Sensitivity, applicability and validation of bi-gaussian off- and on-line models for the evaluation of the consequences of accidental releases in nuclear facilities

International Nuclear Information System (INIS)

Kretzschmar, J.G.; Mertens, I.; Vanderborght, B.

1984-01-01

A computer code CAERS (Computer Aided Emergency Response System) has been developed for the simulation of the short-term concentrations caused by an atmospheric emission. The concentration calculations are based on the bi-gaussian theorem with the possibility of using twelve different sets of turbulence typing schemes and dispersion parameters or the plume can be simulated with a bi-dimensional puff trajectory model with tri-gaussian diffusion of the puffs. With the puff trajectory model the emission and the wind conditions can be variable in time. Sixteen SF 6 tracer dispersion experiments, with mobile as well as stationary time averaging sampling, have been carried out for the validation of the on-line and off-line models of CAERS. The tracer experiments of this study have shown that the CAERS system, using the bi-gaussian model and the SCK/CEN turbulence typing scheme, can simulate short time concentration levels very well. The variations of the plume under non-steady emission and meteo conditions are well simulated by the puff trajectory model. This leads to the general conclusion that the atmospheric dispersion models of the CAERS system can give a significant contribution to the management and the interpretation of air pollution concentration measurements in emergency situations

An unconventional adaptation of a classical Gaussian plume dispersion scheme for the fast assessment of external irradiation from a radioactive cloud

Science.gov (United States)

Pecha, Petr; Pechova, Emilie

2014-06-01

This article focuses on derivation of an effective algorithm for the fast estimation of cloudshine doses/dose rates induced by a large mixture of radionuclides discharged into the atmosphere. A certain special modification of the classical Gaussian plume approach is proposed for approximation of the near-field dispersion problem. Specifically, the accidental radioactivity release is subdivided into consecutive one-hour Gaussian segments, each driven by a short-term meteorological forecast for the respective hours. Determination of the physical quantity of photon fluence rate from an ambient cloud irradiation is coupled to a special decomposition of the Gaussian plume shape into the equivalent virtual elliptic disks. It facilitates solution of the formerly used time-consuming 3-D integration and provides advantages with regard to acceleration of the computational process on a local scale. An optimal choice of integration limit is adopted on the basis of the mean free path of γ-photons in the air. An efficient approach is introduced for treatment of a wide range of energetic spectrum of the emitted photons when the usual multi-nuclide approach is replaced by a new multi-group scheme. The algorithm is capable of generating the radiological responses in a large net of spatial nodes. It predetermines the proposed procedure such as a proper tool for online data assimilation analysis in the near-field areas. A specific technique for numerical integration is verified on the basis of comparison with a partial analytical solution. Convergence of the finite cloud approximation to the tabulated semi-infinite cloud values for dose conversion factors was validated.

Numerical modeling of macrodispersion in heterogeneous media: a comparison of multi-Gaussian and non-multi-Gaussian models

Science.gov (United States)

Wen, Xian-Huan; Gómez-Hernández, J. Jaime

1998-03-01

The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than

On the Pollutant Plume Dispersion in the Urban Canopy Layer over 2D Idealized Street Canyons: A Large-Eddy Simulation Approach

Science.gov (United States)

Wong, Colman C. C.; Liu, Chun-Ho

2010-05-01

Anthropogenic emissions are the major sources of air pollutants in urban areas. To improve the air quality in dense and mega cities, a simple but reliable prediction method is necessary. In the last five decades, the Gaussian pollutant plume model has been widely used for the estimation of air pollutant distribution in the atmospheric boundary layer (ABL) in an operational manner. Whereas, it was originally designed for rural areas with rather open and flat terrain. The recirculating flows below the urban canopy layer substantially modify the near-ground urban wind environment and so does the pollutant distribution. Though the plume height and dispersion are often adjusted empirically, the accuracy of applying the Gaussian pollutant plume model in urban areas, of which the bottom of the flow domain consists of numerous inhomogeneous buildings, is unclear. To elucidate the flow and pollutant transport, as well as to demystify the uncertainty of employing the Gaussian pollutant plume model over urban roughness, this study was performed to examine how the Gaussian-shape pollutant plume in the urban canopy layer is modified by the idealized two-dimensional (2D) street canyons at the bottom of the ABL. The specific objective is to develop a parameterization so that the geometric effects of urban morphology on the operational pollutant plume dispersion models could be taken into account. Because atmospheric turbulence is the major means of pollutant removal from street canyons to the ABL, the large-eddy simulation (LES) was adopted to calculate explicitly the flows and pollutant transport in the urban canopy layer. The subgrid-scale (SGS) turbulent kinetic energy (TKE) conservation was used to model the SGS processes in the incompressible, isothermal conditions. The computational domain consists of 12 identical idealized street canyons of unity aspect ratio which were placed evenly in the streamwise direction. Periodic boundary conditions (BCs) for the flow were applied

Vertical dispersion from surface and elevated releases: An investigation of a Non-Gaussian plume model

International Nuclear Information System (INIS)

Brown, M.J.; Arya, S.P.; Snyder, W.H.

1993-01-01

The vertical diffusion of a passive tracer released from surface and elevated sources in a neutrally stratified boundary layer has been studied by comparing field and laboratory experiments with a non-Gaussian K-theory model that assumes power-law profiles for the mean velocity and vertical eddy diffusivity. Several important differences between model predictions and experimental data were discovered: (1) the model overestimated ground-level concentrations from surface and elevated releases at distances beyond the peak concentration; (2) the model overpredicted vertical mixing near elevated sources, especially in the upward direction; (3) the model-predicted exponent α in the exponential vertical concentration profile for a surface release [bar C(z)∝ exp(-z α )] was smaller than the experimentally measured exponent. Model closure assumptions and experimental short-comings are discussed in relation to their probable effect on model predictions and experimental measurements. 42 refs., 13 figs., 3 tabs

Integrating wildfire plume rises within atmospheric transport models

Science.gov (United States)

Mallia, D. V.; Kochanski, A.; Wu, D.; Urbanski, S. P.; Krueger, S. K.; Lin, J. C.

2016-12-01

Wildfires can generate significant pyro-convection that is responsible for releasing pollutants, greenhouse gases, and trace species into the free troposphere, which are then transported a significant distance downwind from the fire. Oftentimes, atmospheric transport and chemistry models have a difficult time resolving the transport of smoke from these wildfires, primarily due to deficiencies in estimating the plume injection height, which has been highlighted in previous work as the most important aspect of simulating wildfire plume transport. As a result of the uncertainties associated with modeled wildfire plume rise, researchers face difficulties modeling the impacts of wildfire smoke on air quality and constraining fire emissions using inverse modeling techniques. Currently, several plume rise parameterizations exist that are able to determine the injection height of fire emissions; however, the success of these parameterizations has been mixed. With the advent of WRF-SFIRE, the wildfire plume rise and injection height can now be explicitly calculated using a fire spread model (SFIRE) that is dynamically linked with the atmosphere simulated by WRF. However, this model has only been tested on a limited basis due to computational costs. Here, we will test the performance of WRF-SFIRE in addition to several commonly adopted plume parameterizations (Freitas, Sofiev, and Briggs) for the 2013 Patch Springs (Utah) and 2012 Baker Canyon (Washington) fires, for both of which observations of plume rise heights are available. These plume rise techniques will then be incorporated within a Lagrangian atmospheric transport model (STILT) in order to simulate CO and CO2 concentrations during NASA's CARVE Earth Science Airborne Program over Alaska during the summer of 2012. Initial model results showed that STILT model simulations were unable to reproduce enhanced CO concentrations produced by Alaskan fires observed during 2012. Near-surface concentrations were drastically

A study of the atmospheric dispersion of a high release of krypton-85 above a complex coastal terrain, comparison with the predictions of Gaussian models (Briggs, Doury, ADMS4).

Science.gov (United States)

Leroy, C; Maro, D; Hébert, D; Solier, L; Rozet, M; Le Cavelier, S; Connan, O

2010-11-01

Atmospheric releases of krypton-85, from the nuclear fuel reprocessing plant at the AREVA NC facility at La Hague (France), were used to test Gaussian models of dispersion. In 2001-2002, the French Institute for Radiological Protection and Nuclear Safety (IRSN) studied the atmospheric dispersion of 15 releases, using krypton-85 as a tracer for plumes emitted from two 100-m-high stacks. Krypton-85 is a chemically inert radionuclide. Krypton-85 air concentration measurements were performed on the ground in the downwind direction, at distances between 0.36 and 3.3 km from the release, by neutral or slightly unstable atmospheric conditions. The standard deviation for the horizontal dispersion of the plume and the Atmospheric Transfer Coefficient (ATC) were determined from these measurements. The experimental results were compared with calculations using first generation (Doury, Briggs) and second generation (ADMS 4.0) Gaussian models. The ADMS 4.0 model was used in two configurations; one takes account of the effect of the built-up area, and the other the effect of the roughness of the surface on the plume dispersion. Only the Briggs model correctly reproduced the measured values for the width of the plume, whereas the ADMS 4.0 model overestimated it and the Doury model underestimated it. The agreement of the models with measured values of the ATC varied according to distance from the release point. For distances less than 2 km from the release point, the ADMS 4.0 model achieved the best agreement between model and measurement; beyond this distance, the best agreement was achieved by the Briggs and Doury models.

Application of data assimilation to improve the forecasting capability of an atmospheric dispersion model for a radioactive plume

International Nuclear Information System (INIS)

Jeong, H.J.; Han, M.H.; Hwang, W.T.; Kim, E.H.

2008-01-01

Modeling an atmospheric dispersion of a radioactive plume plays an influential role in assessing the environmental impacts caused by nuclear accidents. The performance of data assimilation techniques combined with Gaussian model outputs and measurements to improve forecasting abilities are investigated in this study. Tracer dispersion experiments are performed to produce field data by assuming a radiological emergency. Adaptive neuro-fuzzy inference system (ANFIS) and linear regression filter are considered to assimilate the Gaussian model outputs with measurements. ANFIS is trained so that the model outputs are likely to be more accurate for the experimental data. Linear regression filter is designed to assimilate measurements similar to the ANFIS. It is confirmed that ANFIS could be an appropriate method for an improvement of the forecasting capability of an atmospheric dispersion model in the case of a radiological emergency, judging from the higher correlation coefficients between the measured and the assimilated ones rather than a linear regression filter. This kind of data assimilation method could support a decision-making system when deciding on the best available countermeasures for public health from among emergency preparedness alternatives

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Comparison of Nordic dose models

International Nuclear Information System (INIS)

Thykier-Nielsen, S.

1978-04-01

A comparison is made between the models used in the four Nordic countries, Finland, Norway, Sweden and Denmark, for calculation of concentrations and doses from releases of radioactive material to the atmosphere. The comparison is limited to the near-zone models, i.e. the models for calculation of concentrations and doses within 50 km from the release point, and it comprises the following types of calculation: a. Concentrations of airborne material, b. External gamma doses from a plume, c. External gamma doses from radioactive material deposited on the ground. All models are based on the gaussian dispersion model (the gaussian plume model). Unit releases of specific isotopes under specific meteorological conditions are assumed. On the basis of the calculation results from the models, it is concluded that there are no essential differences. The difference between the calculation results only exceeds a factor of 3 in special cases. It thus lies within the known limits of uncertainty for the gaussian plume model. (author)

Optimized Field Sampling and Monitoring of Airborne Hazardous Transport Plumes; A Geostatistical Simulation Approach

International Nuclear Information System (INIS)

Chen, DI-WEN

2001-01-01

Airborne hazardous plumes inadvertently released during nuclear/chemical/biological incidents are mostly of unknown composition and concentration until measurements are taken of post-accident ground concentrations from plume-ground deposition of constituents. Unfortunately, measurements often are days post-incident and rely on hazardous manned air-vehicle measurements. Before this happens, computational plume migration models are the only source of information on the plume characteristics, constituents, concentrations, directions of travel, ground deposition, etc. A mobile ''lighter than air'' (LTA) system is being developed at Oak Ridge National Laboratory that will be part of the first response in emergency conditions. These interactive and remote unmanned air vehicles will carry light-weight detectors and weather instrumentation to measure the conditions during and after plume release. This requires a cooperative computationally organized, GPS-controlled set of LTA's that self-coordinate around the objectives in an emergency situation in restricted time frames. A critical step before an optimum and cost-effective field sampling and monitoring program proceeds is the collection of data that provides statistically significant information, collected in a reliable and expeditious manner. Efficient aerial arrangements of the detectors taking the data (for active airborne release conditions) are necessary for plume identification, computational 3-dimensional reconstruction, and source distribution functions. This report describes the application of stochastic or geostatistical simulations to delineate the plume for guiding subsequent sampling and monitoring designs. A case study is presented of building digital plume images, based on existing ''hard'' experimental data and ''soft'' preliminary transport modeling results of Prairie Grass Trials Site. Markov Bayes Simulation, a coupled Bayesian/geostatistical methodology, quantitatively combines soft information

Functional Dual Adaptive Control with Recursive Gaussian Process Model

International Nuclear Information System (INIS)

Prüher, Jakub; Král, Ladislav

2015-01-01

The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

Gaussian Mixture Model of Heart Rate Variability

Science.gov (United States)

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Pollutant Plume Dispersion over Hypothetical Urban Areas based on Wind Tunnel Measurements

Science.gov (United States)

Mo, Ziwei; Liu, Chun-Ho

2017-04-01

Gaussian plume model is commonly adopted for pollutant concentration prediction in the atmospheric boundary layer (ABL). However, it has a number of limitations being applied to pollutant dispersion over complex land-surface morphology. In this study, the friction factor (f), as a measure of aerodynamic resistance induced by rough surfaces in the engineering community, was proposed to parameterize the vertical dispersion coefficient (σz) in the Gaussian model. A series of wind tunnel experiments were carried out to verify the mathematical hypothesis and to characterize plume dispersion as a function of surface roughness as well. Hypothetical urban areas, which were assembled in the form of idealized street canyons of different aspect (building-height-to-street-width) ratios (AR = 1/2, 1/4, 1/8 and 1/12), were fabricated by aligning identical square aluminum bars at different separation apart in cross flows. Pollutant emitted from a ground-level line source into the turbulent boundary layer (TBL) was simulated using water vapour generated by ultrasonic atomizer. The humidity and the velocity (mean and fluctuating components) were measured, respectively, by humidity sensors and hot-wire anemometry (HWA) with X-wire probes in streamwise and vertical directions. Wind tunnel results showed that the pollutant concentration exhibits the conventional Gaussian distribution, suggesting the feasibility of using water vapour as a passive scalar in wind tunnel experiments. The friction factor increased with decreasing aspect ratios (widening the building separation). It was peaked at AR = 1/8 and decreased thereafter. Besides, a positive correlation between σz/xn (x is the distance from the pollutant source) and f1/4 (correlation coefficient r2 = 0.61) was observed, formulating the basic parameterization of plume dispersion over urban areas.

PLUME-MoM 1.0: A new integral model of volcanic plumes based on the method of moments

Science.gov (United States)

de'Michieli Vitturi, M.; Neri, A.; Barsotti, S.

2015-08-01

In this paper a new integral mathematical model for volcanic plumes, named PLUME-MoM, is presented. The model describes the steady-state dynamics of a plume in a 3-D coordinate system, accounting for continuous variability in particle size distribution of the pyroclastic mixture ejected at the vent. Volcanic plumes are composed of pyroclastic particles of many different sizes ranging from a few microns up to several centimeters and more. A proper description of such a multi-particle nature is crucial when quantifying changes in grain-size distribution along the plume and, therefore, for better characterization of source conditions of ash dispersal models. The new model is based on the method of moments, which allows for a description of the pyroclastic mixture dynamics not only in the spatial domain but also in the space of parameters of the continuous size distribution of the particles. This is achieved by formulation of fundamental transport equations for the multi-particle mixture with respect to the different moments of the grain-size distribution. Different formulations, in terms of the distribution of the particle number, as well as of the mass distribution expressed in terms of the Krumbein log scale, are also derived. Comparison between the new moments-based formulation and the classical approach, based on the discretization of the mixture in N discrete phases, shows that the new model allows for the same results to be obtained with a significantly lower computational cost (particularly when a large number of discrete phases is adopted). Application of the new model, coupled with uncertainty quantification and global sensitivity analyses, enables the investigation of the response of four key output variables (mean and standard deviation of the grain-size distribution at the top of the plume, plume height and amount of mass lost by the plume during the ascent) to changes in the main input parameters (mean and standard deviation) characterizing the

An integral model of plume rise from high explosive detonations

International Nuclear Information System (INIS)

Boughton, B.A.; De Laurentis, J.M.

1987-01-01

A numerical model has been developed which provides a complete description of the time evolution of both the physical and thermodynamic properties of the cloud formed when a high explosive is detonated. This simulation employs the integral technique. The model equations are derived by integrating the three-dimensional conservation equations of mass, momentum and energy over the plume cross section. Assumptions are made regarding (a) plume symmetry; (b) the shape of profiles of velocity, temperature, etc. across the plume; and (c) the methodology for simulating entrainment and the effects of the crossflow induced pressure drag force on the plume. With these assumptions, the integral equations can be reduced to a set of ordinary differential equations on the plume centerline variables. Only the macroscopic plume characteristics, e.g., plume radius, centerline height, temperature and density, are predicted; details of the plume intrastructure are ignored. The model explicitly takes into account existing meteorology and has been expanded to consider the alterations in plume behavior which occur when aqueous foam is used as a dispersal mitigating material. The simulation was tested by comparison with field measurements of cloud top height and diameter. Predictions were within 25% of field observations over a wide range of explosive yield and atmospheric stability

PLUME-MoM 1.0: a new 1-D model of volcanic plumes based on the method of moments

Science.gov (United States)

de'Michieli Vitturi, M.; Neri, A.; Barsotti, S.

2015-05-01

In this paper a new mathematical model for volcanic plumes, named PlumeMoM, is presented. The model describes the steady-state 1-D dynamics of the plume in a 3-D coordinate system, accounting for continuous variability in particle distribution of the pyroclastic mixture ejected at the vent. Volcanic plumes are composed of pyroclastic particles of many different sizes ranging from a few microns up to several centimeters and more. Proper description of such a multiparticle nature is crucial when quantifying changes in grain-size distribution along the plume and, therefore, for better characterization of source conditions of ash dispersal models. The new model is based on the method of moments, which allows description of the pyroclastic mixture dynamics not only in the spatial domain but also in the space of properties of the continuous size-distribution of the particles. This is achieved by formulation of fundamental transport equations for the multiparticle mixture with respect to the different moments of the grain-size distribution. Different formulations, in terms of the distribution of the particle number, as well as of the mass distribution expressed in terms of the Krumbein log scale, are also derived. Comparison between the new moments-based formulation and the classical approach, based on the discretization of the mixture in N discrete phases, shows that the new model allows the same results to be obtained with a significantly lower computational cost (particularly when a large number of discrete phases is adopted). Application of the new model, coupled with uncertainty quantification and global sensitivity analyses, enables investigation of the response of four key output variables (mean and standard deviation (SD) of the grain-size distribution at the top of the plume, plume height and amount of mass lost by the plume during the ascent) to changes in the main input parameters (mean and SD) characterizing the pyroclastic mixture at the base of the plume

DeepBlow - a Lagrangian plume model for deep water blowouts

International Nuclear Information System (INIS)

Johansen, Oeistein

2000-01-01

This paper presents a sub-sea blowout model designed with special emphasis on deep-water conditions. The model is an integral plume model based on a Lagrangian concept. This concept is applied to multiphase discharges in the formation of water, oil and gas in a stratified water column with variable currents. The gas may be converted to hydrate in combination with seawater, dissolved into the plume water, or leaking out of the plume due to the slip between rising gas bubbles and the plume trajectory. Non-ideal behaviour of the gas is accounted for by the introduction of pressure- and temperature-dependent compressibility z-factor in the equation of state. A number of case studies are presented in the paper. One of the cases (blowout from 100 m depth) is compared with observations from a field experiment conducted in Norwegian waters in June 1996. The model results are found to compare favourably with the field observations when dissolution of gas into seawater is accounted in the model. For discharges at intermediate to shallow depths (100-250 m), the two major processes limiting plume rise will be: (a) dissolution of gas into ambient water, or (b) bubbles rising out of the inclined plume. These processes tend to be self-enforcing, i.e., when a gas is lost by either of these processes, plume rise tends to slow down and more time will be available for dissolution. For discharges in deep waters (700-1500 m depth), hydrate formation is found to be a dominating process in limiting plume rise. (Author)

Subsurface oil release field experiment - observations and modelling of subsurface plume behaviour

International Nuclear Information System (INIS)

Rye, H.; Brandvik, P.J.; Reed, M.

1996-01-01

An experiment was conducted at sea, in which oil was released from 107 metres depth, in order to study plume behaviour. The objective of the underwater release was to simulate a pipeline leakage without gas and high pressure and to study the behaviour of the rising plume. A numerical model for the underwater plume behaviour was used for comparison with field data. The expected path of the plume, the time expected for the plume to reach the sea surface and the width of the plume was modelled. Field data and the numerical model were in good agreement. 10 refs., 2 tabs., 9 figs

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data

Directory of Open Access Journals (Sweden)

Ji Hoon Ryoo

2017-08-01

Full Text Available As in cross sectional studies, longitudinal studies involve non-Gaussian data such as binomial, Poisson, gamma, and inverse-Gaussian distributions, and multivariate exponential families. A number of statistical tools have thus been developed to deal with non-Gaussian longitudinal data, including analytic techniques to estimate parameters in both fixed and random effects models. However, as yet growth modeling with non-Gaussian data is somewhat limited when considering the transformed expectation of the response via a linear predictor as a functional form of explanatory variables. In this study, we introduce a fractional polynomial model (FPM that can be applied to model non-linear growth with non-Gaussian longitudinal data and demonstrate its use by fitting two empirical binary and count data models. The results clearly show the efficiency and flexibility of the FPM for such applications.

Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models.

Directory of Open Access Journals (Sweden)

Georgios C Manikis

Full Text Available The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm2 at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG and non-Gaussian (MNG and BNG were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R2 and Root Mean Square Error (RMSE. To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC and F-ratio.All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.

Kinetic electron model for plasma thruster plumes

Science.gov (United States)

Merino, Mario; Mauriño, Javier; Ahedo, Eduardo

2018-03-01

A paraxial model of an unmagnetized, collisionless plasma plume expanding into vacuum is presented. Electrons are treated kinetically, relying on the adiabatic invariance of their radial action integral for the integration of Vlasov's equation, whereas ions are treated as a cold species. The quasi-2D plasma density, self-consistent electric potential, and electron pressure, temperature, and heat fluxes are analyzed. In particular, the model yields the collisionless cooling of electrons, which differs from the Boltzmann relation and the simple polytropic laws usually employed in fluid and hybrid PIC/fluid plume codes.

Extended Linear Models with Gaussian Priors

DEFF Research Database (Denmark)

Quinonero, Joaquin

2002-01-01

In extended linear models the input space is projected onto a feature space by means of an arbitrary non-linear transformation. A linear model is then applied to the feature space to construct the model output. The dimension of the feature space can be very large, or even infinite, giving the model...... a very big flexibility. Support Vector Machines (SVM's) and Gaussian processes are two examples of such models. In this technical report I present a model in which the dimension of the feature space remains finite, and where a Bayesian approach is used to train the model with Gaussian priors...... on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....

Modeling text with generalizable Gaussian mixtures

DEFF Research Database (Denmark)

Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas

2000-01-01

We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...

A Tracer Experiment to Understand Dispersion Characteristics at a Nuclear Power Plant Site-Focusing on the Comparison with Predictive Results using Reg. Guide 1.145 model

Energy Technology Data Exchange (ETDEWEB)

Jeong, Hyojoon; Kim, Eunhan; Jeong, Haesun; Hwang, Wontae; Han, Moonhee [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2014-10-15

There remains disagreement regarding the application of a Gaussian plume model in PAVAN, as it relates to the complicated geographical features of a coastal area. Therefore, this study was performed in order to figure out the characteristics of the PAVAN program that was developed based on the equations of Gaussian Plume Model, which reflected the actual measured concentration of radioactive materials released to the air. It also evaluated the appropriateness of using a Gaussian plume model for assessing the environmental impact of radiation from a nuclear power plant. In order to analyze the dispersion characteristics of radioactive materials released into the air from the Wolsong nuclear power plant, SF{sub 6} gas was released from the site at night for one hour under stable atmospheric conditions disadvantageous to dilute a tracer gas in this study. The measured concentrations were compared with theoretical estimates derived from meteorological data observed during the experiment period to evaluate the prediction capabilities of the Gaussian plume model. This study conducted a tracer dispersion experiment at the site of Wolsong Nuclear Power Plant site in Korea to analyze the atmospheric dispersion characteristics of radioactive materials. It compared the experimental value with the calculated value using the Gaussian Plume Model as suggested in Reg. 1.145, based on the meteorological data observed in the experiment time period, and evaluated the conservative estimate of the calculated value. In the area where the calculated value is relatively high, the calculated value tends to show higher than the experimental value, which confirmed the conservative manner of the estimating of the calculated value using the Gaussian Plume Model. The short-term exposure of radiation to a human body caused by a nuclear accident would be higher in the area where the atmospheric concentration of radiation is high. Therefore, it is a sufficiently conservative manner to use the

A Tracer Experiment to Understand Dispersion Characteristics at a Nuclear Power Plant Site-Focusing on the Comparison with Predictive Results using Reg. Guide 1.145 model

International Nuclear Information System (INIS)

Jeong, Hyojoon; Kim, Eunhan; Jeong, Haesun; Hwang, Wontae; Han, Moonhee

2014-01-01

There remains disagreement regarding the application of a Gaussian plume model in PAVAN, as it relates to the complicated geographical features of a coastal area. Therefore, this study was performed in order to figure out the characteristics of the PAVAN program that was developed based on the equations of Gaussian Plume Model, which reflected the actual measured concentration of radioactive materials released to the air. It also evaluated the appropriateness of using a Gaussian plume model for assessing the environmental impact of radiation from a nuclear power plant. In order to analyze the dispersion characteristics of radioactive materials released into the air from the Wolsong nuclear power plant, SF 6 gas was released from the site at night for one hour under stable atmospheric conditions disadvantageous to dilute a tracer gas in this study. The measured concentrations were compared with theoretical estimates derived from meteorological data observed during the experiment period to evaluate the prediction capabilities of the Gaussian plume model. This study conducted a tracer dispersion experiment at the site of Wolsong Nuclear Power Plant site in Korea to analyze the atmospheric dispersion characteristics of radioactive materials. It compared the experimental value with the calculated value using the Gaussian Plume Model as suggested in Reg. 1.145, based on the meteorological data observed in the experiment time period, and evaluated the conservative estimate of the calculated value. In the area where the calculated value is relatively high, the calculated value tends to show higher than the experimental value, which confirmed the conservative manner of the estimating of the calculated value using the Gaussian Plume Model. The short-term exposure of radiation to a human body caused by a nuclear accident would be higher in the area where the atmospheric concentration of radiation is high. Therefore, it is a sufficiently conservative manner to use the Gaussian

Laser-generated plasma plume expansion: Combined continuous-microscopic modeling

Science.gov (United States)

Itina, Tatiana E.; Hermann, Jörg; Delaporte, Philippe; Sentis, Marc

2002-12-01

The physical phenomena involved in the interaction of a laser-generated plasma plume with a background gas are studied numerically. A three-dimensional combined model is developed to describe the plasma plume formation and its expansion in vacuum or into a background gas. The proposed approach takes advantages of both continuous and microscopic descriptions. The simulation technique is suitable for the simulation of high-rate laser ablation for a wide range of background pressure. The model takes into account the mass diffusion and the energy exchange between the ablated and background species, as well as the collective motion of the ablated species and the background-gas particles. The developed approach is used to investigate the influence of the background gas on the expansion dynamics of the plume obtained during the laser ablation of aluminum. At moderate pressures, both plume and gas compressions are weak and the process is mainly governed by the diffusive mixing. At higher pressures, the interaction is determined by the plume-gas pressure interplay, the plume front is strongly compressed, and its center exhibits oscillations. In this case, the snowplough effect takes place, leading to the formation of a compressed gas layer in front of the plume. The background pressure needed for the beginning of the snowplough effect is determined from the plume and gas density profiles obtained at various pressures. Simulation results are compared with experimentally measured density distributions. It is shown that the calculations suggest localized formation of molecules during reactive laser ablation.

Laser-generated plasma plume expansion: Combined continuous-microscopic modeling

International Nuclear Information System (INIS)

Itina, Tatiana E.; Hermann, Joerg; Delaporte, Philippe; Sentis, Marc

2002-01-01

The physical phenomena involved in the interaction of a laser-generated plasma plume with a background gas are studied numerically. A three-dimensional combined model is developed to describe the plasma plume formation and its expansion in vacuum or into a background gas. The proposed approach takes advantages of both continuous and microscopic descriptions. The simulation technique is suitable for the simulation of high-rate laser ablation for a wide range of background pressure. The model takes into account the mass diffusion and the energy exchange between the ablated and background species, as well as the collective motion of the ablated species and the background-gas particles. The developed approach is used to investigate the influence of the background gas on the expansion dynamics of the plume obtained during the laser ablation of aluminum. At moderate pressures, both plume and gas compressions are weak and the process is mainly governed by the diffusive mixing. At higher pressures, the interaction is determined by the plume-gas pressure interplay, the plume front is strongly compressed, and its center exhibits oscillations. In this case, the snowplough effect takes place, leading to the formation of a compressed gas layer in front of the plume. The background pressure needed for the beginning of the snowplough effect is determined from the plume and gas density profiles obtained at various pressures. Simulation results are compared with experimentally measured density distributions. It is shown that the calculations suggest localized formation of molecules during reactive laser ablation

A note on moving average models for Gaussian random fields

DEFF Research Database (Denmark)

Hansen, Linda Vadgård; Thorarinsdottir, Thordis L.

The class of moving average models offers a flexible modeling framework for Gaussian random fields with many well known models such as the Matérn covariance family and the Gaussian covariance falling under this framework. Moving average models may also be viewed as a kernel smoothing of a Lévy...... basis, a general modeling framework which includes several types of non-Gaussian models. We propose a new one-parameter spatial correlation model which arises from a power kernel and show that the associated Hausdorff dimension of the sample paths can take any value between 2 and 3. As a result...

Model selection for Gaussian kernel PCA denoising

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Hansen, Lars Kai

2012-01-01

We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

Merits of a Scenario Approach in Dredge Plume Modelling

DEFF Research Database (Denmark)

Pedersen, Claus; Chu, Amy Ling Chu; Hjelmager Jensen, Jacob

2011-01-01

Dredge plume modelling is a key tool for quantification of potential impacts to inform the EIA process. There are, however, significant uncertainties associated with the modelling at the EIA stage when both dredging methodology and schedule are likely to be a guess at best as the dredging...... contractor would rarely have been appointed. Simulation of a few variations of an assumed full dredge period programme will generally not provide a good representation of the overall environmental risks associated with the programme. An alternative dredge plume modelling strategy that attempts to encapsulate...... uncertainties associated with preliminary dredging programmes by using a scenario-based modelling approach is presented. The approach establishes a set of representative and conservative scenarios for key factors controlling the spill and plume dispersion and simulates all combinations of e.g. dredge, climatic...

Revisiting non-Gaussianity from non-attractor inflation models

Science.gov (United States)

Cai, Yi-Fu; Chen, Xingang; Namjoo, Mohammad Hossein; Sasaki, Misao; Wang, Dong-Gang; Wang, Ziwei

2018-05-01

Non-attractor inflation is known as the only single field inflationary scenario that can violate non-Gaussianity consistency relation with the Bunch-Davies vacuum state and generate large local non-Gaussianity. However, it is also known that the non-attractor inflation by itself is incomplete and should be followed by a phase of slow-roll attractor. Moreover, there is a transition process between these two phases. In the past literature, this transition was approximated as instant and the evolution of non-Gaussianity in this phase was not fully studied. In this paper, we follow the detailed evolution of the non-Gaussianity through the transition phase into the slow-roll attractor phase, considering different types of transition. We find that the transition process has important effect on the size of the local non-Gaussianity. We first compute the net contribution of the non-Gaussianities at the end of inflation in canonical non-attractor models. If the curvature perturbations keep evolving during the transition—such as in the case of smooth transition or some sharp transition scenarios—the Script O(1) local non-Gaussianity generated in the non-attractor phase can be completely erased by the subsequent evolution, although the consistency relation remains violated. In extremal cases of sharp transition where the super-horizon modes freeze immediately right after the end of the non-attractor phase, the original non-attractor result can be recovered. We also study models with non-canonical kinetic terms, and find that the transition can typically contribute a suppression factor in the squeezed bispectrum, but the final local non-Gaussianity can still be made parametrically large.

Comparison of in situ observations of air traffic emission signatures in the North Atlantic flight corridor with simulations using a Gaussian plume model

Energy Technology Data Exchange (ETDEWEB)

Konopka, P; Schlager, H; Schulte, P; Schumann, U; Ziereis, H [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere; Hagen, D; Whitefield, P [Missouri Univ., Rolla, MO (United States). Lab. for Cloud and Aerosol Science

1998-12-31

Focussed aircraft measurements including NO, NO{sub 2}, O{sub 3}, and aerosols (CN) have been carried out over the Eastern North Atlantic as part of the POLINAT (Pollution from Aircraft Emissions in the North Atlantic Flight Corridor) project to search for small and large scale signals of air traffic emissions in the corridor region. Here, the experimental data measured at cruising altitudes on November, 6, 1994 close to peak traffic hours are considered. Observed peak concentrations in small scale NO{sub x} spikes exceed background level of about 50 pptv by up to two orders of magnitude. The measured NO{sub x} concentration field is compared with simulations obtained with a plume dispersion model using collected air traffic data and wind measurements. Additionally, the measured and calculated NO/NO{sub x} ratios are considered. The comparison with the model shows that the observed (multiple-)peaks can be understood as a superposition of several aircraft plumes with ages up to 3 hours. (author) 12 refs.

Comparison of in situ observations of air traffic emission signatures in the North Atlantic flight corridor with simulations using a Gaussian plume model

Energy Technology Data Exchange (ETDEWEB)

Konopka, P.; Schlager, H.; Schulte, P.; Schumann, U.; Ziereis, H. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere; Hagen, D.; Whitefield, P. [Missouri Univ., Rolla, MO (United States). Lab. for Cloud and Aerosol Science

1997-12-31

Focussed aircraft measurements including NO, NO{sub 2}, O{sub 3}, and aerosols (CN) have been carried out over the Eastern North Atlantic as part of the POLINAT (Pollution from Aircraft Emissions in the North Atlantic Flight Corridor) project to search for small and large scale signals of air traffic emissions in the corridor region. Here, the experimental data measured at cruising altitudes on November, 6, 1994 close to peak traffic hours are considered. Observed peak concentrations in small scale NO{sub x} spikes exceed background level of about 50 pptv by up to two orders of magnitude. The measured NO{sub x} concentration field is compared with simulations obtained with a plume dispersion model using collected air traffic data and wind measurements. Additionally, the measured and calculated NO/NO{sub x} ratios are considered. The comparison with the model shows that the observed (multiple-)peaks can be understood as a superposition of several aircraft plumes with ages up to 3 hours. (author) 12 refs.

On moistening of ash particles in smoke plumes of industrial sources

International Nuclear Information System (INIS)

Geints, Yu.E.; Zemlyanov, A.A.

1992-01-01

Moistening of ash particles occurring in the humid atmosphere is one of the main factors decreasing the accuracy of the lidar measurements of thickness of smoke emissions. Theoretical investigation of the growth of water coating of smoke particles under different meteorological conditions within the zone of emission has been carried out based on the Gaussian model of smoke plume with slant axis and its parameters. Numerical calculations have shown that in the case of high initial moisture content of the emissions near the source in the smoke plume the zone appears in which water vapor is supersaturated and the effect of particle moistening is significant. Seasonal trends and diurnal variations in temperature and humidity in the surface layer of the atmosphere also substantially affect moistening. Length of the zone of moistening of ash particles is maximum at night in winter under conditions of light breeze. The possibility of retrieving the initial mass concentration of the dry aerosol in the smoke plume has been shown based on lidar measurements of the scattering coefficient within the zone of maximum degree of moistening of smoke plume. 10 refs., 5 figs

Modeling Smoke Plume-Rise and Dispersion from Southern United States Prescribed Burns with Daysmoke

Science.gov (United States)

G L Achtemeier; S L Goodrick; Y Liu; F Garcia-Menendez; Y Hu; M. Odman

2011-01-01

We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric...

EM Modelling of RF Propagation Through Plasma Plumes

Science.gov (United States)

Pandolfo, L.; Bandinelli, M.; Araque Quijano, J. L.; Vecchi, G.; Pawlak, H.; Marliani, F.

2012-05-01

Electric propulsion is a commercially attractive solution for attitude and position control of geostationary satellites. Hall-effect ion thrusters generate a localized plasma flow in the surrounding of the satellite, whose impact on the communication system needs to be qualitatively and quantitatively assessed. An electromagnetic modelling tool has been developed and integrated into the Antenna Design Framework- ElectroMagnetic Satellite (ADF-EMS). The system is able to guide the user from the plume definition phases through plume installation and simulation. A validation activity has been carried out and the system has been applied to the plume modulation analysis of SGEO/Hispasat mission.

Modeling contaminant plumes in fractured limestone aquifers

DEFF Research Database (Denmark)

Mosthaf, Klaus; Brauns, Bentje; Fjordbøge, Annika Sidelmann

Determining the fate and transport of contaminant plumes from contaminated sites in limestone aquifers is important because they are a major drinking water resource. This is challenging because they are often heavily fractured and contain chert layers and nodules, resulting in a complex transport...... model. The paper concludes with recommendations on how to identify and employ suitable models to advance the conceptual understanding and as decision support tools for risk assessment and the planning of remedial actions....... behavior. Improved conceptual models are needed for this type of site. Here conceptual models are developed by combining numerical models with field data. Several types of fracture flow and transport models are available for the modeling of contaminant transport in fractured media. These include...... the established approaches of the equivalent porous medium, discrete fracture and dual continuum models. However, these modeling concepts are not well tested for contaminant plume migration in limestone geologies. Our goal was to develop and evaluate approaches for modeling the transport of dissolved contaminant...

Martian methane plume models for defining Mars rover methane source search strategies

Science.gov (United States)

Nicol, Christopher; Ellery, Alex; Lynch, Brian; Cloutis, Ed

2018-07-01

The detection of atmospheric methane on Mars implies an active methane source. This introduces the possibility of a biotic source with the implied need to determine whether the methane is indeed biotic in nature or geologically generated. There is a clear need for robotic algorithms which are capable of manoeuvring a rover through a methane plume on Mars to locate its source. We explore aspects of Mars methane plume modelling to reveal complex dynamics characterized by advection and diffusion. A statistical analysis of the plume model has been performed and compared to analyses of terrestrial plume models. Finally, we consider a robotic search strategy to find a methane plume source. We find that gradient-based techniques are ineffective, but that more sophisticated model-based search strategies are unlikely to be available in near-term rover missions.

Using satellite imagery for qualitative evaluation of plume transport in modeling the effects of the Kuwait oil fire smoke plumes

International Nuclear Information System (INIS)

Bass, A.; Janota, P.

1992-01-01

To forecast the behavior of the Kuwait oil fire smoke plumes and their possible acute or chronic health effects over the Arabian Gulf region, TASC created a comprehensive health and environmental impacts modeling system. A specially-adapted Lagrangian puff transport model was used to create (a) short-term (multiday) forecasts of plume transport and ground-level concentrations of soot and SO 2 ; and (b) long-term (seasonal and longer) estimates of average surface concentrations and depositions. EPA-approved algorithms were used to transform exposures to SO 2 and soot (as PAH/BaP) into morbidity, mortality and crop damage risks. Absent any ground truth, satellite imagery from the NOAA Polar Orbiter and the ESA Geostationary Meteosat offered the only opportunity for timely qualitative evaluation of the long-range plume transport and diffusion predictions. This paper shows the use of actual satellite images (including animated loops of hourly Meteosat images) to evaluate plume forecasts in near-real-time, and to sanity-check the meso- and long-range plume transport projections for the long-term estimates. Example modeled concentrations, depositions and health effects are shown

Plume dispersion and deposition processes of tracer gas and aerosols in short-distance experiments

International Nuclear Information System (INIS)

Taeschner, M.; Bunnenberg, C.

1988-01-01

Data used in this paper were extracted from field experiments carried out in France and Canada to study the pathway of elementary tritium after possible emissions from future fusion reactors and from short-range experiments with nutrient aerosols performed in a German forest in view of a therapy of damaged coniferous trees by foliar nutrition. Comparisons of dispersion parameters evaluated from the tritium field experiments show that in the case of the 30-min release the variations of the wind directions represent the dominant mechanism of lateral plume dispersion under unstable weather conditions. This corresponds with the observation that for the short 2-min emission the plume remains more concentrated during propagation, and the small lateral dispersion parameters typical for stable conditions have to be applied. The investigations on the dispersion of aerosol plumes into a forest boundary layer show that the Gaussian plume model can be modified by a windspeed factor to be valid for predictions on aerosol concentrations and depositions even in a structured topography like a forest

Linear velocity fields in non-Gaussian models for large-scale structure

Science.gov (United States)

Scherrer, Robert J.

1992-01-01

Linear velocity fields in two types of physically motivated non-Gaussian models are examined for large-scale structure: seed models, in which the density field is a convolution of a density profile with a distribution of points, and local non-Gaussian fields, derived from a local nonlinear transformation on a Gaussian field. The distribution of a single component of the velocity is derived for seed models with randomly distributed seeds, and these results are applied to the seeded hot dark matter model and the global texture model with cold dark matter. An expression for the distribution of a single component of the velocity in arbitrary local non-Gaussian models is given, and these results are applied to such fields with chi-squared and lognormal distributions. It is shown that all seed models with randomly distributed seeds and all local non-Guassian models have single-component velocity distributions with positive kurtosis.

Radiative modeling and characterization of aerosol plumes hyper-spectral imagery

International Nuclear Information System (INIS)

Alakian, A.

