Disparate Scales Research Articles

Helheim Glacier ice velocity variability responds to runoff and terminus position change at different timescales

The Greenland Ice Sheet discharges ice to the ocean through hundreds of outlet glaciers. Recent acceleration of Greenland outlet glaciers has been linked to both oceanic and atmospheric drivers. Here, we leverage temporally dense observations, regional climate model output, and newly developed time series analysis tools to assess the most important forcings causing ice flow variability at one of the largest Greenland outlet glaciers, Helheim Glacier, from 2009 to 2017. We find that ice speed correlates most strongly with catchment-integrated runoff at seasonal to interannual scales, while multi-annual flow variability correlates most strongly with multi-annual terminus variability. The disparate time scales and the influence of subglacial topography on Helheim Glacier’s dynamics highlight different regimes that can inform modeling and forecasting of its future. Notably, our results suggest that the recent terminus history observed at Helheim is a response to, rather than the cause of, upstream changes.

Interpolating resident attitudes toward exurban roadside forest management

Knowledge about spatial patterns of human dimensions data within landscape ecology is nascent despite its importance in natural resources management. We explored this topic within the context of utility roadside forest management, a complex situation involving ecological, cultural, and aesthetic aspects of forests and reliable power. We applied spatial interpolation to investigate patterns of human attitudes toward roadside vegetation management data across an exurban landscape. Mail surveys (n = 1962) were used to collect social science data from residents in four areas of Connecticut, USA. For each area, three attitudes variables were evaluated for spatial autocorrelation using Moran’s I statistic. Based on identified autocorrelation distance or scale, attitudes were interpolated using inverse distance weighting. Model validation of interpolated surfaces was completed using root mean square error. Significant spatial autocorrelation was present for five of 12 study area-attitude pairings (one focused on professionalism; two focused on safety; three focused on tradeoffs between reliable power and maintaining trees) at distances ranging from 200 to 2400 m. Accuracy of interpolations varied among study areas, suggesting that the choice of spatial scale of analysis influenced model results. Social processes influencing attitudes were spatially heterogeneous, existing at disparate scales for the same variables in different locations. Collectively, “enough” roadside forest may exist to ameliorate intermittent vegetation management aesthetically, yet underlying social processes influencing roadside forest outcomes likely are not mutually exclusive. Interpolation assumptions often applied toward ecological studies did not work well for social processes studied in this analysis.

Temporal scale-bridging of chemistry in a multiscale model: Application to reactivity of an energetic material

A heterogeneous multiscale method (HMM) to evolve chemistry across disparate temporal scales is presented. The method directly couples a particle-based, microscale coarse-grain chemistry model to a macroscale continuum finite element model of deformation. The macroscale model obtains both the material equation-of-state and instantaneous chemical reaction rates through evaluation of the microscale model subject to distinct boundary conditions. The approach is demonstrated through several simulations of the energetic material 1,3,5-trinitrohexahydro-s-triazine (RDX) subject to slow heating, including a simulation inspired by the scaled thermal explosion (STEX) experiment.

Modeling fast acoustic streaming: Steady-state and transient flow solutions.

Traditionally, acoustic streaming is assumed to be a steady-state, relatively slow fluid response to passing acoustic waves. This assumption, the so-called slow streaming assumption, was made over a century ago by Lord Rayleigh. It produces a tractable asymptotic perturbation analysis from the nonlinear governing equations, separating the acoustic field from the acoustic streaming that it generates. Unfortunately, this assumption is often invalid in the modern microacoustofluidics context, where the fluid flow and acoustic particle velocities are comparable. Despite this issue, the assumption is still widely used today, as there is no suitable alternative. We describe a mathematical method to supplant the classic approach and properly treat the spatiotemporal scale disparities present between the acoustics and remaining fluid dynamics. The method is applied in this work to well-known problems of semi-infinite extent defined by the Navier-Stokes equations, and preserves unsteady fluid behavior driven by the acoustic wave. The separation of the governing equationsbetween the fast (acoustic) and slow (hydrodynamic) spatiotemporal scales are shown to naturally arise from the intrinsic properties of the fluid under forcing, not by arbitrary assumption beforehand. Solution of the unsteady streaming field equationsprovides physical insight into observed temporal evolution of bulk streaming flows that, to date, have not been modeled. A Burgers equationis derived from our method to represent unsteady flow. By then assuming steady flow, a Riccati equationis found to represent it. Solving these equationsproduces direct, concise insight into the nonlinearity of the acoustic streaming phenomenon alongside an absolute, universal upper bound of 50% for the energy efficiency in transducing acoustic energy input to the acoustic streaming energy output. Rigorous validation with respect to experimental and theoretical results from the classic literature is presented to connect this work to past efforts by many authors.

