Development of a rotorcraft dust-emission parameterization using a CFD model

Flights of rotorcraft over the desert floor can result in significant entrainment of particulate matter into the atmospheric boundary layer. Continuous or widespread operation can lead to local and regional impacts on visibility and air quality. To account for this pollutant source in air quality models, a parameterization scheme is needed that addresses the complex vertical distribution of dust ejected from the rotorcraft wake into the atmospheric surface layer. A method to parameterize the wind and turbulence fields and shear stress at the ground is proposed here utilizing computational fluid dynamics and a parameterized rotor model. Measurements taken from a full scale experiment of rotorcraft flight near the surface are compared to the simulation results in a qualitative manner. The simulation is shown to adequately predict the forward detachment length of the induced ground jet compared to the measured detachment lengths. However, the simulated ground vortex widths and vorticity deviate substantially from the measured values under a range of flight speeds. Results show that the method may be applicable for air quality modeling assuming slow airspeeds of the rotorcraft, with advance ratios of 0.005–0.02.     

Parameter estimation for fractional dispersion model for rivers

The fractional dispersion model for natural rivers, extended by including a first order reaction term, contains four parameters. In order to estimate these parameters a fractional Laplace transform-based method is developed in this paper. Based on 76 dye test data measured in natural streams, the new parameter estimation method shows that the fractional dispersion operator parameter F is the controlling parameter causing the non-Fickian dispersion and F does not take on an integer constant of 2 but instead varies in the range of 1.4–2.0. The adequacy of the fractional Laplace transform-based parameter estimation method is determined by computing dispersion characteristics of the extended fractional dispersion model and these characteristics are compared with those observed from 12 dye tests conducted on the US rivers, including Mississippi, Red, and Monocacy. The agreement between computed and observed dispersion characteristics is found to be good. When combined with the fractional Laplace transform-based parameter estimation method, the extended fractional dispersion model is capable of accurately simulating the non-Fickian dispersion process in natural streams.     

Optimization of ecosystem model parameters using spatio-temporal soil moisture information

Parameters in process-based terrestrial ecosystem models are often nonlinearly related to the water flux to the atmosphere, and they also change temporally and spatially. Therefore, for estimating soil moisture, process-based terrestrial ecosystem models inevitably need to specify spatially and temporally variant model parameters. This study presents a two-stage data assimilation scheme (TSDA) to spatially and temporally optimize some key parameters of an ecosystem model which are closely related to soil moisture. At the first stage, a simplified ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS), is used to obtain the prior estimation of daily soil moisture. After the spatial distribution of 0–10 cm surface soil moisture is derived from remote sensing, an Ensemble Kalman Filter is used to minimize the difference between the remote sensing model results, through optimizing some model parameters spatially. At the second stage, BEPS is reinitialized using the optimized parameters to provide the updated model predictions of daily soil moisture. TSDA has been applied to an arid and semi-arid area of northwest China, and the performance of the model for estimating daily 0–10 cm soil moisture after parameter optimization was validated using field measurements. Results indicate that the TSDA developed in this study is robust and efficient in both temporal and spatial model parameter optimization. After performing the optimization, the correlation (r²) between model-predicted 0–10 cm soil moisture and field measurement increased from 0.66 to 0.75. It is demonstrated that spatial and temporal optimization of ecosystem model parameters can not only improve the model prediction of daily soil moisture but also help to understand the spatial and temporal variation of some key parameters in an ecosystem model and the corresponding ecological mechanisms controlling the variation.     

Verification of a 3D CFD model for vertical slot fish-passes

In the present work, we verified a 3D computational fluid dynamics model for vertical slot fish-passes (VSFs) that employs the renormalization-group k-epsilon turbulence model (RNG KE) and the volume of fluid (VOF) method. We compared model calculations with experiments in two pool designs T1 and T2 of an experimental VSF and with 2D calculations using the shallow water equations (SWE) and the standard k-epsilon (2D SKE) model. Calculations of the 3D model showed (1) good agreement with experiments and 2D calculations in predicting mean flow velocities, (2) better performance in the determination of the water surface in the VSF, which is attributed to the accurate VOF method, (3) superior prediction of turbulence characteristics than the 2D model, which is due to the 3D RNG KE model that overcomes the problem of turbulence overestimation of the 2D SKE model, and to the fact that the 3D model takes into account the 3D features of the flow in the fish pass. Moreover, the present 3D calculations showed that the common assumptions in VSFs that (1) the flow is 2D, and (2) the simulation of 4 pools of a VSF is sufficient to obtain satisfactory results, are not always valid. Flow can be considered as 2D only in pool design T2 and for certain geometries and flow characteristics in pool design T1; while, eventually, all the pools of a fish pass need to be modeled to ensure accurate results. Finally, the present work illustrates the need to perform fish experiments simultaneously with flow experiments.     