2008-03-01

This thesis aims at characterizing aerosols from plumes (biomass burning, industrial discharges, etc.) with hyper-spectral imagery. We want to estimate the optical properties of emitted particles and also their micro-physical properties such as number, size distribution and composition. To reach our goal, we have built a forward semi-analytical model, named APOM (Aerosol Plume Optical Model), which allows to simulate the radiative effects of aerosol plumes in the spectral range [0,4-2,5 μm] for nadir viewing sensors. Mathematical formulation and model coefficients are obtained from simulations performed with the radiative transfer code COMANCHE. APOM is assessed on simulated data and proves to be accurate with modeling errors between 1% and 3%. Three retrieval methods using APOM have been developed: L-APOM, M-APOM and A-APOM. These methods take advantage of spectral and spatial dimensions in hyper-spectral images. L-APOM and M-APOM assume a priori knowledge on particles but can estimate their optical and micro-physical properties. Their performances on simulated data are quite promising. A-APOM method does not require any a priori knowledge on particles but only estimates their optical properties. However, it still needs improvements before being usable. On real images, inversion provides satisfactory results for plumes above water but meets some difficulties for plumes above vegetation, which underlines some possibilities of improvement for the retrieval algorithm. (author)

Numerical model simulation of atmospheric coolant plumes

International Nuclear Information System (INIS)

Gaillard, P.

1980-01-01

The effect of humid atmospheric coolants on the atmosphere is simulated by means of a three-dimensional numerical model. The atmosphere is defined by its natural vertical profiles of horizontal velocity, temperature, pressure and relative humidity. Effluent discharge is characterised by its vertical velocity and the temperature of air satured with water vapour. The subject of investigation is the area in the vicinity of the point of discharge, with due allowance for the wake effect of the tower and buildings and, where application, wind veer with altitude. The model equations express the conservation relationships for mometum, energy, total mass and water mass, for an incompressible fluid behaving in accordance with the Boussinesq assumptions. Condensation is represented by a simple thermodynamic model, and turbulent fluxes are simulated by introduction of turbulent viscosity and diffusivity data based on in-situ and experimental water model measurements. The three-dimensional problem expressed in terms of the primitive variables (u, v, w, p) is governed by an elliptic equation system which is solved numerically by application of an explicit time-marching algorithm in order to predict the steady-flow velocity distribution, temperature, water vapour concentration and the liquid-water concentration defining the visible plume. Windstill conditions are simulated by a program processing the elliptic equations in an axisymmetrical revolution coordinate system. The calculated visible plumes are compared with plumes observed on site with a view to validate the models [fr

Methane Emission Estimates from Landfills Obtained with Dynamic Plume Measurements

International Nuclear Information System (INIS)

Hensen, A.; Scharff, H.

2001-01-01

Methane emissions from 3 different landfills in the Netherlands were estimated using a mobile Tuneable Diode Laser system (TDL). The methane concentration in the cross section of the plume is measured downwind of the source on a transect perpendicular to the wind direction. A gaussian plume model was used to simulate the concentration levels at the transect. The emission from the source is calculated from the measured and modelled concentration levels.Calibration of the plume dispersion model is done using a tracer (N 2 O) that is released from the landfill and measured simultaneously with the TDL system. The emission estimates for the different locations ranged from 3.6 to 16 m 3 ha -1 hr -1 for the different sites. The emission levels were compared to emission estimates based on the landfill gas production models. This comparison suggests oxidation rates that are up to 50% in spring and negligible in November. At one of the three sites measurements were performed in campaigns in 3 consecutive years. Comparison of the emission levels in the first and second year showed a reduction of the methane emission of about 50% due to implementation of a gas extraction system. From the second to the third year emissions increased by a factor of 4 due to new land filling. Furthermore measurements were performed in winter when oxidation efficiency was reduced. This paper describes the measurement technique used, and discusses the results of the experimental sessions that were performed

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI.

Science.gov (United States)

Zhang, Guangwen; Wang, Shuangshuang; Wen, Didi; Zhang, Jing; Wei, Xiaocheng; Ma, Wanling; Zhao, Weiwei; Wang, Mian; Wu, Guosheng; Zhang, Jinsong

2016-12-09

Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R 2  = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.

Non-gaussian turbulence

Energy Technology Data Exchange (ETDEWEB)

Hoejstrup, J [NEG Micon Project Development A/S, Randers (Denmark); Hansen, K S [Denmarks Technical Univ., Dept. of Energy Engineering, Lyngby (Denmark); Pedersen, B J [VESTAS Wind Systems A/S, Lem (Denmark); Nielsen, M [Risoe National Lab., Wind Energy and Atmospheric Physics, Roskilde (Denmark)

1999-03-01

The pdf`s of atmospheric turbulence have somewhat wider tails than a Gaussian, especially regarding accelerations, whereas velocities are close to Gaussian. This behaviour is being investigated using data from a large WEB-database in order to quantify the amount of non-Gaussianity. Models for non-Gaussian turbulence have been developed, by which artificial turbulence can be generated with specified distributions, spectra and cross-correlations. The artificial time series will then be used in load models and the resulting loads in the Gaussian and the non-Gaussian cases will be compared. (au)

Automated Generation of 3D Volcanic Gas Plume Models for Geobrowsers

Science.gov (United States)

Wright, T. E.; Burton, M.; Pyle, D. M.

2007-12-01

A network of five UV spectrometers on Etna automatically gathers column amounts of SO2 during daylight hours. Near-simultaneous scans from adjacent spectrometers, comprising 210 column amounts in total, are then converted to 2D slices showing the spatial distribution of the gas by tomographic reconstruction. The trajectory of the plume is computed using an automatically-submitted query to NOAA's HYSPLIT Trajectory Model. This also provides local estimates of air temperature, which are used to determine the atmospheric stability and therefore the degree to which the plume is dispersed by turbulence. This information is sufficient to construct an animated sequence of models which show how the plume is advected and diffused over time. These models are automatically generated in the Collada Digital Asset Exchange format and combined into a single file which displays the evolution of the plume in Google Earth. These models are useful for visualising and predicting the shape and distribution of the plume for civil defence, to assist field campaigns and as a means of communicating some of the work of volcano observatories to the public. The Simultaneous Algebraic Reconstruction Technique is used to create the 2D slices. This is a well-known method, based on iteratively updating a forward model (from 2D distribution to column amounts). Because it is based on a forward model, it also provides a simple way to quantify errors.

GaussianCpG: a Gaussian model for detection of CpG island in human genome sequences.

Science.gov (United States)

Yu, Ning; Guo, Xuan; Zelikovsky, Alexander; Pan, Yi

2017-05-24

As crucial markers in identifying biological elements and processes in mammalian genomes, CpG islands (CGI) play important roles in DNA methylation, gene regulation, epigenetic inheritance, gene mutation, chromosome inactivation and nuclesome retention. The generally accepted criteria of CGI rely on: (a) %G+C content is ≥ 50%, (b) the ratio of the observed CpG content and the expected CpG content is ≥ 0.6, and (c) the general length of CGI is greater than 200 nucleotides. Most existing computational methods for the prediction of CpG island are programmed on these rules. However, many experimentally verified CpG islands deviate from these artificial criteria. Experiments indicate that in many cases %G+C is human genome. We analyze the energy distribution over genomic primary structure for each CpG site and adopt the parameters from statistics of Human genome. The evaluation results show that the new model can predict CpG islands efficiently by balancing both sensitivity and specificity over known human CGI data sets. Compared with other models, GaussianCpG can achieve better performance in CGI detection. Our Gaussian model aims to simplify the complex interaction between nucleotides. The model is computed not by the linear statistical method but by the Gaussian energy distribution and accumulation. The parameters of Gaussian function are not arbitrarily designated but deliberately chosen by optimizing the biological statistics. By using the pseudopotential analysis on CpG islands, the novel model is validated on both the real and artificial data sets.

Turbulent Plume Dispersion over Two-dimensional Idealized Urban Street Canyons

Science.gov (United States)

Wong, C. C. C.; Liu, C. H.

2012-04-01

Human activities are the primary pollutant sources which degrade the living quality in the current era of dense and compact cities. A simple and reasonably accurate pollutant dispersion model is helpful to reduce pollutant concentrations in city or neighborhood scales by refining architectural design or urban planning. The conventional method to estimate the pollutant concentration from point/line sources is the Gaussian plume model using empirical dispersion coefficients. Its accuracy is pretty well for applying to rural areas. However, the dispersion coefficients only account for the atmospheric stability and streamwise distance that often overlook the roughness of urban surfaces. Large-scale buildings erected in urban areas significantly modify the surface roughness that in turn affects the pollutant transport in the urban canopy layer (UCL). We hypothesize that the aerodynamic resistance is another factor governing the dispersion coefficient in the UCL. This study is thus conceived to study the effects of urban roughness on pollutant dispersion coefficients and the plume behaviors. Large-eddy simulations (LESs) are carried out to examine the plume dispersion from a ground-level pollutant source over idealized 2D street canyons in neutral stratification. Computations with a wide range of aspect ratios (ARs), including skimming flow to isolated flow regimes, are conducted. The vertical profiles of pollutant distribution for different values of friction factor are compared that all reach a self-similar Gaussian shape. Preliminary results show that the pollutant dispersion is closely related to the friction factor. For relatively small roughness, the factors of dispersion coefficient vary linearly with the friction factor until the roughness is over a certain level. When the friction factor is large, its effect on the dispersion coefficient is less significant. Since the linear region covers at least one-third of the full range of friction factor in our empirical

Application Of Shared Gamma And Inverse-Gaussian Frailty Models ...

African Journals Online (AJOL)

Shared Gamma and Inverse-Gaussian Frailty models are used to analyze the survival times of patients who are clustered according to cancer/tumor types under Parametric Proportional Hazard framework. The result of the ... However, no evidence is strong enough for preference of either Gamma or Inverse Gaussian Frailty.

The importance of vertical resolution in the free troposphere for modeling intercontinental plumes

Science.gov (United States)

Zhuang, Jiawei; Jacob, Daniel J.; Eastham, Sebastian D.

2018-05-01

Chemical plumes in the free troposphere can preserve their identity for more than a week as they are transported on intercontinental scales. Current global models cannot reproduce this transport. The plumes dilute far too rapidly due to numerical diffusion in sheared flow. We show how model accuracy can be limited by either horizontal resolution (Δx) or vertical resolution (Δz). Balancing horizontal and vertical numerical diffusion, and weighing computational cost, implies an optimal grid resolution ratio (Δx / Δz)opt ˜ 1000 for simulating the plumes. This is considerably higher than current global models (Δx / Δz ˜ 20) and explains the rapid plume dilution in the models as caused by insufficient vertical resolution. Plume simulations with the Geophysical Fluid Dynamics Laboratory Finite-Volume Cubed-Sphere Dynamical Core (GFDL-FV3) over a range of horizontal and vertical grid resolutions confirm this limiting behavior. Our highest-resolution simulation (Δx ≈ 25 km, Δz ≈ 80 m) preserves the maximum mixing ratio in the plume to within 35 % after 8 days in strongly sheared flow, a drastic improvement over current models. Adding free tropospheric vertical levels in global models is computationally inexpensive and would also improve the simulation of water vapor.

Probabilistic wind power forecasting with online model selection and warped gaussian process

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Feng; Gao, Lin

2014-01-01

Highlights: • A new online ensemble model for the probabilistic wind power forecasting. • Quantifying the non-Gaussian uncertainties in wind power. • Online model selection that tracks the time-varying characteristic of wind generation. • Dynamically altering the input features. • Recursive update of base models. - Abstract: Based on the online model selection and the warped Gaussian process (WGP), this paper presents an ensemble model for the probabilistic wind power forecasting. This model provides the non-Gaussian predictive distributions, which quantify the non-Gaussian uncertainties associated with wind power. In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction. WGP is employed as the base model, which handles the non-Gaussian uncertainties in wind power series. Furthermore, a regime switch strategy is designed to modify the input feature set dynamically, thereby enhancing the adaptiveness of the model. In an online learning framework, the base models should also be time adaptive. To achieve this, a recursive algorithm is introduced, thus permitting the online updating of WGP base models. The proposed model has been tested on the actual data collected from both single and aggregated wind farms

Modeling Macro- and Micro-Scale Turbulent Mixing and Chemistry in Engine Exhaust Plumes

Science.gov (United States)

Menon, Suresh

1998-01-01

Simulation of turbulent mixing and chemical processes in the near-field plume and plume-vortex regimes has been successfully carried out recently using a reduced gas phase kinetics mechanism which substantially decreased the computational cost. A detailed mechanism including gas phase HOx, NOx, and SOx chemistry between the aircraft exhaust and the ambient air in near-field aircraft plumes is compiled. A reduced mechanism capturing the major chemical pathways is developed. Predictions by the reduced mechanism are found to be in good agreement with those by the detailed mechanism. With the reduced chemistry, the computer CPU time is saved by a factor of more than 3.5 for the near-field plume modeling. Distributions of major chemical species are obtained and analyzed. The computed sensitivities of major species with respect to reaction step are deduced for identification of the dominant gas phase kinetic reaction pathways in the jet plume. Both the near field plume and the plume-vortex regimes were investigated using advanced mixing models. In the near field, a stand-alone mixing model was used to investigate the impact of turbulent mixing on the micro- and macro-scale mixing processes using a reduced reaction kinetics model. The plume-vortex regime was simulated using a large-eddy simulation model. Vortex plume behind Boeing 737 and 747 aircraft was simulated along with relevant kinetics. Many features of the computed flow field show reasonable agreement with data. The entrainment of the engine plumes into the wing tip vortices and also the partial detrainment of the plume were numerically captured. The impact of fluid mechanics on the chemical processes was also studied. Results show that there are significant differences between spatial and temporal simulations especially in the predicted SO3 concentrations. This has important implications for the prediction of sulfuric acid aerosols in the wake and may partly explain the discrepancy between past numerical studies

Simulation of ultrasonic surface waves with multi-Gaussian and point source beam models

International Nuclear Information System (INIS)

Zhao, Xinyu; Schmerr, Lester W. Jr.; Li, Xiongbing; Sedov, Alexander

2014-01-01

In the past decade, multi-Gaussian beam models have been developed to solve many complicated bulk wave propagation problems. However, to date those models have not been extended to simulate the generation of Rayleigh waves. Here we will combine Gaussian beams with an explicit high frequency expression for the Rayleigh wave Green function to produce a three-dimensional multi-Gaussian beam model for the fields radiated from an angle beam transducer mounted on a solid wedge. Simulation results obtained with this model are compared to those of a point source model. It is shown that the multi-Gaussian surface wave beam model agrees well with the point source model while being computationally much more efficient

Field studies of submerged-diffuser thermal plumes with comparisons to predictive model results

International Nuclear Information System (INIS)

Frigo, A.A.; Paddock, R.A.; Ditmars, J.D.

1976-01-01

Thermal plumes from submerged discharges of cooling water from two power plants on Lake Michigan were studied. The system for the acquisition of water temperatures and ambient conditions permitted the three-dimensional structure of the plumes to be determined. The Zion Nuclear Power Station has two submerged discharge structures separated by only 94 m. Under conditions of flow from both structures, interaction between the two plumes resulted in larger thermal fields than would be predicted by the superposition of single non-interacting plumes. Maximum temperatures in the near-field region of the plume compared favorably with mathematical model predictions. A comparison of physical-model predictions for the plume at the D. C. Cook Nuclear Plant with prototype measurements indicated good agreement in the near-field region, but differences in the far-field occurred as similitude was not preserved there

An approximate fractional Gaussian noise model with computational cost

KAUST Repository

Sørbye, Sigrunn H.

2017-09-18

Fractional Gaussian noise (fGn) is a stationary time series model with long memory properties applied in various fields like econometrics, hydrology and climatology. The computational cost in fitting an fGn model of length $n$ using a likelihood-based approach is ${\\\\mathcal O}(n^{2})$, exploiting the Toeplitz structure of the covariance matrix. In most realistic cases, we do not observe the fGn process directly but only through indirect Gaussian observations, so the Toeplitz structure is easily lost and the computational cost increases to ${\\\\mathcal O}(n^{3})$. This paper presents an approximate fGn model of ${\\\\mathcal O}(n)$ computational cost, both with direct or indirect Gaussian observations, with or without conditioning. This is achieved by approximating fGn with a weighted sum of independent first-order autoregressive processes, fitting the parameters of the approximation to match the autocorrelation function of the fGn model. The resulting approximation is stationary despite being Markov and gives a remarkably accurate fit using only four components. The performance of the approximate fGn model is demonstrated in simulations and two real data examples.

Infrared signature modelling of a rocket jet plume - comparison with flight measurements

International Nuclear Information System (INIS)

Rialland, V; Perez, P; Roblin, A; Guy, A; Gueyffier, D; Smithson, T

2016-01-01

The infrared signature modelling of rocket plumes is a challenging problem involving rocket geometry, propellant composition, combustion modelling, trajectory calculations, fluid mechanics, atmosphere modelling, calculation of gas and particles radiative properties and of radiative transfer through the atmosphere. This paper presents ONERA simulation tools chained together to achieve infrared signature prediction, and the comparison of the estimated and measured signatures of an in-flight rocket plume. We consider the case of a solid rocket motor with aluminized propellant, the Black Brant sounding rocket. The calculation case reproduces the conditions of an experimental rocket launch, performed at White Sands in 1997, for which we obtained high quality infrared signature data sets from DRDC Valcartier. The jet plume is calculated using an in-house CFD software called CEDRE. The plume infrared signature is then computed on the spectral interval 1900-5000 cm -1 with a step of 5 cm -1 . The models and their hypotheses are presented and discussed. Then the resulting plume properties, radiance and spectra are detailed. Finally, the estimated infrared signature is compared with the spectral imaging measurements. The discrepancies are analyzed and discussed. (paper)

Liquid Booster Module (LBM) plume flowfield model

Science.gov (United States)

Smith, S. D.

1981-01-01

A complete definition of the LBM plume is important for many Shuttle design criteria. The exhaust plume shape has a significant effect on the vehicle base pressure. The LBM definition is also important to the Shuttle base heating, aerodynamics and the influence of the exhaust plume on the launch stand and environment. For these reasons a knowledge of the LBM plume characteristics is necessary. A definition of the sea level LBM plume as well as at several points along the Shuttle trajectory to LBM, burnout is presented.

Direct Importance Estimation with Gaussian Mixture Models

Science.gov (United States)

Yamada, Makoto; Sugiyama, Masashi

The ratio of two probability densities is called the importance and its estimation has gathered a great deal of attention these days since the importance can be used for various data processing purposes. In this paper, we propose a new importance estimation method using Gaussian mixture models (GMMs). Our method is an extention of the Kullback-Leibler importance estimation procedure (KLIEP), an importance estimation method using linear or kernel models. An advantage of GMMs is that covariance matrices can also be learned through an expectation-maximization procedure, so the proposed method — which we call the Gaussian mixture KLIEP (GM-KLIEP) — is expected to work well when the true importance function has high correlation. Through experiments, we show the validity of the proposed approach.

The importance of vertical resolution in the free troposphere for modeling intercontinental plumes

Directory of Open Access Journals (Sweden)

J. Zhuang

2018-05-01

Full Text Available Chemical plumes in the free troposphere can preserve their identity for more than a week as they are transported on intercontinental scales. Current global models cannot reproduce this transport. The plumes dilute far too rapidly due to numerical diffusion in sheared flow. We show how model accuracy can be limited by either horizontal resolution (Δx or vertical resolution (Δz. Balancing horizontal and vertical numerical diffusion, and weighing computational cost, implies an optimal grid resolution ratio (Δx ∕ Δzopt ∼ 1000 for simulating the plumes. This is considerably higher than current global models (Δx ∕ Δz ∼ 20 and explains the rapid plume dilution in the models as caused by insufficient vertical resolution. Plume simulations with the Geophysical Fluid Dynamics Laboratory Finite-Volume Cubed-Sphere Dynamical Core (GFDL-FV3 over a range of horizontal and vertical grid resolutions confirm this limiting behavior. Our highest-resolution simulation (Δx ≈ 25 km, Δz  ≈  80 m preserves the maximum mixing ratio in the plume to within 35 % after 8 days in strongly sheared flow, a drastic improvement over current models. Adding free tropospheric vertical levels in global models is computationally inexpensive and would also improve the simulation of water vapor.

Model Intercomparison Study to Investigate a Dense Contaminant Plume in a Complex Hydrogeologic System

International Nuclear Information System (INIS)

Williams, Mark D.; Cole, Charles R.; Foley, Michael G.; Zinina, Galina A.; Zinin, Alexander I.; Vasil'Kova, Nelly A.; Samsonova, Lilia M.

2001-01-01

A joint Russian and U.S. model intercomparison study was undertaken for developing more realistic contaminant transport models of the Mayak Site, Southern Urals. The test problems were developed by the Russian Team based on their experience modeling contaminant migration near Lake Karachai. The intercomparison problems were designed to address lake and contaminant plume interactions, as well as river interactions and plume density effects. Different numerical codes were used. Overall there is good agreement between the results of both models. Features shown by both models include (1) the sinking of the plume below the lake, (2) the raising of the water table in the fresh water adjacent to the lake in response to the increased pressure from the dense plume, and (3) the formation of a second sinking plume in an area where evapotranspiration exceeded infiltration, thus increasing the solute concentrations above the source (i.e., lake) values

Modeling of the near field plume of a Hall thruster

International Nuclear Information System (INIS)

Boyd, Iain D.; Yim, John T.

2004-01-01

In this study, a detailed numerical model is developed to simulate the xenon plasma near-field plume from a Hall thruster. The model uses a detailed fluid model to describe the electrons and a particle-based kinetic approach is used to model the heavy xenon ions and atoms. The detailed model is applied to compute the near field plume of a small, 200 W Hall thruster. Results from the detailed model are compared with the standard modeling approach that employs the Boltzmann model. The usefulness of the model detailed is assessed through direct comparisons with a number of different measured data sets. The comparisons illustrate that the detailed model accurately predicts a number of features of the measured data not captured by the simpler Boltzmann approach

Formation of mantle "lone plumes" in the global downwelling zone - A multiscale modelling of subduction-controlled plume generation beneath the South China Sea

Science.gov (United States)

Zhang, Nan; Li, Zheng-Xiang

2018-01-01

It has been established that almost all known mantle plumes since the Mesozoic formed above the two lower mantle large low shear velocity provinces (LLSVPs). The Hainan plume is one of the rare exceptions in that instead of rising above the LLSVPs, it is located within the broad global mantle downwelling zone, therefore classified as a "lone plume". Here, we use the Hainan plume example to investigate the feasibility of such lone plumes being generated by subducting slabs in the mantle downwelling zone using 3D geodynamic modelling. Our geodynamic model has a high-resolution regional domain embedded in a relatively low resolution global domain, which is set up in an adaptive-mesh-refined, 3D mantle convection code ASPECT (Advanced Solver for Problems in Earth's ConvecTion). We use a recently published plate motion model to define the top mechanical boundary condition. Our modelling results suggest that cold slabs under the present-day Eurasia, formed from the Mesozoic subduction and closure of the Tethys oceans, have prevented deep mantle hot materials from moving to the South China Sea from regions north or west of the South China Sea. From the east side, the Western Pacific subduction systems started to promote the formation of a lower-mantle thermal-chemical pile in the vicinity of the future South China Sea region since 70 Ma ago. As the top of this lower-mantle thermal-chemical pile rises, it first moved to the west, and finally rested beneath the South China Sea. The presence of a thermochemical layer (possible the D″ layer) in the model helps stabilizing the plume root. Our modelling is the first implementation of multi-scale mesh in the regional model. It has been proved to be an effective way of modelling regional dynamics within a global plate motion and mantle dynamics background.

Cooling tower plume - model and experiment

Science.gov (United States)

Cizek, Jan; Gemperle, Jiri; Strob, Miroslav; Nozicka, Jiri

The paper discusses the description of the simple model of the, so-called, steam plume, which in many cases forms during the operation of the evaporative cooling systems of the power plants, or large technological units. The model is based on semi-empirical equations that describe the behaviour of a mixture of two gases in case of the free jet stream. In the conclusion of the paper, a simple experiment is presented through which the results of the designed model shall be validated in the subsequent period.

A mantle plume model for the Equatorial Highlands of Venus

Science.gov (United States)

Kiefer, Walter S.; Hager, Bradford H.

1991-01-01

The possibility that the Equatorial Highlands are the surface expressions of hot upwelling mantle plumes is considered via a series of mantle plume models developed using a cylindrical axisymmetric finite element code and depth-dependent Newtonian rheology. The results are scaled by assuming whole mantle convection and that Venus and the earth have similar mantle heat flows. The best model fits are for Beta and Atla. The common feature of the allowed viscosity models is that they lack a pronounced low-viscosity zone in the upper mantle. The shape of Venus's long-wavelength admittance spectrum and the slope of its geoid spectrum are also consistent with the lack of a low-viscosity zone. It is argued that the lack of an asthenosphere on Venus is due to the mantle of Venus being drier than the earth's mantle. Mantle plumes may also have contributed to the formation of some smaller highland swells, such as the Bell and Eistla regions and the Hathor/Innini/Ushas region.

Towards LES Models of Jets and Plumes

Science.gov (United States)

Webb, A. T.; Mansour, N. N.

2000-01-01

As pointed out by Rodi standard integral solutions for jets and plumes developed for discharge into infinite, quiescent ambient are difficult to extend to complex situations, particularly in the presence of boundaries such as the sea floor or ocean surface. In such cases the assumption of similarity breaks down and it is impossible to find a suitable entrainment coefficient. The models are also incapable of describing any but the most slowly varying unsteady motions. There is therefore a need for full time-dependent modeling of the flow field for which there are three main approaches: (1) Reynolds averaged numerical simulation (RANS), (2) large eddy simulation (LES), and (3) direct numerical simulation (DNS). Rodi applied RANS modeling to both jets and plumes with considerable success, the test being a match with experimental data for time-averaged velocity and temperature profiles as well as turbulent kinetic energy and rms axial turbulent velocity fluctuations. This model still relies on empirical constants, some eleven in the case of the buoyant jet, and so would not be applicable to a partly laminar plume, may have limited use in the presence of boundaries, and would also be unsuitable if one is after details of the unsteady component of the flow (the turbulent eddies). At the other end of the scale DNS modeling includes all motions down to the viscous scales. Boersma et al. have built such a model for the non-buoyant case which also compares well with measured data for mean and turbulent velocity components. The model demonstrates its versatility by application to a laminar flow case. As its name implies, DNS directly models the Navier-Stokes equations without recourse to subgrid modeling so for flows with a broad spectrum of motions (high Re) the cost can be prohibitive - the number of required grid points scaling with Re(exp 9/4) and the number of time steps with Re(exp 3/4). The middle road is provided by LES whereby the Navier-Stokes equations are formally

Modelling the fate of the Tijuana River discharge plume

Science.gov (United States)

van Ormondt, M.; Terrill, E.; Hibler, L. F.; van Dongeren, A. R.

2010-12-01

After rainfall events, the Tijuana River discharges excess runoff into the ocean in a highly turbid plume. The runoff waters contain large suspended solids concentrations, as well as high levels of toxic contaminants, bacteria, and hepatitis and enteroviruses. Public health hazards posed by the effluent often result in beach closures for several kilometers northward along the U.S. shoreline. A Delft3D model has been set up to predict the fate of the Tijuana River plume. The model takes into account the effects of tides, wind, waves, salinity, and temperature stratification. Heat exchange with the atmosphere is also included. The model consists of a relatively coarse outer domain and a high-resolution surf zone domain that are coupled with Domain Decomposition. The offshore boundary conditions are obtained from the larger NCOM SoCal model (operated by the US Navy) that spans the entire Southern California Bight. A number of discharge events are investigated, in which model results are validated against a wide range of field measurements in the San Diego Bight. These include HF Radar surface currents, REMUS tracks, drifter deployments, satellite imagery, as well as current and temperature profile measurements at a number of locations. The model is able to reproduce the observed current and temperature patterns reasonably well. Under calm conditions, the model results suggest that the hydrodynamics in the San Diego Bight are largely governed by internal waves. During rainfall events, which are typically accompanied by strong winds and high waves, wind and wave driven currents become dominant. An analysis will be made of what conditions determine the trapping and mixing of the plume inside the surfzone and/or the propagation of the plume through the breakers and onto the coastal shelf. The model is now also running in operational mode. Three day forecasts are made every 24 hours. This study was funded by the Office of Naval Research.

Modeling an Iodine Hall Thruster Plume in the Iodine Satellite (ISAT)

Science.gov (United States)

Choi, Maria

2016-01-01

An iodine-operated 200-W Hall thruster plume has been simulated using a hybrid-PIC model to predict the spacecraft surface-plume interaction for spacecraft integration purposes. For validation of the model, the plasma potential, electron temperature, ion current flux, and ion number density of xenon propellant were compared with available measurement data at the nominal operating condition. To simulate iodine plasma, various collision cross sections were found and used in the model. While time-varying atomic iodine species (i.e., I, I+, I2+) information is provided by HPHall simulation at the discharge channel exit, the molecular iodine species (i.e., I2, I2+) are introduced as Maxwellian particles at the channel exit. Simulation results show that xenon and iodine plasma plumes appear to be very similar under the assumptions of the model. Assuming a sticking coefficient of unity, iodine deposition rate is estimated.

Review of air quality modeling techniques. Volume 8

International Nuclear Information System (INIS)

Rosen, L.C.

1977-01-01

Air transport and diffusion models which are applicable to the assessment of the environmental effects of nuclear, geothermal, and fossil-fuel electric generation are reviewed. The general classification of models and model inputs are discussed. A detailed examination of the statistical, Gaussian plume, Gaussian puff, one-box and species-conservation-of-mass models is given. Representative models are discussed with attention given to the assumptions, input data requirement, advantages, disadvantages and applicability of each

Particle-in-cell vs straight-line airflow Gaussian calculations of concentration and deposition of airborne emissions out to 70 km for two sites of differing meteorological and topographical character

International Nuclear Information System (INIS)

Lange, R.; Dickerson, M.A.; Peterson, K.R.; Sherman, C.A.; Sullivan, T.J.

1976-01-01

Two numerical models for the calculation of air concentration and ground deposition of airborne effluent releases are compared. The Particle-in-Cell (PIC) model and the Straight-Line Airflow Gaussian model were used for the simulation. Two sites were selected for comparison: the Hudson River Valley, New York, and the area around the Savannah River Plant, South Carolina. Input for the models was synthesized from meteorological data gathered in previous studies by various investigators. It was found that the PIC model more closely simulated the three-dimensional effects of the meteorology and topography. Overall, the Gaussian model calculated higher concentrations under stable conditions with better agreement between the two methods during neutral to unstable conditions. In addition, because of its consideration of exposure from the returning plume after flow reversal, the PIC model calculated air concentrations over larger areas than did the Gaussian model

Cooling tower plume - model and experiment

Directory of Open Access Journals (Sweden)

Cizek Jan

2017-01-01

Full Text Available The paper discusses the description of the simple model of the, so-called, steam plume, which in many cases forms during the operation of the evaporative cooling systems of the power plants, or large technological units. The model is based on semi-empirical equations that describe the behaviour of a mixture of two gases in case of the free jet stream. In the conclusion of the paper, a simple experiment is presented through which the results of the designed model shall be validated in the subsequent period.

Numerical modeling of plasma plume evolution against ambient background gas in laser blow off experiments

International Nuclear Information System (INIS)

Patel, Bhavesh G.; Das, Amita; Kaw, Predhiman; Singh, Rajesh; Kumar, Ajai

2012-01-01

Two dimensional numerical modelling based on simplified hydrodynamic evolution for an expanding plasma plume (created by laser blow off) against an ambient background gas has been carried out. A comparison with experimental observations shows that these simulations capture most features of the plasma plume expansion. The plume location and other gross features are reproduced as per the experimental observation in quantitative detail. The plume shape evolution and its dependence on the ambient background gas are in good qualitative agreement with the experiment. This suggests that a simplified hydrodynamic expansion model is adequate for the description of plasma plume expansion.

Considering a point-source in a regional air pollution model; Prise en compte d`une source ponctuelle dans un modele regional de pollution atmospherique

Energy Technology Data Exchange (ETDEWEB)

Lipphardt, M.

1997-06-19

This thesis deals with the development and validation of a point-source plume model, with the aim to refine the representation of intensive point-source emissions in regional-scale air quality models. The plume is modelled at four levels of increasing complexity, from a modified Gaussian plume model to the Freiberg and Lusis ring model. Plume elevation is determined by Netterville`s plume rise model, using turbulence and atmospheric stability parameters. A model for the effect of a fine-scale turbulence on the mean concentrations in the plume is developed and integrated in the ring model. A comparison between results with and without considering micro-mixing shows the importance of this effect in a chemically reactive plume. The plume model is integrated into the Eulerian transport/chemistry model AIRQUAL, using an interface between Airqual and the sub-model, and interactions between the two scales are described. A simulation of an air pollution episode over Paris is carried out, showing that the utilization of such a sub-scale model improves the accuracy of the air quality model

American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution

DEFF Research Database (Denmark)

Stentoft, Lars Peter

In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpret...... properties shows that there are important option pricing differences compared to the Gaussian case as well as to the symmetric special case. A large scale empirical examination shows that our model outperforms the Gaussian case for pricing options on three large US stocks as well as a major index...

Observation and modeling of the evolution of Texas power plant plumes

Directory of Open Access Journals (Sweden)

W. Zhou

2012-01-01

Full Text Available During the second Texas Air Quality Study 2006 (TexAQS II, a full range of pollutants was measured by aircraft in eastern Texas during successive transects of power plant plumes (PPPs. A regional photochemical model is applied to simulate the physical and chemical evolution of the plumes. The observations reveal that SO₂ and NO_y were rapidly removed from PPPs on a cloudy day but not on the cloud-free days, indicating efficient aqueous processing of these compounds in clouds. The model reasonably represents observed NO_x oxidation and PAN formation in the plumes, but fails to capture the rapid loss of SO₂ (0.37 h⁻¹ and NO_y (0.24 h⁻¹ in some plumes on the cloudy day. Adjustments to the cloud liquid water content (QC and the default metal concentrations in the cloud module could explain some of the SO₂ loss. However, NO_y in the model was insensitive to QC. These findings highlight cloud processing as a major challenge to atmospheric models. Model-based estimates of ozone production efficiency (OPE in PPPs are 20–50 % lower than observation-based estimates for the cloudy day.

Predicted and observed cooling tower plume rise and visible plume length at the John E. Amos power plant

Energy Technology Data Exchange (ETDEWEB)

Hanna, S R

1976-01-01

A one-dimensional numerical cloud growth model and several empirical models for plume rise and cloud growth are compared with twenty-seven sets of observations of cooling tower plumes from the 2900 MW John E. Amos power plant in West Virginia. The three natural draft cooling towers are 200 m apart. In a cross wind, the plumes begin to merge at a distance of about 500 m downwind. In calm conditions, with reduced entrainment, the plumes often do not merge until heights of 1000 m. The average plume rise, 750 m, is predicted well by the models, but day-to-day variations are simulated with a correlation coefficient of about 0.5. Model predictions of visible plume length agree, on the average, with observations for visible plumes of short to moderate length (less than about 1 km). The prediction of longer plumes is hampered by our lack of knowledge of plume spreading after the plumes level off. Cloud water concentrations predicted by the numerical model agree with those measured in natural cumulus clouds (about 0.1 to 1 g kg/sup -1/).

Improved Expectation Maximization Algorithm for Gaussian Mixed Model Using the Kernel Method

Directory of Open Access Journals (Sweden)

Mohd Izhan Mohd Yusoff

2013-01-01

Full Text Available Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.

Color Texture Segmentation by Decomposition of Gaussian Mixture Model

Czech Academy of Sciences Publication Activity Database

Grim, Jiří; Somol, Petr; Haindl, Michal; Pudil, Pavel

2006-01-01

Roč. 19, č. 4225 (2006), s. 287-296 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA MŠk 2C06019 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : texture segmentation * gaussian mixture model * EM algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/grim-color texture segmentation by decomposition of gaussian mixture model.pdf

Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

Energy Technology Data Exchange (ETDEWEB)

Stein, Michael [Univ. of Chicago, IL (United States)

2017-03-13

Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead to predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the

An Overview of Plume Tracker: Mapping Volcanic Emissions with Interactive Radiative Transfer Modeling

Science.gov (United States)

Realmuto, V. J.; Berk, A.; Guiang, C.

2014-12-01

Infrared remote sensing is a vital tool for the study of volcanic plumes, and radiative transfer (RT) modeling is required to derive quantitative estimation of the sulfur dioxide (SO2), sulfate aerosol (SO4), and silicate ash (pulverized rock) content of these plumes. In the thermal infrared, we must account for the temperature, emissivity, and elevation of the surface beneath the plume, plume altitude and thickness, and local atmospheric temperature and humidity. Our knowledge of these parameters is never perfect, and interactive mapping allows us to evaluate the impact of these uncertainties on our estimates of plume composition. To enable interactive mapping, the Jet Propulsion Laboratory is collaborating with Spectral Sciences, Inc., (SSI) to develop the Plume Tracker toolkit. This project is funded by a NASA AIST Program Grant (AIST-11-0053) to SSI. Plume Tracker integrates (1) retrieval procedures for surface temperature and emissivity, SO2, NH3, or CH4 column abundance, and scaling factors for H2O vapor and O3 profiles, (2) a RT modeling engine based on MODTRAN, and (3) interactive visualization and analysis utilities under a single graphics user interface. The principal obstacle to interactive mapping is the computational overhead of the RT modeling engine. Under AIST-11-0053 we have achieved a 300-fold increase in the performance of the retrieval procedures through the use of indexed caches of model spectra, optimization of the minimization procedures, and scaling of the effects of surface temperature and emissivity on model radiance spectra. In the final year of AIST-11-0053 we will implement parallel processing to exploit multi-core CPUs and cluster computing, and optimize the RT engine to eliminate redundant calculations when iterating over a range of gas concentrations. These enhancements will result in an additional 8 - 12X increase in performance. In addition to the improvements in performance, we have improved the accuracy of the Plume Tracker

Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.

Science.gov (United States)

Savitsky, Terrance; Vannucci, Marina; Sha, Naijun

2011-02-01

This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data. Our specific interest is in the analysis of data sets with predictors that have an a priori unknown form of possibly nonlinear associations to the response. The modeling approach we describe incorporates Gaussian processes in a generalized linear model framework to obtain a class of nonparametric regression models where the covariance matrix depends on the predictors. We consider, in particular, continuous, categorical and count responses. We also look into models that account for survival outcomes. We explore alternative covariance formulations for the Gaussian process prior and demonstrate the flexibility of the construction. Next, we focus on the important problem of selecting variables from the set of possible predictors and describe a general framework that employs mixture priors. We compare alternative MCMC strategies for posterior inference and achieve a computationally efficient and practical approach. We demonstrate performances on simulated and benchmark data sets.

Perturbative corrections for approximate inference in gaussian latent variable models

DEFF Research Database (Denmark)

Opper, Manfred; Paquet, Ulrich; Winther, Ole

2013-01-01

Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact b...... illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution. © 2013 Manfred Opper, Ulrich Paquet and Ole Winther....

Water Resources Research Program. Surface thermal plumes: evaluation of mathematical models for the near and complete field

International Nuclear Information System (INIS)

Dunn, W.E.; Policastro, A.J.; Paddock, R.A.

1975-05-01

This report evaluates mathematical models that may be used to predict the flow and temperature distributions resulting from heated surface discharges from power-plant outfalls. Part One discusses the basic physics of surface-plume dispersion and provides a critical review of 11 of the most popular and promising plume models developed to predict the near- and complete-field plume. The principal conclusion of the report is that the available models, in their present stage of development, may be used to give only general estimates of plume characteristics; precise predictions are not currently possible. The Shirazi-Davis and Pritchard (No. 1) models appear superior to the others tested and are capable of correctly predicting general plume characteristics. (The predictions show roughly factor-of-two accuracy in centerline distance to a given isotherm, factor-of-two accuracy in plume width, and factor-of-five accuracy in isotherm areas.) The state of the art can best be improved by pursuing basic laboratory studies of plume dispersion along with further development of numerical-modeling techniques

Supervised Gaussian mixture model based remote sensing image ...

African Journals Online (AJOL)

Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

Discontinuous Galerkin modeling of the Columbia River's coupled estuary-plume dynamics

Science.gov (United States)

Vallaeys, Valentin; Kärnä, Tuomas; Delandmeter, Philippe; Lambrechts, Jonathan; Baptista, António M.; Deleersnijder, Eric; Hanert, Emmanuel

2018-04-01

The Columbia River (CR) estuary is characterized by high river discharge and strong tides that generate high velocity flows and sharp density gradients. Its dynamics strongly affects the coastal ocean circulation. Tidal straining in turn modulates the stratification in the estuary. Simulating the hydrodynamics of the CR estuary and plume therefore requires a multi-scale model as both shelf and estuarine circulations are coupled. Such a model has to keep numerical dissipation as low as possible in order to correctly represent the plume propagation and the salinity intrusion in the estuary. Here, we show that the 3D baroclinic discontinuous Galerkin finite element model SLIM 3D is able to reproduce the main features of the CR estuary-to-ocean continuum. We introduce new vertical discretization and mode splitting that allow us to model a region characterized by complex bathymetry and sharp density and velocity gradients. Our model takes into account the major forcings, i.e. tides, surface wind stress and river discharge, on a single multi-scale grid. The simulation period covers the end of spring-early summer of 2006, a period of high river flow and strong changes in the wind regime. SLIM 3D is validated with in-situ data on the shelf and at multiple locations in the estuary and compared with an operational implementation of SELFE. The model skill in the estuary and on the shelf indicate that SLIM 3D is able to reproduce the key processes driving the river plume dynamics, such as the occurrence of bidirectional plumes or reversals of the inner shelf coastal currents.

Expansion dynamics and equilibrium conditions in a laser ablation plume of lithium: Modeling and experiment

International Nuclear Information System (INIS)

Stapleton, M.W.; McKiernan, A.P.; Mosnier, J.-P.