Mixed-species bacterial swarms show an interplay of mixing and segregation across scales

Bacterial swarms are a highly-researched example of natural active matter. In particular, the interplay between biological interactions and the physics underlying the swarming dynamics is of both biological and physical interest. In this paper, we study mixed swarms of Bacillus subtilis and Pseudomonas aeruginosa. We find intricate interactions between the species, showing both cooperation and segregation across different spatial and temporal scales. On one hand, even though axenic colonies grow on disparate time scale, an order of magnitude apart, the two-species swarm together, forming a single, combined colony. However, the rapidly moving populations are locally segregated, with different characteristic speeds and lengths (or cluster sizes) that depend on the ratio between the species. Comparison with controlled mutant strains suggest that both the physical and known biological differences in species characteristics may not be enough to explain the segregation between the species in the mixed swarm. We hypothesize that the heterogeneous spatial distribution is due to some mechanism that enables bacteria to recognize their own kind, whose precise origin we could not identify.

Carbon inequality in China: Novel drivers and policy driven scenario analysis

Even though carbon inequality (CI) affects international climate negotiations and regional carbon emission reduction policies, a majority of countries ignore the individual sub-national-level CI and its important drivers (e.g., efficiency, technological change, investment, and industrialization). Thus, there is an urgent need to develop relevant carbon emission reduction policies that can incorporate the effects of these drivers. In this study, we investigated the drivers of CI in China at individual provincial and national levels during 2005–2019, using a newly developed individual Gini decomposition approach and a proposed within-between production-theoretical decomposition-based Theil index; notably, the traditional Theil index approach has not significantly changed for decades, and our study is the first to modify the approach. Our results revealed that the national CI presented a general downward trend from 2005 to 2019, wherein the individual between-group and within-group subcomponents portrayed nearly linear relationships in the west region. Notably, income disparity and energy intensity disparity were the two largest positive drivers, while the between-industrial investment-output share disparity and the investment scale disparity were the most important negative drivers of CI.

Regional Economic Disparities in Europe: Time-Series Clustering of NUTS 3 Regions

The aim of this research is to identify the regional economic disparities in the level of economic wealth and its dynamics in the NUTS 3 regions in EU28 over the period from 2000 to 2017. By performing a time-series clustering analysis at NUTS 3 level, we expect to uncover the economic disparities that might have been hidden in the aggregate NUTS 2 regions. Our results indicate that at a finer spatial scale (NUTS 3 level) disparities flourish, particularly in the period after the global crisis of 2008, in which different recovery rates are observed. In general, NUTS 2 regions tend to spatially cluster at the national level and, although NUTS 3 regions show slightly this tendency as well, the spatial effect is not as strong as it is for NUTS 2 level, revealing specific behaviours of the local economies and markets that remain hidden at the aggregate NUTS 2 level.

General-relativistic quantum-kinetics neutrino transport

We developed a new general-relativistic quantum-kinetics neutrino transport code, GRQKNT, for numerical studies of quantum kinetics of non-equilibrium neutrinos in six-dimensional phase space. This code is intended for use in both local and global simulations of neutrino transport in core-collapse supernova and binary neutron star merger. It has been widely recognized that global simulations of collective neutrino oscillations, in particular fast neutrino-flavor conversions (FFC), require unfeasible computational resources due to large disparity of scales between flavor conversion and astrophysical phenomena. We propose a novel approach to tackle the issue. This paper is devoted to describe the philosophy, design, and numerical implementation of GRQKNT with a number of tests ensuring correct implementation of each module. The code is based on a discrete-ordinate Sn method, finite-difference realization of mean-field quantum kinetic equation. The transport equation is solved based on a conservative formalism, and we use a fifth-order weighted essentially non-oscillatory scheme with fourth-order TVD Runge-Kutta time-integration. The transport module is designed to work with arbitrary spacetimes and currently three different stationary spacetimes (flat spacetime, Schwarzschild black hole, and Kerr black hole) are implemented. The collision term including neutrino emission, absorption, and momentum-exchanged scatterings are also implemented into our code. The oscillation Hamiltonian consists of vacuum, matter, and self-interactions. Both two- and three neutrino-flavor scenarios can be applied. Fluid-velocity dependences in transport-, collision-, and oscillation modules, are also treated self-consistently by using two-energy-grid technique, that has been already established in our another code with full Boltzmann neutrino transport.

