Radiation transport around axisymmetric blunt body vehicles using a modified differential approximation
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In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.
Abstract Bioenergy sorghum has high biomass yield potential, drought resilience, good nitrogen use efficiency, and a root system that contributes to the accumulation of soil organic carbon. In this study, field grown bioenergy sorghum root systems were analyzed during the growing season to characterize their depth, biomass, morphology, anatomy, and gene expression profiles. Bioenergy sorghum roots grew continuously during a 155‐day growing season producing ~175 nodal roots, accumulating ~7 Mg of dry biomass per hectare, and reaching >2 m deep in the soil profile. Nodal roots within 20 cm of the stem were 1–5 mm in diameter, whereas roots deeper in soil profiles were enriched in lateral roots with small diameters (~30–500 µm) enabling growth through soil macropores. In older field‐grown plants, roots with intact endodermal, vascular and inner root tissues were surrounded by degraded or aerenchyma‐filled epidermal and cortical cell layers. Transcriptome analysis of nodal, surface, and deep roots identified >2,500 differentially expressed genes involved in root growth, transport, adaptation, defense, and AMF–root interaction. Deep roots (180–240 cm) differentially expressed genes that regulate lateral root growth. Surface roots (0–20 cm) located mid‐row differentially expressed genes involved in nitrate transport, whereas ammonium transport genes were expressed in surface and deep roots and genes involved in phosphate transport were expressed in nodal, surface, and deep roots. Overall, bioenergy sorghum's long growing season enables root systems to grow deeper and accumulate more biomass than annual grain crops such as maize, attributes that could help restore annual cropland soil organic carbon levels and improve soil productivity. Deep roots active in nutrient transport are positioned to take‐up fertilizer leached deep into soil profiles mitigating potential nutrient run‐off. Bioenergy sorghum's large and deep root system is a key to sustainable production of biofuels, biopower, and bioproducts on annual cropland.
The Sun s global magnetic field is produced and evolved through the emergence of magnetic flux in active regions and its transport across the solar surface by the axisymmetric differential rotation and meridional flow and the non-axisymmetric convective flows of granulation, supergranulation, and giant cell convection. Maps of the global magnetic field serve as the inner boundary condition for space weather. The photospheric magnetic field and its evolution determine the coronal and solar wind structures through which CMEs must propagate and in which solar energetic particles are accelerated and propagate. Producing magnetic maps which best represent the actual field configuration at any instant requires knowing the magnetic field over the observed hemisphere as well as knowing the flows that transport flux. From our Earth-based vantage point we only observe the front-side hemisphere and each pole is observable for only six months of the year at best. Models for the surface magnetic flux transport can be used to provide updates to the magnetic field configuration in those unseen regions. In this presentation I will describe successes and failures of surface flux transport and present new observations on the structure, the solar cycle variability, and the evolution of the flows involved in magnetic flux transport. I find that supergranules play the dominant role due to their strong flow velocities and long lifetimes. Flux is transported by differential rotation and meridional flow only to the extent that the supergranules participate in those two flows.
Blue mold, caused by Penicillium spp., is an impactful postharvest disease resulting in significant economic losses due to reduced pome fruit quality and mycotoxin contamination. Using two Penicillium species with different levels of aggressiveness, transcriptomics were implemented in order to identify genes expressed during apple fruit decay and loci expressed in ungerminated conidia. Total RNA was isolated from ungerminated conidia and decayed apple fruit infected with P. expansum R19 or P. polonicum RS1. There were 2442 differentially expressed genes (DEGs) between the R19 and RS1 in apple. Comparisons within species between apple and conidia revealed 4404 DEGs for R19 and 2935 for RS1, respectively. Gene ontology (GO) analysis revealed differential regulation in fungal transport and metabolism genes during decay, suggesting a flux in nutrient acquisition and detoxification strategies. In R19, the oxidoreductase GO category comprised 20% of all DEG groups in apple verses conidia. Ungerminated conidia from both species showed DEGs encoding the glyoxylate shunt and beta-oxidation, specifying the earliest metabolic requirements for germination. This is the first study to identify pre-loaded transcripts in conidia from blue mold fungi, reveal unique genes between species expressed during apple decay, and show the expression dynamics of known fungal virulence factors. These findings will enable development of targeted approaches for blue mold abatement strategies.
