Simple Dispersion Model Research Articles

A Systematic Algorithm to Compute Hazardous Area Extent for Two-Phase Releases Based on an Improved Low-Dimensional (Simple) Dispersion Model

A Systematic Algorithm to Compute Hazardous Area Extent for Two-Phase Releases Based on an Improved Low-Dimensional (Simple) Dispersion Model

A simple and accurate model for attenuation and dispersion caused by squirt flow in isotropic porous rocks

Seismic waves propagating in fluid-saturated porous rocks exhibit attenuation and velocity dispersion in a broad range of frequencies. At sonic and ultrasonic frequencies, the attenuation is predominantly caused by fluid flow in cracks and grain contacts, so-called squirt flow. This physical mechanism for attenuation also may be relevant at seismic frequencies. We develop a simple and accurate analytical model for attenuation and dispersion caused by squirt flow in isotropic porous rocks. The input material properties for a specific rock model can be directly measured in a laboratory or calculated using analytical and numerical approaches. The results from our squirt flow model are compared with inherently accurate 3D numerical solutions for the same pore geometries. The analytical and numerical results are in good agreement. Furthermore, we observe that our analytical model is more accurate than the currently available analytical solution for squirt flow in isotropic porous rocks. MATLAB routines to reproduce the presented results are made available.

The Behavior of Polymeric Pipes in Drinking Water Distribution System-Comparison with Other Pipe Materials.

The inner walls of the drinking water distribution system (DWDS) are expected to be clean to ensure a safe quality of drinking water. Complex physical, chemical, and biological processes take place when water comes into contact with the pipe surface. This paper describes the impact of leaching different compounds from the water supply pipes into drinking water and subsequent risks. Among these compounds, there are heavy metals. It is necessary to prevent these metals from getting into the DWDS. Those compounds are susceptible to impacting the quality of the water delivered to the population either by leaching dangerous chemicals into water or by enhancing the development of microorganism growth on the pipe surface. The corrosion process of different pipe materials, scale formation mechanisms, and the impact of bacteria formed in corrosion layers are discussed. Water treatment processes and the pipe materials also affect the water composition. Pipe materials act differently in the flowing and stagnation conditions. Moreover, they age differently (e.g., metal-based pipes are subjected to corrosion while polymer-based pipes have a decreased mechanical resistance) and are susceptible to enhanced bacterial film formation. Water distribution pipes are a dynamic environment, therefore, the models that are used must consider the changes that occur over time. Mathematical modeling of the leaching process is complex and includes the description of corrosion development over time, correlated with a model for the biofilm formation and the disinfectants-corrosion products and disinfectants-biofilm interactions. The models used for these processes range from simple longitudinal dispersion models to Monte Carlo simulations and 3D modeling. This review helps to clarify what are the possible sources of compounds responsible for drinking water quality degradation. Additionally, it gives guidance on the measures that are needed to maintain stable and safe drinking water quality.

Application of Resuspension Data of Respirable Particles for Early Phase Inhalation Following Deposition Contamination in Radiological Emergencies.

Abstract In model experiments, wind resuspension rates, Rr, of respirable particles (<10 μm, aerodynamic diameter) and their time dependence after deposition on representatively contaminated urban surfaces were measured under real-life conditions, taking into account different weather conditions (wind velocities, precipitation) as well as countermeasures (fixation). For contamination by dry deposition of particles, short-term resuspension rates averaged over the first half hour, after exposure to wind with a friction velocity, u*, of 0.8 m s−1 ranged between 0.1% h−1 and 2% h−1 depending on the surface material, whereas after wet deposition, resuspension rates were two orders of magnitude lower. The time pattern of the resuspension rates followed a power law decrease, Rr ∝ t −μ , with values of μ close to 1. The measurements revealed a strong dependence on friction velocity, . For a larger area of 200 × 800 m2 contaminated with 106 Bq m−2 of particles in the respirable size range, applying a simple Gaussian dispersion model airborne activity concentration (Bq m−3) was calculated. On this basis, for an initial time of high windspeed, a cautious resuspension factor of Rf = 5 10−6 m−1 is derived for the first day, which diminishes inversely with time. The exposure of persons to external radiation and to inhaled airborne radioactivity is compared with examples for three radionuclides representing strong beta-, gamma- and alpha-radiation.

