Simple Transport Model Research Articles

Sulfuric acid vapor and sulfur dioxide in the atmosphere of Venus as observed by the Venus Express radio science experiment VeRa

The Venus Express radio science experiment VeRa provided more than 900 neutral atmospheric profiles between the years 2006 and 2014. About 800 of these could be used for an analysis of the radio signal absorption at X-Band (wavelength: 3.6 cm), which is mainly caused by sulfuric acid vapor within the Venus atmosphere. The absorptivity profiles were converted into sulfuric acid vapor profiles. The combined measurements from the entire Venus Express mission reveal a distinct latitudinal H2SO4(g) variation. A latitudinal gradient can be observed at the topside of the H2SO4(g) layer, which is located approx. 4 km higher at equatorial latitudes compared to polar latitudes. Regions of enhanced sulfuric acid vapor abundance were found at equatorial and polar latitudes. The highest H2SO4(g) values at equatorial latitudes show mean maximal values of more than 12 ppm at around 47 km altitude. At polar latitudes mean maximal values were found at around 43 km altitude and ranged from 9 to 12 ppm. Both latitudinal regions of increased sulfuric acid vapor abundance are clearly separated by a low abundance region located at mid-latitudes with values of 5 to 7 ppm.A simplified two-dimensional transport model was developed to study the formation processes of sulfuric acid vapor accumulation at equatorial and polar latitudes. It turned out that the H2SO4(g) accumulation observed at high latitudes can be explained by precipitation of H2SO4(l) droplets that evaporate into gaseous sulfuric acid upon entering lower (warmer) altitudes. The influence of wind transport on this formation process was minor. In contrast, the H2SO4(g) accumulation observed at equatorial latitudes could be reproduced in the model by oppositely directed mass transport (upward winds and sedimentation) as well as by simplified evaporation and condensation processes. The low H2SO4(g) abundance observed at mid-latitudes was reproduced by downward winds in the model calculations.The VeRa observations were additionally used to estimate the abundance of SO2 above the cloud bottom. A latitudinal dependence was found with highest values of 90 ± 60 ppm at equatorial latitudes, compared to 150 ± 50 ppm and 160 ± 50 ppm at southern and northern polar latitudes, respectively.Both the equatorial and polar regions displayed show large variability of the H2SO4(g) and SO2 abundances from observation to observation. A weak tidal influence is also visible in the sulfuric acid vapor abundance in the equatorial region. The northern polar H2SO4(g) abundance, as well as the southern and northern SO2 abundances, exhibit distinct long-term variations.

Transporter-mediated ecdysteroid trafficking across cell membranes: A novel target for insect growth regulators

Ecdysteroids are a class of steroid hormones in arthropods that control molting and metamorphosis through interaction with intracellular nuclear receptors. In contrast to the extensive literature describing their biosynthetic pathways and signaling components, little has been known about how these hormones are traveling into and out of the cells through lipid bilayers of the cell membranes. Recently, a series of studies conducted in the fruit fly Drosophila melanogaster revealed that membrane transporters have critical functions in trafficking ecdysteroids across cell membranes, challenging the classical simple diffusion model of steroid hormone transport. Here we summarize recent advances in our understanding of membrane transporters involved in ecdysteroid signaling in Drosophila, with particular focus on Ecdysone Importer (EcI) that is involved in ecdysteroid uptake in peripheral tissues. We then discuss the potential advantage of EcI blockers as a novel pest management tool as compared to classical insect growth regulators.

Particle capture by drops in turbulent flow

Three-phase turbulent flows are crucial in a number of practical problems involving particulate abatement, from scavenging of air pollutants by precipitation to scrubbing processes. These flows are extremely rich in physics and challenging to simulate. Through direct numerical simulations of turbulence, coupled with a phase field interface description and Lagrangian particle tracking, the capture dynamics of small solid particles by large deformable drops is examined in detail. The role of the topologically changing drop interface in connection with the local turbulence structure is highlighted, and a simple transport model for predicting capture efficiency is derived.

