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1.
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2.
A numerical stochastic model is developed for the upcrossing rate across a specified threshold concentration. The model assumes that the concentration time series at a given spatial point within a dispersing plume can be approximated as a first-order Markovian process designed to be consistent with a given time-invariant concentration probability density function (pdf). The model requires only the specification of a concentration pdf with a given mean and variance and a concentration fluctuation integral time scale. Predicted upcrossing rates are compared with atmospheric plume concentration data obtained from a point source near the ground. For this data set, a log-normal pdf is found to give better estimates of the threshold crossing rate than a gamma pdf.  相似文献   

3.
Results are presented from an experimental investigation of turbulent dispersion of a saline plume of large Schmidt number (Sc=830) in a turbulent boundary-layer shear flow simulated in a laboratory water channel. The dispersion measurements are obtained in a neutrally buoyant plume from an elevated point source over a range of downstream distances, where both plume meandering and fine-structure variations in the instantaneous plume are important. High-resolution measurements of the scalar fluctuations in the plume are made with a rake of conductivity probes from which probability distributions of concentration at various points throught the plume are extracted from the time series.Seven candidate probability distributions were tested, namely, the exponential, lognormal, clipped normal, gamma, Weibull, conjugate beta, andK-distributions. Using the measured values of the conditional mean concentration, , and the conditional fluctuation intensity,i p , the Weibull distribution provided the best match to the skewness and kurtosis over all downstream fetches. The skewness and kurtosis were always overpredicted by the lognormal probability density function (pdf), and underpredicted by the gamma pdf. The conjugate beta distribution for which the model parameters are determined using a method of moments based on the fluctuation intensity,i p , and skewness,S p , was capable of modeling the distribution of scalar concentration over a wide range of positions in the plume.  相似文献   

4.
Measurements have been made of concentration fluctuations in a dispersing plume from an elevated point source in the atmospheric surface layer using a recently developed fast-response photoionization detector. This detector, which has a frequency response (–6 dB point) of about 100 Hz, is shown to be capable of resolving the fluctuation variance contributed by the energetic subrange and most of the inertial-convective subrange, with a reduction in the fluctuation variance due to instrument smoothing of the finest scales present in the plume of at most 4%.Concentration time series have been analyzed to obtain the statistical characteristics of both the amplitude and temporal structure of the dispersing plume. We present alongwind and crosswind concentration fluctuation profiles of statistics of amplitude structure such as total and conditional fluctuation intensity, skewness and kurtosis, and of temporal structure such as intermittency factor, burst frequency, and mean burst persistence time. Comparisons of empirical concentration probability distributions with a number of model distributions show that our near-neutral data are best represented by the lognormal distribution at shorter ranges, where both plume meandering and fine-scale in-plume mixing are equally important (turbulent-convective regime), and by the gamma distribution at longer ranges, where internal structure or spottiness is becoming dominant (turbulent-diffusive regime). The gamma distribution provides the best model of the concentration pdf over all downwind fetches for data measured under stable stratification. A physical model is developed to explain the mechanism-induced probabilistic schemes in the alongwind development of a dispersing plume, that lead to the observed probability distributions of concentration. Probability distributions of concentration burst length and burst return period have been extracted and are shown to be modelled well with a powerlaw distribution. Power spectra of concentration fluctuations are presented. These spectra exhibit a significant inertial-convective subrange, with the frequency at the spectral peak decreasing with increasing downwind fetch. The Kolmogorov constant for the inertial-convective subrange has been determined from the measured spectra to be 0.17±0.03.  相似文献   

5.
The effects of source size on plume behaviour have been examined in a 1.2 m wind tunnel boundary layer for isokinetic sources with diameters from 3 to 35 mm at source heights of 230 mm and at ground level. Experimental measurements of mean concentration and the variance, intermittency and probability density functions of the concentration fluctuations were obtained. In addition, a fluctuating Gaussian plume model is presented which reproduces many of the observed features of the elevated emission. The mean plume width becomes independent of source size much more rapidly than the instantaneous plume width. Since it is the meandering of the instantaneous plume which generates most of the concentration fluctuations near the source, these are also dependent on source size. The flux of variance in the plume reaches a maximum, whose value is greatest for the smallest source size, close to the source and thereafter is monotonically decreasing. The intermittency factor reaches a minimum, whose value is lowest for the smallest source, and increases back towards one. Concentration fluctuations for the ground-level source are much less dependent on source size due to the effects of the surface.  相似文献   