By using the laser-speckle strain gauge, the strain of metal at the temperature lower than 250 C is measured. The principle of the gauge is to measure the expansion or contraction of the fine structures of surface by detecting the resultant speckle displacement in an optoelectronic way, whereby the effect of rigid-body motion is automatically cancelled out with the aid of a differential detection system. A transportable apparatus was built and a comparison experiment performed with a resistance strain gauge at room temperature. It has a strain sensitivity of .00002, a gauge length smaller than 1 mm, and no upper limit in a range of strain measurement. In the measurement of high-temperature strain it is free from the need for a dummy gauge and insensitive to an electric drift effect. As examples of strain measurement at high-temperature, thermal expansion and contraction of a top of a soldering iron are measured. The interval of the measurement can be made at shortest 1.6 sec. and the change in the strain is clearly followed until the ultimate stationary temperature is reached.
Heating distributions from analysis of the National Meteorological Center and European Center for Medium Range Weather Forecasts data sets; methods used and problems involved in the inference of diabatic heating; the relationship between differential heating and energy transport; and recommendations on the inference of heat soruces and heat sinks for the planetary show are discussed.
To relate general circulation model (GCM) hydrologic output to readily available river hydrographic data, a runoff routing scheme that routes gridded runoffs through regional- or continental-scale river drainage basins is developed. By following the basin overland flow paths, the routing model generates river discharge hydrographs that can be compared to observed river discharges, thus allowing an analysis of the GCM representation of monthly, seasonal, and annual water balances over large regions. The runoff routing model consists of two linear reservoirs, a surface reservoir and a groundwater reservoir, which store and transport water. The water transport mechanisms operating within these two reservoirs are differentiated by their time scales; the groundwater reservoir transports water much more slowly than the surface reservior. The groundwater reservior feeds the corresponding surface store, and the surface stores are connected via the river network. The routing model is implemented over the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project Mississippi River basin on a rectangular grid of 2 deg X 2.5 deg. Two land surface hydrology parameterizations provide the gridded runoff data required to run the runoff routing scheme: the variable infiltration capacity model, and the soil moisture component of the simple biosphere model. These parameterizations are driven with 4 deg X 5 deg gridded climatological potential evapotranspiration and 1979 First Global Atmospheric Research Program (GARP) Global Experiment precipitation. These investigations have quantified the importance of physically realistic soil moisture holding capacities, evaporation parameters, and runoff mechanisms in land surface hydrology formulations.
A variety of infiltration techniques can be used to fabricate solid materials, particularly composites. In general these processes can be described with at least one time dependent partial differential equation describing the evolution of the solid phase, coupled to one or more partial differential equations describing mass transport through a porous structure. This paper presents a detailed mathematical analysis of a relatively simple set of equations which is used to describe chemical vapor infiltration. The results demonstrate that the process is controlled by only two parameters, alpha and beta. The optimization problem associated with minimizing the infiltration time is also considered. Allowing alpha and beta to vary with time leads to significant reductions in the infiltration time, compared with the conventional case where alpha and beta are treated as constants.
The negative gravitropic response in the grass leaf-sheath pulvinus is a consequence of cell elongation involving all cells except those of the uppermost region of the upper flank of an horizontally oriented pulvinus. The lowermost layer of cells elongate maximally, and the regions in between elongate to intermediate extents. The resulting curvatures of a responding pulvinus can be expressed mathematically by relating the angle of curvature (theta) to the original length (L0) and the maximal length of the lower surface (L1) and the diameter of the organ (D), using the equation, theta = (L1-L0)/D, where theta is in radians. The elongation response (S) of any individual cells within the pulvinus can be expressed by the equation, S = 0.5 - r cos theta, where r is the radius of the pulvinus and theta is in degrees. Microscopic measurement of cell lengths in different regions of the pulvinus supports the mathematical predictions. Indirect support is also obtained from the use of colchicine, coumarin, dichlorobenzonitrile (DCBN) and isopropyl N-chlorophenyl carbamate which exaggerate the inherent asymmetry during gravitropic response. Coumarin and DCBN also induce thickenings in the radial walls which appear first in the statenchyma, and later, in cells located towards the outer periphery of the pulvinus. The distribution patterns of these thickenings suggest that the asymmetric growth response of the pulvinus may be due to a differential and radial, centrifugal transport of growth promotors from the central statenchyma region.
