A physically based analytical spatial air temperature and humidity model
Yang Yang; Theodore A. Endreny; David J. Nowak
2013-01-01
Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat...
A physically based analytical spatial air temperature and humidity model
Yang, Yang; Endreny, Theodore A.; Nowak, David J.
2013-09-01
Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.
Spatial Analytic Hierarchy Process Model for Flood Forecasting: An Integrated Approach
Matori, Abd Nasir; Yusof, Khamaruzaman Wan; Hashim, Mustafa Ahmad; Lawal, Dano Umar; Balogun, Abdul-Lateef
2014-01-01
Various flood influencing factors such as rainfall, geology, slope gradient, land use, soil type, drainage density, temperature etc. are generally considered for flood hazard assessment. However, lack of appropriate handling/integration of data from different sources is a challenge that can make any spatial forecasting difficult and inaccurate. Availability of accurate flood maps and thorough understanding of the subsurface conditions can adequately enhance flood disasters management. This study presents an approach that attempts to provide a solution to this drawback by combining Geographic Information System (GIS)-based Analytic Hierarchy Process (AHP) model as spatial forecasting tools. In achieving the set objectives, spatial forecasting of flood susceptible zones in the study area was made. A total number of five set of criteria/factors believed to be influencing flood generation in the study area were selected. Priority weights were assigned to each criterion/factor based on Saaty's nine point scale of preference and weights were further normalized through the AHP. The model was integrated into a GIS system in order to produce a flood forecasting map
Spatial Game Analytics and Visualization
Drachen, Anders; Schubert, Matthias
2013-01-01
, techniques for spatial analysis had their share in these developments. However, the methods for analyzing and visualizing spatial and spatio-temporal patterns in player behavior being used by the game industry are not as diverse as the range of techniques utilized in game research, leaving room...... for a continuing development. This paper presents a review of current work on spatial and spatio-temporal game analytics across industry and research, describing and defining the key terminology, outlining current techniques and their application. We summarize the current problems and challenges in the field......The recently emerged field of game analytics and the development and adaptation of business intelligence techniques to support game design and development has given data-driven techniques a direct role in game development. Given that all digital games contain some sort of spatial operation...
Oliveira, Fernando Luiz de
2008-01-01
This work describes an analytical solution obtained by the expansion method for the spatial kinetics using the diffusion model with delayed emission for source transients in homogeneous media. In particular, starting from simple models, and increasing the complexity, numerical results were obtained for different types of source transients. An analytical solution of the one group without precursors was solved, followed by considering one precursors family. The general case of G-groups with R families of precursor although having a closed form solution, cannot be solved analytically, since there are no explicit formulae for the eigenvalues, and numerical methods must be used to solve such problem. To illustrate the general solution, the multi-group (three groups) time-dependent problem without precursors was solved and the numerical results of a finite difference code were compared with the exact results for different transients. (author)
Deng, Baoqing; Si, Yinbing; Wang, Jia
2017-12-01
Transient storages may vary along the stream due to stream hydraulic conditions and the characteristics of storage. Analytical solutions of transient storage models in literature didn't cover the spatially non-uniform storage. A novel integral transform strategy is presented that simultaneously performs integral transforms to the concentrations in the stream and in storage zones by using the single set of eigenfunctions derived from the advection-diffusion equation of the stream. The semi-analytical solution of the multiple-zone transient storage model with the spatially non-uniform storage is obtained by applying the generalized integral transform technique to all partial differential equations in the multiple-zone transient storage model. The derived semi-analytical solution is validated against the field data in literature. Good agreement between the computed data and the field data is obtained. Some illustrative examples are formulated to demonstrate the applications of the present solution. It is shown that solute transport can be greatly affected by the variation of mass exchange coefficient and the ratio of cross-sectional areas. When the ratio of cross-sectional areas is big or the mass exchange coefficient is small, more reaches are recommended to calibrate the parameter.