A workflow for hydroacoustic source analyses based on a scale-resolving flow simulation of a hubless propeller

The steady increasing noise level in the oceans caused by shipping traffic and the resulting disturbance of marine mammals enhances the need for environmentally sustainable quiet ship propulsion systems. Acoustic optimizations as well as alternative propulsion concepts are able to reduce the noise emissions of ships. In terms of alternative propeller concepts, hubless propellers are a particularly interesting object of research due to their modified blade geometry and compact design.This work builds on a workflow that allows to calculate and analyze the hydroacoustic pressure field of a marine propeller. The transient pressure and velocity fields from a stress blended eddy simulation (SBES) of the hubless propeller was used for the calculation of the resulting hydroacoustic field using the expansion about incompressible Flow (EIF) approach. The calculation of the acoustic field is performed in a second step after the calculation of the flow field, which avoids the problem of the large disparity of time and length scales between the hydrodynamic and the acoustic field quantities.In addition, coherent flow structures were filtered using the proper orthogonal decomposition (POD) method for specific analysis of the hubless propeller hydrodynamic and hydroacoustic. The acoustic source term ∂p/∂t was furthermore calculated from the POD modes and time coefficients and used for the hydroacoustic analysis in order to identify dominant source regions of individual tonalities. Thus, this research aims to provide a workflow for hydroacoustic calculation and analysis as well as an approach for optimizations of marine propellers.

Integrating a ponderomotive guiding center algorithm into a quasi-static particle-in-cell code based on azimuthal mode decomposition

High fidelity modeling of plasma based acceleration (PBA) requires the use of three dimensional, fully nonlinear, and kinetic descriptions based on the particle-in-cell (PIC) method. In PBA an intense particle beam or laser (driver) propagates through a tenuous plasma whereby it excites a plasma wave wake. Three-dimensional PIC algorithms based on the quasi-static approximation (QSA) have been successfully applied to efficiently model the interaction between relativistic charged particle beams and plasma. In a QSA PIC algorithm, the plasma response to a charged particle beam or laser driver is calculated based on forces from the driver and self-consistent forces from the QSA form of Maxwell's equations. These fields are then used to advance the charged particle beam or laser forward by a large time step. Since the time step is not limited by the regular Courant-Friedrichs-Lewy (CFL) condition that constrains a standard 3D fully electromagnetic PIC code, a 3D QSA PIC code can achieve orders of magnitude speedup in performance. Recently, a new hybrid QSA PIC algorithm that combines another speedup technique known as an azimuthal Fourier decomposition has been proposed and implemented. This hybrid algorithm decomposes the electromagnetic fields, charge and current density into azimuthal harmonics and only the Fourier coefficients need to be updated, which can reduce the algorithmic complexity of a 3D code to that of a 2D code. Modeling the laser-plasma interaction in a full 3D electromagnetic PIC algorithm is very computationally expensive due the enormous disparity of physical scales to be resolved. In the QSA the laser is modeled using the ponderomotive guiding center (PGC) approach. We describe how to implement a PGC algorithm compatible for the QSA PIC algorithms based on the azimuthal mode expansion. This algorithm permits time steps orders of magnitude larger than the cell size and it can be asynchronously parallelized. Details on how this is implemented into the QSA PIC code that utilizes an azimuthal mode expansion, QPAD, are also described. Benchmarks and comparisons between a fully 3D explicit PIC code (OSIRIS), as well as a few examples related to laser wakefield acceleration, are presented.