Evidence of improvement in thermoelectric parameters of n-type Bi2Te3/graphite nanocomposite

Improvement in thermoelectric parameters is reported with graphite incorporation in n-type Bi2Te3/graphite nanocomposite systems. In-depth thermoelectric properties of nanostructured Bi2Te3/graphite composites are probed both microscopically and macroscopically using x-ray diffraction, Raman spectroscopy, inelastic neutron scattering, and measurement of the temperature dependence of thermal conductivity κ, Seebeck coefficient S, resistivity ρ, and carrier concentration nH. Raman spectroscopic analysis confirms that graphite introduces defects and disorder in the system. Graphite addition induces a large (∼17%) decrease of κ, originating from a strong phonon scattering effect. A low lattice thermal conductivity, κL, value of 0.77 W m−1 K−1, approaching the κmin value, estimated using the Cahill–Pohl model, is reported for Bi2Te3 + 1.0 wt. % graphite sample. Graphite dispersion alters the low-energy inelastic neutron scattering spectrum providing evidence for modification of the Bi2Te3 phonon density of states. Improvement in other thermoelectric parameters, viz., Seebeck coefficient and resistivity, is also reported. Theoretical modeling of electrical and thermal transport parameters is carried out and a plausible explanation of the underlying transport mechanism is provided assuming a simple model of ballistic electron transport in 1D contact channels with two different energies.

Assessing the effect of radioactive waste glass dissolution on early-stage radionuclide migration using simplified geological repository Monte Carlo transport models

The vitrification of radioactive waste within glass and subsequent disposal within a geological disposal facility (GDF) requires a comprehensive understanding of the effect of glass dissolution on GDF performance. This paper aims to analyse the effect of both high-level and intermediate-level waste (HLW and ILW) glass dissolution source terms on radionuclide release into the geosphere just above the disposal vault (the ‘crown’). Radionuclide migration was simulated in GoldSim for HLW in either granite or clay host rocks with a bentonite buffer using carbon steel or copper canisters, whereas ILW simulations considered either granite or clay host rocks, in either bentonite buffer or cement backfill, using concrete or cast-iron canisters. Glass dissolution source terms were varied by coupling GoldSim and MATLAB to modify the initial, residual, and resumption dissolution rates of the glass or by applying the analytical GRAAL model to glass dissolution. HLW glass results indicate no preference of granite over clay host rocks for a given canister type but that a copper canister is preferable to steel. ILW results suggest that a granite–bentonite–cast-iron environment yields lowest crown activities with cast-iron preferable to concrete as the canister, bentonite preferable to cement as the buffer/backfill, and granite preferable to clay as the host rock. Varying glass dissolution source terms (initial, residual, and resumption dissolution rates) had an understood effect on radionuclide migration, although changes were arguably insignificant considering peak crown activity for both HLW and ILW.

Sequential changes in ocean circulation and biological export productivity during the last glacial–interglacial cycle: a model–data study