An analytical study of physical models with inherited temporal and spatial memory
Jaradat, Imad; Alquran, Marwan; Al-Khaled, Kamel
2018-04-01
Du et al. (Sci. Reb. 3, 3431 (2013)) demonstrated that the fractional derivative order can be physically interpreted as a memory index by fitting the test data of memory phenomena. The aim of this work is to study analytically the joint effect of the memory index on time and space coordinates simultaneously. For this purpose, we introduce a novel bivariate fractional power series expansion that is accompanied by twofold fractional derivatives ordering α, β\\in(0,1]. Further, some convergence criteria concerning our expansion are presented and an analog of the well-known bivariate Taylor's formula in the sense of mixed fractional derivatives is obtained. Finally, in order to show the functionality and efficiency of this expansion, we employ the corresponding Taylor's series method to obtain closed-form solutions of various physical models with inherited time and space memory.
An analytic method for agent-based modeling of spatially inhomogeneous disease dynamics
Bock, W.; Fattler, T.; Rodiah, I.; Tse, O.T.C.; Villagonzalo, C.D.; Esguerra, J.P.H.; Soriano, M.N.; Bornales, J.B.; Carpio-Bernido, M.V.; Bernido, C.C.
2017-01-01
In this article we set up a microscopic model for the spread of an infectious disease based on configuration space analysis. Using the so-called Vlasov scaling we obtained the corresponding mesoscopic (kinetic) equations, describing the density of susceptible and infected individuals (particles) in
Spatial Correlation Of Streamflows: An Analytical Approach
Betterle, A.; Schirmer, M.; Botter, G.
2016-12-01
The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the
Improved steamflood analytical model
Chandra, S.; Mamora, D.D. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas A and M Univ., TX (United States)
2005-11-01
Predicting the performance of steam flooding can help in the proper execution of enhanced oil recovery (EOR) processes. The Jones model is often used for analytical steam flooding performance prediction, but it does not accurately predict oil production peaks. In this study, an improved steam flood model was developed by modifying 2 of the 3 components of the capture factor in the Jones model. The modifications were based on simulation results from a Society of Petroleum Engineers (SPE) comparative project case model. The production performance of a 5-spot steamflood pattern unit was simulated and compared with results obtained from the Jones model. Three reservoir types were simulated through the use of 3-D Cartesian black oil models. In order to correlate the simulation and the Jones analytical model results for the start and height of the production peak, the dimensionless steam zone size was modified to account for a decrease in oil viscosity during steam flooding and its dependence on the steam injection rate. In addition, the dimensionless volume of displaced oil produced was modified from its square-root format to an exponential form. The modified model improved results for production performance by up to 20 years of simulated steam flooding, compared to the Jones model. Results agreed with simulation results for 13 different cases, including 3 different sets of reservoir and fluid properties. Reservoir engineers will benefit from the improved accuracy of the model. Oil displacement calculations were based on methods proposed in earlier research, in which the oil displacement rate is a function of cumulative oil steam ratio. The cumulative oil steam ratio is a function of overall thermal efficiency. Capture factor component formulae were presented, as well as charts of oil production rates and cumulative oil-steam ratios for various reservoirs. 13 refs., 4 tabs., 29 figs.
Applications of Spatial Data Using Business Analytics Tools
Anca Ioana ANDREESCU
2011-12-01
Full Text Available This paper addresses the possibilities of using spatial data in business analytics tools, with emphasis on SAS software. Various kinds of map data sets containing spatial data are presented and discussed. Examples of map charts illustrating macroeconomic parameters demonstrate the application of spatial data for the creation of map charts in SAS Enterprise Guise. Extended features of map charts are being exemplified by producing charts via SAS programming procedures.
Lawson, Andrew B
2002-01-01
Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...
Analytic Modeling of Insurgencies
2014-08-01
Counterinsurgency, Situational Awareness, Civilians, Lanchester 1. Introduction Combat modeling is one of the oldest areas of operations research, dating...Army. The ground-breaking work of Lanchester in 1916 [1] marks the beginning of formal models of conflicts, where mathematical formulas and, later...Warfare model [3], which is a Lanchester - based mathematical model (see more details about this model later on), and McCormick’s Magic Diamond model [4
Fitzenreiter, R. J.; Scudder, J. D.; Klimas, A. J.