6.
The dynamical characteristics of concentration fluctuations in a dispersing plume over the energetic and inertial-convective range of scales of turbulent motion are studied using a multiscale analysis technique that is based on an orthonormal wavelet representation. It is shown that the Haar wavelet concentration spectrum is similar to the Fourier concentration spectrum in that both spectra exhibit an extensive inertial-convective subrange spanning about two decades in frequency, with a scaling exponent of -5/3. Analysis of the statistical properties (e.g., fluctuation intensity, skewness, and kurtosis) of the concentration wavelet coefficients (i.e., the concentration discrete detailed signal) suggests that the small scales are always more intermittent than the large scales. The degree of intermittency increases monotonically with decreasing scale within the inertial-convective subrange, reaching a plateau at the very small scales associated with the beginning of the near-dissipation subrange. The probability density function (pdf) of the concentration discrete detailed signal displays stretched exponential tails with an intermittency exponent (tail slope) q that increases as a , where is the scale or dilation and a is a power-law exponent that is dependent on downwind distance, plume height, and stratification strength with typical values in the range from about 0.25 to 0.35. It is shown that the concentration variance cascade process requires a phase coherency of eddies between different scales at the small-scale end of the inertial-convective subrange.The variation of the concentration wavelet statistics with height above the ground is investigated. The increased mean shear near the ground smooths the fine-scale plume structure for scales within the inertial-convective subrange, producing a weaker spatiotemporal intermittency in the concentration field compared to that measured higher up in the plume. The pdf of the concentration detailed signal at a fixed scale possesses less elongated tails with decreasing height z. The intermittency exponent q is found to decrease roughly linearly with increasing z.Finally, the results of the wavelet decomposition are combined to provide a conceptual model of the turbulent transport, stirring, and mixing regimes in a dispersing plume. The implications of the results for contaminant texture in a plume are discussed.  相似文献   

7.
A meandering plume model that explicitly incorporates the effects of small-scale structure in the instantaneous plume has been formulated. The model requires the specification of two physically based input parameters; namely, the meander ratio,M, which is dependent on the ratio of the meandering plume dispersion to the instantaneous relative plume dispersion and, a relative in-plume fluctuation measure,k, that is related inversely to the fluctuation intensity in relative coordinates. Simple analytical expressions for crosswind profiles of the higher moments (including the important shape parameters such as fluctuation intensity, skewness, and kurtosis) and for the concentration pdf have been derived from the model. The model has been tested against some field data sets, indicating that it can reproduce many key aspects of the observed behavior of concentration fluctuations, particularly with respect to modeling the change in shape of the concentration pdf in the crosswind direction.List of Symbols C Mean concentration in absolute coordinates - C r Mean concentration in relative coordinates - C0 Centerline mean concentration in absolute coordinates - C r,0 Centerline mean concentration in relative coordinates - f Probability density function of concentration in absolute coordinates - f c Probability density function of plume centroid position - f r Probability density function of concentration in relative coordinates - i Absolute concentration fluctuation intensity (standard deviation to mean ratio) - i r Relative concentration fluctuation intensity (standard deviation to mean ratio) - k Relative in-plume fluctuation measure:k=1/i r 2 - K Concentration fluctuation kurtosis - M Meander ratio of meandering plume variance to relative plume variance - S Concentration fluctuation skewness - x Downwind distance from source - y Crosswind distance from mean-plume centerline - z Vertical distance above ground - Instantaneous (random) concentration - Crosswind dispersion ofnth concentration moment about zero - ny Mean-plume crosswind (absolute) dispersion - y Plume centroid (meandering) dispersion in crosswind direction - y,c Instantaneous plume crosswind (relative) dispersion - Normalized mean concentration in absolute coordinates:C/C 0 - Particular value taken on by instantaneous concentration,   相似文献   