Evaluation of RANS-DEM and LES-DEM Methods in OpenFOAM for Simulation of Particle-Laden Turbulent Flows

CFD-DEM modelling of particle-laden turbulent flow is challenging in terms of the required and obtained CFD resolution, heavy DEM computations, and the limitations of the method. Here, we assess the efficiency of a particle-tracking solver in OpenFOAM with RANS-DEM and LES-DEM approaches under the unresolved CFD-DEM framework. Furthermore, we investigate aspects of the unresolved CFD-DEM method with regard to the coupling regime, particle boundary condition and turbulence modelling. Applying one-way and two-way coupling to our RANS-DEM simulations demonstrates that it is sufficient to include one-way coupling when the particle concentration is small (O ~ 10−5). Moreover, our study suggests an approach to estimate the particle boundary condition for cases when data is unavailable. In contrast to what has been previously reported for the adopted case, our RANS-DEM results demonstrate that simple dispersion models considerably underpredict particle dispersion and previously observed reasonable particle dispersion were due to an error in the numerical setup rather than the used dispersion model claiming to include turbulence effects on particle trajectories. LES-DEM may restrict extreme mesh refinement, and, under such scenarios, dynamic LES turbulence models seem to overcome the poor performance of static LES turbulence models. Sub-grade scale effects cannot be neglected when using coarse mesh resolution in LES-DEM and must be recovered with efficient modelling approaches to predict accurate particle dispersion.

Broadband Dielectric Characterization of High-Permittivity Rogers Substrates via Terahertz Time-Domain Spectroscopy in Reflection Mode

We report the dielectric characterization of three commercially available, high-permittivity Rogers laminates in the sub-terahertz range, by means of terahertz time-domain spectroscopy measurements in reflection mode. A transmission-line model is developed to obtain the reflectance spectra as a function of the frequency-dispersive complex relative permittivity of the substrates. The latter is fitted through optimization to a single Lorentzian term, which is shown to accurately reproduce the measured reflectance spectra. The substrates RO3010 and RT/duroid 6010.2LM exhibit significant frequency dispersion of both their relative permittivity and loss tangent. Conversely, the thermoset microwave laminate TMM10i is characterized by both a lower frequency dispersion and overall dielectric losses, thus making it a promising candidate for the design of low-profile and broadband components for novel terahertz applications. Owing to the simple Lorentzian dispersion model used for the description of the relative permittivity, the presented results can serve as a reference, and they can be directly introduced in design and optimization workflows for novel devices in emerging terahertz applications.

Further analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds

This work presents a theoretical analysis of the near-plug gas flow conditions in micro gas-solid fluidized beds based on the simple one-dimensional dispersion model. The analysis is validated by comparison with the experimental results reported in the literature. It concludes that gas flows can be considered near-plug flow only when: 1) the gas RTD curve is symmetrically shaped; 2) the product of RTD peak height E(t)h and variance σt (i.e., E(t)hσt) approximates 0.4; and 3) E(t)h is greater than 1.0 s−1 (dimensionless Eθ,max > 2.82) or σt2 < 0.25 s2 (and (dimensionless σθ2 > 0.02). This work further improves the criterion for the near-plug flow of gas in micro fluidized beds originally proposed by Geng et al. (CEJ, 351 (2018) 110–118).