Analysis and design of a local time stepping scheme for LES acceleration in reactive and non-reactive flow simulations

Explicit time integration based CFD solvers suffer from restriction on the maximum allowable time step computed from the well known Courant-Friedrichs-Lewy (CFL) stability criterion. This restriction poses severe challenge in carrying out large eddy simulation (LES) of reactive and non-reactive flows, where the grid resolution is fine. The challenge of restricted time step is further augmented when dealing with large computational domains that pose a wide disparity in the system time scales. In this study, a numerical methodology is presented based on local time stepping in an overset grid framework. The attainable speedup is found to be a function of the ratio of time steps used in the sub-domains and the ratio of the number of computational degrees of freedom. The method is analyzed using global spectral analysis (GSA) and shows excellent agreement in solution accuracy with the conventional explicit time integration based solver. The impact of local time stepping on the order of accuracy and global conservation properties are also presented. This method is then applied to simulate three flow test cases to demonstrate the ability of the method to reproduce the first and second-order turbulent statistics at reduced computational time.

A Detection Approach for Floating Debris Using Ground Images Based on Deep Learning

Floating debris has a negative impact on the quality of the water as well as the aesthetics of surface waters. Traditional image processing techniques struggle to adapt to the complexity of water due to factors such as complex lighting conditions, significant scale disparities between far and near objects, and the abundance of small-scale floating debris in real existence. This makes the detection of floating debris extremely difficult. This study proposed a brand-new, effective floating debris detection approach based on YOLOv5. Specifically, the coordinate attention module is added into the YOLOv5 backbone network to help the model detect and recognize objects of interest more precisely so that feature information of small-sized and dense floating debris may be efficiently extracted. The previous feature pyramid network, on the other hand, summarizes the input features without taking into account their individual importance when fusing features. To address this issue, the YOLOv5 feature pyramidal network is changed to a bidirectional feature pyramid network with effective bidirectional cross-scale connection and weighted feature fusion, which enhances the model’s performance in terms of feature extraction. The method has been evaluated using a dataset of floating debris that we built ourselves (SWFD). Experiments show that the proposed method detects floating objects more precisely than earlier methods.

Exponential Bhatnagar-Gross-Krook integrator for multiscale particle-based kinetic simulations.

Despite the development of an extensive toolbox of multiscale rarefied flow simulators, such simulations remain challenging due to the significant disparity of collisional and macroscopic spatiotemporal scales. Our study offers a novel and consistent numerical scheme for a coupled treatment of particles advection and collision governed by the BGK evolution, honoring positivity of the velocity distribution. Our method shares its framework, in spirit, with the unified gas kinetic class of multiscale schemes. Yet it provides attractive features for particle-based stochastic simulations, readily implementable to existing direct simulation Monte Carlo codes. Two main innovations are integrated in the presented BGK particle method. The first ingredient is a high-order time integration that can be interpreted probabilistically, independent of the time step size. The next one is identifying modified particle distributions that remain invariant under the advection-relaxation evolution. We demonstrate accuracy and performance of the devised scheme for prototypic gas flows over a wide range of rarefaction parameters. Due to the resulting robustness and flexibility of the devised exponential BGK integrator, the scheme paves the way towards more affordable simulations of large-scale and multiscale rarefied gas phenomena.

On the Possible Existence of a ‘First Law of Environmental Stewardship’: How Organisations Bring Volunteers Together in Social and Geographic Space

This article contends that environmental organisations vary in type, scale and purpose in ways that help stewards self-sort into the opportunities that align with their individual motivations and environmental concerns. To explore these potential links between personal motivations and environmental organisational attributes, we rely on descriptive and inferential statistics from surveys of two partner environmental organisations: one local scale community based-organisation and one a broader scale environmental non-profit organisation, both located in Central Texas, USA. These partners were selected based on their compatible pro-environmental missions but disparate spatial scales of operation. The survey results (n=377) revealed meaningful between-organisation differences in volunteer environmental stewards, which raise the possibility of a ‘First Law of Environmental Stewardship’ whereby all stewards are related (by their values), but stewards in the same organisation are more related than stewards in different organisations. These findings expose some of the nuances of environmental volunteerism by highlighting connections between personal motivations, geographic scale, and organisation type.