1990-01-01
A model which is consistent with the solar wind and shock surface boundary conditions for the foreshock electron distribution in the absence of wave-particle effects is formulated for an arbitrary location behind the magnetic tangent to the earth's bow shock. Variations of the gyrophase-averaged velocity distribution are compared and contrasted with in situ ISEE observations. It is found that magnetic mirroring of solar wind electrons is the most important process by which nonmonotonic reduced electron distributions in the foreshock are produced. Leakage of particles from the magnetosheath is shown to be relatively unimportant in determining reduced distributions that are nonmonotonic. The two-dimensional distribution function off the magnetic field direction is the crucial contribution in producing reduced distributions which have beams. The time scale for modification of the electron velocity distribution in velocity space can be significantly influenced by steady state spatial gradients in the background imposed by the curved shock geometry.
Fitzenreiter, R.J.; Scudder, J.D.; Klimas, A.J.
1990-01-01
A model of the gyrophase-averaged electron distribution in the Earth's foreshock consistent with boundary conditions at the bow shock and in the solar wind has been constructed according to the reversible guiding center characteristics and compared with ISEE electron and wave observations. This model demonstrates (1) that the basic features and morphology of beams in the observed and reduced distributions F(υ parallel ) are determined almost exclusively by the solar wind electrons mirrored at the shock's magnetic ramp and are relatively insensitive to the leakage fluxes from the magnetosheath, (2) that the wave particle modifications have been detected by contrasting the reversible model with the direct observations, (3) that the nonmonotonic reduced distributions F(υ parallel ) are rarely the result of a nonmonotonic energy spectra but are rather the result of the transverse velocity space integration necessary to produce F(υ parallel ) from the directly observed electron distribution function f(v), (4) that the time scale for beam resupply to F(υ parallel ) from the dc spatial gradients of the self-consistent reversible distribution function can have a factor of 100 variation across the foreshock, being shortest within a few degrees of the magnetic tangent surface, (5) that the beams predicted by the model have strongly varying and correlated variations of mean energy, thermal spread, and number density with angular departure from the magnetic tangent with the coldest, most tenuous, and lowest mean energy beams suggested to be present deep behind the magnetic tangent (≅5 degree-10 degree), and (6) that the lowest-energy beams have low contrast to the background solar wind distributing and although difficult to detect have beam density and temperature parameters compatible with ω pe growth of electrostatic waves
An analytical evaluation for spatial-dependent intra-pebble Dancoff factor and escape probability
Kim, Songhyun; Kim, Hong-Chul; Kim, Jong Kyung; Kim, Soon Young; Noh, Jae Man
2009-01-01
The analytical evaluation of spatial-dependent intra-pebble Dancoff factors and their escape probabilities is pursued by the model developed in this study. Intra-pebble Dancoff factors and their escape probabilities are calculated as a function of fuel kernel radius, number of fuel kernels, and fuel region radius. The method in this study can be easily utilized to analyze the tendency of spatial-dependent intra-pebble Dancoff factor and spatial-dependent fuel region escape probability for the various geometries because it is faster than the MCNP method as well as good accuracy. (author)
Predictive analytics can support the ACO model.
Bradley, Paul
2012-04-01
Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.
Analytical methods used at model facility
Wing, N.S.
1984-01-01
A description of analytical methods used at the model LEU Fuel Fabrication Facility is presented. The methods include gravimetric uranium analysis, isotopic analysis, fluorimetric analysis, and emission spectroscopy
Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.
Endert, A; Fiaux, P; North, C
2012-12-01
Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.
Thermodynamic Model of Spatial Memory
Kaufman, Miron; Allen, P.
1998-03-01
We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.