Finite-temperature full random-phase approximation of bandgap narrowing in quasi-neutral regions: Theory including nonparabolicity and application to silicon and InGaAs

The bandgap narrowing (BGN) in quasi-neutral regions of semiconductors is calculated in a finite-temperature full random-phase approximation formalism based on a simple isotropic dispersion model including band nonparabolicity. The total quasi-particle shift (QPS) is determined by the exchange-correlation self-energy of the free carriers and the correlation energy of the interaction between carriers and ionized dopants. At cryogenic temperatures, the latter part results in giant shifts of the minority band edge in n-type semiconductors with a large ratio of valence to conduction band density of states, as often present in III–V materials. However, at room temperature, the BGN does not exceed common values. The reason for this behavior is explained analytically. Whereas the exchange-correlation energy of free carriers is known to be insensitive to band structure details, the nonparabolicity of the conduction band (CB) has a strong effect on the ionic QPS of the minority carriers in n-type III–V materials. It strongly reduces the BGN at cryogenic temperatures compared to the case of a parabolic CB. This is demonstrated numerically and also analytically for n-type InGaAs. The BGN in n-type silicon becomes independent of temperature at high concentrations, but in p-type silicon, a weak temperature dependence re-emerges above the Mott density, which also can be attributed to the ionic QPS of the minority electrons. The calculated BGN for quasi-neutral regions in silicon is in good agreement with earlier photoluminescence and more recent photo-conductance measurements.

Spatial Interpolation Techniques For innovative Air Quality Monitoring Systems

New technologies for air quality measurement, including real-time on-road air quality monitoring systems (ROMs), have improved the spatial resolution of data. However, measured data can miss due to restricted traffic zones. Different algorithms can estimate the missing data in these points, using available measured data in the neighbourhood. In this study, the results of the applications of an interpolation method taking into account the effect of wind direction and intensity by means of a simple dispersion model is presented. Thanks to the large amount of data provided by the innovative dynamic monitoring system (ROM), the proposed model is able to return, with a good approximation, reliable PM10 and PM2.5 concentration values, with a resolution of 1 km2.

Risk analysis of a cross-regional toxic chemical disaster by using the integrated mesoscale and microscale consequence analysis model

The rapidly growing capacity and scale of the world's petrochemical industries have forced many plants to have an even larger amount of hazardous substances. Once a serious leak occurs, the outcome of the effect zone could be very large or even uncontrollable just like the Bhopal disaster. In order to assess the risk of a cross-regional damage, this study aims to develop a model that can combine the benefits of both CFD model of the microscale simulation and the Gaussian dispersion model of the mesoscale simulation.The developed integrated model is employed on a toxic chemical tank leak accident of a process plant within an industrial park in order to explore the consequences and the risk of the toxic gas dispersion on three different scopes; one is the accident site, the second is the long-distance transmission route of the mesoscale area and the third is a target city. According to the simulation's results, it is obvious that the complexity of the structure surrounding the leaking tank will eventually affect the maximum ground concentration, the cloud shapes and cloud dilution rate, while the released gas is under dispersion. On the other hand, since the simple Gaussian dispersion model doesn't consider the above impacts, its calculation results will have many differences as compared to the realistic situation. This integrated model can be used as a tool for estimating the risk on a microscale or mesoscale areas and it can produce better results when an environmental impact analysis is required for a larger hazardous chemical process.

Seed Rain, Dispersal Distance, and Germination of the Invasive Tree Spathodea campanulata on the Island of Tahiti, French Polynesia (South Pacific)

The African tulip tree Spathodea campanulata is a major invasive species on the island of Tahiti (French Polynesia), where it has established from sea level up to montane cloud forest. This invader continues to spread across the island; however, little information is available about the seed rain and germination rate of Spathodea seeds. In this study, we quantified seed rain of Spathodea, estimated potential seed dispersal distances, and determined temperatures required for seed germination. Seed traps were positioned in a Spathodea-dominated forest and monitored over 86 days during the seed-fall period. The cumulative seed rain generated a density of 289 Spathodea seeds per square meter with a mean daily frequency of 3.3 seeds/m2 in the plot. Based on seed production estimates from canopy pod counts, we inferred that many Spathodea seeds were dispersed away from the plot, rather than being deposited locally in the Spathodea invaded plot. A simple dispersal model indicated that seeds from a single tree perched on a steep precipice are capable of dispersing across the entire island of Tahiti during strong trade winds. Laboratory germination tests of freshly collected seeds showed that the maximum germination (100%) was obtained at 25 °C while 96% germination was observed at 20 °C; however, no germination was observed at 15 °C or 12 °C after 34 days. Thus, Spathodea invasion in Tahiti may currently be limited to elevations <1,500 m due to lack of germination at cooler temperatures. The large number of seeds per adult Spathodea as well as the seed dispersal ability and high rate of germination may provide an important establishment advantage to Spathodea in the tropical rainforests of Tahiti. We unexpectedly found that 61% of Spathodea seeds that fell in seed traps were depredated before falling in the traps. It is not known whether this predispersal seed predation has reduced Spathodea's rate of spread in Tahiti.

