinders in the small gap limit is considered. The amplitude of the Taylor vortex is allowed to depend on a slow time variable, a slow axial variable, and the polar angle. It is shown that the amplitude of the vortex cannot in general be described by a single amplitude equation. However, if the axial variations are periodic a single amplitude equation can be derived. In the absence of any slow axial variations it is shown that a Taylor vortex remains stable to wavy vortex perturbations. Furthermore, in this situation, stable nonaxisymmeric modes can occur but do not bifurcate from the Taylor vortex state. The stability of these modes is shown to be governed by a modified form of the Eckhaus criterion. Previously announced in STAR as N84-10501

Hall, P.↗

Developing fluid flow in a curved duct of square cross-section and its fully developed dual solutions

Developing fluid flow in a curved duct of square cross-section is studied numerically by a factored ADI finite-difference method on a staggered grid. A central-difference scheme with primitive variables is used inside the computational domain to reduce numerical diffusion. Two Reynolds numbers, 574 and 790, based upon a bulk velocity and hydraulic diameter are chosen for curvature ratios of 1/6.45 and 1/2.3, respectively. It is found that the secondary flow is far more complicated than expected, with the appearance of at least two pairs of vortices. Main-flow separation is also observed for the higher curvature ratio. Furthermore, it is observed that the flow develops into two quite different states downstream, depending upon the inlet conditions. Solutions of the fully developed Navier-Stokes equations is shown to be not unique beyond a certain critical Reynolds number. Developing flow seems to evolve into the fully developed state along a particular branch into which the fully developed solution bifurcates.

Soh, W. Y.↗

Adjoint-Based Design of Rotors using the Navier-Stokes Equations in a Noninertial Reference Frame

Optimization of rotorcraft flowfields using an adjoint method generally requires a time-dependent implementation of the equations. The current study examines an intermediate approach in which a subset of rotor flowfields are cast as steady problems in a noninertial reference frame. This technique permits the use of an existing steady-state adjoint formulation with minor modifications to perform sensitivity analyses. The formulation is valid for isolated rigid rotors in hover or where the freestream velocity is aligned with the axis of rotation. Discrete consistency of the implementation is demonstrated using comparisons with a complex-variable technique, and a number of single- and multi-point optimizations for the rotorcraft figure of merit function are shown for varying blade collective angles. Design trends are shown to remain consistent as the grid is refined.

Nielsen, Eric J.↗

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗

Adjoint DSMC for nonlinear spatially-homogeneous Boltzmann equation with a general collision model

We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in Caflisch et al., which was restricted to the case of Maxwell molecules, for which the collision rate is constant. The main difficulty in generalizing the previous results is that a rejection sampling step is required in the DSMC algorithm in order to handle the variable collision rate. We find a new term corresponding to the so-called score function in the adjoint equation and a new adjoint Jacobian matrix capturing the dependence of the collision parameter on the velocities. The new formula works for a much more general class of collision models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗

Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks

Abstract Streamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting

Sun, Alexander Y.↗

Room-temperature skyrmion lattice in a layered magnet (Fe 0.5 Co 0.5 ) 5 GeTe 2

Novel magnetic ground states have been stabilized in two-dimensional (2D) magnets such as skyrmions, with the potential next-generation information technology. Here, we report the experimental observation of a Néel-type skyrmion lattice at room temperature in a single-phase, layered 2D magnet, specifically a 50% Co-doped Fe 5 GeTe 2 (FCGT) system. The thickness-dependent magnetic domain size follows Kittel's law. The static spin textures and spin dynamics in FCGT nanoflakes were studied by Lorentz electron microscopy, variable-temperature magnetic force microscopy, micromagnetic simulations, and magnetotransport measurements. Current-induced skyrmion lattice motion was observed at room temperature, with a threshold current density, j th = 1 × 10 6 A/cm 2 . This discovery of a skyrmion lattice at room temperature in a noncentrosymmetric material opens the way for layered device applications and provides an ideal platform for studies of topological and quantum effects in 2D.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