2005-01-01

The gas dynamics and atomic kinetics of a laser ablation plume of lithium, expanding adiabatically in vacuum, are included in a numerical model, using isothermal and isentropic self-similar analytical solutions and steady-state collisional radiative equations, respectively. Measurements of plume expansion dynamics using ultrafast imaging for various laser wavelengths (266-1064 nm), fluences (2-6.5 J cm -2 ), and spot sizes (50-1000 μm) are performed to provide input parameters for the model and, thereby, study the influence of laser spot size, wavelength, and fluence, respectively, on both the plume expansion dynamics and atomic kinetics. Target recoil pressure, which clearly affects plume dynamics, is included in the model. The effects of laser wavelength and spot size on plume dynamics are discussed in terms of plasma absorption of laser light. A transition from isothermal to isentropic behavior for spot sizes greater than 50 μm is clearly evidenced. Equilibrium conditions are found to exist only up to 300 ns after the plume creation, while complete local thermodynamic equilibrium is found to be confined to the very early parts of the expansion

Plume Characterization of a Laboratory Model 22 N GPIM Thruster via High-Frequency Raman Spectroscopy

Science.gov (United States)

Williams, George J.; Kojima, Jun J.; Arrington, Lynn A.; Deans, Matthew C.; Reed, Brian D.; Kinzbach, McKenzie I.; McLean, Christopher H.

2015-01-01

The Green Propellant Infusion Mission (GPIM) will demonstrate the capability of a green propulsion system, specifically, one using the monopropellant, AF-M315E. One of the risks identified for GPIM is potential contamination of sensitive areas of the spacecraft from the effluents in the plumes of AF-M315E thrusters. Plume characterization of a laboratory-model 22 N thruster via optical diagnostics was conducted at NASA GRC in a space-simulated environment. A high-frequency pulsed laser was coupled with an electron-multiplied ICCD camera to perform Raman spectroscopy in the near-field, low-pressure plume. The Raman data yielded plume constituents and temperatures over a range of thruster chamber pressures and as a function of thruster (catalyst) operating time. Schlieren images of the near-field plume enabled calculation of plume velocities and revealed general plume structure of the otherwise invisible plume. The measured velocities are compared to those predicted by a two-dimensional, kinetic model. Trends in data and numerical results are presented from catalyst mid-life to end-of-life. The results of this investigation were coupled with the Raman and Schlieren data to provide an anchor for plume impingement analysis presented in a companion paper. The results of both analyses will be used to improve understanding of the nature of AF-M315E plumes and their impacts to GPIM and other future missions.

Water Resources Research Program. Surface thermal plumes: evaluation of mathematical models for the near and complete field

International Nuclear Information System (INIS)

Dunn, W.E.; Policastro, A.J.; Paddock, R.A.

1975-08-01

This report evaluates mathematical models that may be used to predict the flow and temperature distributions resulting from heated surface discharges from power-plant outfalls. Part One discusses the basic physics of surface-plume dispersion and provides a critical review of 11 of the most popular and promising plume models developed to predict the near- and complete-field plume. Part Two compares predictions from the models to prototype data, laboratory data, or both. Part Two also provides a generic discussion of the issues surrounding near- and complete-field modeling. The principal conclusion of the report is that the available models, in their present stage of development, may be used to give only general estimates of plume characteristics; precise predictions are not currently possible. The Shirazi-Davis and Pritchard (No. 1) models appear superior to the others tested and are capable of correctly predicting general plume characteristics. (The predictions show roughly factor-of-two accuracy in centerline distance to a given isotherm, factor-of-two accuracy in plume width, and factor-of-five accuracy in isotherm areas.) The state of the art can best be improved by pursuing basic laboratory studies of plume dispersion along with further development of numerical-modeling techniques

Mathematical model of drift deposition from a bifurcated cooling tower plume

International Nuclear Information System (INIS)

Chen, N.C.J.; Jung, L.

1978-01-01

Cooling tower drift deposition modeling has been extended by including centrifugal force induced through plume bifurcation in a crosswind as a mechanism for drift droplet removal from the plume. The model, in its current state of development, is capable of predicting the trajectory of a single droplet from the stage of strong interaction with the vortex field soon after droplet emission at the tower top through the stage of droplet evaporation in an unsaturated atmosphere after droplet breakaway from the plume. The computer program developed from the mathematical formulation has been used to explore the dependency of the droplet trajectory on droplet size, vortex strength, point of droplet emission, drag coefficient, droplet efflux speed, and ambient conditions. A specific application to drift from a mechanical-draft cooling tower (for a wind speed twice the efflux speed, a relative humidity of 70 per cent, and an initial droplet radius of 100 μm) showed the droplet to follow a helical trajectory within the plume, with breakaway occurring at 2.5 tower diameters downwind and ground impact of the droplet (reduced through evaporation to 55 μm radius) at 11 tower diameters

Numerical Modeling of Water Thermal Plumes Emitted by Thermal Power Plants

Directory of Open Access Journals (Sweden)

Azucena Durán-Colmenares

2016-10-01

Full Text Available This work focuses on the study of thermal dispersion of plumes emitted by power plants into the sea. Wastewater discharge from power stations causes impacts that require investigation or monitoring. A study to characterize the physical effects of thermal plumes into the sea is carried out here by numerical modeling and field measurements. The case study is the thermal discharges of the Presidente Adolfo López Mateos Power Plant, located in Veracruz, on the coast of the Gulf of Mexico. This plant is managed by the Federal Electricity Commission of Mexico. The physical effects of such plumes are related to the increase of seawater temperature caused by the hot water discharge of the plant. We focus on the implementation, calibration, and validation of the Delft3D-FLOW model, which solves the shallow-water equations. The numerical simulations consider a critical scenario where meteorological and oceanographic parameters are taken into account to reproduce the proper physical conditions of the environment. The results show a local physical effect of the thermal plumes within the study zone, given the predominant strong winds conditions of the scenario under study.

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

Science.gov (United States)

Semper, Sean R.; Crassidis, John L.; George, Jemin; Mukherjee, Siddharth; Singla, Puneet

2015-01-01

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating

Initialization of the Euler model MODIS with field data from the 'EPRI plume model validation project'

International Nuclear Information System (INIS)

Petersen, G.; Eppel, D.; Lautenschlager, M.; Mueller, A.

1985-01-01

The program deck MODIS (''MOment DIStribution'') is designed to be used as operational tool for modelling the dispersion of a point source under general atmospheric conditions. The concentration distribution is determined by calculating its cross-wind moments on a vertical grid oriented in the main wind direction. The model contains a parametrization for horizontal and vertical coefficients based on a second order closure model. The Eulerian time scales, preliminary determined by fitting measured plume cross sections, are confirmed by comparison with data from the EPRI plume model validation project. (orig.) [de

An approximate fractional Gaussian noise model with computational cost

KAUST Repository

Sø rbye, Sigrunn H.; Myrvoll-Nilsen, Eirik; Rue, Haavard

2017-01-01

Fractional Gaussian noise (fGn) is a stationary time series model with long memory properties applied in various fields like econometrics, hydrology and climatology. The computational cost in fitting an fGn model of length $n$ using a likelihood

Modeling and Mechanisms of Intercontinental Transport of Biomass-Burning Plumes

Science.gov (United States)

Reid, J. S.; Westphal, D. L.; Christopher, S. A.; Prins, E. M.; Justice, C. O.; Richardson, K. A.; Reid, E. A.; Eck, T. F.

2003-12-01

With the aid of fire products from GOES and MODIS, the NRL Aerosol Analysis and Prediction System (NAAPS) successfully monitors and predicts the formation and transport of massive smoke plumes between the continents in near real time. The goal of this system, formed under the joint Navy, NASA, and NOAA sponsored Fire Locating and Modeling of Burning Emissions (FLAMBE) project, is to provide 5 day forecasts of large biomass burning plumes and evaluate impacts on air quality, visibility, and regional radiative balance. In this paper we discuss and compare the mechanisms of intercontinental transport from the three most important sources in the world prone to long range advection: Africa, South/Central America, and Siberia. We demonstrate how these regions impact neighboring continents. As the meteorology of these three regions are distinct, differences in transport phenomenon subsequently result, particularly with respect to vertical distribution. Specific examples will be given on prediction and the impact of Siberian and Central American smoke plumes on the United States as well as transport phenomena from Africa to Australia. We present rules of thumb for radiation and air quality impacts. We also model clear sky bias (both positive and negative) with respect to MODIS data, and show the frequency to which frontal advection of smoke plumes masks remote sensing retrievals of smoke optical depth.

Fractional Gaussian noise: Prior specification and model comparison

KAUST Repository

Sørbye, Sigrunn Holbek

2017-07-07

Fractional Gaussian noise (fGn) is a stationary stochastic process used to model antipersistent or persistent dependency structures in observed time series. Properties of the autocovariance function of fGn are characterised by the Hurst exponent (H), which, in Bayesian contexts, typically has been assigned a uniform prior on the unit interval. This paper argues why a uniform prior is unreasonable and introduces the use of a penalised complexity (PC) prior for H. The PC prior is computed to penalise divergence from the special case of white noise and is invariant to reparameterisations. An immediate advantage is that the exact same prior can be used for the autocorrelation coefficient ϕ(symbol) of a first-order autoregressive process AR(1), as this model also reflects a flexible version of white noise. Within the general setting of latent Gaussian models, this allows us to compare an fGn model component with AR(1) using Bayes factors, avoiding the confounding effects of prior choices for the two hyperparameters H and ϕ(symbol). Among others, this is useful in climate regression models where inference for underlying linear or smooth trends depends heavily on the assumed noise model.

Fractional Gaussian noise: Prior specification and model comparison

KAUST Repository

Sø rbye, Sigrunn Holbek; Rue, Haavard

2017-01-01

Fractional Gaussian noise (fGn) is a stationary stochastic process used to model antipersistent or persistent dependency structures in observed time series. Properties of the autocovariance function of fGn are characterised by the Hurst exponent (H), which, in Bayesian contexts, typically has been assigned a uniform prior on the unit interval. This paper argues why a uniform prior is unreasonable and introduces the use of a penalised complexity (PC) prior for H. The PC prior is computed to penalise divergence from the special case of white noise and is invariant to reparameterisations. An immediate advantage is that the exact same prior can be used for the autocorrelation coefficient ϕ(symbol) of a first-order autoregressive process AR(1), as this model also reflects a flexible version of white noise. Within the general setting of latent Gaussian models, this allows us to compare an fGn model component with AR(1) using Bayes factors, avoiding the confounding effects of prior choices for the two hyperparameters H and ϕ(symbol). Among others, this is useful in climate regression models where inference for underlying linear or smooth trends depends heavily on the assumed noise model.

Simulation of Mexico City plumes during the MIRAGE-Mex field campaign using the WRF-Chem model

Directory of Open Access Journals (Sweden)

X. Tie

2009-07-01

Full Text Available The quantification of tropospheric O₃ production in the downwind of the Mexico City plume is a major objective of the MIRAGE-Mex field campaign. We used a regional chemistry-transport model (WRF-Chem to predict the distribution of O₃ and its precursors in Mexico City and the surrounding region during March 2006, and compared the model with in-situ aircraft measurements of O₃, CO, VOCs, NO_x, and NO_y concentrations. The comparison shows that the model is capable of capturing the timing and location of the measured city plumes, and the calculated variability along the flights is generally consistent with the measured results, showing a rapid increase in O₃ and its precursors when city plumes are detected. However, there are some notable differences between the calculated and measured values, suggesting that, during transport from the surface of the city to the outflow plume, ozone mixing ratios are underestimated by about 0–25% during different flights. The calculated O₃-NO_x, O₃-CO, and O₃-NO_z correlations generally agree with the measured values, and the analyses of these correlations suggest that photochemical O₃ production continues in the plume downwind of the city (aged plume, adding to the O₃ already produced in the city and exported with the plume. The model is also used to quantify the contributions to OH reactivity from various compounds in the aged plume. This analysis suggests that oxygenated organics (OVOCs have the highest OH reactivity and play important roles for the O₃ production in the aging plume. Furthermore, O₃ production per NO_x molecule consumed (O₃ production efficiency is more efficient in the aged plume than in the young plume near the city. The major contributor to the high O₃ production efficiency in the aged plume is the

Investigation of Balcony Plume Entrainment

OpenAIRE

Liu, F.; Nielsen, Peter V.; Heiselberg, Per; Brohus, Henrik; Li, B. Z.

2009-01-01

An investigation on the scenarios of the spill plume and its equation was presented in this paper. The study includes two aspects, i.e., the small-scale experiment and the numerical simulation. Two balcony spill plume models are assessed by comparing with the FDS (Fire Dynamic Simulation) and small scale model experiment results. Besides validating the spill model by experiments, the effect of different fire location on balcony plume is also discussed.The results show that the balcony equatio...

Large-Eddy Simulation on Plume Dispersion within Regular Arrays of Cubic Buildings

Science.gov (United States)

Nakayama, H.; Jurcakova, K.; Nagai, H.

2010-09-01

There is a potential problem that hazardous and flammable materials are accidentally or intentionally released into the atmosphere, either within or close to populated urban areas. For the assessment of human health hazard from toxic substances, the existence of high concentration peaks in a plume should be considered. For the safety analysis of flammable gas, certain critical threshold levels should be evaluated. Therefore, in such a situation, not only average levels but also instantaneous magnitudes of concentration should be accurately predicted. However, plume dispersion is an extremely complicated process strongly influenced by the existence of buildings. In complex turbulent flows, such as impinging, separated and circulation flows around buildings, plume behaviors can be no longer accurately predicted using empirical Gaussian-type plume model. Therefore, we perform Large-Eddy Simulations (LES) on turbulent flows and plume dispersions within and over regular arrays of cubic buildings with various roughness densities and investigate the influence of the building arrangement pattern on the characteristics of mean and fluctuation concentrations. The basic equations for the LES model are composed of the spatially filtered continuity equation, Navier-Stokes equation and transport equation of concentration. The standard Smagorinsky model (Smagorinsky, 1963) that has enough potential for environment flows is used and its constant is set to 0.12 for estimating the eddy viscosity. The turbulent Schmidt number is 0.5. In our LES model, two computational regions are set up. One is a driver region for generation of inflow turbulence and the other is a main region for LES of plume dispersion within a regular array of cubic buildings. First, inflow turbulence is generated by using Kataoka's method (2002) in the driver region and then, its data are imposed at the inlet of the main computational region at each time step. In this study, the cubic building arrays with λf=0

Topology in two dimensions. IV - CDM models with non-Gaussian initial conditions

Science.gov (United States)

Coles, Peter; Moscardini, Lauro; Plionis, Manolis; Lucchin, Francesco; Matarrese, Sabino; Messina, Antonio

1993-02-01

The results of N-body simulations with both Gaussian and non-Gaussian initial conditions are used here to generate projected galaxy catalogs with the same selection criteria as the Shane-Wirtanen counts of galaxies. The Euler-Poincare characteristic is used to compare the statistical nature of the projected galaxy clustering in these simulated data sets with that of the observed galaxy catalog. All the models produce a topology dominated by a meatball shift when normalized to the known small-scale clustering properties of galaxies. Models characterized by a positive skewness of the distribution of primordial density perturbations are inconsistent with the Lick data, suggesting problems in reconciling models based on cosmic textures with observations. Gaussian CDM models fit the distribution of cell counts only if they have a rather high normalization but possess too low a coherence length compared with the Lick counts. This suggests that a CDM model with extra large scale power would probably fit the available data.

A numerical model for buoyant oil jets and smoke plumes

International Nuclear Information System (INIS)

Zheng, L.; Yapa, P. D.

1997-01-01

Development of a 3-D numerical model to simulate the behaviour of buoyant oil jets from underwater accidents and smoke plumes from oil burning was described. These jets/plumes can be oil-in-water, oil/gas mixture in water, gas in water, or gas in air. The ambient can have a 3-D flow structure, and spatially/temporally varying flow conditions. The model is based on the Lagrangian integral technique. The model formulation of oil jet includes the diffusion and dissolution of oil from the jet to the ambient environment. It is suitable to simulate well blowout accidents that can occur in deep waters, including that of the North Sea. The model has been thoroughly tested against a variety of data, including data from both laboratory and field experiments. In all cases the simulation data compared very well with experimental data. 26 refs., 10 figs

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Science.gov (United States)

Borges, G. M.; Ferreira, A. S.; da Silva, M. A. A.; Cressoni, J. C.; Viswanathan, G. M.; Mariz, A. M.

2012-09-01

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e.g., fractional Brownian motion, Lévy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation σt which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

The maximum ground level concentration of air pollutant and the effect of plume rise on concentration estimates

International Nuclear Information System (INIS)

Mayhoub, A.B.; Azzam, A.

1991-01-01

The emission of an air pollutant from an elevated point source according to Gaussian plume model has been presented. An elementary theoretical treatment for both the highest possible ground-level concentration and the downwind distance at which this maximum occurs for different stability classes has been constructed. The effective height release modification was taken into consideration. An illustrative case study, namely, the emission from the research reactor in Inchas, has been studied. The results of these analytical treatments and of the derived semi-empirical formulae are discussed and presented in few illustrative diagrams

A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models

Directory of Open Access Journals (Sweden)

Elias D. Nino-Ruiz

2018-03-01

Full Text Available In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture density whose parameters are approximated by means of an Expectation Maximization method. Then, by using an iterative method, observation operators are linearized about current solutions and posterior modes are estimated via a MCMC implementation. The acceptance/rejection criterion is similar to that of the Metropolis-Hastings rule. Experimental tests are performed on the Lorenz 96 model. The results show that the proposed method can decrease prior errors by several order of magnitudes in a root-mean-square-error sense for nearly sparse or dense observational networks.

Modeling Laser and e-Beam Generated Plasma-Plume Experiments Using LASNEX

CERN Document Server

Ho, D

1999-01-01

The hydrodynamics code LASNEX is used to model the laser and e-beam generated plasma-plume experiments. The laser used has a wavelength of 1 (micro)m and the FWHM spot size is 1 mm. The total laser energy is 160 mJ. The simulation shows that the plume expands at a velocity of about 6 cm/(micro)s. The e-beam generated from the Experimental Test Accelerator (ETA) has 5.5 MeV and FWHM spot size ranges from 2 to 3.3 mm. From the simulations, the plasma plume expansion velocity ranges from about 3 to 6 mm/(micro)s and the velocity increases with decreasing spot size. All the simulation results reported here are in close agreement with experimental data.

Numerical Speadsheet Modeling of Natural Attenuation for Groundwater Contaminant Plumes

National Research Council Canada - National Science Library

Twesme, Troy

1999-01-01

.... The model was used to evaluate natural attenuation for removal of a trichloroethylene (TCE) plume from a surficial aquifer containing three regions with distinctly different processes for degradation of TCE...

Entrainment by turbulent plumes

Science.gov (United States)

Parker, David; Burridge, Henry; Partridge, Jamie; Linden, Paul

2017-11-01

Plumes are of relevance to nature and real consequence to industry. While the Morton, Taylor & Turner (1956) plume model is able to estimate the mean physical flux parameters, the process of entrainment is only parametrised in a time-averaged sense and a deeper understanding is key to understanding how they evolve. Various flow configurations, resulting in different entrainment values, are considered; we perform simultaneous PIV and plume-edge detection on saline plumes in water resulting from a point source, a line source and a line source where a vertical wall is placed immediately adjacent. Of particular interest is the effect the large scale eddies, forming at the edge of the plume and engulfing ambient fluid, have on the entrainment process. By using velocity statistics in a coordinate system based on the instantaneous scalar edge of the plume the significance of this large scale engulfment is quantified. It is found that significant mass is transported outside the plumes, in particular in regions where large scale structures are absent creating regions of relatively high-momentum ambient fluid. This suggests that the large scale processes, whereby ambient fluid is engulfed into the plume, contribute significantly to the entrainment.

The application of an eddy diffusivity model to the dispersion of radionuclides in the atmosphere and the calculation of cloud gamma exposure

International Nuclear Information System (INIS)

Maul, P.R.

1981-05-01

A model which has been applied successfully to the study of the mesoscale transport of sulphur compounds can be adapted for radionuclides released from nuclear power stations. Although more complicated than the conventional Gaussian plume models it has several important advantages including the better representation of dry deposition and the variation of dispersion parameters with height above the surface. Building entrainment can be included in a straightforward manner and an approximate method can be used to incorporate isotope-dependent deposition velocities. A new method of calculating cloud gamma exposure is described which is particularly suited to eddy diffusivity models. This model will be used as an alternative to Gaussian plume methods in the BNL safety code NECTAR. (author)

Mathematical modelling of thermal-plume interaction at Waterford Nuclear Power Station

International Nuclear Information System (INIS)

Tsai, S.Y.H.

1981-01-01

The Waldrop plume model was used to analyze the mixing and interaction of thermal effluents in the Mississippi River resulting from heated-water discharges from the Waterford Nuclear Power Station Unit 3 and from two nearby fossil-fueled power stations. The computer program of the model was modified and expanded to accommodate the multiple intake and discharge boundary conditions at the Waterford site. Numerical results of thermal-plume temperatures for individual and combined operation of the three power stations were obtained for typical low river flow (200,000 cfs) and maximum station operating conditions. The predicted temperature distributions indicated that the surface jet discharge from Waterford Unit 3 would interact with the thermal plumes produced by the two fossil-fueled stations. The results also showed that heat recirculation between the discharge of an upstream fossil-fueled plant and the intake of Waterford Unit 3 is to be expected. However, the resulting combined temperature distributions were found to be well within the thermal standards established by the state of Louisiana

Contaminant dispersion prediction and source estimation with integrated Gaussian-machine learning network model for point source emission in atmosphere

International Nuclear Information System (INIS)

Ma, Denglong; Zhang, Zaoxiao

2016-01-01

Highlights: • The intelligent network models were built to predict contaminant gas concentrations. • The improved network models coupled with Gaussian dispersion model were presented. • New model has high efficiency and accuracy for concentration prediction. • New model were applied to indentify the leakage source with satisfied results. - Abstract: Gas dispersion model is important for predicting the gas concentrations when contaminant gas leakage occurs. Intelligent network models such as radial basis function (RBF), back propagation (BP) neural network and support vector machine (SVM) model can be used for gas dispersion prediction. However, the prediction results from these network models with too many inputs based on original monitoring parameters are not in good agreement with the experimental data. Then, a new series of machine learning algorithms (MLA) models combined classic Gaussian model with MLA algorithm has been presented. The prediction results from new models are improved greatly. Among these models, Gaussian-SVM model performs best and its computation time is close to that of classic Gaussian dispersion model. Finally, Gaussian-MLA models were applied to identifying the emission source parameters with the particle swarm optimization (PSO) method. The estimation performance of PSO with Gaussian-MLA is better than that with Gaussian, Lagrangian stochastic (LS) dispersion model and network models based on original monitoring parameters. Hence, the new prediction model based on Gaussian-MLA is potentially a good method to predict contaminant gas dispersion as well as a good forward model in emission source parameters identification problem.

Contaminant dispersion prediction and source estimation with integrated Gaussian-machine learning network model for point source emission in atmosphere

Energy Technology Data Exchange (ETDEWEB)

Ma, Denglong [Fuli School of Food Equipment Engineering and Science, Xi’an Jiaotong University, No.28 Xianning West Road, Xi’an 710049 (China); Zhang, Zaoxiao, E-mail: zhangzx@mail.xjtu.edu.cn [State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, No.28 Xianning West Road, Xi’an 710049 (China); School of Chemical Engineering and Technology, Xi’an Jiaotong University, No.28 Xianning West Road, Xi’an 710049 (China)

2016-07-05

Highlights: • The intelligent network models were built to predict contaminant gas concentrations. • The improved network models coupled with Gaussian dispersion model were presented. • New model has high efficiency and accuracy for concentration prediction. • New model were applied to indentify the leakage source with satisfied results. - Abstract: Gas dispersion model is important for predicting the gas concentrations when contaminant gas leakage occurs. Intelligent network models such as radial basis function (RBF), back propagation (BP) neural network and support vector machine (SVM) model can be used for gas dispersion prediction. However, the prediction results from these network models with too many inputs based on original monitoring parameters are not in good agreement with the experimental data. Then, a new series of machine learning algorithms (MLA) models combined classic Gaussian model with MLA algorithm has been presented. The prediction results from new models are improved greatly. Among these models, Gaussian-SVM model performs best and its computation time is close to that of classic Gaussian dispersion model. Finally, Gaussian-MLA models were applied to identifying the emission source parameters with the particle swarm optimization (PSO) method. The estimation performance of PSO with Gaussian-MLA is better than that with Gaussian, Lagrangian stochastic (LS) dispersion model and network models based on original monitoring parameters. Hence, the new prediction model based on Gaussian-MLA is potentially a good method to predict contaminant gas dispersion as well as a good forward model in emission source parameters identification problem.

Numerical analysis and modeling of plume meandering in passive scalar dispersion downstream of a wall-mounted cube

International Nuclear Information System (INIS)

Rossi, R.; Iaccarino, G.

2013-01-01

Highlights: • Scalar dispersion downstream of a wall-mounted cube is examined by DNS and RANS models. • Vortex-shedding and plume meandering are established in the wake of the cube. • Low-frequency modulation is observed in the vortex-shedding and plume meandering. • Counter-gradient transport takes place in the streamwise component of the scalar flux. • Concentration decay and plume spread improved by the unsteady RANS model. -- Abstract: A DNS database is employed to examine the onset of plume meandering downstream of a wall-mounted cube and to address the impact of large-scale unsteadiness in modeling dispersion using the RANS equations. The cube is immersed in a uniform stream where the thin boundary-layer developing over the flat plate is responsible for the onset of vortex-shedding in the wake of the bluff-body. Spectra of velocity and concentration fluctuations exhibit a prominent peak in the energy content at the same frequency, showing that the plume meandering is established by the action of the vortex-shedding. The vortex-shedding and plume meandering display a low-frequency modulation where coherent fluctuations are suppressed at times with a quasi-regular period. The onset of the low-frequency modulation is indicated by a secondary peak in the energy spectrum and confirmed by the autocorrelation of velocity and scalar fluctuations. Unsteady RANS simulations performed with the v 2 − f model are able to detect the onset of the plume meandering and show remarkable improvement of the predicted decay rate and rate of spread of the scalar plume when compared to steady RANS solutions. By computing explicitly the periodic component of velocity and scalar fluctuations, the unsteady v 2 − f model is able to provide a representation of scalar flux components consistent with DNS statistics, where the counter-gradient transport mechanism that takes place in the streamwise component is also captured by URANS results. Nonetheless, the agreement with DNS

Modeling investigation of the nutrient and phytoplankton variability in the Chesapeake Bay outflow plume

Science.gov (United States)

Jiang, Long; Xia, Meng

2018-03-01

The Chesapeake Bay outflow plume (CBOP) is the mixing zone between Chesapeake Bay and less eutrophic continental shelf waters. Variations in phytoplankton distribution in the CBOP are critical to the fish nursery habitat quality and ecosystem health; thus, an existing hydrodynamic-biogeochemical model for the bay and the adjacent coastal ocean was applied to understand the nutrient and phytoplankton variability in the plume and the dominant environmental drivers. The simulated nutrient and chlorophyll a distribution agreed well with field data and real-time satellite imagery. Based on the model calculation, the net dissolved inorganic nitrogen (DIN) and phosphorus (DIP) flux at the bay mouth was seaward and landward during 2003-2012, respectively. The CBOP was mostly nitrogen-limited because of the relatively low estuarine DIN export. The highest simulated phytoplankton biomass generally occurred in spring in the near field of the plume. Streamflow variations could regulate the estuarine residence time, and thus modulate nutrient export and phytoplankton biomass in the plume area; in comparison, changing nutrient loading with fixed streamflow had a less extensive impact, especially in the offshore and far-field regions. Correlation analyses and numerical experiments revealed that southerly winds on the shelf were effective in promoting the offshore plume expansion and phytoplankton accumulation. Climate change including precipitation and wind pattern shifts is likely to complicate the driving mechanisms of phytoplankton variability in the plume region.

Fitting non-gaussian Models to Financial data: An Empirical Study

Directory of Open Access Journals (Sweden)

Pablo Olivares

2011-04-01

Full Text Available In this paper are presented some experiences about the modeling of financial data by three classes of models as alternative to Gaussian Linear models. Dynamic Volatility, Stable L'evy and Diffusion with Jumps models are considered. The techniques are illustrated with some examples of financial series on currency, futures and indexes.

Receiver design for SPAD-based VLC systems under Poisson-Gaussian mixed noise model.

Science.gov (United States)

Mao, Tianqi; Wang, Zhaocheng; Wang, Qi

2017-01-23

Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals.

Solar Coronal Plumes

Directory of Open Access Journals (Sweden)

Giannina Poletto

2015-12-01

Full Text Available Polar plumes are thin long ray-like structures that project beyond the limb of the Sun polar regions, maintaining their identity over distances of several solar radii. Plumes have been first observed in white-light (WL images of the Sun, but, with the advent of the space era, they have been identified also in X-ray and UV wavelengths (XUV and, possibly, even in in situ data. This review traces the history of plumes, from the time they have been first imaged, to the complex means by which nowadays we attempt to reconstruct their 3-D structure. Spectroscopic techniques allowed us also to infer the physical parameters of plumes and estimate their electron and kinetic temperatures and their densities. However, perhaps the most interesting problem we need to solve is the role they cover in the solar wind origin and acceleration: Does the solar wind emanate from plumes or from the ambient coronal hole wherein they are embedded? Do plumes have a role in solar wind acceleration and mass loading? Answers to these questions are still somewhat ambiguous and theoretical modeling does not provide definite answers either. Recent data, with an unprecedented high spatial and temporal resolution, provide new information on the fine structure of plumes, their temporal evolution and relationship with other transient phenomena that may shed further light on these elusive features.

'The formula that killed Wall Street': the Gaussian copula and modelling practices in investment banking.

Science.gov (United States)

MacKenzie, Donald; Spears, Taylor

2014-06-01

Drawing on documentary sources and 114 interviews with market participants, this and a companion article discuss the development and use in finance of the Gaussian copula family of models, which are employed to estimate the probability distribution of losses on a pool of loans or bonds, and which were centrally involved in the credit crisis. This article, which explores how and why the Gaussian copula family developed in the way it did, employs the concept of 'evaluation culture', a set of practices, preferences and beliefs concerning how to determine the economic value of financial instruments that is shared by members of multiple organizations. We identify an evaluation culture, dominant within the derivatives departments of investment banks, which we call the 'culture of no-arbitrage modelling', and explore its relation to the development of Gaussian copula models. The article suggests that two themes from the science and technology studies literature on models (modelling as 'impure' bricolage, and modelling as articulating with heterogeneous objectives and constraints) help elucidate the history of Gaussian copula models in finance.

Learning non-Gaussian Time Series using the Box-Cox Gaussian Process

OpenAIRE

Rios, Gonzalo; Tobar, Felipe

2018-01-01

Gaussian processes (GPs) are Bayesian nonparametric generative models that provide interpretability of hyperparameters, admit closed-form expressions for training and inference, and are able to accurately represent uncertainty. To model general non-Gaussian data with complex correlation structure, GPs can be paired with an expressive covariance kernel and then fed into a nonlinear transformation (or warping). However, overparametrising the kernel and the warping is known to, respectively, hin...

A Gaussian beam method for ultrasonic non-destructive evaluation modeling

Science.gov (United States)

Jacquet, O.; Leymarie, N.; Cassereau, D.

2018-05-01

The propagation of high-frequency ultrasonic body waves can be efficiently estimated with a semi-analytic Dynamic Ray Tracing approach using paraxial approximation. Although this asymptotic field estimation avoids the computational cost of numerical methods, it may encounter several limitations in reproducing identified highly interferential features. Nevertheless, some can be managed by allowing paraxial quantities to be complex-valued. This gives rise to localized solutions, known as paraxial Gaussian beams. Whereas their propagation and transmission/reflection laws are well-defined, the fact remains that the adopted complexification introduces additional initial conditions. While their choice is usually performed according to strategies specifically tailored to limited applications, a Gabor frame method has been implemented to indiscriminately initialize a reasonable number of paraxial Gaussian beams. Since this method can be applied for an usefully wide range of ultrasonic transducers, the typical case of the time-harmonic piston radiator is investigated. Compared to the commonly used Multi-Gaussian Beam model [1], a better agreement is obtained throughout the radiated field between the results of numerical integration (or analytical on-axis solution) and the resulting Gaussian beam superposition. Sparsity of the proposed solution is also discussed.

Graphical Gaussian models with edge and vertex symmetries

DEFF Research Database (Denmark)

Højsgaard, Søren; Lauritzen, Steffen L

2008-01-01

We introduce new types of graphical Gaussian models by placing symmetry restrictions on the concentration or correlation matrix. The models can be represented by coloured graphs, where parameters that are associated with edges or vertices of the same colour are restricted to being identical. We...... study the properties of such models and derive the necessary algorithms for calculating maximum likelihood estimates. We identify conditions for restrictions on the concentration and correlation matrices being equivalent. This is for example the case when symmetries are generated by permutation...

XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

Science.gov (United States)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-08-01

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

Modeling Emissions and Vertical Plume Transport of Crop Residue Burning Experiments in the Pacific Northwest

Science.gov (United States)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Pouliot, G.; Elleman, R. A.; ONeill, S. M.; Urbanski, S. P.; Wong, D. C.

2017-12-01

Crop residue burning has long been a common practice in agriculture with the smoke emissions from the burning linked to negative health impacts. A field study in eastern Washington and northern Idaho in August 2013 consisted of multiple burns of well characterized fuels with nearby surface and aerial measurements including trace species concentrations, plume rise height and boundary layer structure. The chemical transport model CMAQ (Community Multiscale Air Quality Model) was used to assess the fire emissions and subsequent vertical plume transport. The study first compared assumptions made by the 2014 National Emission Inventory approach for crop residue burning with the fuel and emissions information obtained from the field study and then investigated the sensitivity of modeled carbon monoxide (CO) and PM2.5 concentrations to these different emission estimates and plume rise treatment with CMAQ. The study suggests that improvements to the current parameterizations are needed in order for CMAQ to reliably reproduce smoke plumes from burning. In addition, there is enough variability in the smoke emissions, stemming from variable field-specific information such as field size, that attempts to model crop residue burning should use field-specific information whenever possible.

Lithosphere erosion atop mantle plumes

Science.gov (United States)

Agrusta, R.; Arcay, D.; Tommasi, A.

2012-12-01

Mantle plumes are traditionally proposed to play an important role in lithosphere erosion. Seismic images beneath Hawaii and Cape Verde show a lithosphere-asthenosphere-boundary (LAB) up to 50 km shallower than the surroundings. However, numerical models show that unless the plate is stationary the thermo-mechanical erosion of the lithosphere does not exceed 30 km. We use 2D petrological-thermo-mechanical numerical models based on a finite-difference method on a staggered grid and marker in cell method to study the role of partial melting on the plume-lithosphere interaction. A homogeneous peridotite composition with a Newtonian temperature- and pressure-dependent viscosity is used to simulate both the plate and the convective mantle. A constant velocity, ranging from 5 to 12.5 cm/yr, is imposed at the top of the plate. Plumes are created by imposing a thermal anomaly of 150 to 350 K on a 50 km wide domain at the base of the model (700 km depth); the plate right above the thermal anomaly is 40 Myr old. Partial melting is modeled using batch-melting solidus and liquidus in anhydrous conditions. We model the progressive depletion of peridotite and its effect on partial melting by assuming that the melting degree only strictly increases through time. Melt is accumulated until a porosity threshold is reached and the melt in excess is then extracted. The rheology of the partially molten peridotite is determined using viscous constitutive relationship based on a contiguity model, which enables to take into account the effects of grain-scale melt distribution. Above a threshold of 1%, melt is instantaneously extracted. The density varies as a function of partial melting degree and extraction. Besides, we analyze the kinematics of the plume as it impacts a moving plate, the dynamics of time-dependent small-scale convection (SSC) instabilities developing in the low-viscosity layer formed by spreading of hot plume material at the lithosphere base, and the resulting thermal

Volcanic Plume Elevation Model Derived From Landsat 8: examples on Holuhraun (Iceland) and Mount Etna (Italy)

Science.gov (United States)

de Michele, Marcello; Raucoules, Daniel; Arason, Þórður; Spinetti, Claudia; Corradini, Stefano; Merucci, Luca

2016-04-01

The retrieval of both height and velocity of a volcanic plume is an important issue in volcanology. As an example, it is known that large volcanic eruptions can temporarily alter the climate, causing global cooling and shifting precipitation patterns; the ash/gas dispersion in the atmosphere, their impact and lifetime around the globe, greatly depends on the injection altitude. Plume height information is critical for ash dispersion modelling and air traffic security. Furthermore, plume height during explosive volcanism is the primary parameter for estimating mass eruption rate. Knowing the plume altitude is also important to get the correct amount of SO2 concentration from dedicated spaceborne spectrometers. Moreover, the distribution of ash deposits on ground greatly depends on the ash cloud altitude, which has an impact on risk assessment and crisis management. Furthermore, a spatially detailed plume height measure could be used as a hint for gas emission rate estimation and for ash plume volume researches, which both have an impact on climate research, air quality assessment for aviation and finally for the understanding of the volcanic system itself as ash/gas emission rates are related to the state of pressurization of the magmatic chamber. Today, the community mainly relies on ground based measurements but often they can be difficult to collect as by definition volcanic areas are dangerous areas (presence of toxic gases) and can be remotely situated and difficult to access. Satellite remote sensing offers a comprehensive and safe way to estimate plume height. Conventional photogrammetric restitution based on satellite imagery fails in precisely retrieving a plume elevation model as the plume own velocity induces an apparent parallax that adds up to the standard parallax given by the stereoscopic view. Therefore, measurements based on standard satellite photogrammeric restitution do not apply as there is an ambiguity in the measurement of the plume position

Stochastic resonance in a piecewise nonlinear model driven by multiplicative non-Gaussian noise and additive white noise

Science.gov (United States)

Guo, Yongfeng; Shen, Yajun; Tan, Jianguo

2016-09-01

The phenomenon of stochastic resonance (SR) in a piecewise nonlinear model driven by a periodic signal and correlated noises for the cases of a multiplicative non-Gaussian noise and an additive Gaussian white noise is investigated. Applying the path integral approach, the unified colored noise approximation and the two-state model theory, the analytical expression of the signal-to-noise ratio (SNR) is derived. It is found that conventional stochastic resonance exists in this system. From numerical computations we obtain that: (i) As a function of the non-Gaussian noise intensity, the SNR is increased when the non-Gaussian noise deviation parameter q is increased. (ii) As a function of the Gaussian noise intensity, the SNR is decreased when q is increased. This demonstrates that the effect of the non-Gaussian noise on SNR is different from that of the Gaussian noise in this system. Moreover, we further discuss the effect of the correlation time of the non-Gaussian noise, cross-correlation strength, the amplitude and frequency of the periodic signal on SR.

Pollutant Plume Dispersion in the Atmospheric Boundary Layer over Idealized Urban Roughness

Science.gov (United States)

Wong, Colman C. C.; Liu, Chun-Ho

2013-05-01

The Gaussian model of plume dispersion is commonly used for pollutant concentration estimates. However, its major parameters, dispersion coefficients, barely account for terrain configuration and surface roughness. Large-scale roughness elements (e.g. buildings in urban areas) can substantially modify the ground features together with the pollutant transport in the atmospheric boundary layer over urban roughness (also known as the urban boundary layer, UBL). This study is thus conceived to investigate how urban roughness affects the flow structure and vertical dispersion coefficient in the UBL. Large-eddy simulation (LES) is carried out to examine the plume dispersion from a ground-level pollutant (area) source over idealized street canyons for cross flows in neutral stratification. A range of building-height-to-street-width (aspect) ratios, covering the regimes of skimming flow, wake interference, and isolated roughness, is employed to control the surface roughness. Apart from the widely used aerodynamic resistance or roughness function, the friction factor is another suitable parameter that measures the drag imposed by urban roughness quantitatively. Previous results from laboratory experiments and mathematical modelling also support the aforementioned approach for both two- and three-dimensional roughness elements. Comparing the UBL plume behaviour, the LES results show that the pollutant dispersion strongly depends on the friction factor. Empirical studies reveal that the vertical dispersion coefficient increases with increasing friction factor in the skimming flow regime (lower resistance) but is more uniform in the regimes of wake interference and isolated roughness (higher resistance). Hence, it is proposed that the friction factor and flow regimes could be adopted concurrently for pollutant concentration estimate in the UBL over urban street canyons of different roughness.

Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

Science.gov (United States)

Teneng, Dean

2013-09-01

We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

Characterization of DNAPL Source Zone Architecture and Prediction of Associated Plume Response: Progress and Perspectives

Science.gov (United States)

Abriola, L. M.; Pennell, K. D.; Ramsburg, C. A.; Miller, E. L.; Christ, J.; Capiro, N. L.; Mendoza-Sanchez, I.; Boroumand, A.; Ervin, R. E.; Walker, D. I.; Zhang, H.

2012-12-01

It is now widely recognized that the distribution of contaminant mass will control both the evolution of aqueous phase plumes and the effectiveness of many source zone remediation technologies at sites contaminated by dense nonaqueous phase liquids (DNAPLs). Advances in the management of sites containing DNAPL source zones, however, are currently hampered by the difficulty associated with characterizing subsurface DNAPL 'architecture'. This presentation provides an overview of recent research, integrating experimental and mathematical modeling studies, designed to improve our ability to characterize DNAPL distributions and predict associated plume response. Here emphasis is placed on estimation of the most information-rich DNAPL architecture metrics, through a combination of localized in situ tests and more readily available plume transect concentration observations. Estimated metrics will then serve as inputs to an upscaled screening model for prediction of long term plume response. Machine learning techniques were developed and refined to identify a variety of source zone metrics and associated confidence intervals through the processing of down gradient concentration data. Estimated metrics include the volumes and volume percentages of DNAPL in pools and ganglia, as well as their ratio (pool fraction). Multiphase flow and transport simulations provided training data for model development and assessment that are representative of field-scale DNAPL source zones and their evolving plumes. Here, a variety of release and site heterogeneity (sequential Gaussian permeability) conditions were investigated. Push-pull tracer tests were also explored as a means to provide localized in situ observations to refine these metric estimates. Here, two-dimensional aquifer cell experiments and mathematical modeling were used to quantify upscaled interphase mass transfer rates and the interplay between injection and extraction rates, local source zone architecture, and tracer

Application of Gaussian cubature to model two-dimensional population balances

Directory of Open Access Journals (Sweden)

Bałdyga Jerzy

2017-09-01

Full Text Available In many systems of engineering interest the moment transformation of population balance is applied. One of the methods to solve the transformed population balance equations is the quadrature method of moments. It is based on the approximation of the density function in the source term by the Gaussian quadrature so that it preserves the moments of the original distribution. In this work we propose another method to be applied to the multivariate population problem in chemical engineering, namely a Gaussian cubature (GC technique that applies linear programming for the approximation of the multivariate distribution. Examples of the application of the Gaussian cubature (GC are presented for four processes typical for chemical engineering applications. The first and second ones are devoted to crystallization modeling with direction-dependent two-dimensional and three-dimensional growth rates, the third one represents drop dispersion accompanied by mass transfer in liquid-liquid dispersions and finally the fourth case regards the aggregation and sintering of particle populations.