Beyond eddy diffusivity: an alternative model for turbulent dispersion

Turbulent dispersion proceeds not only much faster but also in a qualitatively different manner than molecular diffusion. Yet, the majority of hydraulic, oceanic and atmospheric models rely on the concept of an eddy diffusivity. It is shown here that an alternative model can be developed to exhibit observed behavior. The new term in the diffusion equation, which is non-local, may be interpreted in terms of the probability density function (pdf) of the turbulent velocity. Different assumptions about this distribution lead to a family of models, one of which is the model proposed here and another, the classical Fickian model of diffusion. A connection is also made with models using fractional calculus.     

A CFD study of wind patterns over a desert dune and the effect on seed dispersion

In the Namib Desert seed distribution is greatly influenced by wind patterns. Existing literature regarding wind patterns over dunes focuses on two-dimensional simulations of flow over simplified dune structures. The three-dimensional geometries of the sand dunes suggests far more complex flow features exist, which are not captured by two-dimensional simulations. Computational fluid dynamics (CFD) was used to reproduce the three-dimensional near surface wind patterns around a dune with the aim to learn more about seed distribution. Field work included terrain mapping, wind speed, direction and temperature metering. The CFD results show the expected two-dimensional flow features of high pressure at the dune toe, low pressure at the crest and flow acceleration up windward slope. Also observed are some three-dimensional flow features such as a spiral vortex near the crest and transverse flow due to crest-line curvature of the dune. It was also observed how the wall shear stress differs due to the three-dimensional shape of the dune. The wall shear stress suggests that seed accumulation is more likely to occur behind trailing (down-wind) crest edges. Particle tracking showed how seeds tend to move over the dune crest and recirculate towards the crest on the lee-side. The study showed that adding the third dimension makes the simulations more complex, adds to computational requirements and increases simulation time but also provides vital flow information which is not possible with two-dimensional simulations.     

A simple model for simulation of insect pheromone dispersion within forest canopies

Synthetic pheromones and other behavioral chemicals are used by land managers to prevent insect-caused tree mortality or crop failure in forest and agricultural systems. Currently, no method exists to continuously measure pheromone concentration or movement in real-time. To improve our understanding of pheromone fate and transport under different forest canopies, results from a set of surrogate pheromone (sulfur hexafluoride tracer) experimental trials were used to evaluate a simple, instantaneous, three-dimensional Lagrangian dispersion model. The model was designed to predict both instantaneous and time-averaged pheromone concentrations. Overall, the results from the model show simulated time-averaged arc maximum concentrations within a factor of two of the observed data. The model correctly matched the sharp peaks and narrow widths of the meandering plumes observed in the instantaneous data, however the magnitude of the instantaneous peaks was often under-estimated. This model and evaluation provide the basis for a tool that can be used to guide deployment of synthetic pheromones or other semiochemicals for monitoring, mass trapping, or disruption of mating or aggregation.     

Evaluation of CFD Simulation using RANS Turbulence Models for Building Effects on Pollutant Dispersion

CFD evaluations were performed to examine the applicability of the RANS methods in simulating pollutant dispersion near, within and over three typical building configurations: (1) an isolated building, (2) a building array and (3) an urban intersection. The CFD results are compared with values obtained from wind tunnel tests. In some situations major differences between the wind tunnel tests and the CFD results were observed. The main source of difference between the CFD and wind tunnel results was inadequate modelling of local flow patterns using the RANS turbulence models. Also inappropriate evaluation of high intermittent turbulent mixing in the RANS approach may lead to either over-prediction or under-prediction of the concentration level, by up to a factor of 10, depending on the case investigated.     