Self-Similar Compressible Free Vortices

Lie group methods are used to find both exact and numerical similarity solutions for compressible perturbations to all incompressible, two-dimensional, axisymmetric vortex reference flow. The reference flow vorticity satisfies an eigenvalue problem for which the solutions are a set of two-dimensional, self-similar, incompressible vortices. These solutions are augmented by deriving a conserved quantity for each eigenvalue, and identifying a Lie group which leaves the reference flow equations invariant. The partial differential equations governing the compressible perturbations to these reference flows are also invariant under the action of the same group. The similarity variables found with this group are used to determine the decay rates of the velocities and thermodynamic variables in the self-similar flows, and to reduce the governing partial differential equations to a set of ordinary differential equations. The ODE's are solved analytically and numerically for a Taylor vortex reference flow, and numerically for an Oseen vortex reference flow. The solutions are used to examine the dependencies of the temperature, density, entropy, dissipation and radial velocity on the Prandtl number. Also, experimental data on compressible free vortex flow are compared to the analytical results, the evolution of vortices from initial states which are not self-similar is discussed, and the energy transfer in a slightly-compressible vortex is considered.

vonEllenrieder, Karl↗

Adjoint-Based Design of Rotors Using the Navier-Stokes Equations in a Noninertial Reference Frame

Optimization of rotorcraft flowfields using an adjoint method generally requires a time-dependent implementation of the equations. The current study examines an intermediate approach in which a subset of rotor flowfields are cast as steady problems in a noninertial reference frame. This technique permits the use of an existing steady-state adjoint formulation with minor modifications to perform sensitivity analyses. The formulation is valid for isolated rigid rotors in hover or where the freestream velocity is aligned with the axis of rotation. Discrete consistency of the implementation is demonstrated by using comparisons with a complex-variable technique, and a number of single- and multipoint optimizations for the rotorcraft figure of merit function are shown for varying blade collective angles. Design trends are shown to remain consistent as the grid is refined.

Nielsen, Eric J.↗

π-Extended Ligands in Two-Coordinate Coinage Metal Complexes

Two-coordinate carbene-M I -amide (cMa, M I = Cu, Ag, Au) complexes have emerged as highly efficient luminescent materials for use in a variety of photonic applications, due to their extremely fast radiative rates via thermally activated delayed fluorescence (TADF) from an interligand charge transfer (ICT) process. A series of cMa derivatives were prepared to examine the variables which affect the radiative rate with the goal of understanding the parameters that control the radiative TADF process in these materials. We find that blue emissive complexes with high photoluminescence efficiency (Φ PL > 0.95) and fast radiative rates (k r = 4 x 10 6 s -1 ) can be achieved by selectively extending the π-system of the carbene and amide ligands. Of note is the role played by increasing the separation between the hole and electron in the ICT excited state. Analysis of temperature dependent luminescence data along with theoretical calculations indicate that the hole-electron separation alters the energy gap between the lowest energy singlet and triplet states (ΔE ST ) while keeping the radiative rate for the singlet state unchanged. As a result, this interpretation provides guidelines for the design of new cMa derivatives with even faster radiative rates as well as those with slower radiative rates and thus extended excited state lifetimes.

14 SOLAR ENERGY↗

Finite state modeling of aeroelastic systems

A general theory of finite state modeling of aerodynamic loads on thin airfoils and lifting surfaces performing completely arbitrary, small, time-dependent motions in an airstream is developed and presented. The nature of the behavior of the unsteady airloads in the frequency domain is explained, using as raw materials any of the unsteady linearized theories that have been mechanized for simple harmonic oscillations. Each desired aerodynamic transfer function is approximated by means of an appropriate Pade approximant, that is, a rational function of finite degree polynomials in the Laplace transform variable. The modeling technique is applied to several two dimensional and three dimensional airfoils. Circular, elliptic, rectangular and tapered planforms are considered as examples. Identical functions are also obtained for control surfaces for two and three dimensional airfoils.

Vepa, R.↗

A description of the solar wind-magnetosphere coupling based on nonlinear filters

A nonlinear filtering method is introduced for the study of the solar wind -- magnetosphere coupling and related to earlier linear techniques. The filters are derived from the magnetospheric state, a representation of the magnetospheric conditions in terms of a few global variables, here the auroral electrojet indices. The filters also couple to the input, a representation of the solar wind variables, here the rectified electric field. Filter-based iterative prediction of the indices has been obtained for up to 20 hours. The prediction is stable with respect to perturbations in the initial magnetospheric state; these decrease exponentially at the rate of 30/min. The performance of the method is examined for a wide range of parameters and is superior to that of other linear and nonlinear techniques. In the magnetospheric state representation the coupling is modeled as a small number of nonlinear equations under a time-dependent input.