Two-dimensional granular-thin plate interface for shock mitigation

The efficacy for shock mitigation of an interface between a hexagonally-packed ordered granular medium and an elastic solid — referred to as the “granular-solid interface”, is studied. The granular medium is composed of three columns of granules (with the intermediate column composed of “intruders”, i.e., of lighter granules compared to their neighbors) which are closely packed but without any initial precompression. The granular medium is in contact with a thin plate (the elastic solid) in plane stress so that only planar motions are considered. This yields a strongly nonlinear, hybrid, i.e., discrete–continuum 2D acoustical problem. A half -sine distributed shock is applied to the left granular column, and the aim is to mitigate as much as possible the shock energy transmitted to the thin plate. The discrete element (DE) method is adopted to model the granular responses which incorporate not only Hertzian (normal) contact interactions, but also frictional effects due to granule rotations. A computational algorithm based on interpolations and iterations is employed to accurately simulate the contact forces at the interface between the granular medium and the thin plate, modeled using finite element, and the numerical stability is checked at each successive (variable) time step to ensure unconditional convergence of the numerical results. It is shown that the granular medium can be designed to absorb a major portion of the applied impulsive energy. To this end a study of the energy partition in the granular interface is performed by changing the sizes and material properties of the column of intruders, and investigating the amount of impulsive energy that is eventually transmitted to the thin plate. When lighter polytetrafluoroethylene (PTFE) intruders are combined with heavier steel granules, it is shown that the impulsive energy is mostly localized in the first column of the granular medium and negligible energy reaches the thin plate. The reason for this effective shock mitigation is the disparity in the time scales between the responses of the steel granules and the PTFE intruders, which, in turn, leads to an effective impedance mismatch that confines the impulsive energy, preventing it from propagating through the interface. Moreover, being nonlinear, the shock mitigation effectiveness of the granular-solid interface is tunable with energy, with enhanced effectiveness for weaker shocks. The methods and results reported in this work pave the way for predictively designing hybrid interfaces for drastically enhanced shock mitigation, with broad engineering applications.

Bifurcation Analysis of Multiscale Malaria Model with Serratia AS1 Bacteria and Saturated Treatment

Recent experimental results have implied that Serratia AS1 bacteria efficiently suppress the development of P. falciparum, and rapidly disseminate via vertical transmission and sexual transmission throughout mosquito population. In this paper, we propose a new malaria model to investigate the roles of saturated treatment and AS1 bacteria in malaria transmission. One feature of the model is that human and mosquito populations dynamics run on disparate temporal scales. Singular perturbation techniques are used for the separation of fast and slow dynamics. It also enables us to overcome the difficulties of exploring bifurcations in higher dimensional system. We demonstrate that the reduced systems may undergo backward bifurcation, Hopf bifurcation and Bogdanov–Takens bifurcation of codimension 2, which indicates that the delayed effect for treatment has important implications for malaria control. Numerical simulations substantiate these analytical results and show epidemiological insights. Finally, the model without AS1 bacteria transmission is applied to simulate the accumulative malaria cases in Burundi. We observe that malaria may not be eliminated by a single control in Burundi. A variety of available control measures should be adopted to eradicate malaria, such as improving treatment rate, reducing the delayed effect for treatment, and possibly releasing mosquitoes that carry AS1 bacteria.

Strengthening Criteria Independence through Optimization of Alternative Value Ratio Comparisons

Every decision maker’s internal scale is different based on a myriad of possible factors unique to that decision maker. Conflicting criteria within and between alternatives in multicriteria decision making can create negative effects within the weighting schemes and amplify preference biases and scale disparities between decision makers in a group decision context. Additionally, the weighting of group decision-making frameworks can intensify the already skewed criteria values. When making judgments against requirements, it may be preferable to reduce scale trend distortions between decision makers as much as possible. Previous research supports that certain information presentation modes can significantly reduce preference bias and strengthen criteria independence against requirements through cross alternative anchoring. This paper expands that research and proposes a new optimization model for strengthening criteria independence and consensus in group decision making. Initial results indicate the proposed optimization model can significantly reduce scale distortions and smooth comparative alternative value trends between decision makers toward strengthened group consensus. Furthermore, results support the potential and opportunity for semiautonomous group consensus processes.