Abstract. We conduct a model–data analysis of the marine carbon cycle to understand and quantify the drivers of atmospheric CO2 concentration during the last glacial–interglacial cycle. We use a carbon cycle box model, “SCP-M”, combined with multiple proxy data for the atmosphere and ocean, to test for variations in ocean circulation and Southern Ocean biological export productivity across marine isotope stages spanning 130 000 years ago to the present. The model is constrained by proxy data associated with a range of environmental conditions including sea surface temperature, salinity, ocean volume, sea-ice cover and shallow-water carbonate production. Model parameters for global ocean circulation, Atlantic meridional overturning circulation and Southern Ocean biological export productivity are optimized in each marine isotope stage against proxy data for atmospheric CO2, δ13C and Δ14C and deep-ocean δ13C, Δ14C and CO32-. Our model–data results suggest that global overturning circulation weakened during Marine Isotope Stage 5d, coincident with a ∼ 25 ppm fall in atmospheric CO2 from the last interglacial period. There was a transient slowdown in Atlantic meridional overturning circulation during Marine Isotope Stage 5b, followed by a more pronounced slowdown and enhanced Southern Ocean biological export productivity during Marine Isotope Stage 4 (∼ −30 ppm). In this model, the Last Glacial Maximum was characterized by relatively weak global ocean and Atlantic meridional overturning circulation and increased Southern Ocean biological export productivity (∼ −20 ppm during MIS 3 and MIS 2). Ocean circulation and Southern Ocean biological export productivity returned to modern values by the Holocene period. The terrestrial biosphere decreased by 385 Pg C in the lead-up to the Last Glacial Maximum, followed by a period of intense regrowth during the last glacial termination and the Holocene (∼ 600 Pg C). Slowing ocean circulation, a colder ocean and to a lesser extent shallow carbonate dissolution contributed ∼ −70 ppm to atmospheric CO2 in the ∼ 100 000-year lead-up to the Last Glacial Maximum, with a further ∼ −15 ppm contributed during the glacial maximum. Our model results also suggest that an increase in Southern Ocean biological export productivity was one of the ingredients required to achieve the Last Glacial Maximum atmospheric CO2 level. We find that the incorporation of glacial–interglacial proxy data into a simple quantitative ocean transport model provides useful insights into the timing of past changes in ocean processes, enhancing our understanding of the carbon cycle during the last glacial–interglacial period.

Open Fermi-Hubbard model: Landauer's versus master equation approaches

We introduce a simple model for the quantum transport of Fermi particles between two contacts connected by a lead. It generalizes the Landauer formalizm by explicitly taken into account the relaxation processes in the contacts. We calculate the contact resistance and non-equilibrium quasi-momentum distribution of the carriers in the lead and show that they strongly depend on the rate of relaxation processes.

Progress of advanced transport modeling of toroidal plasmas

Integrated modeling is required for predicting the behavior of burning plasma in fusion devices. Core plasma transport modeling is a key component which describes the time evolution of plasma profile. Between the simple 1D diffusive transport model and the large-scale microscopic turbulent transport simulation, advanced transport modeling which requires decent computational resource is desired. Two approaches, 1D fluid transport modeling and 3D kinetic transport modeling, are discussed.

On‐Surface Synthesis of Polyferrocenylene and its Single‐Chain Conformational and Electrical Transport Properties

AbstractUnlike intrinsically conductive organic polymers, which are central to organic electronics/photovoltaics, metallopolymers contain multiple redox‐active centers allowing extra control of their intriguing properties. Ferrocene polymers are particularly attractive in this regard, but research of the iconic poly(1,1′‐ferrocenylene), a main‐chain ferrocene polymer with the most densely bound redox‐active iron centers, has practically stopped because it is an insoluble and rather inhomogeneous material. Herein, its synthesis on the Ag(111) surface is reported, based on the Ullmann coupling of 1′,1″′‐diiodo‐1,1″‐biferrocene. Conformationally flexible single‐chain nanowires up to 50 nm in length, thus overcoming the limits of conventional solution polymerization, are characterized by scanning probe microscopy techniques achieving atomic resolution. Single‐chain electrical conductivity measurements are performed in the longitudinal directions revealing apparent metal‐to‐semiconductor transition (depending on the number of ferrocene units lifted from the surface). A simple transport model is established to rationalize this observation.

Simulation of THz Oscillations in Semiconductor Devices Based on Balance Equations

Instabilities of electron plasma waves in high-mobility semiconductor devices have recently attracted a lot of attention as a possible candidate for closing the THz gap. Conventional moments-based transport models usually neglect time derivatives in the constitutive equations for vectorial quantities, resulting in parabolic systems of partial differential equations (PDE). To describe plasma waves however, such time derivatives need to be included, resulting in hyperbolic rather than parabolic systems of PDEs; thus the fundamental nature of these equation systems is changed completely. Additional nonlinear terms render the existing numerical stabilization methods for semiconductor simulation practically useless. On the other hand there are plenty of numerical methods for hyperbolic systems of PDEs in the form of conservation laws. Standard numerical schemes for conservation laws, however, are often either incapable of correctly handling the large source terms present in semiconductor devices due to built-in electric fields, or rely heavily on variable transformations which are specific to the equation system at hand (e.g. the shallow water equations), and can not be generalized easily to different equations. In this paper we develop a novel well-balanced numerical scheme for hyperbolic systems of PDEs with source terms and apply it to a simple yet non-linear electron transport model.