Modeling dispersal using capture–recapture data: A comparison of dispersal models

AbstractCapture–recapture methods have been a cornerstone of field‐based dispersal ecology. However, obtaining unbiased estimates of dispersal parameters from capture–recapture data is challenging because it is impossible to survey all possible range of dispersal in the field. There are several approaches to address this critical issue of capture–recapture methods. Still, a lack of formal comparisons among these modeling approaches has confused about which is the best practice given the available dataset. Here, I compared the performance of three dispersal models using test datasets simulated under various sampling designs. In the first approach, a probability distribution (a dispersal kernel) was simply fitted to the capture–recapture data (the “simple dispersal model”). In the second approach, a truncated probability distribution was used to account for the finite range of observations (the “truncated dispersal model”). Finally, the dispersal and observation processes were coupled to consider the spatial organization of sampling designs (the “dispersal–observation model”). The simulation study provided three important insights. First, the dispersal–observation model provided reliable estimates of dispersal parameters, even under sampling designs with a few recaptures. Second, the truncated dispersal model was also effective, but only when the number of recaptures was large. Finally, the use of the simple dispersal model caused a substantial underestimation of dispersal parameters regardless of sampling designs; this modeling approach should be avoided where possible. The results of this simulation study should help choose a suitable modeling approach.

Understanding marine larval dispersal in a broadcast-spawning invertebrate: A dispersal modelling approach for optimising spat collection of the Fijian black-lip pearl oyster Pinctada margaritifera.

Fisheries and aquaculture industries worldwide remain reliant on seed supply from wild populations, with their success and sustainability dependent on consistent larval recruitment. Larval dispersal and recruitment in the marine environment are complex processes, influenced by a multitude of physical and biological factors. Biophysical modelling has increasingly been used to investigate dispersal and recruitment dynamics, for optimising management of fisheries and aquaculture resources. In the Fiji Islands, culture of the black-lip pearl oyster (Pinctada margaritifera) is almost exclusively reliant on wild-caught juvenile oysters (spat), through a national spat collection programme. This study used a simple Lagrangian particle dispersal model to investigate current-driven larval dispersal patterns, identify potential larval settlement areas and compare simulated with physical spat-fall, to inform targeted spat collection efforts. Simulations successfully identified country-wide patterns of potential larval dispersal and settlement from 2012–2015, with east-west variations between bi-annual spawning peaks and circulation associated with El Niño Southern Oscillation. Localised regions of larval aggregation were also identified and compared to physical spat-fall recorded at 28 spat collector deployment locations. Significant and positive correlations at these sites across three separate spawning seasons (r(26) = 0.435; r(26) = 0.438; r(26) = 0.428 respectively, p = 0.02), suggest high utility of the model despite its simplicity, for informing future spat collector deployment. Simulation results will further optimise black-lip pearl oyster spat collection activity in Fiji by informing targeted collector deployments, while the model provides a versatile and highly informative toolset for the fishery management and aquaculture of other marine taxa with similar life histories.