Big Data analytics in the Geo-Spatial Domain
R.A. Goncalves (Romulo); M.G. Ivanova (Milena); M.L. Kersten (Martin); H. Scholten; S. Zlatanova; F. Alvanaki (Foteini); P. Nourian (Pirouz); E. Dias
2014-01-01
htmlabstractBig data collections in many scientific domains have inherently rich spatial and geo-spatial features. Spatial location is among the core aspects of data in Earth observation sciences, astronomy, and seismology to name a few. The goal of our project is to design an efficient data
A nonlocal spatial model for Lyme disease
Yu, Xiao; Zhao, Xiao-Qiang
2016-07-01
This paper is devoted to the study of a nonlocal and time-delayed reaction-diffusion model for Lyme disease with a spatially heterogeneous structure. In the case of a bounded domain, we first prove the existence of the positive steady state and a threshold type result for the disease-free system, and then establish the global dynamics for the model system in terms of the basic reproduction number. In the case of an unbound domain, we obtain the existence of the disease spreading speed and its coincidence with the minimal wave speed. At last, we use numerical simulations to verify our analytic results and investigate the influence of model parameters and spatial heterogeneity on the disease infection risk.
A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics
Tian, Yuan; Liu, Zhuo; Klasky, Scott; Wang, Bin; Abbasi, Hasan; Zhou, Shujia; Podhorszki, Norbert; Clune, Tom; Logan, Jeremy; Yu, Weikuan
2013-01-01
In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.
Analytic solution of the Starobinsky model for inflation
Paliathanasis, Andronikos [Universidad Austral de Chile, Instituto de Ciencias Fisicas y Matematicas, Valdivia (Chile); Durban University of Technology, Institute of Systems Science, Durban (South Africa)
2017-07-15
We prove that the field equations of the Starobinsky model for inflation in a Friedmann-Lemaitre-Robertson-Walker metric constitute an integrable system. The analytical solution in terms of a Painleve series for the Starobinsky model is presented for the case of zero and nonzero spatial curvature. In both cases the leading-order term describes the radiation era provided by the corresponding higher-order theory. (orig.)
Analytical Model for Sensor Placement on Microprocessors
Lee, Kyeong-Jae; Skadron, Kevin; Huang, Wei
2005-01-01
.... In this paper, we present an analytical model that describes the maximum temperature differential between a hot spot and a region of interest based on their distance and processor packaging information...
Analytic nearest neighbour model for FCC metals
Idiodi, J.O.A.; Garba, E.J.D.; Akinlade, O.
1991-06-01
A recently proposed analytic nearest-neighbour model for fcc metals is criticised and two alternative nearest-neighbour models derived from the separable potential method (SPM) are recommended. Results for copper and aluminium illustrate the utility of the recommended models. (author). 20 refs, 5 tabs
Extinction threshold of a population in spatial and stochastic model
Soroka, Yevheniia; Rublyov, Bogdan
2016-01-01
In this study, spatial stochastic and logistic model (SSLM) describing dynamics of a population of a certain species was analysed. The behaviour of the extinction threshold as a function of model parameters was studied. More specifically, we studied how the critical values for the model parameters that separate the cases of extinction and persistence depend on the spatial scales of the competition and dispersal kernels. We compared the simulations and analytical results to examine if and how ...
Analytical eigenstates for the quantum Rabi model
Zhong, Honghua; Xie, Qiongtao; Lee, Chaohong; Batchelor, Murray T
2013-01-01
We develop a method to find analytical solutions for the eigenstates of the quantum Rabi model. These include symmetric, anti-symmetric and asymmetric analytic solutions given in terms of the confluent Heun functions. Both regular and exceptional solutions are given in a unified form. In addition, the analytic conditions for determining the energy spectrum are obtained. Our results show that conditions proposed by Braak (2011 Phys. Rev. Lett. 107 100401) are a type of sufficiency condition for determining the regular solutions. The well-known Judd isolated exact solutions appear naturally as truncations of the confluent Heun functions. (paper)
Competition in spatial location models
Webers, H.M.
1996-01-01
Models of spatial competition are designed and analyzed to describe the fact that space, by its very nature, is a source of market power. This field of research, lying at the interface of game theory and economics, has attracted much interest because location problems are related to many aspects of
Analytical theory of Doppler reflectometry in slab plasma model
Gusakov, E.Z.; Surkov, A.V. [Ioffe Institute, Politekhnicheskaya 26, St. Petersburg (Russian Federation)
2004-07-01
Doppler reflectometry is considered in slab plasma model in the frameworks of analytical theory. The diagnostics locality is analyzed for both regimes: linear and nonlinear in turbulence amplitude. The toroidal antenna focusing of probing beam to the cut-off is proposed and discussed as a method to increase diagnostics spatial resolution. It is shown that even in the case of nonlinear regime of multiple scattering, the diagnostics can be used for an estimation (with certain accuracy) of plasma poloidal rotation profile. (authors)
An analytic uranium sources model
Singer, C.E.