Preconditioned least‐squares Petrov–Galerkin reduced order models

AbstractIn this article, we introduce a methodology for improving the accuracy and efficiency of reduced order models (ROMs) constructed using the least‐squares Petrov–Galerkin (LSPG) projection method through the introduction of preconditioning. Unlike prior related work, which focuses on preconditioning the linear systems arising within the ROM numerical solution procedure to improve linear solver performance, our approach leverages a preconditioning matrix directly within the minimization problem underlying the LSPG formulation. Applying preconditioning in this way has the potential to improve ROM accuracy for several reasons. First, preconditioning the LSPG formulation changes the norm defining the residual minimization, which can improve the residual‐based stability constant bounding the ROM solution's error. The incorporation of a preconditioner into the LSPG formulation can have the additional effect of scaling the components of the residual being minimized to make them roughly of the same magnitude, which can be beneficial when applying the LSPG method to problems with disparate scales (e.g., dimensional equations, multi‐physics problems). Importantly, we demonstrate that an “ideal preconditioned” LSPG ROM (a ROM in which the preconditioner is the inverse of the Jacobian of its corresponding full order model) emulates projection of the full order model solution increment onto the reduced basis. This quantity defines a lower bound on the error of a ROM solution for a given reduced basis. By designing preconditioners that approximate the Jacobian inverse—as is common in designing preconditioners for solving linear systems—it is possible to obtain a ROM whose error approaches this lower bound. The proposed approach is evaluated on several mechanical and thermo‐mechanical problems implemented within the Albany HPC code and run in the predictive regime, with prediction across material parameter space. We demonstrate numerically that the introduction of simple Jacobi, Gauss‐Seidel, and ILU preconditioners into the proper orthogonal decomposition/LSPG formulation reduces significantly the ROM solution error, the reduced Jacobian condition number, the number of nonlinear iterations required to reach convergence, and the wall time (thereby improving efficiency). Moreover, our numerical results reveal that the introduction of preconditioning can deliver a robust and accurate solution for test cases in which the unpreconditioned LSPG method fails to converge.

A two-grid simulation framework for fast monitoring of fault stability and ground deformation in multiphase geomechanics

We present a simulation framework for fast monitoring of fault stability and ground deformation in multiphase geomechanics and demonstrate its efficacy for a joint CO2 sequestration and enhanced oil recovery case study. Fault stability is estimated by tracking the time evolution of the change in Coulomb Failure Function at critical points on the fault. The staggered solution algorithm for the coupled problem is augmented with a feature that allows for the flow and geomechanics sub-problems to be solved on two different unstructured tetrahedral grids. We demonstrate the accuracy of the two-grid method on the classical Mandel's problem. For the field scale problem, the geomechanics grid extends to the ground surface while the flow grid is truncated at a depth above which no well activity occurs and the flow field can be assumed to remain unperturbed. This framework reduces the computational burden associated with initialization of pressure and stress fields in the overburden, allows for a study of the critical interaction between overburden and faults, allows for fast renditions of flow-induced ground deformation, and allows choosing flow and geomechanics grid resolutions independently to capture disparate length scales of the underlying physics.

Multi-scale turbulence simulation suggesting improvement of electron heated plasma confinement

Turbulent transport is a key physics process for confining magnetic fusion plasma. Recent theoretical and experimental studies of existing fusion experimental devices revealed the existence of cross-scale interactions between small (electron)-scale and large (ion)-scale turbulence. Since conventional turbulent transport modelling lacks cross-scale interactions, it should be clarified whether cross-scale interactions are needed to be considered in future experiments on burning plasma, whose high electron temperature is sustained with fusion-born alpha particle heating. Here, we present supercomputer simulations showing that electron-scale turbulence in high electron temperature plasma can affect the turbulent transport of not only electrons but also fuels and ash. Electron-scale turbulence disturbs the trajectories of resonant electrons responsible for ion-scale micro-instability and suppresses large-scale turbulent fluctuations. Simultaneously, ion-scale turbulent eddies also suppress electron-scale turbulence. These results indicate a mutually exclusive nature of turbulence with disparate scales. We demonstrate the possibility of reduced heat flux via cross-scale interactions.