ARCON96, Radioactive Plume Concentration in Reactor Control Rooms

International Nuclear Information System (INIS)

Ramsdell, J.V.; Simonen, C.A.

2003-01-01

1 - Description of program or function: ARCON96 was developed to calculate relative concentrations in plumes from nuclear power plants at control room air intakes in the vicinity of the release point. 2 - Methods: ARCON96 implements a straight-line Gaussian dispersion model with dispersion coefficients that are modified to account for low wind meander and building wake effects. Hourly, normalized concentrations (X/Q) are calculated from hourly meteorological data. The hourly values are averaged to form X/Qs for periods ranging from 2 to 720 hours in duration. The calculated values for each period are used to form cumulative frequency distributions. 3 - Restriction on the complexity of the problem: ARCON96 is a single user program. If expanded output is selected by the user, the file includes the hourly input and X/Qs and the intermediate computational results. The output file may exceed a megabyte size

IR sensor design insight from missile-plume prediction models

Science.gov (United States)

Rapanotti, John L.; Gilbert, Bruno; Richer, Guy; Stowe, Robert

2002-08-01

Modern anti-tank missiles and the requirement of rapid deployment have significantly reduced the use of passive armour in protecting land vehicles. Vehicle survivability is becoming more dependent on sensors, computers and countermeasures to detect and avoid threats. An analysis of missile propellants suggests that missile detection based on plume characteristics alone may be more difficult than anticipated. Currently, the passive detection of missiles depends on signatures with a significant ultraviolet component. This approach is effective in detecting anti-aircraft missiles that rely on powerful motors to pursue high-speed aircraft. The high temperature exhaust from these missiles contains significant levels of carbon dioxide, water and, often, metal oxides such as alumina. The plumes emits strongest in the infrared, 1 to 5micrometers , regions with a significant component of the signature extending into the ultraviolet domain. Many anti-tank missiles do not need the same level of propulsion and radiate significantly less. These low velocity missiles, relying on the destructive force of shaped-charge warhead, are more difficult to detect. There is virtually no ultraviolet component and detection based on UV sensors is impractical. The transition in missile detection from UV to IR is reasonable, based on trends in imaging technology, but from the analysis presented in this paper even IR imagers may have difficulty in detecting missile plumes. This suggests that the emphasis should be placed in the detection of the missile hard body in the longer wavelengths of 8 to 12micrometers . The analysis described in this paper is based on solution of the governing equations of plume physics and chemistry. These models will be used to develop better sensors and threat detection algorithms.

An integrated numerical model for the prediction of Gaussian and billet shapes

International Nuclear Information System (INIS)

Hattel, J.H.; Pryds, N.H.; Pedersen, T.B.

2004-01-01

Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency and the shading effect for Gaussian and billet shape, respectively. From the obtained results, the effect of these parameters on the final shape is illustrated

Simulating Fine-Scale Marine Pollution Plumes for Autonomous Robotic Environmental Monitoring

Directory of Open Access Journals (Sweden)

Muhammad Fahad

2018-05-01

Full Text Available Marine plumes exhibit characteristics such as intermittency, sinuous structure, shape and flow field coherency, and a time varying concentration profile. Due to the lack of experimental quantification of these characteristics for marine plumes, existing work often assumes marine plumes exhibit behavior similar to aerial plumes and are commonly modeled by filament based Lagrangian models. Our previous field experiments with Rhodamine dye plumes at Makai Research Pier at Oahu, Hawaii revealed that marine plumes show similar characteristics to aerial plumes qualitatively, but quantitatively they are disparate. Based on the field data collected, this paper presents a calibrated Eulerian plume model that exhibits the qualitative and quantitative characteristics exhibited by experimentally generated marine plumes. We propose a modified model with an intermittent source, and implement it in a Robot Operating System (ROS based simulator. Concentration time series of stationary sampling points and dynamic sampling points across cross-sections and plume fronts are collected and analyzed for statistical parameters of the simulated plume. These parameters are then compared with statistical parameters from experimentally generated plumes. The comparison validates that the simulated plumes exhibit fine-scale qualitative and quantitative characteristics similar to experimental plumes. The ROS plume simulator facilitates future evaluations of environmental monitoring strategies by marine robots, and is made available for community use.

Buoyant plume calculations

International Nuclear Information System (INIS)

Penner, J.E.; Haselman, L.C.; Edwards, L.L.

1985-01-01

Smoke from raging fires produced in the aftermath of a major nuclear exchange has been predicted to cause large decreases in surface temperatures. However, the extent of the decrease and even the sign of the temperature change, depend on how the smoke is distributed with altitude. We present a model capable of evaluating the initial distribution of lofted smoke above a massive fire. Calculations are shown for a two-dimensional slab version of the model and a full three-dimensional version. The model has been evaluated by simulating smoke heights for the Hamburg firestorm of 1943 and a smaller scale oil fire which occurred in Long Beach in 1958. Our plume heights for these fires are compared to those predicted by the classical Morton-Taylor-Turner theory for weakly buoyant plumes. We consider the effect of the added buoyancy caused by condensation of water-laden ground level air being carried to high altitude with the convection column as well as the effects of background wind on the calculated smoke plume heights for several fire intensities. We find that the rise height of the plume depends on the assumed background atmospheric conditions as well as the fire intensity. Little smoke is injected into the stratosphere unless the fire is unusually intense, or atmospheric conditions are more unstable than we have assumed. For intense fires significant amounts of water vapor are condensed raising the possibility of early scavenging of smoke particles by precipitation. 26 references, 11 figures

Chemistry in aircraft plumes

Energy Technology Data Exchange (ETDEWEB)

Kraabol, A.G.; Stordal, F.; Knudsen, S. [Norwegian Inst. for Air Research, Kjeller (Norway); Konopka, P. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere

1997-12-31

An expanding plume model with chemistry has been used to study the chemical conversion of NO{sub x} to reservoir species in aircraft plumes. The heterogeneous conversion of N{sub 2}O{sub 5} to HNO{sub 3}(s) has been investigated when the emissions take place during night-time. The plume from an B747 has been simulated. During a ten-hour calculation the most important reservoir species was HNO{sub 3} for emissions at noon. The heterogeneous reactions had little impact on the chemical loss of NO{sub x} to reservoir species for emissions at night. (author) 4 refs.

Chemistry in aircraft plumes

Energy Technology Data Exchange (ETDEWEB)

Kraabol, A G; Stordal, F; Knudsen, S [Norwegian Inst. for Air Research, Kjeller (Norway); Konopka, P [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere

1998-12-31

An expanding plume model with chemistry has been used to study the chemical conversion of NO{sub x} to reservoir species in aircraft plumes. The heterogeneous conversion of N{sub 2}O{sub 5} to HNO{sub 3}(s) has been investigated when the emissions take place during night-time. The plume from an B747 has been simulated. During a ten-hour calculation the most important reservoir species was HNO{sub 3} for emissions at noon. The heterogeneous reactions had little impact on the chemical loss of NO{sub x} to reservoir species for emissions at night. (author) 4 refs.

White Gaussian Noise - Models for Engineers

Science.gov (United States)

Jondral, Friedrich K.

2018-04-01

This paper assembles some information about white Gaussian noise (WGN) and its applications. It starts from a description of thermal noise, i. e. the irregular motion of free charge carriers in electronic devices. In a second step, mathematical models of WGN processes and their most important parameters, especially autocorrelation functions and power spectrum densities, are introduced. In order to proceed from mathematical models to simulations, we discuss the generation of normally distributed random numbers. The signal-to-noise ratio as the most important quality measure used in communications, control or measurement technology is accurately introduced. As a practical application of WGN, the transmission of quadrature amplitude modulated (QAM) signals over additive WGN channels together with the optimum maximum likelihood (ML) detector is considered in a demonstrative and intuitive way.

Evaluation of Gaussian approximations for data assimilation in reservoir models

KAUST Repository

Iglesias, Marco A.

2013-07-14

The Bayesian framework is the standard approach for data assimilation in reservoir modeling. This framework involves characterizing the posterior distribution of geological parameters in terms of a given prior distribution and data from the reservoir dynamics, together with a forward model connecting the space of geological parameters to the data space. Since the posterior distribution quantifies the uncertainty in the geologic parameters of the reservoir, the characterization of the posterior is fundamental for the optimal management of reservoirs. Unfortunately, due to the large-scale highly nonlinear properties of standard reservoir models, characterizing the posterior is computationally prohibitive. Instead, more affordable ad hoc techniques, based on Gaussian approximations, are often used for characterizing the posterior distribution. Evaluating the performance of those Gaussian approximations is typically conducted by assessing their ability at reproducing the truth within the confidence interval provided by the ad hoc technique under consideration. This has the disadvantage of mixing up the approximation properties of the history matching algorithm employed with the information content of the particular observations used, making it hard to evaluate the effect of the ad hoc approximations alone. In this paper, we avoid this disadvantage by comparing the ad hoc techniques with a fully resolved state-of-the-art probing of the Bayesian posterior distribution. The ad hoc techniques whose performance we assess are based on (1) linearization around the maximum a posteriori estimate, (2) randomized maximum likelihood, and (3) ensemble Kalman filter-type methods. In order to fully resolve the posterior distribution, we implement a state-of-the art Markov chain Monte Carlo (MCMC) method that scales well with respect to the dimension of the parameter space, enabling us to study realistic forward models, in two space dimensions, at a high level of grid refinement. Our

Life Cycle of Mantle Plumes: A perspective from the Galapagos Plume (Invited)

Science.gov (United States)

Gazel, E.; Herzberg, C. T.

2009-12-01

Hotspots are localized sources of heat and magmatism considered as modern-day evidence of mantle plumes. Some hotspots are related to massive magmatic production that generated Large Igneous Provinces (LIPS), an initial-peak phase of plume activity with a mantle source hotter and more magmatically productive than present-day hotspots. Geological mapping and geochronological studies have shown much lower eruption rates for OIB compared to lavas from Large Igneous Provinces LIPS such as oceanic plateaus and continental flood provinces. Our study is the first quantitative petrological comparison of mantle source temperatures and extent of melting for OIB and LIP sources. The wide range of primary magma compositions and inferred mantle potential temperatures for each LIP and OIB occurrence suggest that this rocks originated form a hotspot, a spatially localized source of heat and magmatism restricted in time. Extensive outcrops of basalt, picrite, and sometimes komatiite with circa 65-95 Ma ages occupy portions of the pacific shore of Central and South America included in the Caribbean Large Igneous Province (CLIP). There is general consensus of a Pacific-origin of CLIP and most studies suggest that it was produced by melting in the Galapagos mantle plume. The Galapagos connection is consistent with isotopic and geochemical similarities with lavas from the present-day Galapagos hotspot. A Galapagos link for rocks in South American oceanic complexes (eg. the island of Gorgona) is more controversial and requires future work. The MgO and FeO contents of lavas from the Galapagos related lavas and their primary magmas have decreased since the Cretaceous. From petrological modeling we infer that these changes reflect a cooling of the Galapagos mantle plume from a potential temperature of 1560-1620 C in the Cretaceous to 1500 C at the present time. These temperatures are higher than 1350 C for ambient mantle associated with oceanic ridges, and provide support for the mantle

Parametric estimation of covariance function in Gaussian-process based Kriging models. Application to uncertainty quantification for computer experiments

International Nuclear Information System (INIS)

Bachoc, F.

2013-01-01

The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr

Tachyon mediated non-Gaussianity

International Nuclear Information System (INIS)

Dutta, Bhaskar; Leblond, Louis; Kumar, Jason

2008-01-01

We describe a general scenario where primordial non-Gaussian curvature perturbations are generated in models with extra scalar fields. The extra scalars communicate to the inflaton sector mainly through the tachyonic (waterfall) field condensing at the end of hybrid inflation. These models can yield significant non-Gaussianity of the local shape, and both signs of the bispectrum can be obtained. These models have cosmic strings and a nearly flat power spectrum, which together have been recently shown to be a good fit to WMAP data. We illustrate with a model of inflation inspired from intersecting brane models.

The mantle-plume model, its feasibility and consequences

NARCIS (Netherlands)

Calsteren, van P.W.C.

1981-01-01

High beat-flow foci on the Earth have been named ‘hot-spots’ and are commonly correlated with ‘mantle-plumes’ in the deep. A mantle plume may be described as a portion of mantle material with a higher heat content than its surroundings. The intrusion of a mantle-plume is inferred to be similar to

MESOI, an interactive atmospheric dispersion model for emergency response applications

International Nuclear Information System (INIS)

Ramsdell, J.V.; Athey, G.F.; Glantz, C.S.

1984-01-01

MESOI is an interactive atmospheric dispersion model that has been developed for use by the U.S. Department of Energy, and the U.S. Nuclear Regulatory Commission in responding to emergencies at nuclear facilities. MESOI uses both straight-line Gaussian plume and Lagrangian trajectory Gaussian puff models to estimate time-integrated ground-level air and surface concentrations. Puff trajectories are determined from temporally and spatially varying horizontal wind fields that are defined in 3 dimensions. Other processes treated in MESOI include dry deposition, wet deposition and radioactive decay

MESOI, an interactive atmospheric dispersion model for emergency response applications

International Nuclear Information System (INIS)

Ramsdell, J.V.; Athey, G.F.; Glantz, C.S.

1983-12-01

MESOI is an interactive atmospheric despersion model that has been developed for use by the US Department of Energy, and the US Nuclear Regulatory Commission in responding to emergencies at nuclear facilities. MESOI uses both straight-line Gaussian plume and Lagrangian trajectory Gaussian puff models to estimate time-integrated ground-level air and surface concentrations. Puff trajectories are determined from temporally and spatially varying horizontal wind fields that are defined in 3 dimensions. Other processes treated in MESOI include dry deposition, wet deposition and radioactive decay. 9 references

Speech Enhancement by MAP Spectral Amplitude Estimation Using a Super-Gaussian Speech Model

Directory of Open Access Journals (Sweden)

Lotter Thomas

2005-01-01

Full Text Available This contribution presents two spectral amplitude estimators for acoustical background noise suppression based on maximum a posteriori estimation and super-Gaussian statistical modelling of the speech DFT amplitudes. The probability density function of the speech spectral amplitude is modelled with a simple parametric function, which allows a high approximation accuracy for Laplace- or Gamma-distributed real and imaginary parts of the speech DFT coefficients. Also, the statistical model can be adapted to optimally fit the distribution of the speech spectral amplitudes for a specific noise reduction system. Based on the super-Gaussian statistical model, computationally efficient maximum a posteriori speech estimators are derived, which outperform the commonly applied Ephraim-Malah algorithm.

Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

KAUST Repository

Wang, Shitao

2016-05-27

Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model\\'s estimates of the plume\\'s trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate\\'s contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion

Science.gov (United States)

Mena, Francisco; Bond, Tami C.; Riemer, Nicole

2017-08-01

Residential biofuel combustion is an important source of aerosols and gases in the atmosphere. The change in cloud characteristics due to biofuel burning aerosols is uncertain, in part, due to the uncertainty in the added number of cloud condensation nuclei (CCN) from biofuel burning. We provide estimates of the CCN activity of biofuel burning aerosols by explicitly modeling plume dynamics (coagulation, condensation, chemical reactions, and dilution) in a young biofuel burning plume from emission until plume exit, defined here as the condition when the plume reaches ambient temperature and specific humidity through entrainment. We found that aerosol-scale dynamics affect CCN activity only during the first few seconds of evolution, after which the CCN efficiency reaches a constant value. Homogenizing factors in a plume are co-emission of semi-volatile organic compounds (SVOCs) or emission at small particle sizes; SVOC co-emission can be the main factor determining plume-exit CCN for hydrophobic or small particles. Coagulation limits emission of CCN to about 1016 per kilogram of fuel. Depending on emission factor, particle size, and composition, some of these particles may not activate at low supersaturation (ssat). Hygroscopic Aitken-mode particles can contribute to CCN through self-coagulation but have a small effect on the CCN activity of accumulation-mode particles, regardless of composition differences. Simple models (monodisperse coagulation and average hygroscopicity) can be used to estimate plume-exit CCN within about 20 % if particles are unimodal and have homogeneous composition, or when particles are emitted in the Aitken mode even if they are not homogeneous. On the other hand, if externally mixed particles are emitted in the accumulation mode without SVOCs, an average hygroscopicity overestimates emitted CCN by up to a factor of 2. This work has identified conditions under which particle populations become more homogeneous during plume processes. This

Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models.

Science.gov (United States)

Liu, Zhiguang; Zhou, Liuyang; Leung, Howard; Shum, Hubert P H

2016-11-01

Depth sensor based 3D human motion estimation hardware such as Kinect has made interactive applications more popular recently. However, it is still challenging to accurately recognize postures from a single depth camera due to the inherently noisy data derived from depth images and self-occluding action performed by the user. In this paper, we propose a new real-time probabilistic framework to enhance the accuracy of live captured postures that belong to one of the action classes in the database. We adopt the Gaussian Process model as a prior to leverage the position data obtained from Kinect and marker-based motion capture system. We also incorporate a temporal consistency term into the optimization framework to constrain the velocity variations between successive frames. To ensure that the reconstructed posture resembles the accurate parts of the observed posture, we embed a set of joint reliability measurements into the optimization framework. A major drawback of Gaussian Process is its cubic learning complexity when dealing with a large database due to the inverse of a covariance matrix. To solve the problem, we propose a new method based on a local mixture of Gaussian Processes, in which Gaussian Processes are defined in local regions of the state space. Due to the significantly decreased sample size in each local Gaussian Process, the learning time is greatly reduced. At the same time, the prediction speed is enhanced as the weighted mean prediction for a given sample is determined by the nearby local models only. Our system also allows incrementally updating a specific local Gaussian Process in real time, which enhances the likelihood of adapting to run-time postures that are different from those in the database. Experimental results demonstrate that our system can generate high quality postures even under severe self-occlusion situations, which is beneficial for real-time applications such as motion-based gaming and sport training.

Fractional statistics in 2+1 dimensions through the Gaussian model

International Nuclear Information System (INIS)

Murthy, G.

1986-01-01

The free massless field in 2+1 dimensions is written as an ''integral'' over free massless fields in 1+1 dimensions. Taking the operators with fractional dimension in the Gaussian model as a springboard we construct operators with fractional statistics in the former theory

Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs

DEFF Research Database (Denmark)

Jensen, Jesper Højvang; Ellis, Dan P. W.; Christensen, Mads Græsbøll

2007-01-01

In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although...

Semiparametric Gaussian copula models : Geometry and efficient rank-based estimation

NARCIS (Netherlands)

Segers, J.; van den Akker, R.; Werker, B.J.M.

2014-01-01

We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step update of a rank-based pilot estimator in the direction of

Gaussian and Affine Approximation of Stochastic Diffusion Models for Interest and Mortality Rates

Directory of Open Access Journals (Sweden)

Marcus C. Christiansen

2013-10-01

Full Text Available In the actuarial literature, it has become common practice to model future capital returns and mortality rates stochastically in order to capture market risk and forecasting risk. Although interest rates often should and mortality rates always have to be non-negative, many authors use stochastic diffusion models with an affine drift term and additive noise. As a result, the diffusion process is Gaussian and, thus, analytically tractable, but negative values occur with positive probability. The argument is that the class of Gaussian diffusions would be a good approximation of the real future development. We challenge that reasoning and study the asymptotics of diffusion processes with affine drift and a general noise term with corresponding diffusion processes with an affine drift term and an affine noise term or additive noise. Our study helps to quantify the error that is made by approximating diffusive interest and mortality rate models with Gaussian diffusions and affine diffusions. In particular, we discuss forward interest and forward mortality rates and the error that approximations cause on the valuation of life insurance claims.

Linking network usage patterns to traffic Gaussianity fit

NARCIS (Netherlands)

de Oliveira Schmidt, R.; Sadre, R.; Melnikov, Nikolay; Schönwälder, Jürgen; Pras, Aiko

Gaussian traffic models are widely used in the domain of network traffic modeling. The central assumption is that traffic aggregates are Gaussian distributed. Due to its importance, the Gaussian character of network traffic has been extensively assessed by researchers in the past years. In 2001,

Nonclassicality by Local Gaussian Unitary Operations for Gaussian States

Directory of Open Access Journals (Sweden)

Yangyang Wang

2018-04-01

Full Text Available A measure of nonclassicality N in terms of local Gaussian unitary operations for bipartite Gaussian states is introduced. N is a faithful quantum correlation measure for Gaussian states as product states have no such correlation and every non product Gaussian state contains it. For any bipartite Gaussian state ρ A B , we always have 0 ≤ N ( ρ A B < 1 , where the upper bound 1 is sharp. An explicit formula of N for ( 1 + 1 -mode Gaussian states and an estimate of N for ( n + m -mode Gaussian states are presented. A criterion of entanglement is established in terms of this correlation. The quantum correlation N is also compared with entanglement, Gaussian discord and Gaussian geometric discord.

The 2016 Case for Mantle Plumes and a Plume-Fed Asthenosphere (Augustus Love Medal Lecture)

Science.gov (United States)

Morgan, Jason P.

2016-04-01

The process of science always returns to weighing evidence and arguments for and against a given hypothesis. As hypotheses can only be falsified, never universally proved, doubt and skepticism remain essential elements of the scientific method. In the past decade, even the hypothesis that mantle plumes exist as upwelling currents in the convecting mantle has been subject to intense scrutiny; from geochemists and geochronologists concerned that idealized plume models could not fit many details of their observations, and from seismologists concerned that mantle plumes can sometimes not be 'seen' in their increasingly high-resolution tomographic images of the mantle. In the place of mantle plumes, various locally specific and largely non-predictive hypotheses have been proposed to explain the origins of non-plate boundary volcanism at Hawaii, Samoa, etc. In my opinion, this debate has now passed from what was initially an extremely useful restorative from simply 'believing' in the idealized conventional mantle plume/hotspot scenario to becoming an active impediment to our community's ability to better understand the dynamics of the solid Earth. Having no working hypothesis at all is usually worse for making progress than having an imperfect and incomplete but partially correct one. There continues to be strong arguments and strong emerging evidence for deep mantle plumes. Furthermore, deep thermal plumes should exist in a mantle that is heated at its base, and the existence of Earth's (convective) geodynamo clearly indicates that heat flows from the core to heat the mantle's base. Here I review recent seismic evidence by French, Romanowicz, and coworkers that I feel lends strong new observational support for the existence of deep mantle plumes. I also review recent evidence consistent with the idea that secular core cooling replenishes half the mantle's heat loss through its top surface, e.g. that the present-day mantle is strongly bottom heated. Causes for

Tip-tilt disturbance model identification based on non-linear least squares fitting for Linear Quadratic Gaussian control

Science.gov (United States)

Yang, Kangjian; Yang, Ping; Wang, Shuai; Dong, Lizhi; Xu, Bing

2018-05-01

We propose a method to identify tip-tilt disturbance model for Linear Quadratic Gaussian control. This identification method based on Levenberg-Marquardt method conducts with a little prior information and no auxiliary system and it is convenient to identify the tip-tilt disturbance model on-line for real-time control. This identification method makes it easy that Linear Quadratic Gaussian control runs efficiently in different adaptive optics systems for vibration mitigation. The validity of the Linear Quadratic Gaussian control associated with this tip-tilt disturbance model identification method is verified by experimental data, which is conducted in replay mode by simulation.

Discrimination of numerical proportions: A comparison of binomial and Gaussian models.

Science.gov (United States)

Raidvee, Aire; Lember, Jüri; Allik, Jüri

2017-01-01

Observers discriminated the numerical proportion of two sets of elements (N = 9, 13, 33, and 65) that differed either by color or orientation. According to the standard Thurstonian approach, the accuracy of proportion discrimination is determined by irreducible noise in the nervous system that stochastically transforms the number of presented visual elements onto a continuum of psychological states representing numerosity. As an alternative to this customary approach, we propose a Thurstonian-binomial model, which assumes discrete perceptual states, each of which is associated with a certain visual element. It is shown that the probability β with which each visual element can be noticed and registered by the perceptual system can explain data of numerical proportion discrimination at least as well as the continuous Thurstonian-Gaussian model, and better, if the greater parsimony of the Thurstonian-binomial model is taken into account using AIC model selection. We conclude that Gaussian and binomial models represent two different fundamental principles-internal noise vs. using only a fraction of available information-which are both plausible descriptions of visual perception.

Bayes factor between Student t and Gaussian mixed models within an animal breeding context

Directory of Open Access Journals (Sweden)

García-Cortés Luis

2008-07-01

Full Text Available Abstract The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model. The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months, both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population.

Paducah Gaseous Diffusion Plant Northwest Plume interceptor system evaluation

International Nuclear Information System (INIS)

Laase, A.D.; Clausen, J.L.

1998-01-01

The Paducah Gaseous Diffusion Plant (PGDP) recently installed an interceptor system consisting of four wells, evenly divided between two well fields, to contain the Northwest Plume. As stated in the Northwest Plume Record of Decision (ROD), groundwater will be pumped at a rate to reduce further contamination and initiate control of the northwest contaminant plume. The objective of this evaluation was to determine the optimum (minimal) well field pumping rates required for plume hotspot containment. Plume hotspot, as defined in the Northwest Plume ROD and throughout this report, is that portion of the plume with trichloroethene (TCE) concentrations greater than 1,000 microg/L. An existing 3-dimensional groundwater model was modified and used to perform capture zone analyses of the north and south interceptor system well fields. Model results suggest that the plume hotspot is not contained at the system design pumping rate of 100 gallons per minute (gal/min) per well field. Rather, the modeling determined that north and south well field pumping rates of 400 and 150 gal/min, respectively, are necessary for plume hotspot containment. The difference between the design and optimal pumping rates required for containment can be attributed to the discovery of a highly transmissive zone in the vicinity of the two well fields

Hydrologic Process Parameterization of Electrical Resistivity Imaging of Solute Plumes Using POD McMC

Science.gov (United States)

Awatey, M. T.; Irving, J.; Oware, E. K.

2016-12-01

Markov chain Monte Carlo (McMC) inversion frameworks are becoming increasingly popular in geophysics due to their ability to recover multiple equally plausible geologic features that honor the limited noisy measurements. Standard McMC methods, however, become computationally intractable with increasing dimensionality of the problem, for example, when working with spatially distributed geophysical parameter fields. We present a McMC approach based on a sparse proper orthogonal decomposition (POD) model parameterization that implicitly incorporates the physics of the underlying process. First, we generate training images (TIs) via Monte Carlo simulations of the target process constrained to a conceptual model. We then apply POD to construct basis vectors from the TIs. A small number of basis vectors can represent most of the variability in the TIs, leading to dimensionality reduction. A projection of the starting model into the reduced basis space generates the starting POD coefficients. At each iteration, only coefficients within a specified sampling window are resimulated assuming a Gaussian prior. The sampling window grows at a specified rate as the number of iteration progresses starting from the coefficients corresponding to the highest ranked basis to those of the least informative basis. We found this gradual increment in the sampling window to be more stable compared to resampling all the coefficients right from the first iteration. We demonstrate the performance of the algorithm with both synthetic and lab-scale electrical resistivity imaging of saline tracer experiments, employing the same set of basis vectors for all inversions. We consider two scenarios of unimodal and bimodal plumes. The unimodal plume is consistent with the hypothesis underlying the generation of the TIs whereas bimodality in plume morphology was not theorized. We show that uncertainty quantification using McMC can proceed in the reduced dimensionality space while accounting for the

Numerical Simulation of a Tracer Experiment at the Wolsong Nuclear Site

International Nuclear Information System (INIS)

Jeong, Hyojoon; Kim, Eunhan; Park, Misun; Jeong, Haesun; Hwang, Wontae; Han, Moonhee

2014-01-01

By comparing the concentration of a tracer measured under weather conditions that are disadvantageous to the dilution of radioactive materials released from the Wolsong Nuclear Power Plant, with the concentration of a tracer calculated using an air Dispersion model, it is possible to evaluate the characteristics of the air concentrations of radioactive materials estimated with an air Dispersion model, which can then be used in an environmental impact analysis of radioactive materials. Therefore, a field Dispersion experiment has been carried out to figure out the behavioral characteristics of the tracer under weather conditions that are disadvantageous to the dilution of radioactive materials released from the Wolsong Nuclear Power Plant site in Korea. In addition, through a comparison of the tracer concentrations estimated by the Gaussian plume model with measurements, this study checked the degree of conservative estimation for the Gaussian plume at the Wolsong nuclear site in Korea. A tracer Dispersion experiment using an SF 6 trace was implemented to determine the Dispersion characteristics of radioactive materials at the Wolsong Nuclear Power Plant site in Korea. Based on meteorological data and the emission rate of the tracers, this study estimated the tracer concentrations using a Gaussian plume model, and then compared it with the measurement to check the conservative estimation of the Gaussian plume model. The measured concentrations of the tracer tends to be lower than the concentrations estimated by the Gaussian plume model overall

On the thermodynamic properties of the generalized Gaussian core model

Directory of Open Access Journals (Sweden)

B.M.Mladek

2005-01-01

Full Text Available We present results of a systematic investigation of the properties of the generalized Gaussian core model of index n. The potential of this system interpolates via the index n between the potential of the Gaussian core model and the penetrable sphere system, thereby varying the steepness of the repulsion. We have used both conventional and self-consistent liquid state theories to calculate the structural and thermodynamic properties of the system; reference data are provided by computer simulations. The results indicate that the concept of self-consistency becomes indispensable to guarantee excellent agreement with simulation data; in particular, structural consistency (in our approach taken into account via the zero separation theorem is obviously a very important requirement. Simulation results for the dimensionless equation of state, β P / ρ, indicate that for an index-value of 4, a clustering transition, possibly into a structurally ordered phase might set in as the system is compressed.

CALIOP-based Biomass Burning Smoke Plume Injection Height

Science.gov (United States)

Soja, A. J.; Choi, H. D.; Fairlie, T. D.; Pouliot, G.; Baker, K. R.; Winker, D. M.; Trepte, C. R.; Szykman, J.

2017-12-01

Carbon and aerosols are cycled between terrestrial and atmosphere environments during fire events, and these emissions have strong feedbacks to near-field weather, air quality, and longer-term climate systems. Fire severity and burned area are under the control of weather and climate, and fire emissions have the potential to alter numerous land and atmospheric processes that, in turn, feedback to and interact with climate systems (e.g., changes in patterns of precipitation, black/brown carbon deposition on ice/snow, alteration in landscape and atmospheric/cloud albedo). If plume injection height is incorrectly estimated, then the transport and deposition of those emissions will also be incorrect. The heights to which smoke is injected governs short- or long-range transport, which influences surface pollution, cloud interaction (altered albedo), and modifies patterns of precipitation (cloud condensation nuclei). We are working with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) science team and other stakeholder agencies, primarily the Environmental Protection Agency and regional partners, to generate a biomass burning (BB) plume injection height database using multiple platforms, sensors and models (CALIOP, MODIS, NOAA HMS, Langley Trajectory Model). These data have the capacity to provide enhanced smoke plume injection height parameterization in regional, national and international scientific and air quality models. Statistics that link fire behavior and weather to plume rise are crucial for verifying and enhancing plume rise parameterization in local-, regional- and global-scale models used for air quality, chemical transport and climate. Specifically, we will present: (1) a methodology that links BB injection height and CALIOP air parcels to specific fires; (2) the daily evolution of smoke plumes for specific fires; (3) plumes transport and deposited on the Greenland Ice Sheet; and (4) compare CALIOP-derived smoke plume injection

The influence of model resolution on ozone in industrial volatile organic compound plumes.

Science.gov (United States)

Henderson, Barron H; Jeffries, Harvey E; Kim, Byeong-Uk; Vizuete, William G

2010-09-01

Regions with concentrated petrochemical industrial activity (e.g., Houston or Baton Rouge) frequently experience large, localized releases of volatile organic compounds (VOCs). Aircraft measurements suggest these released VOCs create plumes with ozone (O3) production rates 2-5 times higher than typical urban conditions. Modeling studies found that simulating high O3 productions requires superfine (1-km) horizontal grid cell size. Compared with fine modeling (4-kmin), the superfine resolution increases the peak O3 concentration by as much as 46%. To understand this drastic O3 change, this study quantifies model processes for O3 and "odd oxygen" (Ox) in both resolutions. For the entire plume, the superfine resolution increases the maximum O3 concentration 3% but only decreases the maximum Ox concentration 0.2%. The two grid sizes produce approximately equal Ox mass but by different reaction pathways. Derived sensitivity to oxides of nitrogen (NOx) and VOC emissions suggests resolution-specific sensitivity to NOx and VOC emissions. Different sensitivity to emissions will result in different O3 responses to subsequently encountered emissions (within the city or downwind). Sensitivity of O3 to emission changes also results in different simulated O3 responses to the same control strategies. Sensitivity of O3 to NOx and VOC emission changes is attributed to finer resolved Eulerian grid and finer resolved NOx emissions. Urban NOx concentration gradients are often caused by roadway mobile sources that would not typically be addressed with Plume-in-Grid models. This study shows that grid cell size (an artifact of modeling) influences simulated control strategies and could bias regulatory decisions. Understanding the dynamics of VOC plume dependence on grid size is the first step toward providing more detailed guidance for resolution. These results underscore VOC and NOx resolution interdependencies best addressed by finer resolution. On the basis of these results, the

Source-term development for a contaminant plume for use by multimedia risk assessment models

International Nuclear Information System (INIS)

Whelan, Gene; McDonald, John P.; Taira, Randal Y.; Gnanapragasam, Emmanuel K.; Yu, Charley; Lew, Christine S.; Mills, William B.

1999-01-01

Multimedia modelers from the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE) are collaborating to conduct a comprehensive and quantitative benchmarking analysis of four intermedia models: DOE's Multimedia Environmental Pollutant Assessment System (MEPAS), EPA's MMSOILS, EPA's PRESTO, and DOE's RESidual RADioactivity (RESRAD). These models represent typical analytically, semi-analytically, and empirically based tools that are utilized in human risk and endangerment assessments for use at installations containing radioactive and/or hazardous contaminants. Although the benchmarking exercise traditionally emphasizes the application and comparison of these models, the establishment of a Conceptual Site Model (CSM) should be viewed with equal importance. This paper reviews an approach for developing a CSM of an existing, real-world, Sr-90 plume at DOE's Hanford installation in Richland, Washington, for use in a multimedia-based benchmarking exercise bet ween MEPAS, MMSOILS, PRESTO, and RESRAD. In an unconventional move for analytically based modeling, the benchmarking exercise will begin with the plume as the source of contamination. The source and release mechanism are developed and described within the context of performing a preliminary risk assessment utilizing these analytical models. By beginning with the plume as the source term, this paper reviews a typical process and procedure an analyst would follow in developing a CSM for use in a preliminary assessment using this class of analytical tool

The tropospheric processing of acidic gases and hydrogen sulphide in volcanic gas plumes as inferred from field and model investigations

Directory of Open Access Journals (Sweden)

A. Aiuppa

2007-01-01

Full Text Available Improving the constraints on the atmospheric fate and depletion rates of acidic compounds persistently emitted by non-erupting (quiescent volcanoes is important for quantitatively predicting the environmental impact of volcanic gas plumes. Here, we present new experimental data coupled with modelling studies to investigate the chemical processing of acidic volcanogenic species during tropospheric dispersion. Diffusive tube samplers were deployed at Mount Etna, a very active open-conduit basaltic volcano in eastern Sicily, and Vulcano Island, a closed-conduit quiescent volcano in the Aeolian Islands (northern Sicily. Sulphur dioxide (SO2, hydrogen sulphide (H2S, hydrogen chloride (HCl and hydrogen fluoride (HF concentrations in the volcanic plumes (typically several minutes to a few hours old were repeatedly determined at distances from the summit vents ranging from 0.1 to ~10 km, and under different environmental conditions. At both volcanoes, acidic gas concentrations were found to decrease exponentially with distance from the summit vents (e.g., SO2 decreases from ~10 000 μg/m3at 0.1 km from Etna's vents down to ~7 μg/m3 at ~10 km distance, reflecting the atmospheric dilution of the plume within the acid gas-free background troposphere. Conversely, SO2/HCl, SO2/HF, and SO2/H2S ratios in the plume showed no systematic changes with plume aging, and fit source compositions within analytical error. Assuming that SO2 losses by reaction are small during short-range atmospheric transport within quiescent (ash-free volcanic plumes, our observations suggest that, for these short transport distances, atmospheric reactions for H2S and halogens are also negligible. The one-dimensional model MISTRA was used to simulate quantitatively the evolution of halogen and sulphur compounds in the plume of Mt. Etna. Model predictions support the hypothesis of minor HCl chemical processing during plume transport, at least in cloud-free conditions. Larger

Non-Gaussianity from inflation: theory and observations

Science.gov (United States)

Bartolo, N.; Komatsu, E.; Matarrese, S.; Riotto, A.

2004-11-01

This is a review of models of inflation and of their predictions for the primordial non-Gaussianity in the density perturbations which are thought to be at the origin of structures in the Universe. Non-Gaussianity emerges as a key observable to discriminate among competing scenarios for the generation of cosmological perturbations and is one of the primary targets of present and future Cosmic Microwave Background satellite missions. We give a detailed presentation of the state-of-the-art of the subject of non-Gaussianity, both from the theoretical and the observational point of view, and provide all the tools necessary to compute at second order in perturbation theory the level of non-Gaussianity in any model of cosmological perturbations. We discuss the new wave of models of inflation, which are firmly rooted in modern particle physics theory and predict a significant amount of non-Gaussianity. The review is addressed to both astrophysicists and particle physicists and contains useful tables which summarize the theoretical and observational results regarding non-Gaussianity.

Gaussian Process Regression Model in Spatial Logistic Regression

Science.gov (United States)

Sofro, A.; Oktaviarina, A.

2018-01-01

Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

Soft Sensor Modeling Based on Multiple Gaussian Process Regression and Fuzzy C-mean Clustering

Directory of Open Access Journals (Sweden)

Xianglin ZHU

2014-06-01

Full Text Available In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase and dead phase, the training samples are classified into 4 subcategories by using fuzzy C- mean clustering algorithm. For each sub-category, the samples are trained using the Gaussian process regression and the corresponding soft-sensing sub-model is established respectively. For a new sample, the membership between this sample and sub-models are computed based on the Euclidean distance, and then the prediction output of soft sensor is obtained using the weighting sum. Taking the Lysine fermentation as example, the simulation and experiment are carried out and the corresponding results show that the presented method achieves better fitting and generalization ability than radial basis function neutral network and single Gaussian process regression model.

Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise

Directory of Open Access Journals (Sweden)

Bowen Hou

2017-11-01

Full Text Available As one of the most critical issues for target track, α -jerk model is an effective maneuver target track model. Non-Gaussian noises always exist in the track process, which usually lead to inconsistency and divergence of the track filter. A novel Kalman filter is derived and applied on α -jerk tracking model to handle non-Gaussian noise. The weighted least square solution is presented and the standard Kalman filter is deduced firstly. A novel Kalman filter with the weighted least square based on the maximum correntropy criterion is deduced. The robustness of the maximum correntropy criterion is also analyzed with the influence function and compared with the Huber-based filter, and, moreover, the kernel size of Gaussian kernel plays an important role in the filter algorithm. A new adaptive kernel method is proposed in this paper to adjust the parameter in real time. Finally, simulation results indicate the validity and the efficiency of the proposed filter. The comparison study shows that the proposed filter can significantly reduce the noise influence for α -jerk model.

Ablation plume dynamics in a background gas

DEFF Research Database (Denmark)

Amoruso, Salvatore; Schou, Jørgen; Lunney, James G.

2010-01-01

The expansion of a plume in a background gas of pressure comparable to that used in pulsed laser deposition (PLD) has been analyzed in terms of the model of Predtechensky and Mayorov (PM). This approach gives a relatively clear and simple description of the essential hydrodynamics during the expa......The expansion of a plume in a background gas of pressure comparable to that used in pulsed laser deposition (PLD) has been analyzed in terms of the model of Predtechensky and Mayorov (PM). This approach gives a relatively clear and simple description of the essential hydrodynamics during...... the expansion. The model also leads to an insightful treatment of the stopping behavior in dimensionless units for plumes and background gases of different atomic/molecular masses. The energetics of the plume dynamics can also be treated with this model. Experimental time-of-flight data of silver ions in a neon...... background gas show a fair agreement with predictions from the PM-model. Finally we discuss the validity of the model, if the work done by the pressure of the background gas is neglected....

Statistical imitation system using relational interest points and Gaussian mixture models

CSIR Research Space (South Africa)

Claassens, J

2009-11-01

Full Text Available The author proposes an imitation system that uses relational interest points (RIPs) and Gaussian mixture models (GMMs) to characterize a behaviour. The system's structure is inspired by the Robot Programming by Demonstration (RDP) paradigm...

Inverse Gaussian model for small area estimation via Gibbs sampling

African Journals Online (AJOL)

We present a Bayesian method for estimating small area parameters under an inverse Gaussian model. The method is extended to estimate small area parameters for finite populations. The Gibbs sampler is proposed as a mechanism for implementing the Bayesian paradigm. We illustrate the method by application to ...

Measurements at cooling tower plumes. Part 3. Three-dimensional measurements at cooling tower plumes

International Nuclear Information System (INIS)

Fortak, H.

An extended field experiment is described in which cooling tower plumes were studied by means of three-dimensional in situ measurements. The goal was to obtain input data for numerical models of cooling tower plumes. Of special interest were data for testing or developing assumptions for sub-grid parametrizations. Utilizing modern systems for high-resolution aerology and small aircraft, four measuring campaigns were conducted: two campaigns (1974) at the cooling towers of the RWE power station Neurath and also two (1975) at the single cooling tower of the RWE power station Meppen. Because of the broad spectrum of weather situations it can be assumed that the results are representative with regard to the interrelationship between structure of cooling tower plume and large-scale meteorological situation. A large number of flights with a powered glider crossing the plumes on orthogonal tracks was performed. All flights showed that the plume could be identified up to large downwind distances by discontinuous jumps of temperature and vapor pressure. Therefore, a definite geometry of the plume could always be defined. In all cross sections a vertical circulation could be observed. At the boundary, which could be defined by the mentioned jumps of temperature and vapor pressure, a maximum of downward vertical motion could be observed in most cases. Entrainment along the boundary of a cross section seems to be very small, except at the lower part of the plume. There, the mass entrainment is maximum and is responsible for plume rise as well as for enlargement of the cross section. The visible part of the plume (cloud) was only a small fraction of the whole plume. High-resolution aerology is necessary in order to explain the structure and behavior of such plumes. This is especially the case in investigations regarding the dynamic break-through of temperature inversions. Such cases were observed frequently under various meteorological conditions and are described

Multiphase CFD modeling of nearfield fate of sediment plumes

DEFF Research Database (Denmark)

Saremi, Sina; Hjelmager Jensen, Jacob

2014-01-01

Disposal of dredged material and the overflow discharge during the dredging activities is a matter of concern due to the potential risks imposed by the plumes on surrounding marine environment. This gives rise to accurately prediction of the fate of the sediment plumes released in ambient waters...