8.
Concentration probability density functions (pdfs) calculated according to fluctuating plume models in one- and two-dimensions, representing the limiting cases of one-dimensional dispersion from a line source or a point source in strongly anisotropic turbulence and of axisymmetric dispersion from a point source in isotropic turbulence, are discussed and analyzed in terms of the location of the sampling point within the mean plume and of the ratio, s/m, of the standard deviations for relative dispersion and meandering.In both cases, the pdfs cover the finite concentration range from zero to C 0, the centreline concentration of the instantaneous plume. The main difference between them is that whereas the 2-D pdf is always unimodal, the 1-D pdf has a singularity at C 0 which under some circumstances results in a bimodal form. However, the probability associated with this singularity is not always significant. Differences of practical importance in the shape of the pdfs occur mainly for centreline or near-centreline sampling locations when meandering is not too much larger than relative dispersion (1 < m 2/s2 < 10) and for sampling locations a distance of order s from the centreline when relative dispersion is not too much larger than meandering (1 < s 2/m2 < 5).Comparison against wind tunnel measurements not too far downstream of a line source in grid turbulence shows that the 1-D model reproduces the essential features and trends of the measurements. Under appropriate circumstances the measurements show the bimodal pdf predicted by the 1-D model (but not by the 2-D model) confirming that the effect of the anisotropy in the source distribution is observable.Present address: School of Mechanical Engineering, Aristotle University, Thessaloniki, 54006 Thessaloniki, Greece.  相似文献   

9.
A meandering plume model that explicitly incorporatesinternal fluctuations has been developed and used to model the evolutionof concentration fluctuations in point-source plumes in grid turbulenceobtained from a detailed water-channel simulation. This fluctuating plumemodel includes three physical parameters: the mean plume spread in fixedcoordinates, which represents the outer plume length scale; the meaninstantaneous plume spread in coordinates attached to the instantaneousplume centroid, which represents the inner plume length scale; and, theconcentration fluctuation intensity in the meandering reference frame,which represents the in-plume fluctuation scale. These parameters arespecified in terms of a set of coupled dynamical equations that modeltheir development with downstream distance from the source. Explicitexpressions for the concentration moments of arbitrary integral orderand the concentration probability density function have been obtainedfrom the fluctuating plume model. Detailed comparisons of model predictionsagainst water-channel measurements for the first four concentrationmoments and the concentration probability distributions generally showvery good overall quantitative agreement. Exact quantitative conditions,expressed in terms of the physical parameters of the fluctuating plumemodel, have been derived for the emergence of off-centreline peaks inthe concentration variance profile. These quantitative conditions havebeen illustrated in terms of a diagram of states of the dispersing plume,and the qualitatively different regimes of plume concentration variancebehaviour on this state diagram have been identified and characterized.  相似文献   

10.
This paper presents a new model of concentration fluctuations for neutrally buoyant gas clouds dispersing in a wind tunnel. It is derived from a series of exact results, which apply in the hypothetical case when there is no molecular diffusion, coupled with a probability density function model previously used to describe steady releases of contaminant. A simple self-similar relationship between the evolution of the concentration intensity and mean is established. As a first step the time independent variant of the model, applicable to a continuous plume, is tested against some previously published experimental data for steady wind-tunnel releases. Comparisons of experimental results and model predictions at different downwind positions, heights and source geometry are presented. Then, the results for the time dependent model, applicable to instantaneous releases, are discussed. The experimental evidence presented here supports the self-similar relationship established earlier. The implications for modelling higher moments of concentration and the fixed point probability density function are investigated.  相似文献   

11.
The assumptions and predictions of four diffusion-deposition models are compared, and two simple plume depletion models are recommended. One model applies an analytical, constant eddy-diffusivity solution of the advection-diffusion equation as a deposition correction to the general Gaussian plume model. Predictions of this model compare moderately well with those of the surface depletion model, an exact treatment of plume depletion, and it is particularly useful for estimating the transport and deposition of settling particles. The second model is a correction to the simple source depletion model that also accounts for the change in the vertical concentration profile caused by deposition. The computational requirements of this model are similar to those of the unmodified source depletion model, while its predictions near the surface are very close to those of the surface depletion model.  相似文献   