Modelling of Transportation Process in Plane Flows with Stagnation Points

We study transport of passive tracers by plane laminar flows with stagnation points. This setup serves as a simple model of transport in porous media. Close to stagnation points, the flow velocity is much lower than on the average. Many experimental data disclose that transport through porous media is slower than predictions of the standard advection-diffusion model. Commonly, in descriptions of flows through porous media the heterogeneity of flow is disregarded, and some average velocity is adopted. To model regular arrays of flow patterns with stagnation points, we employ the construction of special flow: a combination of mapping and a sort of ceiling function with singularity. We show that, depending on the type of stagnation points, many experimentally established effects can be reproduced. This includes the linear sorption, usually described by the standard MIM model, as well as subdiffusion, described by the fractional MIM model. We also show that slow molecular diffusion does not eliminate the effects of the transport slowdown.

Deep learning emulators for groundwater contaminant transport modelling

Groundwater flow and transport models are routinely applied for contamination risk assessments and remediation plan design. The computational burden of such models has limited their application when a large number of model runs are required to conduct history-matching, sensitivity analysis, uncertainty analysis and optimisation. Deep learning has shown great potential in relaxing this limitation by emulating the process-based models for computational-intensive application. The current study investigates the feasibility of implementing deep learning emulators for a generalised flow and contaminant transport model based on the hydrogeology of an aquifer located in South Australia where contamination risk from on-shore gas development needs to be assessed. Three types of representative predictions are emulated: (i) contaminant concentration at a specific location and time (point variable), (ii) objective functions used for model calibration and uncertainty analysis (lumped variable), and (iii) contaminant breakthrough curves (sequence variable). Our study demonstrates that accurate, efficient and scalable deep learning emulators can be achieved with only a few thousand training samples for a simple transport model. Equipped with the fast-running DNN emulators, contaminant transport models can be applied in more sophisticated environmental modelling to support risk-based decision making. The study sheds light on hybrid modelling that combines the strength of process-based environmental models and data-driven machine learning models.

Thermal, spalling, and mechanical behaviour of various types of cementitious composites exposed to fire: Experimental and numerical analysis

Nowadays, new types of cementitious composites are increasingly being used for the construction of structural members. This poses a problem regarding the structural fire safety design as the thermal behaviour and mechanical properties at high temperatures of these materials are usually not known. The main aim of this paper is to investigate and present the thermal behaviour, propensity to spalling, and residual strength of various types of cementitious composites exposed to fire. Namely, the following materials are investigated: ordinary normal-weight concrete with or without fibres, light-weight aggregate (LWA) concrete with or without fibres, recycled aggregate concrete with or without fibres, LWA concrete with open structure, and two novel cementitious composites – LWA concrete containing crushed textile and foam plastic, and concrete containing mineral wool insulation shreds. Additional aim of this investigation is to resolve whether widely-used simple transport and material models are suitable for numerical simulations of thermal behaviour of unusual cementitious composites. For the purposes of the investigation, experimental program was proposed and executed, and numerical simulations were performed. The experimental program consisted of fire test of wall-panel specimens and cube specimens in a vertical furnace and of measurement of physical and mechanical properties of the investigated materials. The numerical simulations consisted of finite element analysis of temperature evolutions in the wall-panel specimens. The paper summarizes the results and conclusions of the experimental and numerical investigations. Within the paper, compressive strengths and residual compressive strengths of the investigated materials are presented and discussed. Moreover, experimentally measured thermal behaviour is analysed and compared with the thermal behaviour predicted by numerical simulations. In addition to this, spalling behaviour and surface damage of the specimens made of the investigated materials are presented and discussed. The main conclusion of this paper is that widely-used simple heat transport and material models are suitable for numerical simulations of thermal behaviour of various cementitious composites. Additional important conclusion is that concrete containing mineral wool shreds performs very well when subjected to fire.