A model of non-Gaussian diffusion in heterogeneous media

Science.gov (United States)

Lanoiselée, Yann; Grebenkov, Denis S.

2018-04-01

Recent progress in single-particle tracking has shown evidence of the non-Gaussian distribution of displacements in living cells, both near the cellular membrane and inside the cytoskeleton. Similar behavior has also been observed in granular materials, turbulent flows, gels and colloidal suspensions, suggesting that this is a general feature of diffusion in complex media. A possible interpretation of this phenomenon is that a tracer explores a medium with spatio-temporal fluctuations which result in local changes of diffusivity. We propose and investigate an ergodic, easily interpretable model, which implements the concept of diffusing diffusivity. Depending on the parameters, the distribution of displacements can be either flat or peaked at small displacements with an exponential tail at large displacements. We show that the distribution converges slowly to a Gaussian one. We calculate statistical properties, derive the asymptotic behavior and discuss some implications and extensions.

A regional scale model for ozone in the United States with subgrid representation of urban and power plant plumes

International Nuclear Information System (INIS)

Sillman, S.; Logan, J.A.; Wofsy, S.C.

1990-01-01

A new approach to modeling regional air chemistry is presented for application to industrialized regions such as the continental US. Rural chemistry and transport are simulated using a coarse grid, while chemistry and transport in urban and power plant plumes are represented by detailed subgrid models. Emissions from urban and power plant sources are processed in generalized plumes where chemistry and dilution proceed for 8-12 hours before mixing with air in a large resolution element. A realistic fraction of pollutants reacts under high-NO x conditions, and NO x is removed significantly before dispersal. Results from this model are compared with results from grid odels that do not distinguish plumes and with observational data defining regional ozone distributions. Grid models with coarse resolution are found to artificially disperse NO x over rural areas, therefore overestimating rural levels of both NO x and O 3 . Regional net ozone production is too high in coarse grid models, because production of O 3 is more efficient per molecule of NO x in the low-concentration regime of rural areas than in heavily polluted plumes from major emission sources. Ozone levels simulated by this model are shown to agree with observations in urban plumes and in rural regions. The model reproduces accurately average regional and peak ozone concentrations observed during a 4-day ozone episode. Computational costs for the model are reduced 25-to 100-fold as compared to fine-mesh models

The Gaussian copula model for the joint deficit index for droughts

Science.gov (United States)

Van de Vyver, H.; Van den Bergh, J.

2018-06-01

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.

Variational Gaussian approximation for Poisson data

Science.gov (United States)

Arridge, Simon R.; Ito, Kazufumi; Jin, Bangti; Zhang, Chen

2018-02-01

The Poisson model is frequently employed to describe count data, but in a Bayesian context it leads to an analytically intractable posterior probability distribution. In this work, we analyze a variational Gaussian approximation to the posterior distribution arising from the Poisson model with a Gaussian prior. This is achieved by seeking an optimal Gaussian distribution minimizing the Kullback-Leibler divergence from the posterior distribution to the approximation, or equivalently maximizing the lower bound for the model evidence. We derive an explicit expression for the lower bound, and show the existence and uniqueness of the optimal Gaussian approximation. The lower bound functional can be viewed as a variant of classical Tikhonov regularization that penalizes also the covariance. Then we develop an efficient alternating direction maximization algorithm for solving the optimization problem, and analyze its convergence. We discuss strategies for reducing the computational complexity via low rank structure of the forward operator and the sparsity of the covariance. Further, as an application of the lower bound, we discuss hierarchical Bayesian modeling for selecting the hyperparameter in the prior distribution, and propose a monotonically convergent algorithm for determining the hyperparameter. We present extensive numerical experiments to illustrate the Gaussian approximation and the algorithms.

Infrared maritime target detection using a probabilistic single Gaussian model of sea clutter in Fourier domain

Science.gov (United States)

Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei

2018-02-01

For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.

Small rocket exhaust plume data

Science.gov (United States)

Chirivella, J. E.; Moynihan, P. I.; Simon, W.

1972-01-01

During recent cryodeposit tests with an 0.18-N thruster, the mass flux in the plume back field was measured for the first time for nitrogen, carbon dioxide, and a mixture of nitrogen, hydrogen, and ammonia at various inlet pressures. This mixture simulated gases that would be generated by a hydrazine plenum attitude propulsion system. The measurements furnish a base upon which to build a mathematical model of plume back flow that will be used in predicting the mass distribution in the boundary region of other plumes. The results are analyzed and compared with existing analytical predictions.

Interactive Gaussian Graphical Models for Discovering Depth Trends in ChemCam Data

Science.gov (United States)

Oyen, D. A.; Komurlu, C.; Lanza, N. L.

2018-04-01

Interactive Gaussian graphical models discover surface compositional features on rocks in ChemCam targets. Our approach visualizes shot-to-shot relationships among LIBS observations, and identifies the wavelengths involved in the trend.

Aquatic dispersion modelling of a tritium plume in Lake Ontario

International Nuclear Information System (INIS)

Klukas, M.H.; Moltyaner, G.L.

1996-05-01

Approximately 2900 kg of tritiated water, containing 2.3E+15 Bq of tritium, were released to Lake Ontario via the cooling water discharge when a leak developed in a moderator heat exchanger in Unit 1 at the Pickering Nuclear Generating Station (PNGS) on 1992 August 2. The release provided the opportunity to study the dispersion of a tritium plume in the coastal zone of Lake Ontario. Current direction over the two-week period following the release was predominantly parallel to the shore, and elevated tritium concentrations were observed up to 20 km east and 85 km west of the PNGS. Predictions of the tritium plume movement were made using current velocity measurements taken at 8-m depth, 2.5 km offshore from Darlington and using a empirical relationship where alongshore current speed is assumed to be proportional to the alongshore component of the wind speed. The tritium migration was best described using current velocity measurements. The tritium plume dispersion is modelled using the one-dimensional advection-dispersion equation. Transport parameters are the alongshore current speed and longitudinal dispersion coefficient. Longitudinal dispersion coefficients, estimated by fitting the solution of the advection-dispersion equation to measured concentration distance profiles ranged from 3.75 to 10.57 m 2 s -1 . Simulations using the fitted values of the dispersion coefficient were able to describe maximum tritium concentrations measured at water supply plants located within 25 km of Pickering to within a factor of 3. The dispersion coefficient is a function of spatial and temporal variability in current velocity and the fitted dispersion coefficients estimated here may not be suitable for predicting tritium plume dispersion under different current conditions. The sensitivity of the dispersion coefficient to variability in current conditions should be evaluated in further field experiments. (author). 13 refs., 7 tabs., 12 figs

Stochastic cluster algorithms for discrete Gaussian (SOS) models

International Nuclear Information System (INIS)

Evertz, H.G.; Hamburg Univ.; Hasenbusch, M.; Marcu, M.; Tel Aviv Univ.; Pinn, K.; Muenster Univ.; Solomon, S.

1990-10-01

We present new Monte Carlo cluster algorithms which eliminate critical slowing down in the simulation of solid-on-solid models. In this letter we focus on the two-dimensional discrete Gaussian model. The algorithms are based on reflecting the integer valued spin variables with respect to appropriately chosen reflection planes. The proper choice of the reflection plane turns out to be crucial in order to obtain a small dynamical exponent z. Actually, the successful versions of our algorithm are a mixture of two different procedures for choosing the reflection plane, one of them ergodic but slow, the other one non-ergodic and also slow when combined with a Metropolis algorithm. (orig.)

Ground states and formal duality relations in the Gaussian core model

NARCIS (Netherlands)

Cohn, H.; Kumar, A.; Schürmann, A.

2009-01-01

We study dimensional trends in ground states for soft-matter systems. Specifically, using a high-dimensional version of Parrinello-Rahman dynamics, we investigate the behavior of the Gaussian core model in up to eight dimensions. The results include unexpected geometric structures, with surprising

Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models

NARCIS (Netherlands)

Koopman, S.J.; Lucas, A.; Scharth, M.

2015-01-01

We propose a general likelihood evaluation method for nonlinear non-Gaussian state-space models using the simulation-based method of efficient importance sampling. We minimize the simulation effort by replacing some key steps of the likelihood estimation procedure by numerical integration. We refer

Multi-scale Modeling of Power Plant Plume Emissions and Comparisons with Observations

Science.gov (United States)

Costigan, K. R.; Lee, S.; Reisner, J.; Dubey, M. K.; Love, S. P.; Henderson, B. G.; Chylek, P.

2011-12-01

The Remote Sensing Verification Project (RSVP) test-bed located in the Four Corners region of Arizona, Utah, Colorado, and New Mexico offers a unique opportunity to develop new approaches for estimating emissions of CO2. Two major power plants located in this area produce very large signals of co-emitted CO2 and NO2 in this rural region. In addition to the Environmental Protection Agency (EPA) maintaining Continuous Emissions Monitoring Systems (CEMS) on each of the power plant stacks, the RSVP program has deployed an array of in-situ and remote sensing instruments, which provide both point and integrated measurements. To aid in the synthesis and interpretation of the measurements, a multi-scale atmospheric modeling approach is implemented, using two atmospheric numerical models: the Weather Research and Forecasting Model with chemistry (WRF-Chem; Grell et al., 2005) and the HIGRAD model (Reisner et al., 2003). The high fidelity HIGRAD model incorporates a multi-phase Lagrangian particle based approach to track individual chemical species of stack plumes at ultra-high resolution, using an adaptive mesh. It is particularly suited to model buoyancy effects and entrainment processes at the edges of the power plant plumes. WRF-Chem is a community model that has been applied to a number of air quality problems and offers several physical and chemical schemes that can be used to model the transport and chemical transformation of the anthropogenic plumes out of the local region. Multiple nested grids employed in this study allow the model to incorporate atmospheric variability ranging from synoptic scales to micro-scales (~200 m), while including locally developed flows influenced by the nearby complex terrain of the San Juan Mountains. The simulated local atmospheric dynamics are provided to force the HIGRAD model, which links mesoscale atmospheric variability to the small-scale simulation of the power plant plumes. We will discuss how these two models are applied and

The Green Propellant Infusion Mission Thruster Performance Testing for Plume Diagnostics

Science.gov (United States)

Deans, Matthew C.; Reed, Brian D.; Arrington, Lynn A.; Williams, George J.; Kojima, Jun J.; Kinzbach, McKenzie I.; McLean, Christopher H.

2014-01-01

The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters are currently being tested in a small rocket, altitude facility at NASA GRC. A suite of diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, and Schlieren imaging are being used to acquire plume measurements of AF-M315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.

Gaussian Process-Mixture Conditional Heteroscedasticity.

Science.gov (United States)

Platanios, Emmanouil A; Chatzis, Sotirios P

2014-05-01

Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.

Flowfield and Radiation Analysis of Missile Exhaust Plumes Using a Turbulent-Chemistry Interaction Model

National Research Council Canada - National Science Library

Calhoon, W. H; Kenzakowski, D. C

2000-01-01

... components and missile defense systems. Current engineering level models neglect turbulent-chemistry interactions and typically underpredict the intensity of plume afterburning and afterburning burnout...

Gaussian random bridges and a geometric model for information equilibrium

Science.gov (United States)

Mengütürk, Levent Ali

2018-03-01

The paper introduces a class of conditioned stochastic processes that we call Gaussian random bridges (GRBs) and proves some of their properties. Due to the anticipative representation of any GRB as the sum of a random variable and a Gaussian (T , 0) -bridge, GRBs can model noisy information processes in partially observed systems. In this spirit, we propose an asset pricing model with respect to what we call information equilibrium in a market with multiple sources of information. The idea is to work on a topological manifold endowed with a metric that enables us to systematically determine an equilibrium point of a stochastic system that can be represented by multiple points on that manifold at each fixed time. In doing so, we formulate GRB-based information diversity over a Riemannian manifold and show that it is pinned to zero over the boundary determined by Dirac measures. We then define an influence factor that controls the dominance of an information source in determining the best estimate of a signal in the L2-sense. When there are two sources, this allows us to construct information equilibrium as a functional of a geodesic-valued stochastic process, which is driven by an equilibrium convergence rate representing the signal-to-noise ratio. This leads us to derive price dynamics under what can be considered as an equilibrium probability measure. We also provide a semimartingale representation of Markovian GRBs associated with Gaussian martingales and a non-anticipative representation of fractional Brownian random bridges that can incorporate degrees of information coupling in a given system via the Hurst exponent.

Gaussian limit of compact spin systems

International Nuclear Information System (INIS)

Bellissard, J.; Angelis, G.F. de

1981-01-01

It is shown that the Wilson and Wilson-Villain U(1) models reproduce, in the low coupling limit, the gaussian lattice approximation of the Euclidean electromagnetic field. By the same methods it is also possible to prove that the plane rotator and the Villain model share a common gaussian behaviour in the low temperature limit. (Auth.)

Plume rise measurements at Turbigo

Energy Technology Data Exchange (ETDEWEB)

Anfossi, D

1982-01-01

This paper presents analyses of plume measurements obtained during that campaign by the ENEL ground-based Lidar. The five stacks of Turbigo Power Plant have different heights and emission parameters and their plumes usually combine, so a model for multiple sources was used to predict the plume rises. These predictions are compared with the observations. Measurements of sigma/sub v/ and sigma/sub z/ over the first 1000 m are compared with the curves derived from other observations in the Po Valley, using the no-lift balloon technique over the same range of downwind distance. Skewness and kurtosis distributions are shown, both along the vertical and the horizontal directions. In order to show the plume structure in more detail, we present two examples of Lidar-derived cross sections and the corresponding vertically and horizontally integrated concentration profiles.

Treatment of non-Gaussian tails of multiple Coulomb scattering in track fitting with a Gaussian-sum filter

International Nuclear Information System (INIS)

Strandlie, A.; Wroldsen, J.

2006-01-01

If any of the probability densities involved in track fitting deviate from the Gaussian assumption, it is plausible that a non-linear estimator which better takes the actual shape of the distribution into account can do better. One such non-linear estimator is the Gaussian-sum filter, which is adequate if the distributions under consideration can be approximated by Gaussian mixtures. The main purpose of this paper is to present a Gaussian-sum filter for track fitting, based on a two-component approximation of the distribution of angular deflections due to multiple scattering. In a simulation study within a linear track model the Gaussian-sum filter is shown to be a competitive alternative to the Kalman filter. Scenarios at various momenta and with various maximum number of components in the Gaussian-sum filter are considered. Particularly at low momenta the Gaussian-sum filter yields a better estimate of the uncertainties than the Kalman filter, and it is also slightly more precise than the latter

Non-gaussianity versus nonlinearity of cosmological perturbations.

Science.gov (United States)

Verde, L

2001-06-01

Following the discovery of the cosmic microwave background, the hot big-bang model has become the standard cosmological model. In this theory, small primordial fluctuations are subsequently amplified by gravity to form the large-scale structure seen today. Different theories for unified models of particle physics, lead to different predictions for the statistical properties of the primordial fluctuations, that can be divided in two classes: gaussian and non-gaussian. Convincing evidence against or for gaussian initial conditions would rule out many scenarios and point us toward a physical theory for the origin of structures. The statistical distribution of cosmological perturbations, as we observe them, can deviate from the gaussian distribution in several different ways. Even if perturbations start off gaussian, nonlinear gravitational evolution can introduce non-gaussian features. Additionally, our knowledge of the Universe comes principally from the study of luminous material such as galaxies, but galaxies might not be faithful tracers of the underlying mass distribution. The relationship between fluctuations in the mass and in the galaxies distribution (bias), is often assumed to be local, but could well be nonlinear. Moreover, galaxy catalogues use the redshift as third spatial coordinate: the resulting redshift-space map of the galaxy distribution is nonlinearly distorted by peculiar velocities. Nonlinear gravitational evolution, biasing, and redshift-space distortion introduce non-gaussianity, even in an initially gaussian fluctuation field. I investigate the statistical tools that allow us, in principle, to disentangle the above different effects, and the observational datasets we require to do so in practice.

Gaussian process regression analysis for functional data

CERN Document Server

Shi, Jian Qing

2011-01-01

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

Modeling of Heat Transfer and Ablation of Refractory Material Due to Rocket Plume Impingement

Science.gov (United States)

Harris, Michael F.; Vu, Bruce T.

2012-01-01

CR Tech's Thermal Desktop-SINDA/FLUINT software was used in the thermal analysis of a flame deflector design for Launch Complex 39B at Kennedy Space Center, Florida. The analysis of the flame deflector takes into account heat transfer due to plume impingement from expected vehicles to be launched at KSC. The heat flux from the plume was computed using computational fluid dynamics provided by Ames Research Center in Moffet Field, California. The results from the CFD solutions were mapped onto a 3-D Thermal Desktop model of the flame deflector using the boundary condition mapping capabilities in Thermal Desktop. The ablation subroutine in SINDA/FLUINT was then used to model the ablation of the refractory material.

Coupled petrological-geodynamical modeling of a compositionally heterogeneous mantle plume

Science.gov (United States)

Rummel, Lisa; Kaus, Boris J. P.; White, Richard W.; Mertz, Dieter F.; Yang, Jianfeng; Baumann, Tobias S.

2018-01-01

Self-consistent geodynamic modeling that includes melting is challenging as the chemistry of the source rocks continuously changes as a result of melt extraction. Here, we describe a new method to study the interaction between physical and chemical processes in an uprising heterogeneous mantle plume by combining a geodynamic code with a thermodynamic modeling approach for magma generation and evolution. We pre-computed hundreds of phase diagrams, each of them for a different chemical system. After melt is extracted, the phase diagram with the closest bulk rock chemistry to the depleted source rock is updated locally. The petrological evolution of rocks is tracked via evolving chemical compositions of source rocks and extracted melts using twelve oxide compositional parameters. As a result, a wide variety of newly generated magmatic rocks can in principle be produced from mantle rocks with different degrees of depletion. The results show that a variable geothermal gradient, the amount of extracted melt and plume excess temperature affect the magma production and chemistry by influencing decompression melting and the depletion of rocks. Decompression melting is facilitated by a shallower lithosphere-asthenosphere boundary and an increase in the amount of extracted magma is induced by a lower critical melt fraction for melt extraction and/or higher plume temperatures. Increasing critical melt fractions activates the extraction of melts triggered by decompression at a later stage and slows down the depletion process from the metasomatized mantle. Melt compositional trends are used to determine melting related processes by focusing on K2O/Na2O ratio as indicator for the rock type that has been molten. Thus, a step-like-profile in K2O/Na2O might be explained by a transition between melting metasomatized and pyrolitic mantle components reproducible through numerical modeling of a heterogeneous asthenospheric mantle source. A potential application of the developed method

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan; Genton, Marc G.

2017-01-01

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Gaussian likelihood inference on data from trans-Gaussian random fields with Matérn covariance function

KAUST Repository

Yan, Yuan

2017-07-13

Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.

Estimation of the environmental impact of emissions from the La Reina NEC, by atmospheric dispersion modeling

International Nuclear Information System (INIS)

Bustamante C, Paula M.; Ortiz R, Marcela A.

1996-01-01

Based on a dispersion model, an accidental release of radioactive material to the atmosphere was simulated. To evaluate the consequences of the accidental release it was used the P C COSYMA program (KfK and NRPB). The atmospheric dispersion model was MUSEMET, a segmented Gaussian plume model which requires information on meteorological conditions for a period of one year. This study was carried out to determine the plume's behavior and path, and to define protective actions. The meteorological analysis shows an airflow from the WSW and a channeling flow from the S E at night, due to topographical influences. (author)

Investigation of non-Gaussian effects in the Brazilian option market

Science.gov (United States)

Sosa-Correa, William O.; Ramos, Antônio M. T.; Vasconcelos, Giovani L.

2018-04-01

An empirical study of the Brazilian option market is presented in light of three option pricing models, namely the Black-Scholes model, the exponential model, and a model based on a power law distribution, the so-called q-Gaussian distribution or Tsallis distribution. It is found that the q-Gaussian model performs better than the Black-Scholes model in about one third of the option chains analyzed. But among these cases, the exponential model performs better than the q-Gaussian model in 75% of the time. The superiority of the exponential model over the q-Gaussian model is particularly impressive for options close to the expiration date, where its success rate rises above ninety percent.

Imprint of primordial non-Gaussianity on dark matter halo profiles

Energy Technology Data Exchange (ETDEWEB)

Dizgah, Azadeh Moradinezhad; Dodelson, Scott; Riotto, Antonio

2013-09-01

We study the impact of primordial non-Gaussianity on the density profile of dark matter halos by using the semi-analytical model introduced recently by Dalal {\\it et al.} which relates the peaks of the initial linear density field to the final density profile of dark matter halos. Models with primordial non-Gaussianity typically produce an initial density field that differs from that produced in Gaussian models. We use the path-integral formulation of excursion set theory to calculate the non-Gaussian corrections to the peak profile and derive the statistics of the peaks of non-Gaussian density field. In the context of the semi-analytic model for halo profiles, currently allowed values for primordial non-Gaussianity would increase the shapes of the inner dark matter profiles, but only at the sub-percent level except in the very innermost regions.

Observation of thermal plumes from submerged discharges in the Great Lakes and their implications for modeling and monitoring

International Nuclear Information System (INIS)

Ditmars, J.D.; Paddock, R.A.; Frigo, A.A.

1977-01-01

Measurements of thermal plumes from submerged discharges of power plant cooling waters into the Great Lakes provide the opportunity to view the mixing processes at prototype scales and to observe the effects of the ambient environment on those processes. Examples of thermal plume behavior in Great Lakes' ambient environments are presented to demonstrate the importance of measurements of the detailed structure of the ambient environment, as well as of the plumes, for interpretation of prototype data for modeling and monitoring purposes. The examples are drawn from studies by Argonne National Laboratory (ANL) at the Zion Nuclear PowerStation and the D. C. Cook Nuclear Plant on Lake Michigan and at the J. A. FitzPatrick Nuclear Power Plant on Lake Ontario. These studies included measurements of water temperatures from a moving boat which provide a quasi-synoptic view of the three-dimensional temperature structure of the thermal plume and ambient water environment. Additional measurements of water velocities, which are made with continuously recording, moored, and profiling current meters, and of wind provide data on the detailed structure of the ambient environment. The detailed structure of the ambient environment, in terms of current, current shear, variable winds, and temperature stratification, often influence greatly thermal plume behavior. Although predictive model techniques and monitoring objectives often ignore the detailed aspects of the ambient environment, useful interpretation of prototype data for model evaluation or calibration and monitoring purposes requires detailed measurement of the ambient environment. Examination of prototype thermal plume data indicates that, in several instances, attention to only the gross characteristics of the ambient environment can be misleading and could result in significant errors in model calibration and extrapolation of data bases gathered in monitoring observations

Clustering gene expression time series data using an infinite Gaussian process mixture model.

Science.gov (United States)

McDowell, Ian C; Manandhar, Dinesh; Vockley, Christopher M; Schmid, Amy K; Reddy, Timothy E; Engelhardt, Barbara E

2018-01-01

Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

Clustering gene expression time series data using an infinite Gaussian process mixture model.

Directory of Open Access Journals (Sweden)

Ian C McDowell

2018-01-01

Full Text Available Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP, which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

Are splash plumes the origin of minor hotspots?

Science.gov (United States)

Davies, J. H.; Bunge, H.-P.

2006-05-01

It has been claimed that focused hot cylindrical upwelling plumes cause many of the surface volcanic hotspots on Earth. It has also been argued that they must originate from thermal boundary layers. In this paper, we present spherical simulations of mantle circulation at close to Earth-like vigor with significant internal heating. These show, in addition to thermal boundary layer plumes, a new class of plumes that are not rooted in thermal boundary layers. These plumes develop as instabilities from the edge of bowls of hot mantle, which are produced by cold downwelling material deforming hot sheets of mantle. The resulting bowl and plume structure can look a bit like the “splash” of a water droplet. These splash plumes might provide an explanation for some hotspots that are not underlain by thermal boundary layer sourced plumes and not initiated by large igneous provinces. We suggest that in Earth's mantle, lithospheric instabilities or small pieces of subducting slab could play the role of the model downwelling material in initiating splash plumes. Splash plumes would have implications for interpreting ocean-island basalt geochemistry, plume fixity, excess plume temperature, and estimating core heat flux. Improved seismic imaging will ultimately test this hypothesis.

Numerical modeling of Gaussian beam propagation and diffraction in inhomogeneous media based on the complex eikonal equation

Science.gov (United States)

Huang, Xingguo; Sun, Hui

2018-05-01

Gaussian beam is an important complex geometrical optical technology for modeling seismic wave propagation and diffraction in the subsurface with complex geological structure. Current methods for Gaussian beam modeling rely on the dynamic ray tracing and the evanescent wave tracking. However, the dynamic ray tracing method is based on the paraxial ray approximation and the evanescent wave tracking method cannot describe strongly evanescent fields. This leads to inaccuracy of the computed wave fields in the region with a strong inhomogeneous medium. To address this problem, we compute Gaussian beam wave fields using the complex phase by directly solving the complex eikonal equation. In this method, the fast marching method, which is widely used for phase calculation, is combined with Gauss-Newton optimization algorithm to obtain the complex phase at the regular grid points. The main theoretical challenge in combination of this method with Gaussian beam modeling is to address the irregular boundary near the curved central ray. To cope with this challenge, we present the non-uniform finite difference operator and a modified fast marching method. The numerical results confirm the proposed approach.

Interconversion of pure Gaussian states requiring non-Gaussian operations

Science.gov (United States)

Jabbour, Michael G.; García-Patrón, Raúl; Cerf, Nicolas J.

2015-01-01

We analyze the conditions under which local operations and classical communication enable entanglement transformations between bipartite pure Gaussian states. A set of necessary and sufficient conditions had been found [G. Giedke et al., Quant. Inf. Comput. 3, 211 (2003)] for the interconversion between such states that is restricted to Gaussian local operations and classical communication. Here, we exploit majorization theory in order to derive more general (sufficient) conditions for the interconversion between bipartite pure Gaussian states that goes beyond Gaussian local operations. While our technique is applicable to an arbitrary number of modes for each party, it allows us to exhibit surprisingly simple examples of 2 ×2 Gaussian states that necessarily require non-Gaussian local operations to be transformed into each other.

Model-independent test for scale-dependent non-Gaussianities in the cosmic microwave background.

Science.gov (United States)

Räth, C; Morfill, G E; Rossmanith, G; Banday, A J; Górski, K M

2009-04-03

We present a model-independent method to test for scale-dependent non-Gaussianities in combination with scaling indices as test statistics. Therefore, surrogate data sets are generated, in which the power spectrum of the original data is preserved, while the higher order correlations are partly randomized by applying a scale-dependent shuffling procedure to the Fourier phases. We apply this method to the Wilkinson Microwave Anisotropy Probe data of the cosmic microwave background and find signatures for non-Gaussianities on large scales. Further tests are required to elucidate the origin of the detected anomalies.

Performance modeling and analysis of parallel Gaussian elimination on multi-core computers

Directory of Open Access Journals (Sweden)

Fadi N. Sibai

2014-01-01

Full Text Available Gaussian elimination is used in many applications and in particular in the solution of systems of linear equations. This paper presents mathematical performance models and analysis of four parallel Gaussian Elimination methods (precisely the Original method and the new Meet in the Middle –MiM– algorithms and their variants with SIMD vectorization on multi-core systems. Analytical performance models of the four methods are formulated and presented followed by evaluations of these models with modern multi-core systems’ operation latencies. Our results reveal that the four methods generally exhibit good performance scaling with increasing matrix size and number of cores. SIMD vectorization only makes a large difference in performance for low number of cores. For a large matrix size (n ⩾ 16 K, the performance difference between the MiM and Original methods falls from 16× with four cores to 4× with 16 K cores. The efficiencies of all four methods are low with 1 K cores or more stressing a major problem of multi-core systems where the network-on-chip and memory latencies are too high in relation to basic arithmetic operations. Thus Gaussian Elimination can greatly benefit from the resources of multi-core systems, but higher performance gains can be achieved if multi-core systems can be designed with lower memory operation, synchronization, and interconnect communication latencies, requirements of utmost importance and challenge in the exascale computing age.

Making tensor factorizations robust to non-gaussian noise.

Energy Technology Data Exchange (ETDEWEB)

Chi, Eric C. (Rice University, Houston, TX); Kolda, Tamara Gibson

2011-03-01

Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).

On a Generalized Squared Gaussian Diffusion Model for Option Valuation

Directory of Open Access Journals (Sweden)

Edeki S.O.

2017-01-01

Full Text Available In financial mathematics, option pricing models are vital tools whose usefulness cannot be overemphasized. Modern approaches and modelling of financial derivatives are therefore required in option pricing and valuation settings. In this paper, we derive via the application of Ito lemma, a pricing model referred to as Generalized Squared Gaussian Diffusion Model (GSGDM for option pricing and valuation. Same approach can be considered via Stratonovich stochastic dynamics. We also show that the classical Black-Scholes, and the square root constant elasticity of variance models are special cases of the GSGDM. In addition, general solution of the GSGDM is obtained using modified variational iterative method (MVIM.

Scalable Gaussian Processes and the search for exoplanets

CERN Multimedia

CERN. Geneva

2015-01-01

Gaussian Processes are a class of non-parametric models that are often used to model stochastic behavior in time series or spatial data. A major limitation for the application of these models to large datasets is the computational cost. The cost of a single evaluation of the model likelihood scales as the third power of the number of data points. In the search for transiting exoplanets, the datasets of interest have tens of thousands to millions of measurements with uneven sampling, rendering naive application of a Gaussian Process model impractical. To attack this problem, we have developed robust approximate methods for Gaussian Process regression that can be applied at this scale. I will describe the general problem of Gaussian Process regression and offer several applicable use cases. Finally, I will present our work on scaling this model to the exciting field of exoplanet discovery and introduce a well-tested open source implementation of these new methods.

Modeling ozone plumes observed downwind of New York City over the North Atlantic Ocean during the ICARTT field campaign

Directory of Open Access Journals (Sweden)

S.-H. Lee

2011-07-01

Full Text Available Transport and chemical transformation of well-defined New York City (NYC urban plumes over the North Atlantic Ocean were studied using aircraft measurements collected on 20–21 July 2004 during the ICARTT (International Consortium for Atmospheric Research on Transport and Transformation field campaign and WRF-Chem (Weather Research and Forecasting-Chemistry model simulations. The strong NYC urban plumes were characterized by carbon monoxide (CO mixing ratios of 350–400 parts per billion by volume (ppbv and ozone (O₃ levels of about 100 ppbv near New York City on 20 July in the WP-3D in-situ and DC-3 lidar aircraft measurements. On 21 July, the two aircraft captured strong urban plumes with about 350 ppbv CO and over 150 ppbv O₃ (~160 ppbv maximum about 600 km downwind of NYC over the North Atlantic Ocean. The measured urban plumes extended vertically up to about 2 km near New York City, but shrank to 1–1.5 km over the stable marine boundary layer (MBL over the North Atlantic Ocean. The WRF-Chem model reproduced ozone formation processes, chemical characteristics, and meteorology of the measured urban plumes near New York City (20 July and in the far downwind region over the North Atlantic Ocean (21 July. The quasi-Lagrangian analysis of transport and chemical transformation of the simulated NYC urban plumes using WRF-Chem results showed that the pollutants can be efficiently transported in (isentropic layers in the lower atmosphere (<2–3 km over the North Atlantic Ocean while maintaining a dynamic vertical decoupling by cessation of turbulence in the stable MBL. The O₃ mixing ratio in the NYC urban plumes remained at 80–90 ppbv during nocturnal transport over the stable MBL, then grew to over 100 ppbv by daytime oxidation of nitrogen oxides (NO_x = NO + NO₂ with mixing ratios on the order of 1 ppbv. Efficient transport of reactive nitrogen species (NO_y, specifically nitric

Experimental investigation of bubble plume structure instability

Energy Technology Data Exchange (ETDEWEB)

Marco Simiano; Robert Zboray; Francois de Cachard [Thermal-Hydraulics Laboratory, Paul Scherrer Institut, 5232 Villigen PSI (Switzerland); Djamel Lakehal; George Yadigaroglu [Institute of Energy Technology, Swiss Federal Institute of Technology, ETH-Zentrum/CLT, 8092 Zurich (Switzerland)

2005-07-01

Full text of publication follows: The hydrodynamic properties of a 3D bubble plume in a large water pool are investigated experimentally. Bubble plumes are present in various industrial processes, including chemical plants, stirred reactors, and nuclear power plants, e.g. in BWR suppression pools. In these applications, the main issue is to predict the currents induced by the bubbles in the liquid phase, and to determine the consequent mixing. Bubble plumes, especially large and unconfined ones, present strong 3D effects and a superposition of different characteristic length scales. Thus, they represent relevant test cases for assessment and verification of 3D models in thermal-hydraulic codes. Bubble plumes are often unsteady, with fluctuations in size and shape of the bubble swarm, and global movements of the plume. In this case, local time-averaged data are not sufficient to characterize the flow. Additional information regarding changes in plume shape and position is required. The effect of scale on the 3D flow structure and stability being complex, there was a need to conduct studies in a fairly large facility, closer to industrial applications. Air bubble plumes, up to 30 cm in base diameter and 2 m in height were extensively studied in a 2 m diameter water pool. Homogeneously sized bubbles were obtained using a particular injector. The main hydrodynamic parameters. i.e., gas and liquid velocities, void fraction, bubble shape and size, plume shape and position, were determined experimentally. Photographic and image processing techniques were used to characterize the bubble shape, and double-tip optical probes to measure bubble size and void fraction. Electromagnetic probes measured the recirculation velocity in the pool. Simultaneous two-phase flow particle image velocimetry (STPFPIV) in a vertical plane containing the vessel axis provided instantaneous velocity fields for both phases and therefore the relative velocity field. Video recording using two CCD

Dilution in Transition Zone between Rising Plumes and Surface Plumes

DEFF Research Database (Denmark)

Larsen, Torben

2004-01-01

The papers presents some physical experiments with the dilution of sea outfall plumes with emphasize on the transition zone where the relative fast flowing vertical plume turns to a horizontal surface plume following the slow sea surface currents. The experiments show that a considerable dilution...

Plume Tracker: Interactive mapping of volcanic sulfur dioxide emissions with high-performance radiative transfer modeling

Science.gov (United States)

Realmuto, Vincent J.; Berk, Alexander

2016-11-01

We describe the development of Plume Tracker, an interactive toolkit for the analysis of multispectral thermal infrared observations of volcanic plumes and clouds. Plume Tracker is the successor to MAP_SO2, and together these flexible and comprehensive tools have enabled investigators to map sulfur dioxide (SO2) emissions from a number of volcanoes with TIR data from a variety of airborne and satellite instruments. Our objective for the development of Plume Tracker was to improve the computational performance of the retrieval procedures while retaining the accuracy of the retrievals. We have achieved a 300 × improvement in the benchmark performance of the retrieval procedures through the introduction of innovative data binning and signal reconstruction strategies, and improved the accuracy of the retrievals with a new method for evaluating the misfit between model and observed radiance spectra. We evaluated the accuracy of Plume Tracker retrievals with case studies based on MODIS and AIRS data acquired over Sarychev Peak Volcano, and ASTER data acquired over Kilauea and Turrialba Volcanoes. In the Sarychev Peak study, the AIRS-based estimate of total SO2 mass was 40% lower than the MODIS-based estimate. This result was consistent with a 45% reduction in the AIRS-based estimate of plume area relative to the corresponding MODIS-based estimate. In addition, we found that our AIRS-based estimate agreed with an independent estimate, based on a competing retrieval technique, within a margin of ± 20%. In the Kilauea study, the ASTER-based concentration estimates from 21 May 2012 were within ± 50% of concurrent ground-level concentration measurements. In the Turrialba study, the ASTER-based concentration estimates on 21 January 2012 were in exact agreement with SO2 concentrations measured at plume altitude on 1 February 2012.

Field studies of the thermal plume from the D. C. Cook submerged discharge with comparisons to hydraulic-model results

International Nuclear Information System (INIS)

Frigo, A.A.; Paddock, R.A.; McCown, D.L.

1975-06-01

The Donald C. Cook Nuclear Plant at Bridgman, Michigan, uses submerged-diffuser discharges as a means of disposing waste heat into Lake Michigan. Preliminary results of temperature surveys of the thermal plume at the D. C. Cook Plant are presented. Indications are that the spatial extent of the plume at the surface is much smaller than previous results for surface shoreline discharges, particularly in the near and intermediate portions of the plume. Comparisons of limited prototype data with hydraulic (tank)-model predictions indicate that the model predictions for centerline temperature decay at the surface are too high for the initial 200 m from the discharge, but are generally correct beyond this point to the limits of the model. In addition, the hydraulic-model results underestimate the areal extent of the near and intermediate portions of the plume at the surface. Because this is the first report of a new field program, several inadequacies in the field-measurement techniques are noted and discussed. New techniques that have been developed to remedy these deficiencies, and which will be implemented for future field work, are also described. (auth)

The impact from emitted NO{sub x} and VOC in an aircraft plume. Model results for the free troposphere

Energy Technology Data Exchange (ETDEWEB)

Pleijel, K.

1998-04-01

The chemical fate of gaseous species in a specific aircraft plume is investigated using an expanding box model. The model treats the gas phase chemical reactions in detail, while other parameters are subject to a high degree of simplification. Model simulations were carried out in a plume up to an age of three days. The role of emitted VOC, NO{sub x} and CO as well as of background concentrations of VOC, NO{sub x} and ozone on aircraft plume chemistry was investigated. Background concentrations were varied in a span of measured values in the free troposphere. High background concentrations of VOC were found to double the average plume production of ozone and organic nitrates. In a high NO{sub x} environment the plume production of ozone and organic nitrates decreased by around 50%. The production of nitric acid was found to be less sensitive to background concentrations of VOC, and increased by up to 50% in a high NO{sub x} environment. Mainly, emitted NO{sub x} caused the plume production of ozone, nitric acid and organic nitrates. The ozone production during the first hours is determined by the relative amount of NO{sub 2} in the NO{sub x} emissions. The impact from emitted VOC was in relative values up to 20% of the ozone production and 65% of the production of organic nitrates. The strongest relative influence from VOC was found in an environment characterized by low VOC and high NO{sub x} background concentrations, where the absolute peak production was lower than in the other scenarios. The effect from emitting VOC and NO{sub x} at the same time added around 5% for ozone, 15% for nitric acid and 10% for organic nitrates to the plume production caused by NO{sub x} and VOC when emitted separately 47 refs, 15 figs, 4 tabs

Gaussian Mixture Random Coefficient model based framework for SHM in structures with time-dependent dynamics under uncertainty

Science.gov (United States)

Avendaño-Valencia, Luis David; Fassois, Spilios D.

2017-12-01

The problem of vibration-based damage diagnosis in structures characterized by time-dependent dynamics under significant environmental and/or operational uncertainty is considered. A stochastic framework consisting of a Gaussian Mixture Random Coefficient model of the uncertain time-dependent dynamics under each structural health state, proper estimation methods, and Bayesian or minimum distance type decision making, is postulated. The Random Coefficient (RC) time-dependent stochastic model with coefficients following a multivariate Gaussian Mixture Model (GMM) allows for significant flexibility in uncertainty representation. Certain of the model parameters are estimated via a simple procedure which is founded on the related Multiple Model (MM) concept, while the GMM weights are explicitly estimated for optimizing damage diagnostic performance. The postulated framework is demonstrated via damage detection in a simple simulated model of a quarter-car active suspension with time-dependent dynamics and considerable uncertainty on the payload. Comparisons with a simpler Gaussian RC model based method are also presented, with the postulated framework shown to be capable of offering considerable improvement in diagnostic performance.

Plume rise from stacks with scrubbers: a state-of-the-art review

International Nuclear Information System (INIS)

Schatzmann, M.; Policastro, A.J.

1984-01-01

The state of the art of predicting plume rise from stacks with scrubbers is evaluated critically. The significant moisture content of the scrubbed plume upon exit leads to important thermodynamic effects during plume rise that are unaccounted for in the usual dry plume rise theories. For example, under conditionally unstable atmospheres, a wet scrubbed plume treated as completely dry acts as if the atmosphere were stable, whereas in reality the scrubbed plume behaves instead as if the atmosphere were unstable. Even the use of moist plume models developed for application to cooling tower plume rise is not valid since these models 1) employ the Boussinesq approximation, 2) use a number of additional simplifying approximations that require small exit temperature differences between tower exit and ambient temperatures, and 3) are not calibrated to stack data

Integrating a street-canyon model with a regional Gaussian dispersion model for improved characterisation of near-road air pollution

Science.gov (United States)

Fallah-Shorshani, Masoud; Shekarrizfard, Maryam; Hatzopoulou, Marianne

2017-03-01

The development and use of dispersion models that simulate traffic-related air pollution in urban areas has risen significantly in support of air pollution exposure research. In order to accurately estimate population exposure, it is important to generate concentration surfaces that take into account near-road concentrations as well as the transport of pollutants throughout an urban region. In this paper, an integrated modelling chain was developed to simulate ambient Nitrogen Dioxide (NO2) in a dense urban neighbourhood while taking into account traffic emissions, the regional background, and the transport of pollutants within the urban canopy. For this purpose, we developed a hybrid configuration including 1) a street canyon model, which simulates pollutant transfer along streets and intersections, taking into account the geometry of buildings and other obstacles, and 2) a Gaussian puff model, which resolves the transport of contaminants at the top of the urban canopy and accounts for regional meteorology. Each dispersion model was validated against measured concentrations and compared against the hybrid configuration. Our results demonstrate that the hybrid approach significantly improves the output of each model on its own. An underestimation appears clearly for the Gaussian model and street-canyon model compared to observed data. This is due to ignoring the building effect by the Gaussian model and undermining the contribution of other roads by the canyon model. The hybrid approach reduced the RMSE (of observed vs. predicted concentrations) by 16%-25% compared to each model on its own, and increased FAC2 (fraction of predictions within a factor of two of the observations) by 10%-34%.