12.
This paper describes a study of the vertical structure of concentration fluctuations in a neutrally buoyant plume from an elevated point source in slightly convective to moderately stable meteorological conditions at ranges of between 12.5 and 100 m for a range of source heights between 1 and 5 m. Observations were made of concentration fluctuations in a dispersing plume using a vertical array of sixteen very fast-response photoionization detectors placed at heights between 0.5 and 16 m. Vertical profiles of a number of concentration statistics were extracted, namely, mean concentration, fluctuation intensity, intermittency factor, peak-to-mean concentration ratio, mean dissipation rate of concentration variance, and various concentration time and length scales of dominant motions in the plume (e.g., integral macro-scale, in-plume mid-scale and Taylor micro-scale). The profiles revealed a similarity to corresponding crosswind profiles for a fully elevated plume, but showed greater and greater departure from the latter shapes once the plume had grown in the vertical so that its lower dege began to interact progressively more strongly with the ground. The evolution of the concentration probability density function at a fixed range, but with decreasing height from the ground, is similar to that obtained at a fixed height but with increasing distance from the source. Concentration power spectra obtained at different heights all had an extensive inertial-convective subrange spanning at least two decades in frequency, but spectra measured near the ground had a greater proportion of the total concentration variance in the lower frequencies (energetic subrange), with a correspondingly smaller proportion in the higher frequencies (inertial-convective subrange). It is believed that these effects result from the increased mean shear near the surface, and blocking by the surface. The effect of enhanced shear-induced molecular diffusion on concentration fluctuations is examined.  相似文献   

13.
Measurements of concentration fluctuation intensity, intermittency factor, and integral time scale were made in a water channel for a plume dispersing in a well-developed, rough surface, neutrally stable, boundary layer, and in grid-generated turbulence with no mean velocity shear. The water-channel simulations apply to full-scale atmospheric plumes with very short averaging times, on the order of 1–4 min, because plume meandering was suppressed by the water-channel side walls. High spatial and temporal resolution vertical and crosswind profiles of fluctuations in the plume were obtained using a linescan camera laser-induced dye tracer fluorescence technique. A semi-empirical algebraic mean velocity shear history model was developed to predict these concentration statistics. This shear history concentration fluctuation model requires only a minimal set of parameters to be known: atmospheric stability, surface roughness, vertical velocity profile, and vertical and crosswind plume spreads. The universal shear history parameter used was the mean velocity shear normalized by surface friction velocity, plume travel time, and local mean wind speed. The reference height at which this non-dimensional shear history was calculated was important, because both the source and the receptor positions influence the history of particles passing through the receptor position.  相似文献   

14.
The fluctuations of the instantaneous values of line integrated concentrations across plumes from point sources diffusing in turbulent shear flows, and in grid generated turbulence, have been studied experimentally using a fast response system which measured the attenuation of the intensity of an infrared beam crossing the plume. Analysis of the measurements show that the dimensionless statistical properties of the fluctuations at different distances from the source at each flow are approximately similar, in the sense that they depend primarily on the relative off-center location of the line of integration and almost independent of the distance from the source and the nature of the turbulence in the flows, as long as the characteristic length of the mean plume is not large compared to the size of the large eddies. The characteristic time of the fluctuations, on the other hand, was found to grow with the distance from the source and the autocorrelations of the fluctuations, particularly in the case of a plume diffusing in grid generated turbulence, were it found to be proportional to the lateral size of the mean plume. A—5/3 decay law of the power spectrum of the fluctuations was observed in the low frequency range which corresponds to the scale of the large eddies. The decay of the fluctuations caused by smaller eddies was much faster, as expected.  相似文献   

15.
A Lagrangian particle dispersion model (LPDM) driven by velocity fields from large-eddy simulations (LESs) is used to determine the mean and variability of plume dispersion in a highly convective planetary boundary layer (PBL). The total velocity of a “particle” is divided into resolved and unresolved or random (subfilter scale, SFS) velocities with the resolved component obtained from the LES and the SFS velocity from a Lagrangian stochastic model. This LPDM-LES model is used to obtain an ensemble of dispersion realizations for calculating the mean, root-mean-square (r.m.s.) deviation, and fluctuating fields of dispersion quantities. An ensemble of 30 realizations is generated for each of three source heights: surface, near-surface, and elevated. We compare the LPDM calculations with convection tank experiments and field observations to assess the realism of the results. The overall conclusion is that the LPDM-LES model produces a realistic range of dispersion realizations and statistical variability (i.e., r.m.s. deviations) that match observations in this highly convective PBL, while also matching the ensemble-mean properties. This is true for the plume height or trajectory, vertical dispersion, and the surface values of the crosswind-integrated concentration (CWIC), and their dependence on downstream distance. One exception is the crosswind dispersion for an elevated source, which is underestimated by the model. Other analyses that highlight important LPDM results include: (1) the plume meander and CWIC fluctuation intensity at the surface, (2) the applicability of a similarity theory for plume height from a surface source to only the very strong updraft plumes—not the mean height, and (3) the appropriate variation with distance of the mean surface CWIC and the lower bound of the CWIC realizations for a surface source.  相似文献   