Simple transport models for karst systems

Tracer tests are useful field methods with a wide range of applications in karst aquifers. The measured tracer breakthrough curve at a karst spring allows the estimation of the important transport properties of the karst system. The breakthrough curve is typically characterized by a long tailing and a low tracer recovery that is not captured by the classical one-dimensional advection dispersion model. Partitioning models are often used and require a large number of parameters. In the present work, simplified transport models are proposed to simulate the typical karst breakthrough curve. The model setup consists of a karst conduit that is interacting laterally with the surrounding matrix. The solute transport in both the conduit and matrix are governed by the one-dimensional advection-dispersion equation and the resulting mathematical model consists of a coupled system of differential equations. The Laplace transform method is used to derive the transport models for various flow and boundary conditions. The models are in terms of four physically meaningful parameters that represent the advection and dispersion properties of the flow in the conduit and matrix. Algebraic relationships to estimate the model parameters are also derived in terms of the key features of the breakthrough curves. The main advantage of the proposed models are their simple formulation and ability to capture the long tailing of the breakthrough curve in terms of just a few parameters. Application of the models to two real karst aquifers demonstrate their effectiveness in simulating the observed breakthrough curves and estimating the key transport parameters.

Diffuse interface modelling of reactive multi-phase flows applied to a sub-critical cryogenic jet

In order to simulate cryogenic H2−O2 jets under subcritical condition, a numerical model is constructed to solve compressible reactive multi-component flows which involve complex multi-physics processes such as moving material interfaces, shock waves, phase transition and combustion. The liquid and reactive gaseous mixture are described by a homogeneous mixture model with diffusion transport for heat, momentum and species. A hybrid thermodynamic closure strategy is proposed to construct an equation of state (EOS) for the mixture. The phase transition process is modeled by a recent fast relaxation method which gradually reaches the thermo-chemical equilibrium without iterative process. A simplified transport model is also implemented to ensure the accurate behavior in the limit of pure fluids and maintain computational efficiency. Last, a 12-step chemistry model is included to account for hydrogen combustion. Then the developed numerical model is solved with the finite volume method where a low dissipation AUSM (advection upstream splitting method) Riemann solver is extended for multi-component flows. A homogeneous reconstruction strategy compatible with the homogeneous mixture model is adopted to prevent numerical oscillations across material interfaces.Having included these elements, the model is validated on a number of canonical configurations, first for multiphase flows, and second for reactive flows. These tests allow recovery of the expected behavior in both the multiphase and reactive limits, and the model capability is further demonstrated on a 2D burning cryogenic H2−O2 jet, in a configuration reminiscent of rocket engine ignition.

Simple charge transport model for efficient search of high-mobility organic semiconductor crystals

Search for materials with high charge mobilities among the plethora of synthesizable organic semiconductors is of paramount importance for organic electronics, and virtual screening is expected to guide and streamline this process. However, a model for rapid but reliable prediction of charge mobility in organic semiconductors is still lacking. To address this challenge, a simple “diffusion-of-delocalized-polaron” model is suggested in this study. It considers the most essential factors governing the charge transport: intermolecular electronic coupling, electron-phonon interaction, charge delocalization, static and dynamic disorder. The suggested model reproduces experimental charge mobilities in various organic semiconductors remarkably well, and significantly outperforms another approach previously used for screening of organic semiconductors – the Marcus model. Moreover, charge mobility values predicted by our model are closer to the experiment than those provided by the two state-of-the-art approaches – quantum nuclear tunneling model and second-order cumulant expansion of the density matrix – and are on par with the popular transient localization theory. It is thus anticipated that the suggested model is an efficient tool for the search of high-mobility materials, revealing of structure-mobility relationships and rational design of organic semiconductors. Its possible integration with crystal structure prediction can boost the development of organic electronics.