A dispersion model for traffic produced turbulence in a two-way traffic scenario

Low wind speed conditions are often associated with poor air quality in urban areas, especially near roadways. Predictions of pollutant concentration under such conditions, i.e. low wind-speeds and near road locations, are, however, complicated by the role of traffic produced turbulence (TPT) on pollutant mixing and dilution. Existing dispersion models consider the effect of TPT on pollutant concentrations near roadways, accounting for parameters such as vehicle intensity, vehicle speeds, etc, but do not explicitly account for the contribution of two-way traffic interaction on the pollutant dispersion parameter. The turbulent kinetic energy (TKE) resulting from a two-way traffic condition will be higher than that with a one-way traffic pattern. Here, we obtain a simple formulation for TKE under a two-way traffic pattern from the balance of production and dissipation of turbulence. Considering the vorticity generated by the two-way traffic and determining the equivalent drag coefficient, an expression for TKE due to the two-way traffic interaction was obtained for three different traffic density regimes: light, intermediate, and heavy. The model predictions are validated by comparison with published data from a field study. An improved parameterization of the TPT considering the two-way traffic interaction effect is seen to significantly improve predictions of near roadway pollutant concentrations.     

A CFD-based wind solver for an urban fast response transport and dispersion model

In many cities, ambient air quality is deteriorating leading to concerns about the health of city inhabitants. In urban areas with narrow streets surrounded by clusters of tall buildings, called street canyons, air pollution from traffic emissions and other sources may accumulate resulting in high pollutant concentrations. For various situations, including the evacuation of populated areas in the event of an accidental or deliberate release of chemical, biological and radiological agents, it is important that models should be developed that produce urban flow fields quickly. Various computational techniques have been used to calculate these flow fields, but these techniques are often computationally intensive. Most fast response models currently in use are at a disadvantage in these cases as they are unable to correlate highly heterogeneous urban structures with the diagnostic parameterizations on which they are based. In this paper, a novel variant of the popular projection method for solving the Navier–Stokes equations has been developed and applied to produce fast and reasonably accurate parallel computational fluid dynamics (CFD) solutions for flow in complex urban areas. This model, called QUIC-CFD represents an intermediate balance between fast (on the order of minutes for a several block problem) and reasonably accurate solutions. This paper details the solution procedure and validates this model for various simple and complex urban geometries.     

Estimation of the longitudinal dispersion coefficient using a two-zone model in a channel partially covered with artificial emergent vegetation

Environmental Fluid Mechanics - Understanding scalar transport in solvents is important in chemical engineering, pollution control, and water remediation, where the longitudinal dispersion...     

A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation

Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil–vegetation–atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016.The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed.     

A dry deposition scheme for particulate matter coupled with a well-known Lagrangian Stochastic model for pollutant dispersion

Environmental Fluid Mechanics - A 3D dry deposition scheme for particulate matter (PM) is presented as a Free-Libre and Open-Source Software (FOSS) library, DePaSITIA (RSE SpA). This combines some...     

Spectrophotometric determination of trifluralin in commercial formulations and agricultural samples using factorial design

A simple spectrophotometric method was developed for determination of trifluralin in commercial formulation and food samples. The method was based on the hydrolysis of trifluralin with sodium hydroxide to form 2,6-dinitro-4-trifluoromethylaniline. The resultant aniline group was diazotized with nitrate in acidic media and the diazotized product was coupled with β-naphthol to form red colored product having λ_max 550 nm. The reaction conditions were optimized for hydrolysis as well as for the diazotization reaction. The Beer’s law was obeyed over the range of 0.2–17 μg mL⁻¹ with molar absorptivity of 1.5 × 10⁴ L mol⁻¹ cm⁻¹. The relative standard deviation was found to be 3.6%. A two level factorial design of 2³ was used for optimization of all parameters. The influence of different factors and their interactions on the final azo dye formation were also studied from these factorial designs. The method has been applied successfully for the analysis of commercial formulations and agricultural samples. The recovery for the determination of trifluralin was found to be in the range 95–97%.     