Modelling and control of dynamic systems using gaussian process models

CERN Document Server

Kocijan, Juš

2016-01-01

This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior know...

Non-Gaussian halo assembly bias

International Nuclear Information System (INIS)

Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro

2010-01-01

The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively

Gaussian free turbulence: structures and relaxation in plasma models

International Nuclear Information System (INIS)

Gruzinov, A.V.

1993-01-01

Free-turbulent relaxation in two-dimensional MHD, the degenerate Hasegawa-Mima equation and a two-dimensional microtearing model are studied. The Gibbs distributions of these three systems can be completely analyzed, due to the special structure of their invariants and due to the existence of ultraviolet catastrophe. The free-turbulent field is seen to be a sum of a certain coherent structure (statistical attractor) and Gaussian random noise. Two-dimensional current layers are shown to be statistical attractors in 2D MHD. (author)

CFD investigation of balcony spill plumes in atria

International Nuclear Information System (INIS)

McCartney, C.J.; Lougheed, G.D.; Weckman, E.J.

2004-01-01

Smoke management in buildings during fire events often uses mechanical ventilation systems to maintain smoke layer elevation above a safe evacuation path. Design of these systems requires accurate correlations for the smoke production rate of the buoyant fire plume. One design issue is the smoke production rate of fire plumes which spill out from a fire compartment, under a balcony and up through an atrium or other large volume. Current engineering correlations for these balcony spill plumes are based on a combination of one-tenth scale test data and theoretical analysis. Questions have arisen over the suitability of these correlations for real-scale designs. A combined program of full-scale experimentation and CFD modeling is being conducted to analyze the accuracy of these correlations. A full-scale experimental facility was constructed with a 5 m by 5 m by 15 m fire compartment connected to a four-story atrium. Propane fires in the compartment produce balcony spill plumes which form steady-state smoke layers in the atrium. Experimental variables include fire size, compartment opening width, balcony depth and compartment fascia depth. A variable exhaust system was used to achieve various smoke layer heights for each of 100 compartment configurations. Temperature, smoke obscuration and gas concentrations were measured in the compartment, atrium and exhaust system. The experimental data was used to determine the atrium smoke layer elevation and balcony spill plume smoke production rate for each configuration and fire size. Comparison of this data with zone model results and design correlations for atrium smoke management systems will be performed to evaluate their accuracy. A CFD model of the experimental facility was implemented using the Fire Dynamics Simulator software (Version 3). Large-eddy simulations of the flow were performed with a constant radiative fraction and an infinitely fast mixture fraction combustion model. A grid sensitivity analysis was

Measurements at cooling tower plumes. Pt. 1

International Nuclear Information System (INIS)

Gassmann, F.; Haschke, D.; Solfrian, W.

1976-04-01

Referring to the present status of knowledge model conceptions, assumptions and approaches are summarized, which can lead to mathematical models for the simulation of dry or wet cooling tower plumes. By developing a one-dimensional plume model (FOG) the most important problems are considered in detail. It is shown that for the calibration of the necessary parameters as well as for the development of models full scale measurements are of decisive importance. After a discussion of different possibilities of measurement the organisation of a campaign of measurement is described. (orig.) [de

The Gaussian streaming model and convolution Lagrangian effective field theory

Energy Technology Data Exchange (ETDEWEB)

Vlah, Zvonimir [Stanford Institute for Theoretical Physics and Department of Physics, Stanford University, Stanford, CA 94306 (United States); Castorina, Emanuele; White, Martin, E-mail: zvlah@stanford.edu, E-mail: ecastorina@berkeley.edu, E-mail: mwhite@berkeley.edu [Department of Physics, University of California, Berkeley, CA 94720 (United States)

2016-12-01

We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM to a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.

Prediction of Geological Subsurfaces Based on Gaussian Random Field Models

Energy Technology Data Exchange (ETDEWEB)

Abrahamsen, Petter

1997-12-31

During the sixties, random functions became practical tools for predicting ore reserves with associated precision measures in the mining industry. This was the start of the geostatistical methods called kriging. These methods are used, for example, in petroleum exploration. This thesis reviews the possibilities for using Gaussian random functions in modelling of geological subsurfaces. It develops methods for including many sources of information and observations for precise prediction of the depth of geological subsurfaces. The simple properties of Gaussian distributions make it possible to calculate optimal predictors in the mean square sense. This is done in a discussion of kriging predictors. These predictors are then extended to deal with several subsurfaces simultaneously. It is shown how additional velocity observations can be used to improve predictions. The use of gradient data and even higher order derivatives are also considered and gradient data are used in an example. 130 refs., 44 figs., 12 tabs.

Childhood malnutrition in Egypt using geoadditive Gaussian and latent variable models.

Science.gov (United States)

Khatab, Khaled

2010-04-01

Major progress has been made over the last 30 years in reducing the prevalence of malnutrition amongst children less than 5 years of age in developing countries. However, approximately 27% of children under the age of 5 in these countries are still malnourished. This work focuses on the childhood malnutrition in one of the biggest developing countries, Egypt. This study examined the association between bio-demographic and socioeconomic determinants and the malnutrition problem in children less than 5 years of age using the 2003 Demographic and Health survey data for Egypt. In the first step, we use separate geoadditive Gaussian models with the continuous response variables stunting (height-for-age), underweight (weight-for-age), and wasting (weight-for-height) as indicators of nutritional status in our case study. In a second step, based on the results of the first step, we apply the geoadditive Gaussian latent variable model for continuous indicators in which the 3 measurements of the malnutrition status of children are assumed as indicators for the latent variable "nutritional status".

Gaussian vs non-Gaussian turbulence: impact on wind turbine loads

DEFF Research Database (Denmark)

Berg, Jacob; Natarajan, Anand; Mann, Jakob

2016-01-01

taking into account the safety factor for extreme moments. Other extreme load moments as well as the fatigue loads are not affected because of the use of non-Gaussian turbulent inflow. It is suggested that the turbine thus acts like a low-pass filter that averages out the non-Gaussian behaviour, which......From large-eddy simulations of atmospheric turbulence, a representation of Gaussian turbulence is constructed by randomizing the phases of the individual modes of variability. Time series of Gaussian turbulence are constructed and compared with its non-Gaussian counterpart. Time series from the two...

Ozone production efficiency of a ship-plume: ITCT 2K2 case study.

Science.gov (United States)

Kim, Hyun S; Kim, Yong H; Han, Kyung M; Kim, Jhoon; Song, Chul H

2016-01-01

Ozone production efficiency (OPE) of ship plume was first evaluated in this study, based on ship-plume photochemical/dynamic model simulations and the ship-plume composition data measured during the ITCT 2K2 (Intercontinental Transport and Chemical Transformation 2002) aircraft campaign. The averaged instantaneous OPEs (OPE(i)‾) estimated via the ship-plume photochemical/dynamic modeling for the ITCT 2K2 ship-plume ranged between 4.61 and 18.92, showing that the values vary with the extent of chemical evolution (or chemical stage) of the ship plume and the stability classes of the marine boundary layer (MBL). Together with OPE(i)‾, the equivalent OPEs (OPE(e)‾) for the entire ITCT 2K2 ship-plume were also estimated. The OPE(e)‾ values varied between 9.73 (for the stable MBL) and 12.73 (for the moderately stable MBL), which agreed well with the OPE(e)‾ of 12.85 estimated based on the ITCT 2K2 ship-plume observations. It was also found that both the model-simulated and observation-based OPE(e)‾ inside the ship-plume were 0.29-0.38 times smaller than the OPE(e)‾ calculated/measured outside the ITCT 2K2 ship-plume. Such low OPEs insides the ship plume were due to the high levels of NO and non-liner ship-plume photochemistry. Possible implications of this ship-plume OPE study in the global chemistry-transport modeling are also discussed. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Case studies in Gaussian process modelling of computer codes

International Nuclear Information System (INIS)

Kennedy, Marc C.; Anderson, Clive W.; Conti, Stefano; O'Hagan, Anthony

2006-01-01

In this paper we present a number of recent applications in which an emulator of a computer code is created using a Gaussian process model. Tools are then applied to the emulator to perform sensitivity analysis and uncertainty analysis. Sensitivity analysis is used both as an aid to model improvement and as a guide to how much the output uncertainty might be reduced by learning about specific inputs. Uncertainty analysis allows us to reflect output uncertainty due to unknown input parameters, when the finished code is used for prediction. The computer codes themselves are currently being developed within the UK Centre for Terrestrial Carbon Dynamics

DSMC Simulations of Io's Pele Plume

Science.gov (United States)

McDoniel, William; Goldstein, D.; Varghese, P.; Trafton, L.

2012-10-01

Io’s Pele plume rises over 300km in altitude and leaves a deposition ring 1200km across on the surface of the moon. Material emerges from an irregularly-shaped vent, and this geometry gives rise to complex 3D flow features. The Direct Simulation Monte Carlo method is used to model the gas flow in the rarefied plume, demonstrating how the geometry of the source region is responsible for the asymmetric structure of the deposition ring and illustrating the importance of very small-scale vent geometry in explaining large observed features of interest. Simulations of small particles in the plume and comparisons to the black “butterfly wings” seen at Pele are used to constrain particle sizes and entrainment mechanisms. Preliminary results for the effects of plasma energy and momentum transfer to the plume will also be presented.

Multiscale Approach to Small River Plumes off California

Science.gov (United States)

Basdurak, N. B.; Largier, J. L.; Nidzieko, N.

2012-12-01

While larger scale plumes have received significant attention, the dynamics of plumes associated with small rivers typical of California are little studied. Since small streams are not dominated by a momentum flux, their plumes are more susceptible to conditions in the coastal ocean such as wind and waves. In order to correctly model water transport at smaller scales, there is a need to capture larger scale processes. To do this, one-way nested grids with varying grid resolution (1 km and 10 m for the parent and the child grid respectively) were constructed. CENCOOS (Central and Northern California Ocean Observing System) model results were used as boundary conditions to the parent grid. Semi-idealized model results for Santa Rosa Creek, California are presented from an implementation of the Regional Ocean Modeling System (ROMS v3.0), a three-dimensional, free-surface, terrain-following numerical model. In these preliminary results, the interaction between tides, winds, and buoyancy forcing in plume dynamics is explored for scenarios including different strengths of freshwater flow with different modes (steady and pulsed). Seasonal changes in transport dynamics and dispersion patterns are analyzed.

Legendre Duality of Spherical and Gaussian Spin Glasses

Energy Technology Data Exchange (ETDEWEB)

Genovese, Giuseppe, E-mail: giuseppe.genovese@math.uzh.ch [Universität Zürich, Institut für Mathematik (Switzerland); Tantari, Daniele, E-mail: daniele.tantari@sns.it [Scuola Normale Superiore di Pisa, Centro Ennio de Giorgi (Italy)

2015-12-15

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model.

Legendre Duality of Spherical and Gaussian Spin Glasses

International Nuclear Information System (INIS)

Genovese, Giuseppe; Tantari, Daniele

2015-01-01

The classical result of concentration of the Gaussian measure on the sphere in the limit of large dimension induces a natural duality between Gaussian and spherical models of spin glass. We analyse the Legendre variational structure linking the free energies of these two systems, in the spirit of the equivalence of ensembles of statistical mechanics. Our analysis, combined with the previous work (Barra et al., J. Phys. A: Math. Theor. 47, 155002, 2014), shows that such models are replica symmetric. Lastly, we briefly discuss an application of our result to the study of the Gaussian Hopfield model

MCEM algorithm for the log-Gaussian Cox process

OpenAIRE

Delmas, Celine; Dubois-Peyrard, Nathalie; Sabbadin, Regis

2014-01-01

Log-Gaussian Cox processes are an important class of models for aggregated point patterns. They have been largely used in spatial epidemiology (Diggle et al., 2005), in agronomy (Bourgeois et al., 2012), in forestry (Moller et al.), in ecology (sightings of wild animals) or in environmental sciences (radioactivity counts). A log-Gaussian Cox process is a Poisson process with a stochastic intensity depending on a Gaussian random eld. We consider the case where this Gaussian random eld is ...

Ocean outfall plume characterization using an Autonomous Underwater Vehicle.

Science.gov (United States)

Rogowski, Peter; Terrill, Eric; Otero, Mark; Hazard, Lisa; Middleton, William

2013-01-01

A monitoring mission to map and characterize the Point Loma Ocean Outfall (PLOO) wastewater plume using an Autonomous Underwater Vehicle (AUV) was performed on 3 March 2011. The mobility of an AUV provides a significant advantage in surveying discharge plumes over traditional cast-based methods, and when combined with optical and oceanographic sensors, provides a capability for both detecting plumes and assessing their mixing in the near and far-fields. Unique to this study is the measurement of Colored Dissolved Organic Matter (CDOM) in the discharge plume and its application for quantitative estimates of the plume's dilution. AUV mission planning methodologies for discharge plume sampling, plume characterization using onboard optical sensors, and comparison of observational data to model results are presented. The results suggest that even under variable oceanic conditions, properly planned missions for AUVs equipped with an optical CDOM sensor in addition to traditional oceanographic sensors, can accurately characterize and track ocean outfall plumes at higher resolutions than cast-based techniques.

Poisson-Gaussian Noise Reduction Using the Hidden Markov Model in Contourlet Domain for Fluorescence Microscopy Images

Science.gov (United States)

Yang, Sejung; Lee, Byung-Uk

2015-01-01

In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138

Overview of NASA GRCs Green Propellant Infusion Mission Thruster Testing and Plume Diagnostics

Science.gov (United States)

Deans, Matthew C.; Reed, Brian D.; Yim, John T.; Arrington, Lynn A.; Williams, George J.; Kojima, Jun J.; McLean, Christopher H.

2014-01-01

The Green Propellant Infusion Mission (GPIM) is sponsored by NASA's Space Technology Mission Directorate (STMD) Technology Demonstration Mission (TDM) office. The goal of GPIM is to advance the technology readiness level of a green propulsion system, specifically, one using the monopropellant, AF-M315E, by demonstrating ground handling, spacecraft processing, and on-orbit operations. One of the risks identified for GPIM is potential contamination of sensitive spacecraft surfaces from the effluents in the plumes of AF-M315E thrusters. NASA Glenn Research Center (GRC) is conducting activities to characterize the effects of AF-M315E plume impingement and deposition. GRC has established individual plume models of the 22-N and 1-N thrusters that will be used on the GPIM spacecraft. The models describe the pressure, temperature, density, Mach number, and species concentration of the AF-M315E thruster exhaust plumes. The models are being used to assess the impingement effects of the AF-M315E thrusters on the GPIM spacecraft. The model simulations will be correlated with plume measurement data from Laboratory and Engineering Model 22-N, AF-M315E thrusters. The thrusters will be tested in a small rocket, altitude facility at NASA GRC. The GRC thruster testing will be conducted at duty cycles representatives of the planned GPIM maneuvers. A suite of laser-based diagnostics, including Raman spectroscopy, Rayleigh spectroscopy, Schlieren imaging, and physical probes will be used to acquire plume measurements of AFM315E thrusters. Plume data will include temperature, velocity, relative density, and species concentration. The plume measurement data will be compared to the corresponding simulations of the plume model. The GRC effort will establish a data set of AF-M315E plume measurements and a plume model that can be used for future AF-M315E applications.

High-Order Local Pooling and Encoding Gaussians Over a Dictionary of Gaussians.

Science.gov (United States)

Li, Peihua; Zeng, Hui; Wang, Qilong; Shiu, Simon C K; Zhang, Lei

2017-07-01

Local pooling (LP) in configuration (feature) space proposed by Boureau et al. explicitly restricts similar features to be aggregated, which can preserve as much discriminative information as possible. At the time it appeared, this method combined with sparse coding achieved competitive classification results with only a small dictionary. However, its performance lags far behind the state-of-the-art results as only the zero-order information is exploited. Inspired by the success of high-order statistical information in existing advanced feature coding or pooling methods, we make an attempt to address the limitation of LP. To this end, we present a novel method called high-order LP (HO-LP) to leverage the information higher than the zero-order one. Our idea is intuitively simple: we compute the first- and second-order statistics per configuration bin and model them as a Gaussian. Accordingly, we employ a collection of Gaussians as visual words to represent the universal probability distribution of features from all classes. Our problem is naturally formulated as encoding Gaussians over a dictionary of Gaussians as visual words. This problem, however, is challenging since the space of Gaussians is not a Euclidean space but forms a Riemannian manifold. We address this challenge by mapping Gaussians into the Euclidean space, which enables us to perform coding with common Euclidean operations rather than complex and often expensive Riemannian operations. Our HO-LP preserves the advantages of the original LP: pooling only similar features and using a small dictionary. Meanwhile, it achieves very promising performance on standard benchmarks, with either conventional, hand-engineered features or deep learning-based features.

Saharan dust plume charging observed over the UK

Science.gov (United States)

Harrison, R. Giles; Nicoll, Keri A.; Marlton, Graeme J.; Ryder, Claire L.; Bennett, Alec J.

2018-05-01

A plume of Saharan dust and Iberian smoke was carried across the southern UK on 16th October 2017, entrained into an Atlantic cyclone which had originated as Hurricane Ophelia. The dust plume aloft was widely noticed as it was sufficiently dense to redden the visual appearance of the sun. Time series of backscatter from ceilometers at Reading and Chilbolton show two plumes: one carried upwards to 2.5 km, and another below 800 m into the boundary layer, with a clear slot between. Steady descent of particles at about 50 cm s‑1 continued throughout the morning, and coarse mode particles reached the surface. Plumes containing dust are frequently observed to be strongly charged, often through frictional effects. This plume passed over atmospheric electric field sensors at Bristol, Chilbolton and Reading. Consistent measurements at these three sites indicated negative plume charge. The lower edge plume charge density was (‑8.0 ± 3.3) nC m‑2, which is several times greater than that typical for stratiform water clouds, implying an active in situ charge generation mechanism such as turbulent triboelectrification. A meteorological radiosonde measuring temperature and humidity was launched into the plume at 1412 UTC, specially instrumented with charge and turbulence sensors. This detected charge in the boundary layer and in the upper plume region, and strong turbulent mixing was observed throughout the atmosphere’s lowest 4 km. The clear slot region, through which particles sedimented, was anomalously dry compared with modelled values, with water clouds forming intermittently in the air beneath. Electrical aspects of dust should be included in numerical models, particularly the charge-related effects on cloud microphysical properties, to accurately represent particle behaviour and transport.

Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives

NARCIS (Netherlands)

Durbin, J.; Koopman, S.J.M.

1998-01-01

The analysis of non-Gaussian time series using state space models is considered from both classical and Bayesian perspectives. The treatment in both cases is based on simulation using importance sampling and antithetic variables; Monte Carlo Markov chain methods are not employed. Non-Gaussian

Tidally induced lateral dispersion of the Storfjorden overflow plume

Directory of Open Access Journals (Sweden)

F. Wobus

2013-10-01

Full Text Available We investigate the flow of brine-enriched shelf water from Storfjorden (Svalbard into Fram Strait and onto the western Svalbard Shelf using a regional set-up of NEMO-SHELF, a 3-D numerical ocean circulation model. The model is set up with realistic bathymetry, atmospheric forcing, open boundary conditions and tides. The model has 3 km horizontal resolution and 50 vertical levels in the sh-coordinate system which is specially designed to resolve bottom boundary layer processes. In a series of modelling experiments we focus on the influence of tides on the propagation of the dense water plume by comparing results from tidal and non-tidal model runs. Comparisons of non-tidal to tidal simulations reveal a hotspot of tidally induced horizontal diffusion leading to the lateral dispersion of the plume at the southernmost headland of Spitsbergen which is in close proximity to the plume path. As a result the lighter fractions in the diluted upper layer of the plume are drawn into the shallow coastal current that carries Storfjorden water onto the western Svalbard Shelf, while the dense bottom layer continues to sink down the slope. This bifurcation of the plume into a diluted shelf branch and a dense downslope branch is enhanced by tidally induced shear dispersion at the headland. Tidal effects at the headland are shown to cause a net reduction in the downslope flux of Storfjorden water into the deep Fram Strait. This finding contrasts previous results from observations of a dense plume on a different shelf without abrupt topography.

3D Numerical Model of Continental Breakup via Plume Lithosphere Interaction Near Cratonic Blocks: Implications for the Tanzanian Craton

Science.gov (United States)

Koptev, A.; Calais, E.; Burov, E. B.; Leroy, S. D.; Gerya, T.

2014-12-01

Although many continental rift basins and their successfully rifted counterparts at passive continental margins are magmatic, some are not. This dichotomy prompted end-member views of the mechanism driving continental rifting, deep-seated and mantle plume-driven for some, owing to shallow lithospheric stretching for others. In that regard, the East African Rift (EAR), the 3000 km-long divergent boundary between the Nubian and Somalian plates, provides a unique setting with the juxtaposition of the eastern, magma-rich, and western, magma-poor, branches on either sides of the 250-km thick Tanzanian craton. Here we implement high-resolution rheologically realistic 3D numerical model of plume-lithosphere interactions in extensional far-field settings to explain this contrasted behaviour in a unified framework starting from simple, symmetrical initial conditions with an isolated mantle plume rising beneath a craton in an east-west tensional far field stress. The upwelling mantle plume is deflected by the cratonic keel and preferentially channelled along one of its sides. This leads to the coeval development of a magma-rich branch above the plume head and a magma-poor one along the opposite side of the craton, the formation of a rotating microplate between the two rift branches, and the feeding of melt to both branches form a single mantle source. The model bears strong similarities with the evolution of the eastern and western branches of the central EAR and the geodetically observed rotation of the Victoria microplate. This result reconciles the passive (plume-activated) versus active (far-field tectonic stresses) rift models as our experiments shows both processes in action and demonstrate the possibility of developing both magmatic and amagmatic rifts in identical geotectonic environments.

Teaching the Mantle Plumes Debate

Science.gov (United States)

Foulger, G. R.

2010-12-01

There is an ongoing debate regarding whether or not mantle plumes exist. This debate has highlighted a number of issues regarding how Earth science is currently practised, and how this feeds into approaches toward teaching students. The plume model is an hypothesis, not a proven fact. And yet many researchers assume a priori that plumes exist. This assumption feeds into teaching. That the plume model is unproven, and that many practising researchers are skeptical, may be at best only mentioned in passing to students, with most teachers assuming that plumes are proven to exist. There is typically little emphasis, in particular in undergraduate teaching, that the origin of melting anomalies is currently uncertain and that scientists do not know all the answers. Little encouragement is given to students to become involved in the debate and to consider the pros and cons for themselves. Typically teachers take the approach that “an answer” (or even “the answer”) must be taught to students. Such a pedagogic approach misses an excellent opportunity to allow students to participate in an important ongoing debate in Earth sciences. It also misses the opportunity to illustrate to students several critical aspects regarding correct application of the scientific method. The scientific method involves attempting to disprove hypotheses, not to prove them. A priori assumptions should be kept uppermost in mind and reconsidered at all stages. Multiple working hypotheses should be entertained. The predictions of a hypothesis should be tested, and unpredicted observations taken as weakening the original hypothesis. Hypotheses should not be endlessly adapted to fit unexpected observations. The difficulty with pedagogic treatment of the mantle plumes debate highlights a general uncertainty about how to teach issues in Earth science that are not yet resolved with certainty. It also represents a missed opportunity to let students experience how scientific theories evolve, warts

Measurements on cooling tower plumes. Pt. 3

International Nuclear Information System (INIS)

Fortak, H.

1975-11-01

In this paper an extended field experiment is described in which cooling tower plumes were investigated by means of three-dimensional in situ measurements. The goal of this program was to obtain input data for numerical models of cooling tower plumes. Data for testing or developing assumptions for sub-grid parametrizations were of special interest. Utilizing modern systems for high-resolution aerology and small aircraft, four measuring campaigns were conducted: two campaigns (1974) at the cooling towers of the RWE power station at Neurath and also two (1975) at the single cooling tower of the RWE power station at Meppen. Because of the broad spectrum of weather situations, it can be assumed that the results are representative with regard to the interrelationship between the structure of cooling tower plumes and the large-scale meteorological situation. A large number of flights with a powered glider ASK 16 (more than 100 flight hours) crossing the plumes on orthogonal tracks was performed. All flights showed that the plume could be identified up to large downwind distances by discontinuous jumps of temperature and vapour pressure. Therefore a definite geometry of the plume could always be defined. In all cross sections a vertical circulation could be observed. At the plumes boundaries, which could be defined by the mentioned jumps of temperature and vapour pressure, a maximum of downward vertical motion was observed in most cases. Entrainment along the boundary of a cross section seems to be very small, except at the lower part of the plume. There, the mass entrainment is maximum and is responsible for plume rise as well as for enlargement of the cross section. The visible part of the plume (cloud) was only a small fraction of the whole plume. The discontinuities of temperature and vapour pressure show that the plume fills the space below the visible plume down to the ground. However, all effects decrease rapidly towards the ground. It turned out that high

Fast uncertainty reduction strategies relying on Gaussian process models

International Nuclear Information System (INIS)

Chevalier, Clement

2013-01-01

This work deals with sequential and batch-sequential evaluation strategies of real-valued functions under limited evaluation budget, using Gaussian process models. Optimal Stepwise Uncertainty Reduction (SUR) strategies are investigated for two different problems, motivated by real test cases in nuclear safety. First we consider the problem of identifying the excursion set above a given threshold T of a real-valued function f. Then we study the question of finding the set of 'safe controlled configurations', i.e. the set of controlled inputs where the function remains below T, whatever the value of some others non-controlled inputs. New SUR strategies are presented, together with efficient procedures and formulas to compute and use them in real world applications. The use of fast formulas to recalculate quickly the posterior mean or covariance function of a Gaussian process (referred to as the 'kriging update formulas') does not only provide substantial computational savings. It is also one of the key tools to derive closed form formulas enabling a practical use of computationally-intensive sampling strategies. A contribution in batch-sequential optimization (with the multi-points Expected Improvement) is also presented. (author)

Accident consequence assessments with different atmospheric dispersion models

International Nuclear Information System (INIS)

Panitz, H.J.

1989-11-01

An essential aim of the improvements of the new program system UFOMOD for Accident Consequence Assessments (ACAs) was to substitute the straight-line Gaussian plume model conventionally used in ACA models by more realistic atmospheric dispersion models. To identify improved models which can be applied in ACA codes and to quantify the implications of different dispersion models on the results of an ACA, probabilistic comparative calculations with different atmospheric dispersion models have been performed. The study showed that there are trajectory models available which can be applied in ACAs and that they provide more realistic results of ACAs than straight-line Gaussian models. This led to a completely novel concept of atmospheric dispersion modelling in which two different distance ranges of validity are distinguished: the near range of some ten kilometres distance and the adjacent far range which are assigned to respective trajectory models. (orig.) [de

Modelling the transport of suspended particulate matter by the Rhone River plume (France). Implications for pollutant dispersion

International Nuclear Information System (INIS)

Perianez, R.

2005-01-01

A model to simulate the transport of suspended particulate matter by the Rhone River plume has been developed. The model solves the 3D hydrodynamic equations, including baroclinic terms and a 1-equation turbulence model, and the suspended matter equations including advection/diffusion of particles, settling and deposition. Four particle classes are considered simultaneously according to observations in the Rhone. Computed currents, salinity and particle distributions are, in general, in good agreement with observations or previous calculations. The model also provides sedimentation rates and the distribution of different particle classes over the sea bed. It has been found that high sedimentation rates close to the river mouth are due to coarse particles that sink rapidly. Computed sedimentation rates are also similar to those derived from observations. The model has been applied to simulate the transport of radionuclides by the plume, since suspended matter is the main vector for them. The radionuclide transport model, previously described and validated, includes exchanges of radionuclides between water, suspended matter and bottom sediment described in terms of kinetic rates. A new feature is the explicit inclusion of the dependence of kinetic rates upon salinity. The model has been applied to 137 Cs and 239,240 Pu. Results are, in general, in good agreement with observations. - A model has been developed to simulate transport of suspended particulate matter in the Rhone River plume

New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model.

Science.gov (United States)

Chen, Zhaoxue; Chen, Hao

2014-01-01

A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

Effect of grid resolution and subgrid assumptions on the model prediction of a reactive buoyant plume under convective conditions

International Nuclear Information System (INIS)

Chock, D.P.; Winkler, S.L.; Pu Sun

2002-01-01

We have introduced a new and elaborate approach to understand the impact of grid resolution and subgrid chemistry assumption on the grid-model prediction of species concentrations for a system with highly non-homogeneous chemistry - a reactive buoyant plume immediately downwind of the stack in a convective boundary layer. The Parcel-Grid approach plume was used to describe both the air parcel turbulent transport and chemistry. This approach allows an identical transport process for all simulations. It also allows a description of subgrid chemistry. The ambient and plume parcel transport follows the description of Luhar and Britter (Atmos. Environ, 23 (1989) 1911, 26A (1992) 1283). The chemistry follows that of the Carbon-Bond mechanism. Three different grid sizes were considered: fine, medium and coarse, together with three different subgrid chemistry assumptions: micro-scale or individual parcel, tagged-parcel (plume and ambient parcels treated separately), and untagged-parcel (plume and ambient parcels treated indiscriminately). Reducing the subgrid information is not necessarily similar to increasing the model grid size. In our example, increasing the grid size leads to a reduction in the suppression of ozone in the presence of a high-NO x stack plume, and a reduction in the effectiveness of the NO x -inhibition effect. On the other hand, reducing the subgrid information (by using the untagged-parcel assumption) leads to an increase in ozone reduction and an enhancement of the NO x -inhibition effect insofar as the ozone extremum is concerned. (author)

Segmenting Continuous Motions with Hidden Semi-markov Models and Gaussian Processes

Directory of Open Access Journals (Sweden)

Tomoaki Nakamura

2017-12-01

Full Text Available Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions. People can divide continuous information into segments without using explicit segment points. This capacity for unsupervised segmentation is also useful for robots, because it enables them to flexibly learn languages, gestures, and actions. In this paper, we propose a Gaussian process-hidden semi-Markov model (GP-HSMM that can divide continuous time series data into segments in an unsupervised manner. Our proposed method consists of a generative model based on the hidden semi-Markov model (HSMM, the emission distributions of which are Gaussian processes (GPs. Continuous time series data is generated by connecting segments generated by the GP. Segmentation can be achieved by using forward filtering-backward sampling to estimate the model's parameters, including the lengths and classes of the segments. In an experiment using the CMU motion capture dataset, we tested GP-HSMM with motion capture data containing simple exercise motions; the results of this experiment showed that the proposed GP-HSMM was comparable with other methods. We also conducted an experiment using karate motion capture data, which is more complex than exercise motion capture data; in this experiment, the segmentation accuracy of GP-HSMM was 0.92, which outperformed other methods.

HGSYSTEM/UF6 model enhancements for plume rise and dispersion around buildings, lift-off of buoyant plumes, and robustness of numerical solver

International Nuclear Information System (INIS)

Hanna, S.R.; Chang, J.C.

1997-01-01

The HGSYSTEM/UF 6 model was developed for use in preparing Safety Analysis Reports (SARs) by estimating the consequences of possible accidental releases of UF 6 to the atmosphere at the gaseous diffusion plants (GDPs) located in Portsmouth, Ohio, and Paducah, Kentucky. Although the latter report carries a 1996 date, the work that is described was completed in late 1994. When that report was written, the primary release scenarios of interest were thought to be gas pipeline and liquid tank ruptures over open terrain away from the influence of buildings. However, upon further analysis of possible release scenarios, the developers of the SARs decided it was necessary to also consider accidental releases within buildings. Consequently, during the fall and winter of 1995-96, modules were added to HGSYSTEM/UF 6 to account for flow and dispersion around buildings. The original HGSYSTEM/UF 6 model also contained a preliminary method for accounting for the possible lift-off of ground-based buoyant plumes. An improved model and a new set of wind tunnel data for buoyant plumes trapped in building recirculation cavities have become available that appear to be useful for revising the lift-off algorithm and modifying it for use in recirculation cavities. This improved lift-off model has been incorporated in the updated modules for dispersion around buildings

Gaussian processes for machine learning.

Science.gov (United States)

Seeger, Matthias

2004-04-01

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.

Evaluation of the influence of double and triple Gaussian proton kernel models on accuracy of dose calculations for spot scanning technique.

Science.gov (United States)

Hirayama, Shusuke; Takayanagi, Taisuke; Fujii, Yusuke; Fujimoto, Rintaro; Fujitaka, Shinichiro; Umezawa, Masumi; Nagamine, Yoshihiko; Hosaka, Masahiro; Yasui, Keisuke; Omachi, Chihiro; Toshito, Toshiyuki

2016-03-01

The main purpose in this study was to present the results of beam modeling and how the authors systematically investigated the influence of double and triple Gaussian proton kernel models on the accuracy of dose calculations for spot scanning technique. The accuracy of calculations was important for treatment planning software (TPS) because the energy, spot position, and absolute dose had to be determined by TPS for the spot scanning technique. The dose distribution was calculated by convolving in-air fluence with the dose kernel. The dose kernel was the in-water 3D dose distribution of an infinitesimal pencil beam and consisted of an integral depth dose (IDD) and a lateral distribution. Accurate modeling of the low-dose region was important for spot scanning technique because the dose distribution was formed by cumulating hundreds or thousands of delivered beams. The authors employed a double Gaussian function as the in-air fluence model of an individual beam. Double and triple Gaussian kernel models were also prepared for comparison. The parameters of the kernel lateral model were derived by fitting a simulated in-water lateral dose profile induced by an infinitesimal proton beam, whose emittance was zero, at various depths using Monte Carlo (MC) simulation. The fitted parameters were interpolated as a function of depth in water and stored as a separate look-up table. These stored parameters for each energy and depth in water were acquired from the look-up table when incorporating them into the TPS. The modeling process for the in-air fluence and IDD was based on the method proposed in the literature. These were derived using MC simulation and measured data. The authors compared the measured and calculated absolute doses at the center of the spread-out Bragg peak (SOBP) under various volumetric irradiation conditions to systematically investigate the influence of the two types of kernel models on the dose calculations. The authors investigated the difference

Sinking, merging and stationary plumes in a coupled chemotaxis-fluid model: a high-resolution numerical approach

KAUST Repository

Chertock, A.

2012-02-02

Aquatic bacteria like Bacillus subtilis are heavier than water yet they are able to swim up an oxygen gradient and concentrate in a layer below the water surface, which will undergo Rayleigh-Taylor-type instabilities for sufficiently high concentrations. In the literature, a simplified chemotaxis-fluid system has been proposed as a model for bio-convection in modestly diluted cell suspensions. It couples a convective chemotaxis system for the oxygen-consuming and oxytactic bacteria with the incompressible Navier-Stokes equations subject to a gravitational force proportional to the relative surplus of the cell density compared to the water density. In this paper, we derive a high-resolution vorticity-based hybrid finite-volume finite-difference scheme, which allows us to investigate the nonlinear dynamics of a two-dimensional chemotaxis-fluid system with boundary conditions matching an experiment of Hillesdon et al. (Bull. Math. Biol., vol. 57, 1995, pp. 299-344). We present selected numerical examples, which illustrate (i) the formation of sinking plumes, (ii) the possible merging of neighbouring plumes and (iii) the convergence towards numerically stable stationary plumes. The examples with stable stationary plumes show how the surface-directed oxytaxis continuously feeds cells into a high-concentration layer near the surface, from where the fluid flow (recurring upwards in the space between the plumes) transports the cells into the plumes, where then gravity makes the cells sink and constitutes the driving force in maintaining the fluid convection and, thus, in shaping the plumes into (numerically) stable stationary states. Our numerical method is fully capable of solving the coupled chemotaxis-fluid system and enabling a full exploration of its dynamics, which cannot be done in a linearised framework. © 2012 Cambridge University Press.

Modelling Inverse Gaussian Data with Censored Response Values: EM versus MCMC

Directory of Open Access Journals (Sweden)

R. S. Sparks

2011-01-01

Full Text Available Low detection limits are common in measure environmental variables. Building models using data containing low or high detection limits without adjusting for the censoring produces biased models. This paper offers approaches to estimate an inverse Gaussian distribution when some of the data used are censored because of low or high detection limits. Adjustments for the censoring can be made if there is between 2% and 20% censoring using either the EM algorithm or MCMC. This paper compares these approaches.

Hybrid 3D model for the interaction of plasma thruster plumes with nearby objects

Science.gov (United States)

Cichocki, Filippo; Domínguez-Vázquez, Adrián; Merino, Mario; Ahedo, Eduardo

2017-12-01

This paper presents a hybrid particle-in-cell (PIC) fluid approach to model the interaction of a plasma plume with a spacecraft and/or any nearby object. Ions and neutrals are modeled with a PIC approach, while electrons are treated as a fluid. After a first iteration of the code, the domain is split into quasineutral and non-neutral regions, based on non-neutrality criteria, such as the relative charge density and the Debye length-to-cell size ratio. At the material boundaries of the former quasineutral region, a dedicated algorithm ensures that the Bohm condition is met. In the latter non-neutral regions, the electron density and electric potential are obtained by solving the coupled electron momentum balance and Poisson equations. Boundary conditions for both the electric current and potential are finally obtained with a plasma sheath sub-code and an equivalent circuit model. The hybrid code is validated by applying it to a typical plasma plume-spacecraft interaction scenario, and the physics and capabilities of the model are finally discussed.

Verification of the pollutant transport model 'MODIS' using EPRI plains site data from a tall stack

Energy Technology Data Exchange (ETDEWEB)

Petersen, G; Eppel, D; Grassl, H

1988-01-01

A comprehensive numerical model for the simulation of pollutant dispersion from a point source into the mixing layer of the atmosphere over flat terrain is described. A moment reduction technique is used (MODIS = Moment Distribution) to combine the simplicity of the Gaussian plume description with the versatility of Eulerian grid formulations. Turbulent dispersion coefficients are parameterized in terms of mean square wind variances which in turn are obtained by a simplified second order closure model. The data base of the 'EPRI Plume Model Validation and Development Project' is used to validate the model for wind velocities above 0.5 m/s and for horizontal scales up to about one hundred kilometers. The model describes the three-dimensional structure of a plume also for stable conditions including a nighttime low level jet. For a convective planetary boundary layer it underestimates maximum ground concentration as do other models. However, it is capable of approaching measured maximum ground concentration under stable conditions.

Loop corrections to primordial non-Gaussianity

Science.gov (United States)

Boran, Sibel; Kahya, E. O.

2018-02-01

We discuss quantum gravitational loop effects to observable quantities such as curvature power spectrum and primordial non-Gaussianity of cosmic microwave background (CMB) radiation. We first review the previously shown case where one gets a time dependence for zeta-zeta correlator due to loop corrections. Then we investigate the effect of loop corrections to primordial non-Gaussianity of CMB. We conclude that, even with a single scalar inflaton, one might get a huge value for non-Gaussianity which would exceed the observed value by at least 30 orders of magnitude. Finally we discuss the consequences of this result for scalar driven inflationary models.

tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models

Directory of Open Access Journals (Sweden)

Robert B. Gramacy

2007-06-01

Full Text Available The tgp package for R is a tool for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model. Special cases also implemented include Bayesian linear models, linear CART, stationary separable and isotropic Gaussian processes. In addition to inference and posterior prediction, the package supports the (sequential design of experiments under these models paired with several objective criteria. 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions (requiring maptree and combinat packages, are also provided for visualization of tgp objects.

Gaussian entanglement revisited

Science.gov (United States)

Lami, Ludovico; Serafini, Alessio; Adesso, Gerardo

2018-02-01

We present a novel approach to the separability problem for Gaussian quantum states of bosonic continuous variable systems. We derive a simplified necessary and sufficient separability criterion for arbitrary Gaussian states of m versus n modes, which relies on convex optimisation over marginal covariance matrices on one subsystem only. We further revisit the currently known results stating the equivalence between separability and positive partial transposition (PPT) for specific classes of Gaussian states. Using techniques based on matrix analysis, such as Schur complements and matrix means, we then provide a unified treatment and compact proofs of all these results. In particular, we recover the PPT-separability equivalence for: (i) Gaussian states of 1 versus n modes; and (ii) isotropic Gaussian states. In passing, we also retrieve (iii) the recently established equivalence between separability of a Gaussian state and and its complete Gaussian extendability. Our techniques are then applied to progress beyond the state of the art. We prove that: (iv) Gaussian states that are invariant under partial transposition are necessarily separable; (v) the PPT criterion is necessary and sufficient for separability for Gaussian states of m versus n modes that are symmetric under the exchange of any two modes belonging to one of the parties; and (vi) Gaussian states which remain PPT under passive optical operations can not be entangled by them either. This is not a foregone conclusion per se (since Gaussian bound entangled states do exist) and settles a question that had been left unanswered in the existing literature on the subject. This paper, enjoyable by both the quantum optics and the matrix analysis communities, overall delivers technical and conceptual advances which are likely to be useful for further applications in continuous variable quantum information theory, beyond the separability problem.

A new conceptual model for whole mantle convection and the origin of hotspot plumes

Science.gov (United States)

Yoshida, Masaki

2014-08-01

A new conceptual model of mantle convection is constructed for consideration of the origin of hotspot plumes, using recent evidence from seismology, high-pressure experiments, geodynamic modeling, geoid inversion studies, and post-glacial rebound analyses. This conceptual model delivers several key points. Firstly, some of the small-scale mantle upwellings observed as hotspots on the Earth's surface originate at the base of the mantle transition zone (MTZ), in which the Archean granitic continental material crust (TTG; tonalite-trondhjemite-granodiorite) with abundant radiogenic elements is accumulated. Secondly, the TTG crust and the subducted oceanic crust that have accumulated at the base of MTZ could act as thermal or mechanical insulators, leading to the formation of a hot and less viscous layer just beneath the MTZ; which may enhance the instability of plume generation at the base of the MTZ. Thirdly, the origin of some hotspot plumes is isolated from the large low shear-wave velocity provinces (LLSVPs) under Africa and the South Pacific. I consider that the conceptual model explains why almost all the hotspots around Africa are located above the margins of the African LLSVP. Because a planetary-scale trench system surrounding a “Pangean cell” has been spatially stable throughout the Phanerozoic, a large amount of the oceanic crustal layer is likely to be trapped in the MTZ under the Pangean cell. Therefore, under Africa, almost all of the hotspot plumes originate from the base of the MTZ, where a large amount of TTG and/or oceanic crusts has accumulated. This conceptual model may explain the fact that almost all the hotspots around Africa are located on margins above the African LLSVP. It is also considered that some of the hotspot plumes under the South Pacific thread through the TTG/oceanic crusts accumulated around the bottom of the MTZ, and some have their roots in the South Pacific LLSVP while others originate from the MTZ. The numerical simulations

A numerical study of the Magellan Plume

Science.gov (United States)

Palma, Elbio D.; Matano, Ricardo P.