The fundamental laws of the physics of fluid flow in the continuum regime are embedded in a somewhat "simple" set of partial differential equations describing the transport of mass, momentum, energy, and/orentropy. These basic equations can be manipulated to construct other important physical quantities such as vorticity that help further elucidate flow physics. Additionally, these equations can be nondimensionalized to identify important nondimensional groups governing compressible, reacting fluid flows, most prominently Reynolds, Mach, Froude, Prandtl, Lewis, Schmidt, Damkohler, and Zeldovich numbers. In this lecture, we present these governing equations and discuss the significance of the different terms and nondimensional groups. Furthermore, since these equations cannot be solved directly on current supercomputers for turbulent flows at Reynolds numbers of engineering interest, a scale reduction by averaging or filtering is introduced, which leads to a "closure" problem. The closure is then provided by introducing some common models. The current introduction is by no means complete, but it and the references herein may serve as a good starting point for learning about the most common approaches to turbulent reacting flows.
The Brine Availability Tests in Salt is a US Department of Energy Office of Nuclear Energy supported activity as part of the Spent Fuel and Waste Disposition Campaign where we are performing simultaneous heated and control experiments in adjacent horizontal boreholes in the WIPP Salt Disposal Investigation drifts as part of experimental Phase 1. Phase 1a of BATS, a low-cost, small spatial-scale experiment performed in order to design instrumentation and methods for further experimentation in the URL, has been completed (June 2018 - May 2019) and is described elsewhere. In coincidence with multiple physical parameters that will be measured over the duration of the experiment, we will be measuring the liquid and vapor phases of H{sub 2}O as well as its isotopic content (not measured in Phase 1a). Three different forms of water occur in natural salts: as fluid in macro scale (mm size) inclusions, as intergranular free H{sub 2}O and as H{sub 2}O incorporated in hydrous minerals. Each of these forms has potentially different stable isotope signatures and will be influenced differentially by heat induced transport and by interaction with introduced tracers. Continuous measurement of vapor phase H{sub 2}O isotopes during borehole heating will be impacted by several effects: 1) evaporation as liquid brine flows into the borehole and evaporates completely or partially into the dry N{sub 2} stream; 2) steam from dehydration of hydrous minerals, that may enter the borehole; and 3) hydrous minerals that may form in the borehole (preferentially incorporating heavier isotopes). The continuous time series collected over the course of the heating test will be combined with analyses of pre-test and post-test collected samples of test site salt to investigate the contributions of each of the three water types as H{sub 2}O is mobilized due to the effects of heating. (authors)
Modeling of phenomena such as anomalous transport via fractional-order differential equations has been established as an effective alternative to partial differential equations, due to the inherent ability to describe large-scale behavior with greater efficiency than fully-resolved classical models. In this review article, we first provide a broad overview of fractional-order derivatives with a clear emphasis on the stochastic processes that underlie their use. We then survey three exemplary application areas – subsurface transport, turbulence, and anomalous materials – in which fractional-order differential equations provide accurate and predictive models. For each area, we report on the evidence of anomalous behavior that justifies the use of fractional-order models, and survey both foundational models as well as more expressive state-of-the-art models. We also propose avenues for future research, including more advanced and physically sound models, as well as tools for calibration and discovery of fractional-order models.