2001-01-01
This document presents a method for estimating uranium resources as a continuous function of extraction costs and describing the uncertainty in the resulting fit. The estimated functions provide convenient extrapolations of currently available data on uranium extraction cost and can be used to predict the effect of resource depletion on future uranium supply costs. As such, they are a useful input for economic models of the nuclear energy sector. The method described here pays careful attention to minimizing built-in biases in the fitting procedure and defines ways to describe the uncertainty in the resulting fits in order to render the procedure and its results useful to the widest possible variety of potential users. (author)
Analytical model for screening potential CO2 repositories
Okwen, R.T.; Stewart, M.T.; Cunningham, J.A.
2011-01-01
Assessing potential repositories for geologic sequestration of carbon dioxide using numerical models can be complicated, costly, and time-consuming, especially when faced with the challenge of selecting a repository from a multitude of potential repositories. This paper presents a set of simple analytical equations (model), based on the work of previous researchers, that could be used to evaluate the suitability of candidate repositories for subsurface sequestration of carbon dioxide. We considered the injection of carbon dioxide at a constant rate into a confined saline aquifer via a fully perforated vertical injection well. The validity of the analytical model was assessed via comparison with the TOUGH2 numerical model. The metrics used in comparing the two models include (1) spatial variations in formation pressure and (2) vertically integrated brine saturation profile. The analytical model and TOUGH2 show excellent agreement in their results when similar input conditions and assumptions are applied in both. The analytical model neglects capillary pressure and the pressure dependence of fluid properties. However, simulations in TOUGH2 indicate that little error is introduced by these simplifications. Sensitivity studies indicate that the agreement between the analytical model and TOUGH2 depends strongly on (1) the residual brine saturation, (2) the difference in density between carbon dioxide and resident brine (buoyancy), and (3) the relationship between relative permeability and brine saturation. The results achieved suggest that the analytical model is valid when the relationship between relative permeability and brine saturation is linear or quasi-linear and when the irreducible saturation of brine is zero or very small. ?? 2011 Springer Science+Business Media B.V.
MASCOTTE: analytical model of eddy current signals
Delsarte, G.; Levy, R.
1992-01-01
Tube examination is a major application of the eddy current technique in the nuclear and petrochemical industries. Such examination configurations being specially adapted to analytical modes, a physical model is developed on portable computers. It includes simple approximations made possible by the effective conditions of the examinations. The eddy current signal is described by an analytical formulation that takes into account the tube dimensions, the sensor conception, the physical characteristics of the defect and the examination parameters. Moreover, the model makes it possible to associate real signals and simulated signals
Modeling of the Global Water Cycle - Analytical Models
Yongqiang Liu; Roni Avissar
2005-01-01
Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...
Flood Risk Assessment in Urban Areas Based on Spatial Analytics and Social Factors
Costas Armenakis
2017-11-01
Full Text Available Flood maps alone are not sufficient to determine and assess the risks to people, property, infrastructure, and services due to a flood event. Simply put, the risk is almost zero to minimum if the flooded region is “empty” (i.e., unpopulated, has not properties, no industry, no infrastructure, and no socio-economic activity. High spatial resolution Earth Observation (EO data can contribute to the generation and updating of flood risk maps based on several aspects including population, economic development, and critical infrastructure, which can enhance a city’s flood mitigation and preparedness planning. In this case study for the Don River watershed, Toronto, the flood risk is determined and flood risk index maps are generated by implementing a methodology for estimating risk based on the geographic coverage of the flood hazard, vulnerability of people, and the exposure of large building structures to flood water. Specifically, the spatial flood risk index maps have been generated through analytical spatial modeling which takes into account the areas in which a flood hazard is expected to occur, the terrain’s morphological characteristics, socio-economic parameters based on demographic data, and the density of large building complexes. Generated flood risk maps are verified through visual inspection with 3D city flood maps. Findings illustrate that areas of higher flood risk coincide with areas of high flood hazard and social and building exposure vulnerability.