2012-05-01

In this modeling study we investigate the dynamical mechanisms controlling the spreading of the Magellan Plume, which is a low-salinity tongue that extends along the Patagonian Shelf. Our results indicate that the overall characteristics of the plume (width, depth, spreading rate, etc.) are primarily influenced by tidal forcing, which manifests through tidal mixing and tidal residual currents. Tidal forcing produces a homogenization of the plume's waters and an offshore displacement of its salinity front. The interaction between tidal and wind-forcing reinforces the downstream and upstream buoyancy transports of the plume. The influence of the Malvinas Current on the Magellan Plume is more dominant north of 50°S, where it increases the along-shelf velocities and generates intrusions of saltier waters from the outer shelf, thus causing a reduction of the downstream buoyancy transport. Our experiments also indicate that the northern limit of the Magellan Plume is set by a high salinity discharge from the San Matias Gulf. Sensitivity experiments show that increments of the wind stress cause a decrease of the downstream buoyancy transport and an increase of the upstream buoyancy transport. Variations of the magnitude of the discharge produce substantial modifications in the downstream penetration of the plume and buoyancy transport. The Magellan discharge generates a northeastward current in the middle shelf, a recirculation gyre south of the inlet and a region of weak currents father north.

Airborne Detection and Dynamic Modeling of Carbon Dioxide and Methane Plumes

Science.gov (United States)

Jacob, Jamey; Mitchell, Taylor; Whyte, Seabrook

2015-11-01

To facilitate safe storage of greenhouse gases such as CO2 and CH4, airborne monitoring is investigated. Conventional soil gas monitoring has difficulty in distinguishing gas flux signals from leakage with those associated with meteorologically driven changes. A low-cost, lightweight sensor system has been developed and implemented onboard a small unmanned aircraft that measures gas concentration and is combined with other atmospheric diagnostics, including thermodynamic data and velocity from hot-wire and multi-hole probes. To characterize the system behavior and verify its effectiveness, field tests have been conducted over controlled rangeland burns and over simulated leaks. In the former case, since fire produces carbon dioxide over a large area, this was an opportunity to test in an environment that while only vaguely similar to a carbon sequestration leak source, also exhibits interesting plume behavior. In the simulated field tests, compressed gas tanks are used to mimic leaks and generate gaseous plumes. Since the sensor response time is a function of vehicle airspeed, dynamic calibration models are required to determine accurate location of gas concentration in (x , y , z , t) . Results are compared with simulations using combined flight and atmospheric dynamic models. Supported by Department of Energy Award DE-FE0012173.

Efficient Blind System Identification of Non-Gaussian Auto-Regressive Models with HMM Modeling of the Excitation

DEFF Research Database (Denmark)

Li, Chunjian; Andersen, Søren Vang

2007-01-01

We propose two blind system identification methods that exploit the underlying dynamics of non-Gaussian signals. The two signal models to be identified are: an Auto-Regressive (AR) model driven by a discrete-state Hidden Markov process, and the same model whose output is perturbed by white Gaussi...... outputs. The signal models are general and suitable to numerous important signals, such as speech signals and base-band communication signals. Applications to speech analysis and blind channel equalization are given to exemplify the efficiency of the new methods....

Field experimental observations of highly graded sediment plumes

DEFF Research Database (Denmark)

Hjelmager Jensen, Jacob; Saremi, Sina; Jimenez, Carlos

2015-01-01

A field experiment in the waters off the south-eastern coast of Cyprus was carried out to study near-field formation of sediment plumes from dumping. Different loads of sediment were poured into calm and limpid waters one at the time from just above the sea surface. The associated plumes......-bed positions gives unique insight into the dynamics of the descending plume and near-field dispersion processes, and enables good understanding of flow and sediment transport processes involved from-release-to-deposition of the load in a non-scaled environment. The high resolution images and footages...... are available through the link provided herein. Observations support the development of a detailed multi-fractional sediment plume model....

Gaussian measures of entanglement versus negativities: Ordering of two-mode Gaussian states

International Nuclear Information System (INIS)

Adesso, Gerardo; Illuminati, Fabrizio

2005-01-01

We study the entanglement of general (pure or mixed) two-mode Gaussian states of continuous-variable systems by comparing the two available classes of computable measures of entanglement: entropy-inspired Gaussian convex-roof measures and positive partial transposition-inspired measures (negativity and logarithmic negativity). We first review the formalism of Gaussian measures of entanglement, adopting the framework introduced in M. M. Wolf et al., Phys. Rev. A 69, 052320 (2004), where the Gaussian entanglement of formation was defined. We compute explicitly Gaussian measures of entanglement for two important families of nonsymmetric two-mode Gaussian state: namely, the states of extremal (maximal and minimal) negativities at fixed global and local purities, introduced in G. Adesso et al., Phys. Rev. Lett. 92, 087901 (2004). This analysis allows us to compare the different orderings induced on the set of entangled two-mode Gaussian states by the negativities and by the Gaussian measures of entanglement. We find that in a certain range of values of the global and local purities (characterizing the covariance matrix of the corresponding extremal states), states of minimum negativity can have more Gaussian entanglement of formation than states of maximum negativity. Consequently, Gaussian measures and negativities are definitely inequivalent measures of entanglement on nonsymmetric two-mode Gaussian states, even when restricted to a class of extremal states. On the other hand, the two families of entanglement measures are completely equivalent on symmetric states, for which the Gaussian entanglement of formation coincides with the true entanglement of formation. Finally, we show that the inequivalence between the two families of continuous-variable entanglement measures is somehow limited. Namely, we rigorously prove that, at fixed negativities, the Gaussian measures of entanglement are bounded from below. Moreover, we provide some strong evidence suggesting that they

Using MOPITT data and a Chemistry and Transport Model to Investigate Injection Height of Plumes from Boreal Forest Fires

Science.gov (United States)

Hyer, E. J.; Allen, D. J.; Kasischke, E. S.; Warner, J. X.

2003-12-01

Trace gas emissions from boreal forest fires are a significant factor in atmospheric composition and its interannual variability. A number of recent observations of emissions plumes above individual fire events (Fromm and Servranckx, 2003; COBRA 2003; Lamarque et al., 2003; Wotawa and Trainer, 2000) suggest that vertical properties of forest fire emission plumes can be very different from fossil fuel emission plumes. Understanding and constraining the vertical properties of forest fire emission plumes and their injection into the atmosphere during fire events is critical for accurate modeling of atmospheric transport and chemistry. While excellent data have been collected in a handful of experiments on individual fire events, a systematic examination of the range of behavior observed in fire events has been hampered by the scarcity of vertical profiles of atmospheric composition. In this study, we used a high-resolution model of boreal forest fire emissions (Kasischke et al, in review) as input to the Goddard/UM CTM driven by the GEOS-3 DAS, operating at 2 by 2.5 degrees with 35 vertical levels. We modeled atmospheric injection and transport of CO emissions during the fire season of 2000 (May-September). We altered the parameters of the model to simulate a range of scenarios of plume injection, and compared the resulting output to the CO profiles from the MOPITT instrument. The results presented here pertain to the boreal forest, but our methods should be useful for atmospheric modelers hoping to more realistically model transport of emission plumes from biomass burning. References: COBRA2003: see http://www.fas.harvard.edu/~cobra/smoke_canada_030530.pdf Fromm, M. and R. Servranckx, 2003. "Stratospheric Injection of Forest Fire Emissions on August 4, 1998: A Satellite Image Analysis of the Causal Supercell Convection." Geophysical Research Abstracts 5:13118. Kasischke, E.S.; E.J. Hyer, N.H.F. French, A.I. Sukhinin, J.H. Hewson, B.J. Stocks, in review. "Carbon

An integrated numerical model for the prediction of Gaussian and billet shapes

DEFF Research Database (Denmark)

Hattel, Jesper; Pryds, Nini; Pedersen, Trine Bjerre

2004-01-01

Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained...... by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency...

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

Science.gov (United States)

Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric

2017-12-01

This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.

Phase statistics in non-Gaussian scattering

International Nuclear Information System (INIS)

Watson, Stephen M; Jakeman, Eric; Ridley, Kevin D

2006-01-01

Amplitude weighting can improve the accuracy of frequency measurements in signals corrupted by multiplicative speckle noise. When the speckle field constitutes a circular complex Gaussian process, the optimal function of amplitude weighting is provided by the field intensity, corresponding to the intensity-weighted phase derivative statistic. In this paper, we investigate the phase derivative and intensity-weighted phase derivative returned from a two-dimensional random walk, which constitutes a generic scattering model capable of producing both Gaussian and non-Gaussian fluctuations. Analytical results are developed for the correlation properties of the intensity-weighted phase derivative, as well as limiting probability densities of the scattered field. Numerical simulation is used to generate further probability densities and determine optimal weighting criteria from non-Gaussian fields. The results are relevant to frequency retrieval in radiation scattered from random media

Bounded Gaussian process regression

DEFF Research Database (Denmark)

Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

2013-01-01

We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....

Scale dependence of the halo bias in general local-type non-Gaussian models I: analytical predictions and consistency relations

International Nuclear Information System (INIS)

Nishimichi, Takahiro

2012-01-01

The large-scale clustering pattern of biased tracers is known to be a powerful probe of the non-Gaussianities in the primordial fluctuations. The so-called scale-dependent bias has been reported in various type of models of primordial non-Gaussianities. We focus on local-type non-Gaussianities, and unify the derivations in the literature of the scale-dependent bias in the presence of multiple Gaussian source fields as well as higher-order coupling to cover the models described by frequently-discussed f NL , g NL and t NL parameterization. We find that the resultant power spectrum is characterized by two parameters responsible for the shape and the amplitude of the scale-dependent bias in addition to the Gaussian bias factor. We show how (a generalized version of) Suyama-Yamaguchi inequality between f NL and t NL can directly be accessible from the observed power spectrum through the dependence on our new parameter which controls the shape of the scale-dependent bias. The other parameter for the amplitude of the scale-dependent bias is shown to be useful to distinguish the simplest quadratic non-Gaussianities (i.e., f NL -type) from higher-order ones (g NL and higher), if one measures it from multiple species of galaxies or clusters of galaxies. We discuss the validity and limitations of our analytic results by comparison with numerical simulations in an accompanying paper

Hydrogeological modeling constraints provided by geophysical and geochemical mapping of a chlorinated ethenes plume in northern France

Science.gov (United States)

Razafindratsima, Stephen; Guérin, Roger; Bendjoudi, Hocine; de Marsily, Ghislain

2014-09-01

A methodological approach is described which combines geophysical and geochemical data to delineate the extent of a chlorinated ethenes plume in northern France; the methodology was used to calibrate a hydrogeological model of the contaminants' migration and degradation. The existence of strong reducing conditions in some parts of the aquifer is first determined by measuring in situ the redox potential and dissolved oxygen, dissolved ferrous iron and chloride concentrations. Electrical resistivity imaging and electromagnetic mapping, using the Slingram method, are then used to determine the shape of the pollutant plume. A decreasing empirical exponential relation between measured chloride concentrations in the water and aquifer electrical resistivity is observed; the resistivity formation factor calculated at a few points also shows a major contribution of chloride concentration in the resistivity of the saturated porous medium. MODFLOW software and MT3D99 first-order parent-daughter chain reaction and the RT3D aerobic-anaerobic model for tetrachloroethene (PCE)/trichloroethene (TCE) dechlorination are finally used for a first attempt at modeling the degradation of the chlorinated ethenes. After calibration, the distribution of the chlorinated ethenes and their degradation products simulated with the model approximately reflects the mean measured values in the observation wells, confirming the data-derived image of the plume.

Improving the modelling of redshift-space distortions - I. A bivariate Gaussian description for the galaxy pairwise velocity distributions

Science.gov (United States)

Bianchi, Davide; Chiesa, Matteo; Guzzo, Luigi

2015-01-01

As a step towards a more accurate modelling of redshift-space distortions (RSD) in galaxy surveys, we develop a general description of the probability distribution function of galaxy pairwise velocities within the framework of the so-called streaming model. For a given galaxy separation r, such function can be described as a superposition of virtually infinite local distributions. We characterize these in terms of their moments and then consider the specific case in which they are Gaussian functions, each with its own mean μ and dispersion σ. Based on physical considerations, we make the further crucial assumption that these two parameters are in turn distributed according to a bivariate Gaussian, with its own mean and covariance matrix. Tests using numerical simulations explicitly show that with this compact description one can correctly model redshift-space distortions on all scales, fully capturing the overall linear and non-linear dynamics of the galaxy flow at different separations. In particular, we naturally obtain Gaussian/exponential, skewed/unskewed distribution functions, depending on separation as observed in simulations and data. Also, the recently proposed single-Gaussian description of RSD is included in this model as a limiting case, when the bivariate Gaussian is collapsed to a two-dimensional Dirac delta function. We also show how this description naturally allows for the Taylor expansion of 1 + ξS(s) around 1 + ξR(r), which leads to the Kaiser linear formula when truncated to second order, explicating its connection with the moments of the velocity distribution functions. More work is needed, but these results indicate a very promising path to make definitive progress in our programme to improve RSD estimators.

N Reactor thermal plume characterization during Pu-only mode of operation

Energy Technology Data Exchange (ETDEWEB)

Ecker, R.M.; Thompson, F.L.; Whelan, G.

1983-04-01

Pacific Northwest Laboratories (PNL) performed field and modeling studies -from March 1982 through June 1983 to characterize the thermal plume from the N Reactor heated water outfall while the N Reactor operated in the Pu-only mode. Part 1 of this report deals with the field studies conducted to characterize the N Reactor thermal plume while in the Pu-only mode of operation. It includes a description of the study area, a description of field tasks and procedures, and data collection results and discussion. Part 2 describes the computer simulation of the thermal plume under different flow conditions and the calibration of the model used. It includes a description of the computer model and the assumptions on which it is based, a presentation of the input data used in this application, and a discussion of modeling results. Because the field studies were restricted by the NPOES permit variance to the spring months when high Columbia River flows prevail the mathematical modeling of the N Reactor thermal plume while the reactor operates in the Pu-only mode is instrumental in characterizing the plume during low Columbia River flows.

Simulation of plume rise: Study the effect of stably stratified turbulence layer on the rise of a buoyant plume from a continuous source by observing the plume centroid

Science.gov (United States)

Bhimireddy, Sudheer Reddy; Bhaganagar, Kiran

2016-11-01

Buoyant plumes are common in atmosphere when there exists a difference in temperature or density between the source and its ambience. In a stratified environment, plume rise happens until the buoyancy variation exists between the plume and ambience. In a calm no wind ambience, this plume rise is purely vertical and the entrainment happens because of the relative motion of the plume with ambience and also ambient turbulence. In this study, a plume centroid is defined as the plume mass center and is calculated from the kinematic equation which relates the rate of change of centroids position to the plume rise velocity. Parameters needed to describe the plume are considered as the plume radius, plumes vertical velocity and local buoyancy of the plume. The plume rise velocity is calculated by the mass, momentum and heat conservation equations in their differential form. Our study focuses on the entrainment velocity, as it depicts the extent of plume growth. This entrainment velocity is made up as sum of fractions of plume's relative velocity and ambient turbulence. From the results, we studied the effect of turbulence on the plume growth by observing the variation in the plume radius at different heights and the centroid height reached before loosing its buoyancy.

Fire analog: a comparison between fire plumes and energy center cooling tower plumes

Energy Technology Data Exchange (ETDEWEB)

Orgill, M.M.

1977-10-01

Thermal plumes or convection columns associated with large fires are compared to thermal plumes from cooling towers and proposed energy centers to evaluate the fire analog concept. Energy release rates of mass fires are generally larger than for single or small groups of cooling towers but are comparable to proposed large energy centers. However, significant physical differences exist between cooling tower plumes and fire plumes. Cooling tower plumes are generally dominated by ambient wind, stability and turbulence conditions. Fire plumes, depending on burning rates and other factors, can transform into convective columns which may cause the fire behavior to become more violent. This transformation can cause strong inflow winds and updrafts, turbulence and concentrated vortices. Intense convective columns may interact with ambient winds to create significant downwind effects such as wakes and Karman vortex streets. These characteristics have not been observed with cooling tower plumes to date. The differences in physical characteristics between cooling tower and fire plumes makes the fire analog concept very questionable even though the approximate energy requirements appear to be satisfied in case of large energy centers. Additional research is suggested in studying the upper-level plume characteristics of small experimental fires so this information can be correlated with similar data from cooling towers. Numerical simulation of fires and proposed multiple cooling tower systems could also provide comparative data.

Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder

DEFF Research Database (Denmark)

Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David

2015-01-01

recommend using the Laplace approximation combined with automatic differentiation (as implemented in the novel R package Template Model Builder; TMB) for the fast fitting of continuous-time multivariate non-Gaussian SSMs. Through Argos satellite tracking data, we demonstrate that the use of continuous...... are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational time. The model implementation is made available through the R package argosTrack....

Export of reactive nitrogen from coal-fired power plants in the U.S.: Estimates from a plume-in-grid modeling study - article no. D04308

Energy Technology Data Exchange (ETDEWEB)

Vijayaraghavan, K.; Zhang, Y.; Seigneur, C.; Karamchandani, P.; Snell, H.E.

2009-02-15

The export of reactive nitrogen (nitrogen oxides and their oxidation products, collectively referred to as NOy) from coal-fired power plants in the U.S. to the rest of the world could have a significant global contribution to ozone. Traditional Eulerian gridded air quality models cannot characterize accurately the chemistry and transport of plumes from elevated point sources such as power plant stacks. A state-of-the-science plume-in-grid (PinG) air quality model, a reactive plume model embedded in an Eulerian gridded model, is used to estimate the export of NOy from 25 large coal-fired power plants in the U. S. (in terms of NOx and SO{sub 2} emissions) in July 2001 to the global atmosphere. The PinG model used is the Community Multiscale Air Quality Model with Advanced Plume Treatment (CMAQ-APT). A benchmark simulation with only the gridded model, CMAQ, is also conducted for comparison purposes. The simulations with and without advanced plume treatment show differences in the calculated export of NOy from the 25 plants considered reflecting the effect of using a detailed and explicit treatment of plume transport and chemistry. The advanced plume treatment results in 31% greater simulated export of NOy compared to the purely grid-based modeling approach. The export efficiency of NOy (the fraction of NOy emitted that is exported) is predicted to be 21% without APT and 27% with APT. When considering only export through the eastern boundary across the Atlantic, CMAQ-APT predicts that the export efficiency is 24% and that 2% of NOy is exported as NOx, 49% as inorganic nitrate, and 25% as PAN. These results are in reasonably good agreement with an analysis reported in the literature of aircraft measurements over the North Atlantic.

On the relative motions of long-lived Pacific mantle plumes.

Science.gov (United States)

Konrad, Kevin; Koppers, Anthony A P; Steinberger, Bernhard; Finlayson, Valerie A; Konter, Jasper G; Jackson, Matthew G

2018-02-27

Mantle plumes upwelling beneath moving tectonic plates generate age-progressive chains of volcanos (hotspot chains) used to reconstruct plate motion. However, these hotspots appear to move relative to each other, implying that plumes are not laterally fixed. The lack of age constraints on long-lived, coeval hotspot chains hinders attempts to reconstruct plate motion and quantify relative plume motions. Here we provide 40 Ar/ 39 Ar ages for a newly identified long-lived mantle plume, which formed the Rurutu hotspot chain. By comparing the inter-hotspot distances between three Pacific hotspots, we show that Hawaii is unique in its strong, rapid southward motion from 60 to 50 Myrs ago, consistent with paleomagnetic observations. Conversely, the Rurutu and Louisville chains show little motion. Current geodynamic plume motion models can reproduce the first-order motions for these plumes, but only when each plume is rooted in the lowermost mantle.

The effect of sediments on turbulent plume dynamics in a stratified fluid

Science.gov (United States)

Stenberg, Erik; Ezhova, Ekaterina; Brandt, Luca

2017-11-01

We report large eddy simulation results of sediment-loaded turbulent plumes in a stratified fluid. The configuration, where the plume is discharged from a round source, provides an idealized model of subglacial discharge from a submarine tidewater glacier and is a starting point for understanding the effect of sediments on the dynamics of the rising plume. The transport of sediments is modeled by means of an advection-diffusion equation where sediment settling velocity is taken into account. We initially follow the experimental setup of Sutherland (Phys. Rev. Fluids, 2016), considering uniformly stratified ambients and further extend the work to pycnocline-type stratifications typical of Greenland fjords. Apart from examining the rise height, radial spread and intrusion of the rising plume, we gain further insights of the plume dynamics by extracting turbulent characteristics and the distribution of the sediments inside the plume.

Active space of pheromone plume and its relationship to effective attraction radius in applied models.

Science.gov (United States)

Byers, John A

2008-09-01

The release rate of a semiochemical lure that attracts flying insects has a specific effective attraction radius (EAR) that corresponds to the lure's orientation response strength. EAR is defined as the radius of a passive sphere that intercepts the same number of insects as a semiochemical-baited trap. It is estimated by calculating the ratio of trap catches in the field in baited and unbaited traps and the interception area of the unbaited trap. EAR serves as a standardized method for comparing the attractive strengths of lures that is independent of population density. In two-dimensional encounter rate models that are used to describe insect mass trapping and mating disruption, a circular EAR (EAR(c)) describes a key parameter that affects catch or influence by pheromone in the models. However, the spherical EAR, as measured in the field, should be transformed to an EAR(c) for appropriate predictions in such models. The EAR(c) is calculated as (pi/2EAR(2))/F (L), where F (L) is the effective thickness of the flight layer where the insect searches. F (L) was estimated from catches of insects (42 species in the orders Coleoptera, Lepidoptera, Diptera, Hemiptera, and Thysanoptera) on traps at various heights as reported in the literature. The EAR(c) was proposed further as a simple but equivalent alternative to simulations of highly complex active-space plumes with variable response surfaces that have proven exceedingly difficult to quantify in nature. This hypothesis was explored in simulations where flying insects, represented as coordinate points, moved about in a correlated random walk in an area that contained a pheromone plume, represented as a sector of active space composed of a capture probability surface of variable complexity. In this plume model, catch was monitored at a constant density of flying insects and then compared to simulations in which a circular EAR(c) was enlarged until an equivalent rate was caught. This demonstrated that there is a

Radiative modeling and characterization of aerosol plumes hyper-spectral imagery; Modelisation radiative et caracterisation des panaches d'aerosols en imagerie hyperspectrale

Energy Technology Data Exchange (ETDEWEB)

Alakian, A

2008-03-15

This thesis aims at characterizing aerosols from plumes (biomass burning, industrial discharges, etc.) with hyper-spectral imagery. We want to estimate the optical properties of emitted particles and also their micro-physical properties such as number, size distribution and composition. To reach our goal, we have built a forward semi-analytical model, named APOM (Aerosol Plume Optical Model), which allows to simulate the radiative effects of aerosol plumes in the spectral range [0,4-2,5 {mu}m] for nadir viewing sensors. Mathematical formulation and model coefficients are obtained from simulations performed with the radiative transfer code COMANCHE. APOM is assessed on simulated data and proves to be accurate with modeling errors between 1% and 3%. Three retrieval methods using APOM have been developed: L-APOM, M-APOM and A-APOM. These methods take advantage of spectral and spatial dimensions in hyper-spectral images. L-APOM and M-APOM assume a priori knowledge on particles but can estimate their optical and micro-physical properties. Their performances on simulated data are quite promising. A-APOM method does not require any a priori knowledge on particles but only estimates their optical properties. However, it still needs improvements before being usable. On real images, inversion provides satisfactory results for plumes above water but meets some difficulties for plumes above vegetation, which underlines some possibilities of improvement for the retrieval algorithm. (author)

Study of asymmetry in motor areas related to handedness using the fMRI BOLD response Gaussian convolution model

Energy Technology Data Exchange (ETDEWEB)

Gao Qing [School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054 (China); School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054 (China); Chen Huafu [School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054 (China); School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054 (China)], E-mail: Chenhf@uestc.edu.cn; Gong Qiyong [Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041 (China)

2009-10-30

Brain asymmetry is a phenomenon well known for handedness, and has been studied in the motor cortex. However, few studies have quantitatively assessed the asymmetrical cortical activities for handedness in motor areas. In the present study, we systematically and quantitatively investigated asymmetry in the left and right primary motor cortices during sequential finger movements using the Gaussian convolution model approach based on the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) response. Six right-handed and six left-handed subjects were recruited to perform three types of hand movement tasks. The results for the expected value of the Gaussian convolution model showed that it took the dominant hand a longer average interval of response delay regardless of the handedness and bi- or uni-manual performance. The results for the standard deviation of the Gaussian model suggested that in the mass neurons, these intervals of the dominant hand were much more variable than those of the non-dominant hand. When comparing bi-manual movement conditions with uni-manual movement conditions in the primary motor cortex (PMC), both the expected value and standard deviation in the Gaussian function were significantly smaller (p < 0.05) in the bi-manual conditions, showing that the movement of the non-dominant hand influenced that of the dominant hand.

Study of asymmetry in motor areas related to handedness using the fMRI BOLD response Gaussian convolution model

International Nuclear Information System (INIS)

Gao Qing; Chen Huafu; Gong Qiyong

2009-01-01

Brain asymmetry is a phenomenon well known for handedness, and has been studied in the motor cortex. However, few studies have quantitatively assessed the asymmetrical cortical activities for handedness in motor areas. In the present study, we systematically and quantitatively investigated asymmetry in the left and right primary motor cortices during sequential finger movements using the Gaussian convolution model approach based on the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) response. Six right-handed and six left-handed subjects were recruited to perform three types of hand movement tasks. The results for the expected value of the Gaussian convolution model showed that it took the dominant hand a longer average interval of response delay regardless of the handedness and bi- or uni-manual performance. The results for the standard deviation of the Gaussian model suggested that in the mass neurons, these intervals of the dominant hand were much more variable than those of the non-dominant hand. When comparing bi-manual movement conditions with uni-manual movement conditions in the primary motor cortex (PMC), both the expected value and standard deviation in the Gaussian function were significantly smaller (p < 0.05) in the bi-manual conditions, showing that the movement of the non-dominant hand influenced that of the dominant hand.

Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

Science.gov (United States)

Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

2017-11-01

Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

Nannofossils in 2011 El Hierro eruptive products reinstate plume model for Canary Islands

Science.gov (United States)

Zaczek, Kirsten; Troll, Valentin R.; Cachao, Mario; Ferreira, Jorge; Deegan, Frances M.; Carracedo, Juan Carlos; Soler, Vicente; Meade, Fiona C.; Burchardt, Steffi

2015-01-01

The origin and life cycle of ocean islands have been debated since the early days of Geology. In the case of the Canary archipelago, its proximity to the Atlas orogen led to initial fracture-controlled models for island genesis, while later workers cited a Miocene-Quaternary east-west age-progression to support an underlying mantle-plume. The recent discovery of submarine Cretaceous volcanic rocks near the westernmost island of El Hierro now questions this systematic age-progression within the archipelago. If a mantle-plume is indeed responsible for the Canaries, the onshore volcanic age-progression should be complemented by progressively younger pre-island sedimentary strata towards the west, however, direct age constraints for the westernmost pre-island sediments are lacking. Here we report on new age data obtained from calcareous nannofossils in sedimentary xenoliths erupted during the 2011 El Hierro events, which date the sub-island sedimentary rocks to between late Cretaceous and Pliocene in age. This age-range includes substantially younger pre-volcanic sedimentary rocks than the Jurassic to Miocene strata known from the older eastern islands and now reinstate the mantle-plume hypothesis as the most plausible explanation for Canary volcanism. The recently discovered Cretaceous submarine volcanic rocks in the region are, in turn, part of an older, fracture-related tectonic episode.

Sinking, merging and stationary plumes in a coupled chemotaxis-fluid model: a high-resolution numerical approach

KAUST Repository

Chertock, A.; Fellner, K.; Kurganov, A.; Lorz, A.; Markowich, P. A.

2012-01-01

examples, which illustrate (i) the formation of sinking plumes, (ii) the possible merging of neighbouring plumes and (iii) the convergence towards numerically stable stationary plumes. The examples with stable stationary plumes show how the surface

Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

FOOTPRINT: A Screening Model for Estimating the Area of a Plume Produced From Gasoline Containing Ethanol

Science.gov (United States)

FOOTPRINT is a screening model used to estimate the length and surface area of benzene, toluene, ethylbenzene, and xylene (BTEX) plumes in groundwater, produced from a gasoline spill that contains ethanol.

Plume structure in high-Rayleigh-number convection

Science.gov (United States)

Puthenveettil, Baburaj A.; Arakeri, Jaywant H.

2005-10-01

Near-wall structures in turbulent natural convection at Rayleigh numbers of 10^{10} to 10^{11} at A Schmidt number of 602 are visualized by a new method of driving the convection across a fine membrane using concentration differences of sodium chloride. The visualizations show the near-wall flow to consist of sheet plumes. A wide variety of large-scale flow cells, scaling with the cross-section dimension, are observed. Multiple large-scale flow cells are seen at aspect ratio (AR)= 0.65, while only a single circulation cell is detected at AR= 0.435. The cells (or the mean wind) are driven by plumes coming together to form columns of rising lighter fluid. The wind in turn aligns the sheet plumes along the direction of shear. the mean wind direction is seen to change with time. The near-wall dynamics show plumes initiated at points, which elongate to form sheets and then merge. Increase in rayleigh number results in a larger number of closely and regularly spaced plumes. The plume spacings show a common log normal probability distribution function, independent of the rayleigh number and the aspect ratio. We propose that the near-wall structure is made of laminar natural-convection boundary layers, which become unstable to give rise to sheet plumes, and show that the predictions of a model constructed on this hypothesis match the experiments. Based on these findings, we conclude that in the presence of a mean wind, the local near-wall boundary layers associated with each sheet plume in high-rayleigh-number turbulent natural convection are likely to be laminar mixed convection type.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

Science.gov (United States)

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

Directory of Open Access Journals (Sweden)

Fernando A. Auat Cheein

2013-01-01

Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

The evolution of photochemical smog in a power plant plume

Science.gov (United States)

Luria, Menachem; Valente, Ralph J.; Tanner, Roger L.; Gillani, Noor V.; Imhoff, Robert E.; Mueller, Stephen F.; Olszyna, Kenneth J.; Meagher, James F. Present address: Aeronomy Laboratory, NOAA, 325 Broadway, Boulder CO 80303, USA.)

The evolution of photochemical smog in a plant plume was investigated with the aid of an instrumented helicopter. Air samples were taken in the plume of the Cumberland Power Plant, located in central Tennessee, during the afternoon of 16 July 1995 as part of the Southern Oxidants Study - Nashville Middle Tennessee Ozone Study. Twelve cross-wind air sampling traverses were made at six distance groups from 35 to 116 km from the source. During the sampling period the winds were from the west-northwest and the plume drifted towards the city of Nashville TN. Ten of the traverses were made upwind of the city, where the power plant plume was isolated, and two traverses downwind of the city when the plumes were possibly mixed. The results revealed that even six hours after the release, excess ozone production was limited to the edges of the plume. Only when the plume was sufficiently dispersed, but still upwind of Nashville, was excess ozone (up to 109 ppbv, 50-60 ppbv above background levels) produced in the center of the plume. The concentrations image of the plume and a Lagrangian particle model suggests that portions of the power plant plume mixed with the urban plume. The mixed urban power plant plume began to regenerate O 3 that peaked at 120 ppbv at a short distance (15-25 km) downwind of Nashville. Ozone productivity (the ratio of excess O 3 to NO y and NO z) in the isolated plume was significantly lower compared with that found in the city plume. The production of nitrate, a chain termination product, was significantly higher in the power plant plume compared to the mixed plume, indicating shorter chain length of the photochemical smog chain reaction mechanism.

The evolution of photochemical smog in a power plant plume

International Nuclear Information System (INIS)

Luria, M.; The Hebrew University, Jerusalem; Valente, R.J.; Tanner, R.L.; Imhoff, R.E.; Mueller, S.F.; Olszyna, K.J.; Meagher, J.F.; Gillani, N.V.; University of Alabama, Huntsville, AL

1999-01-01

The evolution of photochemical smog in a plant plume was investigated with the aid of an instrumented helicopter. Air samples were taken in the plume of the Cumberland Power Plant, located in central Tennessee, during the afternoon of 16 July 1995 as part of the Southern Oxidants Study - Nashville Middle Tennessee Ozone Study. Twelve cross-wind air sampling traverses were made at six distance groups from 35 to 116 km from the source. During the sampling period the winds were from the west-northwest and the plume drifted towards the city of Nashville TN. Ten of the traverses were made upwind of the city, where the power plant plume was isolated, and two traverses downwind of the city when the plumes were possibly mixed. The results revealed that even six hours after the release, excess ozone production was limited to the edges of the plume. Only when the plume was sufficiently dispersed, but still upwind of Nashville, was excess ozone (up to 109 ppbv, 50-60 ppbv above background levels) produced in the center of the plume. The concentrations image of the plume and a Lagrangian particle model suggests that portions of the power plant plume mixed with the urban plume. The mixed urban power plant plume began to regenerate O 3 that peaked at 120 ppbv at a short distance (15-25 km) downwind of Nashville. Ozone productivity (the ratio of excess O 3 to NO y and NO z ) in the isolated plume was significantly lower compared with that found in the city plume. The production of nitrate, a chain termination product, was significantly higher in the power plant plume compared to the mixed plume, indicating shorter chain length of the photochemical smog chain reaction mechanism. (author)

Analysis of dissolved benzene plumes and methyl tertiary butyl ether (MTBE) plumes in ground water at leaking underground fuel tank (LUFT) sites

International Nuclear Information System (INIS)

Happel, A.M.; Rice, D.; Beckenbach, E.; Savalin, L.; Temko, H.; Rempel, R.; Dooher, B.

1996-11-01

The 1990 Clean Air Act Amendments mandate the addition of oxygenates to gasoline products to abate air pollution. Currently, many areas of the country utilize oxygenated or reformulated fuel containing 15- percent and I I-percent MTBE by volume, respectively. This increased use of MTBE in gasoline products has resulted in accidental point source releases of MTBE containing gasoline products to ground water. Recent studies have shown MTBE to be frequently detected in samples of shallow ground water from urban areas throughout the United States (Squillace et al., 1995). Knowledge of the subsurface fate and transport of MTBE in ground water at leaking underground fuel tank (LUFT) sites and the spatial extent of MTBE plumes is needed to address these releases. The goal of this research is to utilize data from a large number of LUFT sites to gain insights into the fate, transport, and spatial extent of MTBE plumes. Specific goals include defining the spatial configuration of dissolved MTBE plumes, evaluating plume stability or degradation over time, evaluating the impact of point source releases of MTBE to ground water, and attempting to identify the controlling factors influencing the magnitude and extent of the MTBE plumes. We are examining the relationships between dissolved TPH, BTEX, and MTBE plumes at LUFT sites using parallel approaches of best professional judgment and a computer-aided plume model fitting procedure to determine plume parameters. Here we present our initial results comparing dissolved benzene and MTBE plumes lengths, the statistical significance of these results, and configuration of benzene and MTBE plumes at individual LUFT sites

Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

Directory of Open Access Journals (Sweden)

Yang Xiaoke

2015-03-01

Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

Is the 'Fast Halo' around Hawaii as imaged in the PLUME experiment direct evidence for buoyant plume-fed asthenosphere?

Science.gov (United States)

Morgan, J. P.; Shi, C.; Hasenclever, J.

2010-12-01

An intriguing spatial pattern of variations in shear-wave arrival times has been mapped in the PLUME ocean bottom experiment (Wolfe et al., 2009) around Hawaii. The pattern consists of a halo of fast travel times surrounding a disk of slow arrivals from waves traveling up though the plume. We think it is directly sensing the pattern of dynamic uplift of the base of a buoyant asthenosphere - the buoyancy of the plume conduit lifting a 'rim' of the cooler, denser mantle that the plume rises through. The PLUME analysis inverted for lateral shear velocity variations beneath the lithosphere, after removing the assumed 1-D model velocity structure IASP91. They found that a slow plume-conduit extends to at least 1200 km below the Hawaiian hotspot. In this inversion the slow plume conduit is — quite surprisingly - surrounded by a fast wavespeed halo. A fast halo is impossible to explain as a thermal halo around the plume; this should lead to a slow wavespeed halo, not a fast one. Plume-related shearwave anisotropy also cannot simply explain this pattern — simple vertical strain around the plume conduit would result in an anisotropic slow shear-wavespeed halo, not a fast one. (Note the PLUME experiment’s uniform ‘fast-halo’ structure from 50-400km is likely to have strong vertical streaking in the seismic image; Pacific Plate-driven shear across a low-viscosity asthenosphere would be expected to disrupt and distort any cold sheet of vertical downwelling structure between 50-400km depths so that it would no longer be vertical as it is in the 2009 PLUME image with its extremely poor vertical depth control.) If the asthenosphere is plume-fed, hence more buoyant than underlying mantle, then there can be a simple explanation for this pattern. The anomaly would be due to faster traveltimes resulting from dynamic relief at the asthenosphere-mesosphere interface; uplift of the denser mesosphere by the buoyancy of the rising plume increases the distance a wave travels

Adaptive Laguerre-Gaussian variant of the Gaussian beam expansion method.

Science.gov (United States)

Cagniot, Emmanuel; Fromager, Michael; Ait-Ameur, Kamel

2009-11-01

A variant of the Gaussian beam expansion method consists in expanding the Bessel function J0 appearing in the Fresnel-Kirchhoff integral into a finite sum of complex Gaussian functions to derive an analytical expression for a Laguerre-Gaussian beam diffracted through a hard-edge aperture. However, the validity range of the approximation depends on the number of expansion coefficients that are obtained by optimization-computation directly. We propose another solution consisting in expanding J0 onto a set of collimated Laguerre-Gaussian functions whose waist depends on their number and then, depending on its argument, predicting the suitable number of expansion functions to calculate the integral recursively.

Improved atmospheric dispersion modelling in the new program system UFOMOD for accident consequence assessments

International Nuclear Information System (INIS)

Panitz, H.J.

1988-01-01

An essential aim of the improvements of the new program system UFOMOD for Accident Consequence Assessments (ACAs) was to substitute the straightline Gaussian plume model conventionally used in ACA models by more realistic atmospheric dispersion models. To identify improved models which can be applied in ACA codes and to quantify the implications of different concepts of dispersion modelling on the results of an ACA, probabilistic comparative calculations with different atmospheric dispersion models have been carried out. The study showed that there are trajectory models available which can be applied in ACAs and that these trajectory models provide more realistic results of ACAs than straight-line Gaussian models. This led to a completly novel concept of atmospheric dispersion modelling which distinguish between two different distance ranges of validity: the near range ( 50 km). The two ranges are assigned to respective trajectory models

Learning conditional Gaussian networks

DEFF Research Database (Denmark)

Bøttcher, Susanne Gammelgaard

This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

Reactive transport modelling of biogeochemical processes and carbon isotope geochemistry inside a landfill leachate plume.

NARCIS (Netherlands)

van Breukelen, B.M.; Griffioen, J.; Roling, W.F.M.; van Verseveld, H.W.

2004-01-01

The biogeochemical processes governing leachate attenuation inside a landfill leachate plume (Banisveld, the Netherlands) were revealed and quantified using the 1D reactive transport model PHREEQC-2. Biodegradation of dissolved organic carbon (DOC) was simulated assuming first-order oxidation of two

Out-of-equilibrium dynamics in a Gaussian trap model

International Nuclear Information System (INIS)

Diezemann, Gregor

2007-01-01

The violations of the fluctuation-dissipation theorem are analysed for a trap model with a Gaussian density of states. In this model, the system reaches thermal equilibrium for long times after a quench to any finite temperature and therefore all ageing effect are of a transient nature. For not too long times after the quench it is found that the so-called fluctuation-dissipation ratio tends to a non-trivial limit, thus indicating the possibility for the definition of a timescale-dependent effective temperature. However, different definitions of the effective temperature yield distinct results. In particular, plots of the integrated response versus the correlation function strongly depend on the way they are constructed. Also the definition of effective temperatures in the frequency domain is not unique for the model considered. This may have some implications for the interpretation of results from computer simulations and experimental determinations of effective temperatures

A novel Gaussian model based battery state estimation approach: State-of-Energy

International Nuclear Information System (INIS)

He, HongWen; Zhang, YongZhi; Xiong, Rui; Wang, Chun

2015-01-01

Highlights: • The Gaussian model is employed to construct a novel battery model. • The genetic algorithm is used to implement model parameter identification. • The AIC is used to decide the best hysteresis order of the battery model. • A novel battery SoE estimator is proposed and verified by two kinds of batteries. - Abstract: State-of-energy (SoE) is a very important index for battery management system (BMS) used in electric vehicles (EVs), it is indispensable for ensuring safety and reliable operation of batteries. For achieving battery SoE accurately, the main work can be summarized in three aspects. (1) In considering that different kinds of batteries show different open circuit voltage behaviors, the Gaussian model is employed to construct the battery model. What is more, the genetic algorithm is employed to locate the optimal parameter for the selecting battery model. (2) To determine an optimal tradeoff between battery model complexity and prediction precision, the Akaike information criterion (AIC) is used to determine the best hysteresis order of the combined battery model. Results from a comparative analysis show that the first-order hysteresis battery model is thought of being the best based on the AIC values. (3) The central difference Kalman filter (CDKF) is used to estimate the real-time SoE and an erroneous initial SoE is considered to evaluate the robustness of the SoE estimator. Lastly, two kinds of lithium-ion batteries are used to verify the proposed SoE estimation approach. The results show that the maximum SoE estimation error is within 1% for both LiFePO 4 and LiMn 2 O 4 battery datasets

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

2012-01-01

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina

2012-08-03

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

Using ASCEM Modeling and Visualization to Inform Stakeholders of Contaminant Plume Evolution and Remediation Efficacy at F-Basin Savannah River, SC – 15156

Energy Technology Data Exchange (ETDEWEB)

Flach, G. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wainwright, H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Molins, S. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Davis, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Arora, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Faybishenko, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Krishnan, H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hubbard, S. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Flach, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Denham, M. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Eddy-Dilek, C. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Moulton, D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lipnikov, K. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gable, C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Miller, T. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Freshley, M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-01-28

Communication with stakeholders, regulatory agencies, and the public is an essential part of implementing different remediation and monitoring activities, and developing site closure strategies at contaminated sites. Modeling of contaminant plume evolution plays a critical role in estimating the benefit, cost, and risk of particular options. At the same time, effective visualization of monitoring data and modeling results are particularly important for conveying the significance of the results and observations. In this paper, we present the results of the Advanced Simulation Capability for Environmental Management (ASCEM) project, including the discussion of the capabilities of newly developed ASCEM software package, along with its application to the F-Area Seepage Basins located in the U.S. Department of Energy Savannah River Site (SRS). ASCEM software includes state-of-the-art numerical methods for simulating complex flow and reactive transport, as well as various toolsets such as a graphical user interface (GUI), visualization, data management, uncertainty quantification, and parameter estimation. Using this software, we have developed an advanced visualization of tritium plume migration coupled with a data management system, and simulated a three-dimensional model of flow and plume evolution on a high-performance computing platform. We evaluated the effect of engineered flow barriers on a nonreactive tritium plume, through advanced plume visualization and modeling of tritium plume migration. In addition, we developed a geochemical reaction network to describe complex geochemical processes at the site, and evaluated the impact of coupled hydrological and geochemical heterogeneity. These results are expected to support SRS’s monitoring activities and operational decisions.