Dispersal of a forest liana into grasslands and post-establishment stand expansion

Encroachment into the moist coastal grasslands within eThekwini Municipality by Dalbergia obovata, an indigenous forest liana that forms dense monospecific stands, poses a potential biodiversity threat. Identification of the mechanisms of D. obovata diaspore dispersal from neighbouring adjacent forests, and subsequent patterns of propagation within the grasslands, was required to understand how D. obovata encroached into the grasslands. A simple wind dispersal model for D. obovata diaspores was developed to determine potential dispersal distances under different wind conditions. Field surveys were undertaken to map the distribution of plants within stands of D. obovata in the grasslands of two urban nature reserves and these were compared against historic orthophoto records to determine when establishment occurred. Stands were excavated to investigate the primary method of propagation by D. obovata once it had become established. The results of the wind dispersal modelling and field surveys showed that D. obovata dispersal was a product of the height of diaspore release and wind velocity. For successful dispersal to occur, diaspores would have to occupy positions close to the forest margin. Successful establishment of D. obovata was infrequent, and likely associated with extreme weather events, but once established, clonal propagation via roots and lateral branches resulted in expansion of the stands. The progressive expansion of the stands in the grasslands represents a threat to the grasslands.

Determination of the fundamental absorption and optical bandgap of dielectric thin films from single optical transmittance measurements.

In this work, we propose a method to retrieve the thickness and optical constants of dielectric thin films from single optical transmittance measurements. The method is based on the envelope method and requires a simple dispersion model for the real part of the refractive index with few fitting parameters, while the absorption coefficient can be determined without the aid of a dispersion model. The wavelength-dependent optical constants can be obtained even from spectra that exhibit few interference fringes. We have tested the method with simulated and real transmittance data from thin films in the spectral range covering the fundamental absorption. In order to assess the method's reliability to retrieve the optical constants and optical bandgap, a comparison is performed with the method by Chambouleyron, known as the Pointwise Unconstrained Minimization Approach, and a fit using the Cody-Lorentz dispersion model. We evaluate the methods' capability to retrieve the fundamental absorption and optical bandgap, and their compromise with film thickness accuracy. Finally, the methods are tested and contrasted using optical transmittance of three different semiconductor material thin films.

Compensation of Dispersion in Sinuous Antennas for Polarimetric Ground Penetrating Radar Applications

In order to improve the accuracy of subsurface target classification with ground penetrating radar (GPR) systems, it is desired to transmit and receive ultra-wide band pulses with varying combinations of polarization (a technique referred to as polarimetry). The sinuous antenna exhibits such desirable properties as ultra-wide bandwidth, polarization diversity, and low-profile form factor, making it an excellent candidate for the radiating element of such systems. However, sinuous antennas are dispersive since the active region moves with frequency along the structure, resulting in the distortion of radiated pulses. This distortion may be compensated in signal processing with accurately simulated or measured antenna phase information. However, in a practical GPR, the antenna performance may deviate from that simulated, accurate measurements may be impractical, and/or the dielectric loading of the environment may cause deviations. In such cases, it may be desirable to employ a simple dispersion model based on antenna design parameters which may be optimized in situ. This paper explores the dispersive properties of the sinuous antenna and presents a simple, adjustable, model that may be used to correct dispersed pulses. The dispersion model is successfully applied to both simulated and measured scenarios, thereby enabling the use of sinuous antennas in polarimetric GPR applications.

AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification

The measurement of methane emissions from landfills is important to the understanding of landfills’ contribution to greenhouse gas emissions. The Tracer Dispersion Method (TDM) is becoming widely accepted as a technique, which allows landfill emissions to be quantified accurately provided that measurements are taken where the plumes of a released tracer-gas and landfill-gas are well-mixed. However, the distance at which full mixing of the gases occurs is generally unknown prior to any experimental campaign.To overcome this problem the present paper demonstrates that, for any specific TDM application, a simple Gaussian dispersion model (AERMOD) can be run beforehand to help determine the distance from the source at which full mixing conditions occur, and the likely associated measurement errors. An AERMOD model was created to simulate a series of TDM trials carried out at a UK landfill, and was benchmarked against the experimental data obtained. The model was used to investigate the impact of different factors (e.g. tracer cylinder placements, wind directions, atmospheric stability parameters) on TDM results to identify appropriate experimental set ups for different conditions.The contribution of incomplete vertical mixing of tracer and landfill gas on TDM measurement error was explored using the model. It was observed that full mixing conditions at ground level do not imply full mixing over the entire plume height. However, when full mixing conditions were satisfied at ground level, then the error introduced by variations in mixing higher up were always less than 10%.