Transition between thin film boiling and evaporation on nanoporous membranes near the kinetic limit

Nanoporous structures including single nanopores and nanoporous membranes have been utilized as a platform to study fundamental liquid-vapor phase change heat transfer (PCHT) processes as well as a promising candidate for high flux heat dissipation. Both thin film boiling and evaporation through nanoporous structures have been demonstrated to achieve high heat flux, but they are usually considered two mutually exclusive regimes operated under vastly different conditions, and the factors dictating how close the PCHT process is to the kinetic limit are elusive. In this work, we utilized a unique transition between thin film boiling and evaporation through nanoporous membranes to clarify the factors determining the heat flux and heat transfer coefficient (HTC) with respect to the kinetic limit conditions. We unambiguously showed the controllable transition from boiling to evaporation, when the liquid receded into the nanopores and provided additional driving force from capillary pumping sustained in the nanoscale pores. We showed that this transition is universal and can be understood from a simple fluid transport model for all the four types of fluids we studied, which cover a wide span of surface tension (water, ethanol, isopropanol (IPA), FC-72). More importantly, PCHT conditions at the transition points between boiling and evaporation were close to those of the kinetic limit of all these fluids. However, further increase of the heat flux beyond the transition points led to decreasing HTC and deviation from the kinetic limit, which can be attributed to the increasing vapor resistance in the vapor space and inside the nanopores. This increasing vapor resistance was also confirmed by experiments on IPA with different vapor pressures.

Bayesian Optimization of a Free-Electron Laser.

The Linac coherent light source x-ray free-electron laser is a complex scientific apparatus which changes configurations multiple times per day, necessitating fast tuning strategies to reduce setup time for successive experiments. To this end, we employ a Bayesian approach to maximizing x-ray laser pulse energy by controlling groups of quadrupole magnets. A Gaussian process model provides probabilistic predictions for the machine response with respect to control parameters, enabling a balance of exploration and exploitation in the search for the global optimum. We show that the model parameters can be learned from archived scans, and correlations between devices can be extracted from the beam transport. The result is a sample-efficient optimization routine, combining both historical data and knowledge of accelerator physics to significantly outperform existing optimizers.

Moisture Transport in Wood-Based Structural Panels under Transient Hygroscopic Conditions

Abstract Development of moisture gradients within wood and wood-based composites can result in irreversible moisture-induced damage. Accelerated weathering (AW), generally employing harsh environmental conditions, is a common tool for assessing moisture durability of wood composite products. Use of milder AW conditions, such as cyclic changes in relative humidity (RH), may be of interest to the wood-based composites industry in assessing moisture durability under more realistic conditions. The primary objective of this study was to determine whether moisture profile development in oriented strand board and plywood during cyclic RH changes could be reasonably predicted with a simple moisture transport model, which may be practical for wood-based composite industry members seeking to develop new AW protocols. The diffusion model based on Fick's second law with empirically determined moisture transport parameters fits the experimental data reasonably well for the purpose of screening RH parameters.

The Thermoelectric Properties of n-Type Bismuth Telluride: Bismuth Selenide Alloys Bi2Te3-x Se x.

Alloying bismuth telluride with antimony telluride and bismuth selenide for p- and n-type materials, respectively, improves the thermoelectric quality factor for use in room temperature modules. As the electronic and thermal transports can vary substantially, the alloy composition is a key engineering parameter. The n-type Bi2Te3-xSex alloy lags its p-type counterpart in thermoelectric performance and does not lend itself as readily to simple transport modeling which complicates engineering. Combining literature data with recent results across the entire alloy composition range, the complex electronic structure dynamics and trends in lattice thermal conductivity are explored. Spin-orbit interaction plays a critical role in determining the position and degeneracy of the various conduction band minima. This behavior is incorporated into a two-band effective mass model to estimate the transport parameters in each band. An alloy scattering model is utilized to demonstrate how phonon scattering behaves differently on either side of the intermediate ordered compound Bi2Te2Se due to chalcogen site occupancy preference. The parametrization of the electronic and thermal transports presented can be used in future optimization efforts.