Investigations of the adequacy of the meteorological transport model developed for the reactor safety study

International Nuclear Information System (INIS)

Spring, J.L.; Brown, W.D.; Church, H.W.; McGrath, P.E.; Ritchie, L.T.; Russo, A.J.; Steck, G.P.; Wayland, J.R.; Blond, R.M.; Wall, I.B.

1978-01-01

A computer model (CRAC) was developed for the Reactor Safety Study (WASH-1400) [1] to estimate the consequences of postulated accidents at U.S. commercial nuclear power plants. One hundred reactors at 68 sites were included in the study. The 68 sites were divided into 6 classes according to their geographic location and meteorology. For each site class, a composite population distribution was constructed from the true population distributions at each of the sites comprising that class, and a reference site was chosen for which a full year of meteorological data (wind speed, atmospheric stability, occurrence of rain) was obtained. Given data about a postulated accident (probability, amounts of the released radionuclides, etc.) and the reference reactor site (meteorology, composite population, land usage), CRAC was used to calculate the atmospheric dispersion and ground deposition of the released radionuclides (Gaussian plume submodel) and the health effects (dosimetric and dose response submodels) and costs (land interdiction and decontamination submodel) resulting from their release. The Gaussian plume model used in CRAC either did not treat or treated simplistically a number of meteorological phenomena. Simplified models were used to treat plume rise, inversion layers, and rainstorms, while wind shear, wind direction, and correlations between wind fields and population distributions were not treated at all. Some of the effects of all of these phenomena on predictions of accident consequences as calculated using CRAC have been or are being investigated. The results of these studies are summarized

Resonant non-Gaussianity with equilateral properties

International Nuclear Information System (INIS)

Gwyn, Rhiannon; Rummel, Markus

2012-11-01

We discuss the effect of superimposing multiple sources of resonant non-Gaussianity, which arise for instance in models of axion inflation. The resulting sum of oscillating shape contributions can be used to ''Fourier synthesize'' different non-oscillating shapes in the bispectrum. As an example we reproduce an approximately equilateral shape from the superposition of O(10) oscillatory contributions with resonant shape. This implies a possible degeneracy between the equilateral-type non-Gaussianity typical of models with non-canonical kinetic terms, such as DBI inflation, and an equilateral-type shape arising from a superposition of resonant-type contributions in theories with canonical kinetic terms. The absence of oscillations in the 2-point function together with the structure of the resonant N-point functions, imply that detection of equilateral non-Gaussianity at a level greater than the PLANCK sensitivity of f NL ∝O(5) will rule out a resonant origin. We comment on the questions arising from possible embeddings of this idea in a string theory setting.

Large-eddy simulation study of oil/gas plumes in stratified fluid with cross current

Science.gov (United States)

Yang, Di; Xiao, Shuolin; Chen, Bicheng; Chamecki, Marcelo; Meneveau, Charles

2017-11-01

Dynamics of the oil/gas plume from a subsea blowout are strongly affected by the seawater stratification and cross current. The buoyant plume entrains ambient seawater and lifts it up to higher elevations. During the rising process, the continuously increasing density difference between the entrained and ambient seawater caused by the stable stratification eventually results in a detrainment of the entrained seawater and small oil droplets at a height of maximum rise (peel height), forming a downward plume outside the rising inner plume. The presence of a cross current breaks the plume's axisymmetry and causes the outer plume to fall along the downstream side of the inner plume. The detrained seawater and oil eventually fall to a neutral buoyancy level (trap height), and disperse horizontally to form an intrusion layer. In this study, the complex plume dynamics is investigated using large-eddy simulation (LES). Various laboratory and field scale cases are simulated to explore the effect of cross current and stratification on the plume dynamics. Based on the LES data, various turbulence statistics of the plume are systematically quantified, leading to some useful insights for modeling the mean plume dynamics using integral plume models. This research is made possible by a RFP-V Grant from The Gulf of Mexico Research Initiative.

NW Iberia Shelf Dynamics. Study of the Douro River Plume.

Directory of Open Access Journals (Sweden)

Isabel Iglesias

2014-06-01

Full Text Available River plumes are one of the most important mechanisms that transport the terrestrial materials to the coast and the ocean. Some examples of those materials are pollutants, essential nutrients, which enhance the phytoplankton productivity or sediments, which settle on the seabed producing modifications on the bathymetry affecting the navigation channels. The mixing between the riverine and the oceanic waters can induce instabilities, which might generate bulges, filaments, and buoyant currents over the continental shelf. Offshore, the buoyant riverine water could form a front with the oceanic waters often related with the occurrence of current-jets, eddies and strong mixing. The study and modelling of the river plumes is a key factor for the complete understanding of sediment transport mechanisms and patterns, and of coastal physics and dynamic processes. On this study the Douro River plume will be simulated. The Douro River is located on the north-west Iberian coast and its daily averaged freshwater discharge can range values from 0 to 13000 m3/s. This variability impacts the formation of the river plumes and its dispersion along the continental shelf. This study builds on the long-term objective of generate a Douro River plume forecasting system as part of the RAIA and RAIA.co projects. Satellite imagery was analyzed showing that the river Douro is one of the main sources of suspended particles, dissolved material and chlorophyll in the NW Iberian Shelf. The Regional Oceanic Modeling System (ROMS model was selected to reproduce scenarios of plume generation, retention and dispersion. Whit this model, three types of simulations were performed: (i schematic winds simulations with prescribed river flow, wind speed and direction; (ii multi-year climatological simulation, with river flow and temperature change for each month; (iii extreme case simulation, based on the Entre-os-Rios accident situation. The schematic wind case-studies suggest that the

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

Science.gov (United States)

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model

KAUST Repository

Liu, Bo

2016-02-03

An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.

Gaussian-log-Gaussian wavelet trees, frequentist and Bayesian inference, and statistical signal processing applications

DEFF Research Database (Denmark)

Møller, Jesper; Jacobsen, Robert Dahl

We introduce a promising alternative to the usual hidden Markov tree model for Gaussian wavelet coefficients, where their variances are specified by the hidden states and take values in a finite set. In our new model, the hidden states have a similar dependence structure but they are jointly Gaus...

A Gaussian graphical model approach to climate networks

International Nuclear Information System (INIS)

Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus

2014-01-01

Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately

A Gaussian graphical model approach to climate networks

Energy Technology Data Exchange (ETDEWEB)

Zerenner, Tanja, E-mail: tanjaz@uni-bonn.de [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)

2014-06-15

Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.

Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

KAUST Repository

Wang, Shitao; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Winokur, Justin; Knio, Omar

2016-01-01

Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

Biodegradation at Dynamic Plume Fringes: Mixing Versus Reaction Control

Science.gov (United States)

Cirpka, O. A.; Eckert, D.; Griebler, C.; Haberer, C.; Kürzinger, P.; Bauer, R.; Mellage, A.

2014-12-01

Biodegradation of continuously emitted plumes is known to be most pronounced at the plume fringe, where mixing of contaminated water and ambient groundwater, containing dissolved electron acceptors, stimulates microbial activity. Under steady-state conditions, physical mixing of contaminant and electron acceptor by transverse dispersion was shown to be the major bottleneck for biodegradation, with plume lengths scaling inversely with the bulk transverse dispersivity in quasi two-dimensional settings. Under these conditions, the presence of suitable microbes is essential but the biokinetic parameters do not play an important role. When the location of the plume shifts (caused, e.g., by a fluctuating groundwater table), however, the bacteria are no more situated at the plume fringe and biomass growth, decay, activation and deactivation determine the time lag until the fringe-controlled steady state is approached again. During this time lag, degradation is incomplete. The objective of the presented study was to analyze to which extent flow and transport dynamics diminish effectiveness of fringe-controlled biodegradation and which microbial processes and related biokinetic parameters determine the system response in overall degradation to hydraulic fluctuations. We performed experiments in quasi-two-dimensional flow through microcosms on aerobic toluene degradation by Pseudomonas putida F1. Plume dynamics were simulated by vertical alteration of the toluene plume position and experimental results were analyzed by reactive-transport modeling. We found that, even after disappearance of the toluene plume for two weeks, the majority of microorganisms stayed attached to the sediment and regained their full biodegradation potential within two days after reappearance of the toluene plume. Our results underline that besides microbial growth and maintenance (often subsumed as "biomass decay") microbial dormancy (that is, change into a metabolically inactive state) and

Studies of the environmental impact of evaporative cooling tower plumes

International Nuclear Information System (INIS)

Thomson, D.W.

1978-01-01

This ongoing research program of the environmental impact of natural-draft evaporative cooling tower plumes consists principally of a comprehensive series of airborne measurements of a variety of the physical characteristics of the plumes and, to a lesser extent, of preliminary studies of remote sodar plume probing techniques and the development of simplified dynamical numerical models suitable for use in conducting field measurement programs. The PSU Doppler sodar was used at the Keystone Power Plant in southwestern Pennsylvania for an extended series of remote measurements of the characteristics of plume turbulent temperature and velocity fluctuations and results are discussed

Modelling tools for integrating geological, geophysical and contamination data for characterization of groundwater plumes

DEFF Research Database (Denmark)

Balbarini, Nicola

the contaminant plume in a shallow and a deep plume. These plumes have different chemical characteristics and different migration paths to the stream. This has implications for the risk assessment of the stream and groundwater in the area. The difficulty of determining groundwater flow paths means that it is also...... receptors, including streams. Key risk assessment parameters, such as contaminant mass discharge estimates, and tools are then used to evaluate the risk. The cost of drilling often makes investigations of large and/or deep contaminant plumes unfeasible. For this reason, it is important to develop cost...... organic compounds, including pharmaceutical compounds and chlorinated ethenes. The correlation between DCIP and organic compounds is indirect and depends on the chemical composition of the contaminant plume and the transport processes. Thus, the correlations are site specific and may change between...

Resource theory of non-Gaussian operations

Science.gov (United States)

Zhuang, Quntao; Shor, Peter W.; Shapiro, Jeffrey H.

2018-05-01

Non-Gaussian states and operations are crucial for various continuous-variable quantum information processing tasks. To quantitatively understand non-Gaussianity beyond states, we establish a resource theory for non-Gaussian operations. In our framework, we consider Gaussian operations as free operations, and non-Gaussian operations as resources. We define entanglement-assisted non-Gaussianity generating power and show that it is a monotone that is nonincreasing under the set of free superoperations, i.e., concatenation and tensoring with Gaussian channels. For conditional unitary maps, this monotone can be analytically calculated. As examples, we show that the non-Gaussianity of ideal photon-number subtraction and photon-number addition equal the non-Gaussianity of the single-photon Fock state. Based on our non-Gaussianity monotone, we divide non-Gaussian operations into two classes: (i) the finite non-Gaussianity class, e.g., photon-number subtraction, photon-number addition, and all Gaussian-dilatable non-Gaussian channels; and (ii) the diverging non-Gaussianity class, e.g., the binary phase-shift channel and the Kerr nonlinearity. This classification also implies that not all non-Gaussian channels are exactly Gaussian dilatable. Our resource theory enables a quantitative characterization and a first classification of non-Gaussian operations, paving the way towards the full understanding of non-Gaussianity.

Turbulent structure of thermal plume. Velocity field

International Nuclear Information System (INIS)

Guillou, B.; Brahimi, M.; Doan-kim-son

1986-01-01

An experimental investigation and a numerical study of the dynamics of a turbulent plume rising from a strongly heated source are described. This type of flow is met in thermal effluents (air, vapor) from, e.g., cooling towers of thermal power plants. The mean and fluctuating values of the vertical component of the velocity were determined using a Laser-Doppler anemometer. The measurements allow us to distinguish three regions in the plume-a developing region near the source, an intermediate region, and a self-preserving region. The characteristics of each zone have been determined. In the self-preserving zone, especially, the turbulence level on the axis and the entrainment coefficient are almost twice of the values observed in jets. The numerical model proposed takes into account an important phenomenon, the intermittency, observed in the plume. This model, established with the self-preserving hypothesis, brings out analytical laws. These laws and the predicted velocity profile are in agreement with the experimental evolutions [fr

Seismic Imaging of Mantle Plumes

Science.gov (United States)

Nataf, Henri-Claude

The mantle plume hypothesis was proposed thirty years ago by Jason Morgan to explain hotspot volcanoes such as Hawaii. A thermal diapir (or plume) rises from the thermal boundary layer at the base of the mantle and produces a chain of volcanoes as a plate moves on top of it. The idea is very attractive, but direct evidence for actual plumes is weak, and many questions remain unanswered. With the great improvement of seismic imagery in the past ten years, new prospects have arisen. Mantle plumes are expected to be rather narrow, and their detection by seismic techniques requires specific developments as well as dedicated field experiments. Regional travel-time tomography has provided good evidence for plumes in the upper mantle beneath a few hotspots (Yellowstone, Massif Central, Iceland). Beneath Hawaii and Iceland, the plume can be detected in the transition zone because it deflects the seismic discontinuities at 410 and 660 km depths. In the lower mantle, plumes are very difficult to detect, so specific methods have been worked out for this purpose. There are hints of a plume beneath the weak Bowie hotspot, as well as intriguing observations for Hawaii. Beneath Iceland, high-resolution tomography has just revealed a wide and meandering plume-like structure extending from the core-mantle boundary up to the surface. Among the many phenomena that seem to take place in the lowermost mantle (or D''), there are also signs there of the presence of plumes. In this article I review the main results obtained so far from these studies and discuss their implications for plume dynamics. Seismic imaging of mantle plumes is still in its infancy but should soon become a turbulent teenager.

Implementation and use of Gaussian process meta model for sensitivity analysis of numerical models: application to a hydrogeological transport computer code

International Nuclear Information System (INIS)

Marrel, A.

2008-01-01

In the studies of environmental transfer and risk assessment, numerical models are used to simulate, understand and predict the transfer of pollutant. These computer codes can depend on a high number of uncertain input parameters (geophysical variables, chemical parameters, etc.) and can be often too computer time expensive. To conduct uncertainty propagation studies and to measure the importance of each input on the response variability, the computer code has to be approximated by a meta model which is build on an acceptable number of simulations of the code and requires a negligible calculation time. We focused our research work on the use of Gaussian process meta model to make the sensitivity analysis of the code. We proposed a methodology with estimation and input selection procedures in order to build the meta model in the case of a high number of inputs and with few simulations available. Then, we compared two approaches to compute the sensitivity indices with the meta model and proposed an algorithm to build prediction intervals for these indices. Afterwards, we were interested in the choice of the code simulations. We studied the influence of different sampling strategies on the predictiveness of the Gaussian process meta model. Finally, we extended our statistical tools to a functional output of a computer code. We combined a decomposition on a wavelet basis with the Gaussian process modelling before computing the functional sensitivity indices. All the tools and statistical methodologies that we developed were applied to the real case of a complex hydrogeological computer code, simulating radionuclide transport in groundwater. (author) [fr

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

Science.gov (United States)

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it

Modeling of plasma plume induced during laser welding

International Nuclear Information System (INIS)

Moscicki, T.; Hoffman, J.; Szymanski, Z.

2005-01-01

During laser welding, the interaction of intense laser radiation with a work-piece leads to the formation of a long, thin, cylindrical cavity in a metal, called a keyhole. Generation of a keyhole enables the laser beam to penetrate into the work-piece and is essential for deep welding. The keyhole contains ionized metal vapour and is surrounded by molten material called the weld pool. The metal vapour, which flows from the keyhole mixes with the shielding gas flowing from the opposite direction and forms a plasma plume over the keyhole mouth. The plasma plume has considerable influence on the processing conditions. Plasma strongly absorbs laser radiation and significantly changes energy transfer from the laser beam to a material. In this paper the results of theoretical modelling of plasma plume induced during welding with CO 2 laser are presented. The set of equations consists of equation of conservation of mass, energy, momentum and the diffusion equation: ∂ρ/∂t + ∇·(ρ ρ ν =0; ∂(ρE)/∂t + ∇·( ρ ν (ρE + p)) = ∇ (k eff ∇T - Σ j h j ρ J j + (τ eff · ρ ν )) + Σ i κ i I i - R; ∂/∂t(ρ ρ ν ) + ∇· (ρ ρ ν ρ ν ) = - ∇p + ∇(τ) + ρ ρ g + ρ F, where τ is viscous tensor τ = μ[(∇ ρ ν + ∇ ρT ν )-2/3∇· ρ ν I]; ∂/∂t(ρY i ) + ∇·(ρ ρ ν Y i ) = ∇·ρD i,m ∇T i ; where μ ν denotes velocity vector, E - energy, ρ mass density; k - thermal conductivity, T- temperature, κ - absorption coefficient, I i local laser intensity, R - radiation loss function, p - pressure, h j enthalpy, J j - diffusion flux of j component, ν g - gravity, μ F - external force, μ - dynamic viscosity, I - unit tensor, Y i - mass fraction of iron vapor in the gas mixture, D i,m - mass diffusion coefficient. The terms k eff and τ eff contain the turbulent component of the thermal conductivity and the viscosity, respectively. All the material functions are functions of the temperature and mass fraction only. The equations

Model correction factor method for reliability problems involving integrals of non-Gaussian random fields

DEFF Research Database (Denmark)

Franchin, P.; Ditlevsen, Ove Dalager; Kiureghian, Armen Der

2002-01-01

The model correction factor method (MCFM) is used in conjunction with the first-order reliability method (FORM) to solve structural reliability problems involving integrals of non-Gaussian random fields. The approach replaces the limit-state function with an idealized one, in which the integrals ...

Extreme-Strike and Small-time Asymptotics for Gaussian Stochastic Volatility Models

OpenAIRE

Zhang, Xin

2016-01-01

Asymptotic behavior of implied volatility is of our interest in this dissertation. For extreme strike, we consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Loève expansion for the integrated variance, and using sharp estimates of the density of a general second-chaos variable, we derive asymptotics for the asset price density for large or smal...

How Non-Gaussian Shocks Affect Risk Premia in Non-Linear DSGE Models

DEFF Research Database (Denmark)

Andreasen, Martin Møller

This paper studies how non-Gaussian shocks affect risk premia in DSGE models approximated to second and third order. Based on an extension of the results in Schmitt-Grohé & Uribe (2004) to third order, we derive propositions for how rare disasters, stochastic volatility, and GARCH affect any risk...... premia in a wide class of DSGE models. To quantify these effects, we then set up a standard New Keynesian DSGE model where total factor productivity includes rare disasters, stochastic volatility, and GARCH. We …find that rare disasters increase the mean level of the 10-year nominal term premium, whereas...

Field experimental observations of highly graded sediment plumes.

Science.gov (United States)

Jensen, Jacob Hjelmager; Saremi, Sina; Jimenez, Carlos; Hadjioannou, Louis

2015-06-15

A field experiment in the waters off the south-eastern coast of Cyprus was carried out to study near-field formation of sediment plumes from dumping. Different loads of sediment were poured into calm and limpid waters one at the time from just above the sea surface. The associated plumes, gravitating towards the seafloor, were filmed simultaneously by four divers situated at different depths in the water column, and facing the plume at different angles. The processes were captured using GoPro-Hero-series cameras. The high-quality underwater footage from near-surface, mid-depth and near-bed positions gives unique insight into the dynamics of the descending plume and near-field dispersion processes, and enables good understanding of flow and sediment transport processes involved from-release-to-deposition of the load in a non-scaled environment. The high resolution images and footages are available through the link provided herein. Observations support the development of a detailed multi-fractional sediment plume model. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Research of Indoor Positioning Based on Double-peak Gaussian Model

Directory of Open Access Journals (Sweden)

Lina Chen

2014-04-01

Full Text Available Location fingerprinting using Wi-Fi signals has been very popular and is a well accepted indoor positioning method. The key issue of the fingerprinting approach is generating the fingerprint radio map. Limited by the practical workload, only a few samples of the received signal strength are collected at each reference point. Unfortunately, fewer samples cannot accurately represent the actual distribution of the signal strength from each access point. This study finds most Wi- Fi signals have two peaks. According to the new finding, a double-peak Gaussian arithmetic is proposed to generate a fingerprint radio map. This approach requires little time to receive WiFi signals and it easy to estimate the parameters of the double-peak Gaussian function. Compared to the Gaussian function and histogram method to generate a fingerprint radio map, this method better approximates the occurrence signal distribution. This paper also compared the positioning accuracy using K-Nearest Neighbour theory for three radio maps, the test results show that the positioning distance error utilizing the double-peak Gaussian function is better than the other two methods.

Current inversion induced by colored non-Gaussian noise

International Nuclear Information System (INIS)

Bag, Bidhan Chandra; Hu, Chin-Kung

2009-01-01

We study a stochastic process driven by colored non-Gaussian noises. For the flashing ratchet model we find that there is a current inversion in the variation of the current with the half-cycle period which accounts for the potential on–off operation. The current inversion almost disappears if one switches from non-Gaussian (NG) to Gaussian (G) noise. We also find that at low value of the asymmetry parameter of the potential the mobility controlled current is more negative for NG noise as compared to G noise. But at large magnitude of the parameter the diffusion controlled positive current is higher for the former than for the latter. On increasing the noise correlation time (τ), keeping the noise strength fixed, the mean velocity of a particle first increases and then decreases after passing through a maximum if the noise is non-Gaussian. For Gaussian noise, the current monotonically decreases. The current increases with the noise parameter p, 0< p<5/3, which is 1 for Gaussian noise

Numerical study of single and two interacting turbulent plumes in atmospheric cross flow

Science.gov (United States)

Mokhtarzadeh-Dehghan, M. R.; König, C. S.; Robins, A. G.

The paper presents a numerical study of two interacting full-scale dry plumes issued into neutral boundary layer cross flow. The study simulates plumes from a mechanical draught cooling tower. The plumes are placed in tandem or side-by-side. Results are first presented for plumes with a density ratio of 0.74 and plume-to-crosswind speed ratio of 2.33, for which data from a small-scale wind tunnel experiment were available and were used to assess the accuracy of the numerical results. Further results are then presented for the more physically realistic density ratio of 0.95, maintaining the same speed ratio. The sensitivity of the results with respect to three turbulence models, namely, the standard k- ɛ model, the RNG k- ɛ model and the Differential Flux Model (DFM) is presented. Comparisons are also made between the predicted rise height and the values obtained from existing integral models. The formation of two counter-rotating vortices is well predicted. The results show good agreement for the rise height predicted by different turbulence models, but the DFM predicts temperature profiles more accurately. The values of predicted rise height are also in general agreement. However, discrepancies between the present results for the rise height for single and multiple plumes and the values obtained from known analytical relations are apparent and possible reasons for these are discussed.

A novel multitarget model of radiation-induced cell killing based on the Gaussian distribution.

Science.gov (United States)

Zhao, Lei; Mi, Dong; Sun, Yeqing

2017-05-07

The multitarget version of the traditional target theory based on the Poisson distribution is still used to describe the dose-survival curves of cells after ionizing radiation in radiobiology and radiotherapy. However, noting that the usual ionizing radiation damage is the result of two sequential stochastic processes, the probability distribution of the damage number per cell should follow a compound Poisson distribution, like e.g. Neyman's distribution of type A (N. A.). In consideration of that the Gaussian distribution can be considered as the approximation of the N. A. in the case of high flux, a multitarget model based on the Gaussian distribution is proposed to describe the cell inactivation effects in low linear energy transfer (LET) radiation with high dose-rate. Theoretical analysis and experimental data fitting indicate that the present theory is superior to the traditional multitarget model and similar to the Linear - Quadratic (LQ) model in describing the biological effects of low-LET radiation with high dose-rate, and the parameter ratio in the present model can be used as an alternative indicator to reflect the radiation damage and radiosensitivity of the cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

Coupling of Realistic Rate Estimates with Genomics for Assessing Contaminant Attenuation and Long-Term Plume Containment - Task 4: Modeling - Final Report

International Nuclear Information System (INIS)

Robert C. Starr

2005-01-01

seven plumes at 24 DOE facilities were screened, and 14 plumes were selected for detailed examination. In the plumes selected for further study, spatial changes in the concentration of a conservative co-contaminant were used to compensate for the effects of mixing and temporal changes in TCE release from the contaminant source. Decline in TCE concentration along a flow path in excess of the co contaminant concentration decline was attributed to cometabolic degradation. This study indicated that TCE was degraded in 9 of the 14 plumes examined, with first order degradation half-lives ranging from about 1 to 12 years. TCE degradation in about two-thirds of the plumes examined suggests that cometabolism of TCE in aerobic groundwater is a common occurrence, in contrast to the conventional wisdom that TCE is recalcitrant in aerobic groundwater. The degradation half-life values calculated in this study are short enough that natural attenuation may be a viable remedy in many aerobic plumes. Computer modeling of groundwater flow and contaminant transport and degradation is frequently used to predict the evolution of groundwater plumes, and for evaluating natural attenuation and other remedial alternatives. An important aspect of a computer model is the mathematical approach for describing degradation kinetics. A common approach is to assume that degradation occurs as a first-order process. First order kinetics are easily incorporated into transport models and require only a single value (a degradation half-life) to describe reaction kinetics. The use of first order kinetics is justified in many cases because more elaborate kinetic equations often closely approximate first order kinetics under typical field conditions. A previous modeling study successfully simulated the INL TCE plume using first order degradation kinetics. TCE cometabolism is the result of TCE reacting with microbial enzymes that were produced for other purposes, such as oxidizing a growth substrate to obtain

Non-Gaussianity from tachyonic preheating in hybrid inflation

International Nuclear Information System (INIS)

Barnaby, Neil; Cline, James M.

2007-01-01

In a previous work we showed that large non-Gaussianities and nonscale-invariant distortions in the cosmic microwave background power spectrum can be generated in hybrid inflation models, due to the contributions of the tachyon (waterfall) field to the second order curvature perturbation. Here we clarify, correct, and extend those results. We show that large non-Gaussianity occurs only when the tachyon remains light throughout inflation, whereas n=4 contamination to the spectrum is the dominant effect when the tachyon is heavy. We find constraints on the parameters of warped-throat brane-antibrane inflation from non-Gaussianity. For F-term and D-term inflation models from supergravity, we obtain nontrivial constraints from the spectral distortion effect. We also establish that our analysis applies to complex tachyon fields

A buoyant plume adjacent to a headland-Observations of the Elwha River plume

Science.gov (United States)

Warrick, J.A.; Stevens, A.W.

2011-01-01

Small rivers commonly discharge into coastal settings with topographic complexities - such as headlands and islands - but these settings are underrepresented in river plume studies compared to more simplified, straight coasts. The Elwha River provides a unique opportunity to study the effects of coastal topography on a buoyant plume, because it discharges into the Strait of Juan de Fuca on the western side of its deltaic headland. Here we show that this headland induces flow separation and transient eddies in the tidally dominated currents (O(100. cm/s)), consistent with other headlands in oscillatory flow. These flow conditions are observed to strongly influence the buoyant river plume, as predicted by the "small-scale" or "narrow" dynamical classification using Garvine's (1995) system. Because of the transient eddies and the location of the river mouth on the headland, flow immediately offshore of the river mouth is directed eastward twice as frequently as it is westward. This results in a buoyant plume that is much more frequently "bent over" toward the east than the west. During bent over plume conditions, the plume was attached to the eastern shoreline while having a distinct, cuspate front along its westernmost boundary. The location of the front was found to be related to the magnitude and direction of local flow during the preceding O(1. h), and increases in alongshore flow resulted in deeper freshwater mixing, stronger baroclinic anomalies, and stronger hugging of the coast. During bent over plume conditions, we observed significant convergence of river plume water toward the frontal boundary within 1. km of the river mouth. These results show how coastal topography can strongly influence buoyant plume behavior, and they should assist with understanding of initial coastal sediment dispersal pathways from the Elwha River during a pending dam removal project. ?? 2010.

Tracing Mantle Plumes: Quantifying their Morphology and Behavior from Seismic Tomography

Science.gov (United States)

O'Farrell, K. A.; Eakin, C. M.; Jones, T. D.; Garcia, E.; Robson, A.; Mittal, T.; Lithgow-Bertelloni, C. R.; Jackson, M. G.; Lekic, V.; Rudolph, M. L.

2016-12-01

Hotspot volcanism provides a direct link between the deep mantle and the surface, but the location, depth and source of the mantle plumes that feed hotspots are highly controversial. In order to address this issue it is important to understand the journey along which plumes have travelled through the mantle. The general behavior of plumes in the mantle also has the potential to tell us about the vigor of mantle convection, net rotation of the mantle, the role of thermal versus chemical anomalies, and important bulk physical properties of the mantle such as the viscosity profile. To address these questions we developed an algorithm to trace plume-like features in shear-wave (Vs) seismic tomographic models based on picking local minima in velocity and searching for continuous features with depth. We apply this method to several of the latest tomographic models and can recover 30 or more continuous plume conduits that are >750 km long. Around half of these can be associated with a known hotspot at the surface. We study the morphology of these plume chains and find that the largest lateral deflections occur near the base of the lower mantle and in the upper mantle. We analyze the preferred orientation of the plume deflections and their gradient to infer large scale mantle flow patterns and the depth of viscosity contrasts in the mantle respectively. We also retrieve Vs profiles for our traced plumes and compare with velocity profiles predicted for different mantle adiabat temperatures. We use this to constrain the thermal anomaly associated with these plumes. This thermal anomaly is then converted to a density anomaly and an upwelling velocity is derived. We compare this to buoyancy fluxes calculated at the surface and use this in conjunction with our measured plume tilts/deflections to estimate the strength of the "mantle wind".

Study of atmospheric stratification influence on pollutants dispersion using a numerical fluid mechanics model. Code-Saturne validation with the Prairie Grass experiment/Study of atmospheric stratification influence on pollutants dispersion using a numerical fluid mechanics software

International Nuclear Information System (INIS)

Coulon, Fanny

2010-09-01

A validation of Code-Saturne, a computational fluids dynamics model developed by EDF, is proposed for stable conditions. The goal is to guarantee the performance of the model in order to use it for impacts study. A comparison with the Prairie Grass data field experiment and with two Gaussian plume models will be done [fr

Gaussian mixture models and semantic gating improve reconstructions from human brain activity

Directory of Open Access Journals (Sweden)

Sanne eSchoenmakers

2015-01-01

Full Text Available Better acquisition protocols and analysis techniques are making it possible to use fMRI to obtain highly detailed visualizations of brain processes. In particular we focus on the reconstruction of natural images from BOLD responses in visual cortex. We expand our linear Gaussian framework for percept decoding with Gaussian mixture models to better represent the prior distribution of natural images. Reconstruction of such images then boils down to probabilistic inference in a hybrid Bayesian network. In our set-up, different mixture components correspond to different character categories. Our framework can automatically infer higher-order semantic categories from lower-level brain areas. Furthermore the framework can gate semantic information from higher-order brain areas to enforce the correct category during reconstruction. When categorical information is not available, we show that automatically learned clusters in the data give a similar improvement in reconstruction. The hybrid Bayesian network leads to highly accurate reconstructions in both supervised and unsupervised settings.

Argonne National Laboratory's thermal plume measurements: instruments and techniques

International Nuclear Information System (INIS)

Van Loon, L.S.; Frigo, A.A.; Paddock, R.A.

1977-12-01

Instrumentation and techniques were developed at Argonne National Laboratory for measuring the three-dimensional temperature structure of thermal plumes from power plants, along with the limnological, meteorological, and plant operating conditions affecting their behavior. The equipment and procedures were designed to provide field data for use in evaluating predictive models that describe thermal plume behavior, and over 100 sets of these data have been collected. The instrument systems and techniques employed in a typical thermal discharge survey are highly integrated. Continuous monitoring of ambient and plant conditions is coupled with plume mapping from a moving survey boat. The instantaneous location of the boat together with subsurface temperature measurements from a towed thermistor chain provide a quasisynoptic view of the plume structure. Real-time, onboard display of the boat path and vertical temperatures supply feedback to investigators for determining the extent and spatial resolution of measurements required. The unique design, reliability, accuracy, calibration, and historical development of the components of these integrated systems are described. Survey system interfaces with data handling and processing techniques are also explained. Special supportive studies to investigate plume dynamics, values of eddy diffusivities, time-temperature histories of water parcels in thermal plumes, and rapid changes in plume shape are also described along with instrumentation used

EDITORIAL: Non-linear and non-Gaussian cosmological perturbations Non-linear and non-Gaussian cosmological perturbations

Science.gov (United States)

Sasaki, Misao; Wands, David

2010-06-01

In recent years there has been a resurgence of interest in the study of non-linear perturbations of cosmological models. This has been the result of both theoretical developments and observational advances. New theoretical challenges arise at second and higher order due to mode coupling and the need to develop new gauge-invariant variables beyond first order. In particular, non-linear interactions lead to deviations from a Gaussian distribution of primordial perturbations even if initial vacuum fluctuations are exactly Gaussian. These non-Gaussianities provide an important probe of models for the origin of structure in the very early universe. We now have a detailed picture of the primordial distribution of matter from surveys of the cosmic microwave background, notably NASA's WMAP satellite. The situation will continue to improve with future data from the ESA Planck satellite launched in 2009. To fully exploit these data cosmologists need to extend non-linear cosmological perturbation theory beyond the linear theory that has previously been sufficient on cosmological scales. Another recent development has been the realization that large-scale structure, revealed in high-redshift galaxy surveys, could also be sensitive to non-linearities in the primordial curvature perturbation. This focus section brings together a collection of invited papers which explore several topical issues in this subject. We hope it will be of interest to theoretical physicists and astrophysicists alike interested in understanding and interpreting recent developments in cosmological perturbation theory and models of the early universe. Of course it is only an incomplete snapshot of a rapidly developing field and we hope the reader will be inspired to read further work on the subject and, perhaps, fill in some of the missing pieces. This focus section is dedicated to the memory of Lev Kofman (1957-2009), an enthusiastic pioneer of inflationary cosmology and non-Gaussian perturbations.

Characteristics of bubble plumes, bubble-plume bubbles and waves from wind-steepened wave breaking

NARCIS (Netherlands)

Leifer, I.; Caulliez, G.; Leeuw, G. de

2007-01-01

Observations of breaking waves, associated bubble plumes and bubble-plume size distributions were used to explore the coupled evolution of wave-breaking, wave properties and bubble-plume characteristics. Experiments were made in a large, freshwater, wind-wave channel with mechanical wind-steepened

On predicting mantle mushroom plumes

Directory of Open Access Journals (Sweden)

Ka-Kheng Tan

2011-04-01

Top cooling may produce plunging plumes of diameter of 585 km and at least 195 Myr old. The number of cold plumes is estimated to be 569, which has not been observed by seismic tomography or as cold spots. The cold plunging plumes may overwhelm and entrap some of the hot rising plumes from CMB, so that together they may settle in the transition zone.

Gaussian random-matrix process and universal parametric correlations in complex systems

International Nuclear Information System (INIS)

Attias, H.; Alhassid, Y.

1995-01-01

We introduce the framework of the Gaussian random-matrix process as an extension of Dyson's Gaussian ensembles and use it to discuss the statistical properties of complex quantum systems that depend on an external parameter. We classify the Gaussian processes according to the short-distance diffusive behavior of their energy levels and demonstrate that all parametric correlation functions become universal upon the appropriate scaling of the parameter. The class of differentiable Gaussian processes is identified as the relevant one for most physical systems. We reproduce the known spectral correlators and compute eigenfunction correlators in their universal form. Numerical evidence from both a chaotic model and weakly disordered model confirms our predictions

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Science.gov (United States)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-06-01

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Energy Technology Data Exchange (ETDEWEB)

Holoien, Thomas W.-S.; /Ohio State U., Dept. Astron. /Ohio State U., CCAPP /KIPAC, Menlo Park /SLAC; Marshall, Philip J.; Wechsler, Risa H.; /KIPAC, Menlo Park /SLAC

2017-05-11

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

Gaussian copula as a likelihood function for environmental models

Science.gov (United States)

Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.

2017-12-01

Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an

Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models

DEFF Research Database (Denmark)

Vehtari, Aki; Mononen, Tommi; Tolvanen, Ville

2016-01-01

The future predictive performance of a Bayesian model can be estimated using Bayesian cross-validation. In this article, we consider Gaussian latent variable models where the integration over the latent values is approximated using the Laplace method or expectation propagation (EP). We study...... the properties of several Bayesian leave-one-out (LOO) cross-validation approximations that in most cases can be computed with a small additional cost after forming the posterior approximation given the full data. Our main objective is to assess the accuracy of the approximative LOO cross-validation estimators...

A Plume Scale Model of Chlorinated Ethene Degradation

DEFF Research Database (Denmark)

Murray, Alexandra Marie; Broholm, Mette Martina; Badin, Alice

leaked from a dry cleaning facility, and a 2 km plume extends from the source in an unconfined aquifer of homogenous fluvio-glacial sand. The area has significant iron deposits, most notably pyrite, which can abiotically degrade chlorinated ethenes. The source zone underwent thermal (steam) remediation...

Descent and mixing of the overflow plume from Storfjord in Svalbard: an idealized numerical model study

Directory of Open Access Journals (Sweden)

I. Fer

2008-05-01

Full Text Available Storfjorden in the Svalbard Archipelago is a sill-fjord that produces significant volumes of dense, brine-enriched shelf water through ice formation. The dense water produced in the fjord overflows the sill and can reach deep into the Fram Strait. For conditions corresponding to a moderate ice production year, the pathway of the overflow, its descent and evolving water mass properties due to mixing are investigated for the first time using a high resolution 3-D numerical model. An idealized modeling approach forced by a typical annual cycle of buoyancy forcing due to ice production is chosen in a terrain-following vertical co-ordinate. Comparison with observational data, including hydrography, fine resolution current measurements and direct turbulence measurements using a microstructure profiler, gives confidence on the model performance. The model eddy diffusivity profiles contrasted to those inferred from the turbulence measurements give confidence on the skill of the Mellor Yamada scheme in representing sub-grid scale mixing for the Storfjorden overflow, and probably for gravity current modeling, in general. The Storfjorden overflow is characterized by low Froude number dynamics except at the shelf break where the plume narrows, accelerates with speed reaching 0.6 m s⁻¹, yielding local Froude number in excess of unity. The volume flux of the plume increases by five-fold from the sill to downstream of the shelf-break. Rotational hydraulic control is not applicable for transport estimates at the sill using upstream basin information. To the leading order, geostrophy establishes the lateral slope of the plume interface at the sill. This allows for a transport estimate that is consistent with the model results by evaluating a weir relation at the sill.

Marine snow, organic solute plumes, and optimal chemosensory behavior of bacteria

DEFF Research Database (Denmark)

Kiørboe, Thomas; Jackson, G.A.

2001-01-01

Leaking organic solutes form an elongated plume in the wake of a sinking aggregate. These solutes may both be assimilated by suspended bacteria and guide bacteria with chemokinetic swimming behavior toward the aggregate. We used modifications of previously published models of the flow and concent......Leaking organic solutes form an elongated plume in the wake of a sinking aggregate. These solutes may both be assimilated by suspended bacteria and guide bacteria with chemokinetic swimming behavior toward the aggregate. We used modifications of previously published models of the flow...... behavior was used to examine the potential contribution of aggregate-generated solute plumes for water column bacteria] production. Despite occupying only a small volume fraction, the plumes may provide important growth habitats for free bacteria and account for a significant proportion of water column...

Dynamics of Mantle Plume Controlled by both Post-spinel and Post-garnet Phase Transitions

Science.gov (United States)

Liu, H.; Leng, W.

2017-12-01

Mineralogical studies indicate that two major phase transitions occur near 660 km depth in the Earth's pyrolitic mantle: the ringwoodite (Rw) to perovskite (Pv) + magnesiowüstite (Mw) and majorite (Mj) to perovskite (Pv) phase transitions. Seismological results also show a complicated phase boundary structure for plume regions at this depth, including broad pulse, double reflections and depressed 660 km discontinuity beneath hot regions etc… These observations have been attributed to the co-existence of these two phase transformations. However, previous geodynamical modeling mainly focused on the effects of Rw-Pv+Mw phase transition on the plume dynamics and largely neglected the effects of Mj-Pv phase transition. Here we develop a 3-D regional spherical geodynamic model to study the influence of the combination of Rw - Pv+Mw and Mj - Pv phase transitions on plume dynamics, including the topography fluctuation of 660 km discontinuity, plume shape and penetration capability of plume. Our results show that (1) a double phase boundary occurs at the hot center area of plume while for other regions with relatively lower temperature the phase boundary is single and flat, which respectively corresponds to the double reflections in the seismic observations and a high velocity prism-like structure at the top of 660 km discontinuity; (2) a large amount of low temperature plume materials could be trapped to form a complex trapezoid overlying the 660 km depth; (3) Mj - Pv phase change strongly enhances the plume penetration capability at 660 km depth, which significantly increases the plume mass flux due to the increased plume radius, but significantly reduces plume heat flux due to the decreased plume temperature in the upper mantle. Our model results provide new enlightenments for better constraining seismic structure and mineral reactions at 660 km phase boundaries.