Long-path measurements of pollutants and micrometeorology over Highway 401 in Toronto

Abstract. Traffic emissions contribute significantly to urban air pollution. Measurements were conducted over Highway 401 in Toronto, Canada, with a long-path Fourier transform infrared (FTIR) spectrometer combined with a suite of micrometeorological instruments to identify and quantify a range of air pollutants. Results were compared with simultaneous in situ observations at a roadside monitoring station, and with output from a special version of the operational Canadian air quality forecast model (GEM-MACH). Elevated mixing ratios of ammonia (0–23 ppb) were observed, of which 76 % were associated with traffic emissions. Hydrogen cyanide was identified at mixing ratios between 0 and 4 ppb. Using a simple dispersion model, an integrated emission factor of on average 2.6 g km−1 carbon monoxide was calculated for this defined section of Highway 401, which agreed well with estimates based on vehicular emission factors and observed traffic volumes. Based on the same dispersion calculations, vehicular average emission factors of 0.04, 0.36, and 0.15 g km−1 were calculated for ammonia, nitrogen oxide, and methanol, respectively.

Fluctuation Scaling, Calibration of Dispersion, and Detection of Differences.

Fluctuation scaling describes the relationship between the mean and standard deviation of a set of measurements. An example is Horwitz scaling, which has been reported from interlaboratory studies. Horwitz and similar studies have reported simple exponential and segmented scaling laws with exponents (α) typically between 0.85 (Horwitz) and 1 when not operating near a detection limit. When approaching a detection limit, the exponents change and approach an apparently Gaussian (α = 0) model. This behavior is often presented as a property of interlaboratory studies, which makes controlled replication to understand the behavior costly to perform. To assess the contribution of instrumentation to larger scale fluctuation scaling, we measured the behavior of two inductively coupled plasma atomic emission spectrometry (ICP-AES) systems, in two laboratories measuring thulium using two emission lines. The standard deviation universally increased with the uncalibrated signal, indicating the system was heteroscedastic. The response from all lines and both instruments was consistent with a single exponential dispersion model having parameters α = 1.09 and β = 0.0035. No evidence of Horwitz scaling was found, and there was no evidence of Poisson noise limiting behavior. The "Gaussian" component was a consequence of background subtraction for all lines and both instruments. The observation of a simple exponential dispersion model in the data allows for the definition of a difference detection limit (DDL) with universal applicability to systems following known dispersion. The DDL is the minimum separation between two points along a dispersion model required to claim they are different according to a particular statistical test. The DDL scales transparently with the mean and works at any location in a response function.

Chemical Measurement and Fluctuation Scaling.

Fluctuation scaling reports on all processes producing a data set. Some fluctuation scaling relationships, such as the Horwitz curve, follow exponential dispersion models which have useful properties. The mean-variance method applied to Poisson distributed data is a special case of these properties allowing the gain of a system to be measured. Here, a general method is described for investigating gain (G), dispersion (β), and process (α) in any system whose fluctuation scaling follows a simple exponential dispersion model, a segmented exponential dispersion model, or complex scaling following such a model locally. When gain and dispersion cannot be obtained directly, relative parameters, GR and βR, may be used. The method was demonstrated on data sets conforming to simple, segmented, and complex scaling. These included mass, fluorescence intensity, and absorbance measurements and specifications for classes of calibration weights. Changes in gain, dispersion, and process were observed in the scaling of these data sets in response to instrument parameters, photon fluxes, mathematical processing, and calibration weight class. The process parameter which limits the type of statistical process that can be invoked to explain a data set typically exhibited 0 < α < 1, with α > 4 possible. With two exceptions, calibration weight class definitions only affected β. Adjusting photomultiplier voltage while measuring fluorescence intensity changed all three parameters (0 < α < 0.8; 0 < βR < 3; 0 < GR < 4.1). The method provides a framework for calibrating and interpreting uncertainty in chemical measurement allowing robust comparison of specific instruments, conditions, and methods.