An analytical model of an urban heat island circulation in calm conditions

Environmental Fluid Mechanics - We obtain an analytical model solution to an idealization of an urban heat island (UHI) circulation—the steady shallow convective flow of a viscous stably...     

Long-term forest-floor litter dynamics in Canada's boreal forest: Comparison of two model formulations

Litter decomposition is a key component in ecosystem material cycling that determines (i) forest soil carbon (C) and nutrient content, (ii) release of carbon dioxide to the atmosphere, and (iii) generation and mass transfer of dissolved organic carbon from terrestrial to aquatic ecosystems. In this study, we provide simulations of long term forest-floor litter dynamics generated with both (i) an existing forest nutrient cycling and biomass growth model (ForNBM) with a single-pool formulation of forest-floor litter decomposition (Zhu et al., 2003. Ecol. Model. 169, 347-360), and (ii) a revised version of the model produced by substituting the single-pool formulation with a three-pool version of the formulation tested against data from litterbag experiments (FLDM; Zhang et al., 2010. Ecol. Model. 221, 1944-1953). This is done to determine the importance of subdividing the litter mass into categories of rates of decay (i.e., fast, slow, and very slow) on model accuracy. Forest-forest litter dynamics simulated with the two models are subsequently compared against field measurements collected at several northern jack pine (Pinus banksiana) stands along a southwest-northeast oriented transect (climate gradient) associated with the Boreal Forest Transect Case Study in northwest Canada. Initial comparison shows that the single-pool formulation underpredicts residual litter mass when forests are <65 years old, largely due to the improper treatment of the very slow decomposing litter component. This underprediction is resolved when the three-pool formulation is used. From a ecosystems-response point of view, the revised ForNBM (with the three-pool formulation) demonstrates that (i) forest-floor litter initially increases with forest growth and reaches a plateau once the forest matures; (ii) the forest floor stores more litter and C at the southern and warmer sites than at the northern sites; and (iii) in a similar climate regime, the forest floor stores more litter and C at productive than at nutrient-poor sites.     

Prediction of particulate air pollution from a landfill site using CFD and LIDAR techniques

Landfill sites have been the most common way of eliminating solid urban waste, as well as that of public and mining wastes. Landfill sites are a constant source of environmental pollution and wind is the most important contributing factor to air pollution, due to the erosion which it produces over the landfill site surfaces, transporting dust away from the source point. This causes serious risks for human health and general dirt in the surrounding areas of the landfill site. The result of dust air pollution produced in a landfill site is analysed through CFD3D (Computational Fluid Dynamics) by joining the LIDAR (Light Detection and Ranging) technique and Ansys CFX 10.0 software. The CFD simulations determine the wind velocity distribution on the landfill site surface and the different particle threshold friction velocities which determine the dust emission in multiphase simulations (air-particles). These simulations are validated from field data obtained in three measurement programmes for each type of landfill site surface treatment which has been studied. It was determined that the superficial landfill site treatment with the lowest air pollution is tall grass and bushes. The methodology used can be applied to the dust emission calculation in the design or evaluation of other landfill sites.     

Embedded large eddy simulation approach for pollutant dispersion around a model building in atmospheric boundary layer

In the present article, the potential of embedded large eddy simulation (ELES) approach to reliably predict pollutant dispersion around a model building in atmospheric boundary layer is assessed. The performance of ELES in comparison with large eddy simulation (LES) is evaluated in several ways. These include a number of qualitative and quantitative comparisons of time-averaged and instantaneous results with wind tunnel measurements supplemented by statistical data analyses using scatter plots and standard evaluation metrics. Results obtained by both LES and ELES approaches show very good agreement with the experiment. However, addition of turbulence to mean flow at Reynolds averaged Navier–Stokes (RANS)–LES interface in ELES approach not only increases the turbulence intensity, it also results in larger values of turbulent kinetic energy (TKE) as well as a shorter reattachment length in the wake region. Accordingly, higher levels of TKE predicted by ELES increase the local intensity of concentration leading to shorter plume shapes as compared with LES. In general, ELES shows better agreement with experiment on the surfaces of model building and also in the downstream wake region. In terms of computational costs, the CPU time required to obtain statistical values in ELES is about 49 % lower than that of LES and the number of iterations per time step is also reduced by 55 % as compared with LES.     

Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.