Vassiliadis, D.↗

U.S. Coast Guard Boat Recovery Simulation at the NASA Ames Vertical Motion Simulator

The U.S. Coast Guard routinely uses the Over-The-Horizon (OTH-IV), a cutter deployed, rigid-hulled inflatable boat for rescue and law enforcement operations. The term "cutter" refers to a Coast Guard vessel 65 feet in length or greater with accommodations for crew to live aboard and the ability to deploy smaller boats including the OTH-IV. A deployment method employed by some cutter class vessels is a davit crane system and specialized hook mechanism to connect the smaller boat. The launch and recovery operation requires several crewmembers, where one is tasked with releasing and connecting the hook to the small boat. Manipulating the hook can pose a risk to the crewmember depending on sea conditions combined with fatigue level or task expertise. Equipment and crewmembers are tested extensively due to the inherent risk of the task, but the sea conditions cannot be controlled. To address the sea condition variable, the U.S. Coast Guard and NASA leveraged the Vertical Motion Simulator (VMS) as a platform to test new equipment or train crewmembers in varying sea conditions. With 6 degrees of freedom and a vertical displacement of +/- 22ft, the VMS is capable of simulating conditions up to sea-state 5. The proof of concept experiment took place in September 2018 and demonstrated that the VMS can accurately simulate varying sea-states, collect performance data, and design a reliable and safe system for participants. The U.S. Coast Guard provided boat displacement data from the Large Amplitude Motion Program (LAMP). The program generates multi-directional waves with a cosine squared spreading function which produced a time history response of displacement data (surge, sway, heave, roll, pitch, yaw) of the OTH-IV's center of gravity (C.G). The displacement data was differentiated into acceleration evaluated at the crewmember's position at the front (bow) of the boat. Those accelerations were transformed to the VMS coordinate system and used as command inputs to the motion system's washout filters. The VMS uses Interchangeable Cabs (ICab) to perform flight simulations on a variety of aircraft or spacecraft configurations. An ICab typically contains seats, restraints, pilot controls, instrument panel, and out-the-window projectors all enclosed in a familiar cockpit configuration. To replicate the launch and recovery of a small boat, all the conventional features of a flight simulator and canopy were removed to be replaced with a to-scale OTH-IV bow mockup. The bow section was constructed from aluminum, and a connection point known as the davit ring. Additionally, a hook replica was suspended by a cable from the ceiling as if it were hanging from a davit crane aboard a cutter vessel. The last step was providing an auxiliary control to close the distance between suspended hook and the davit ring on the bow mockup. Without control the boat would simulate the wave motion, but with no guarantee that the crewmember will be in reach of the hook. Since the wave motion was repeatable, an additional acceleration command sent to the washout filters to move the simulator in the surge, sway, and heave directions, independently. The commands were rate limited such that the additional movement was not detectable with respect to the wave motion. The results showed that for each wave profile, a unique set of acceleration commands provided opportunities for crewmembers to gain control of the hook and connect it to the davit ring.

Riccobono, Nicholas S.↗

Understanding Economic and Deployment Benefits of Wind-PV Hybrid Power Plants

The least-cost approach to decarbonizing the U.S. electricity supply will likely involve a significantly expanded share of variable renewable energy (VRE) generation. Many strategies and approaches have been identified to address integration challenges in a VRE-dominated system, including standalone and coupled battery systems. In this study, we explored the current and future potential of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Analysis results include temporal complementarity of wind and PV resources across the contiguous United States, with an emphasis on metrics that quantify reductions in variability that can be achieved through hybridization. We further use a price-taker model with simulated hourly energy and capacity prices to determine the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. We find that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60-80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility. Finally, capacity expansion modeling of PV-wind systems indicates that hybridization can reduce transmission expansion requirements associated with a heavily decarbonized U.S. electricity system.

complementarity↗