16.
As a result of several air quality model evaluation exercises involving a large number of source scenarios and types of models, it is becoming clear that the magnitudes of the uncertainties in model predictions are similar from one application to another. When considering continuous point sources and receptors at distances of about 0.1 km to 1 km downwind, the uncertainties in ground-level concentration predictions lead to typical mean biases of about ±20 to 40% and typical relative root-mean-square errors of about 60 to 80%. In fact, in two otherwise identical model applications at two independent sites, it is not unusual for the same model to overpredict by 50% at one site and underpredict by 50% at the second site. It is concluded that this fundamental level of model uncertainty is likely to exist due to data input errors and stochastic fluctuations, no matter how sophisticated a model becomes. The tracer studies that lead to these conclusions and have been considered in this study include: (1) tests of the Offshore and Coastal Dispersion (OCD) model at four coastal sites; (2) tests of the Hybrid Plume Dispersion Model (HPDM) at five power plants; (3) tests of a similarity model for near-surface point source releases at four sites; and (4) tests of 14 hazardous gas models at eight sites including six sets of experiments where dense gases were released.  相似文献   

17.
An expression for concentration fluctuations in a smoke plume is derived from airborne measurements ofNO X. A linear relation between the standard deviation of the fluctuations around a Gaussian concentration profile and the average gradient in the concentrations is assumed. With this relation the probability density function of expectedNO 2 concentrations at 3 km from a source ofNO X is modelled under the assumption of photostatic equilibrium, and is compared with measurements. A parametrisation for the concentration fluctuations of std(C)= 26(+/–7)*dc/dr is proposed (r in metres). CalculatedNO 2 distributions are in reasonable agreement with the measurements and the averageNO 2 concentration appeared not to be affected by the concentration fluctuations in theNO X concentration. The spatial resolution of all measurements was 40 m.  相似文献   

18.
The dispersion of a point-source release of a passive scalar in a regular array of cubical, urban-like, obstacles is investigated by means of direct numerical simulations. The simulations are conducted under conditions of neutral stability and fully rough turbulent flow, at a roughness Reynolds number of Re τ  = 500. The Navier–Stokes and scalar equations are integrated assuming a constant rate release from a point source close to the ground within the array. We focus on short-range dispersion, when most of the material is still within the building canopy. Mean and fluctuating concentrations are computed for three different pressure gradient directions (0°, 30°, 45°). The results agree well with available experimental data measured in a water channel for a flow angle of 0°. Profiles of mean concentration and the three-dimensional structure of the dispersion pattern are compared for the different forcing angles. A number of processes affecting the plume structure are identified and discussed, including: (i) advection or channelling of scalar down ‘streets’, (ii) lateral dispersion by turbulent fluctuations and topological dispersion induced by dividing streamlines around buildings, (iii) skewing of the plume due to flow turning with height, (iv) detrainment by turbulent dispersion or mean recirculation, (v) entrainment and release of scalar in building wakes, giving rise to ‘secondary sources’, (vi) plume meandering due to unsteady turbulent fluctuations. Finally, results on relative concentration fluctuations are presented and compared with the literature for point source dispersion over flat terrain and urban arrays.  相似文献   

19.
Observations of the dispersion of a contaminant plume in the atmospheric boundary layer, obtained using a Lidar, are analysed in the coordinate frame relative to the instantaneous centre of mass of the plume, as well as the absolute (or fixed) coordinate frame. The study extends the work presented in a previous article, which analysed the structure of the probability density function (pdf) of concentration within the relative coordinate frame. Firstly, the plume displacement component, or plume meander, is analysed and a simple parametric form for the pdf of the plume centreline position is suggested. This is then used to analyse the accuracy and applicability of absolute framework statistical quantities obtained by a convolution of the relative frame statistical quantity with the plume centreline pdf.  相似文献   

20.
The reduction in variance of concentration fluctuations due to line averaging is estimated assuming that the process is influenced by the integral distance scale, y I , of ambient turbulence and the scaling width, W, of the time-averaged plume. An analytical formula is derived for the line-averaged variance for situations where the autocorrelogram is exponential and the point variance decreases exponentially with distance from plume centerline. Predictions of concentration fluctuation variance are compared with water tank and field data, with the result that the decrease of variance with averaging distance is well-simulated if the model parameters y I and W are carefully chosen.  相似文献   

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