Although it is generally accepted that structural parameters like width, shape, and edge structure crucially affect the electronic characteristics of graphene nanoribbons (GNRs), the exact relationship between geometry and charge transport remains largely unexplored. Here, in this paper, we present in situ through-transport measurements of various topological GNRs and GNR heterostructures by lifting the ribbon with the tip of a scanning tunneling microscope. At the same time, we develop a comprehensive transport model that enables us to understand various features, such as obscuring of localized states in through transport, the effect of topology on transport, as well as negative differential conductance in heterostructures with localized electronic modes. The combined experimental and theoretical efforts described in this paper serve to elucidate general charge transport phenomena in GNRs and GNR heterostructures.
Monte Carlo radiation transport codes such as RITRACKS or Geant4 are used to simulate the interaction of ions with matter. These codes rely on sampling algorithms to determine interactions and various physical properties of particles involved in the simulations. It is crucial to develop efficient sampling algorithms since Monte Carlo radiation transport simulations can be time consuming. This work presents an efficient sampling algorithm to determine the energy of secondary electrons following ion-water interactions. The applicability and intended use of the algorithm are discussed in detail, and it is shown that the new algorithm is up to 6X10 4 times faster than the method currently used in Geant4-DNA.
Recent observations of nonlocal transport in ultraclean two-dimensional materials raised the tantalizing possibility of accessing hydrodynamic correlated transport of a many-electron state. However, it has been pointed out that nonlocal transport can also arise from impurity scattering rather than interaction. At the crux of the ambiguity is the focus on linear effects, i.e., Ohm's law, which cannot easily differentiate among different modes of transport. Furthermore we propose experiments that can reveal rich hydrodynamic features in the system by tapping into the nonlinearity of the Navier-Stokes equation. Three experiments we propose will each manifest a unique phenomenon that is well known in classical fluids: the Bernoulli effect, Eckart streaming, and Rayleigh streaming. Analysis of known parameters confirms that the proposed experiments are feasible and the hydrodynamic signatures are within reach of graphene-based devices. Experimental realization of any one of the three phenomena will provide a stepping stone to formulating and exploring the notions of nonlinear electron fluid dynamics with an eye to celebrated examples from classical nonlaminar flows, e.g., pattern formation and turbulence.
The rapid transport of specific ions through matter is critical to energy storage, membrane separations, and health. However, commercial materials resist ion transport, lack specificity, or both, making ion transport costly and ineffective. Inspiration for new material designs can be taken from biology, where membrane transport proteins exert exquisite control over the specificity and rate of ion transport. The challenge in understanding and designing transport pathways is that ions often exchange their hydrating waters for direct contacts with atoms in the transport pathway. Despite intense study over decades, no theory exists to explain local ion binding and transport mechanisms and experiments cannot differentiate reliably between ions and water in binding sites. Here, we developed a new approach, based on quantum methods and extension of the quasi-chemical free energy theory, to understand and design pathways through materials for rapid transport of specific ions. Understanding ion transport mechanisms will significantly advance our nation’s ability to develop cost-effective materials for energy sustainability and therapeutics for health.
Abstract Differentially rotating stars and planets transport angular momentum (AM) internally due to turbulence at rates that have long been a challenge to predict reliably. We develop a self-consistent saturation theory, using a statistical closure approximation, for hydrodynamic turbulence driven by the axisymmetric Goldreich–Schubert–Fricke instability at the stellar equator with radial differential rotation. This instability arises when fast thermal diffusion eliminates the stabilizing effects of buoyancy forces in a system where a stabilizing entropy gradient dominates over the destabilizing AM gradient. Our turbulence closure invokes a dominant three-wave coupling between pairs of linearly unstable eigenmodes and a near-zero frequency, viscously damped eigenmode that features latitudinal jets. We derive turbulent transport rates of momentum and heat and provide them in analytic forms. Such formulae, free of tunable model parameters, are tested against direct numerical simulations; the comparison shows good agreement. They improve upon prior quasi-linear or “parasitic saturation” models containing a free parameter. Given model correspondences, we also extend this theory to heat and compositional transport for axisymmetric thermohaline-instability-driven turbulence in certain regimes.