Analytical model for Stirling cycle machine design
Formosa, F. [Laboratoire SYMME, Universite de Savoie, BP 80439, 74944 Annecy le Vieux Cedex (France); Despesse, G. [Laboratoire Capteurs Actionneurs et Recuperation d' Energie, CEA-LETI-MINATEC, Grenoble (France)
2010-10-15
In order to study further the promising free piston Stirling engine architecture, there is a need of an analytical thermodynamic model which could be used in a dynamical analysis for preliminary design. To aim at more realistic values, the models have to take into account the heat losses and irreversibilities on the engine. An analytical model which encompasses the critical flaws of the regenerator and furthermore the heat exchangers effectivenesses has been developed. This model has been validated using the whole range of the experimental data available from the General Motor GPU-3 Stirling engine prototype. The effects of the technological and operating parameters on Stirling engine performance have been investigated. In addition to the regenerator influence, the effect of the cooler effectiveness is underlined. (author)
Integrative Spatial Data Analytics for Public Health Studies of New York State.
Chen, Xin; Wang, Fusheng
2016-01-01
Increased accessibility of health data made available by the government provides unique opportunity for spatial analytics with much higher resolution to discover patterns of diseases, and their correlation with spatial impact indicators. This paper demonstrated our vision of integrative spatial analytics for public health by linking the New York Cancer Mapping Dataset with datasets containing potential spatial impact indicators. We performed spatial based discovery of disease patterns and variations across New York State, and identify potential correlations between diseases and demographic, socio-economic and environmental indicators. Our methods were validated by three correlation studies: the correlation between stomach cancer and Asian race, the correlation between breast cancer and high education population, and the correlation between lung cancer and air toxics. Our work will allow public health researchers, government officials or other practitioners to adequately identify, analyze, and monitor health problems at the community or neighborhood level for New York State.
Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic
Natalia Andrienko
2015-04-01
Full Text Available By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists.
Automated statistical modeling of analytical measurement systems
Jacobson, J.J.
1992-01-01
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Big Data analytics in the Geo-Spatial Domain
R.A. Goncalves (Romulo); M.G. Ivanova (Milena); M.L. Kersten (Martin); H. Scholten; S. Zlatanova; F. Alvanaki (Foteini); P. Nourian (Pirouz); E. Dias
2014-01-01
htmlabstractDigital 3D city models play a crucial role in research of urban phenomena; they form the basis for flow simulations, urban planning, and analysis of underground formations. Urban scenes consist of large collections of semantically rich objects which have a large number of properties such
Effective modelling for predictive analytics in data science ...
Effective modelling for predictive analytics in data science. ... the nearabsence of empirical or factual predictive analytics in the mainstream research going on ... Keywords: Predictive Analytics, Big Data, Business Intelligence, Project Planning.
SIMMER-III analytic thermophysical property model
Morita, K; Tobita, Y.; Kondo, Sa.; Fischer, E.A.
1999-05-01
An analytic thermophysical property model using general function forms is developed for a reactor safety analysis code, SIMMER-III. The function forms are designed to represent correct behavior of properties of reactor-core materials over wide temperature ranges, especially for the thermal conductivity and the viscosity near the critical point. The most up-to-date and reliable sources for uranium dioxide, mixed-oxide fuel, stainless steel, and sodium available at present are used to determine parameters in the proposed functions. This model is also designed to be consistent with a SIMMER-III model on thermodynamic properties and equations of state for reactor-core materials. (author)
Continuous Spatial Process Models for Spatial Extreme Values
Sang, Huiyan; Gelfand, Alan E.
2010-01-01
process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters
Leveraging spatial abstraction in traffic analysis and forecasting with visual analytics
Andrienko, N.; Andrienko, G.; Rinzivillo, S.
2016-01-01
A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered that the traffic intensity (a.k.a. traffic flow or traffic flux) and the mean velocity are interrelated in a spatially abstracted transportation net...
Organizational Models for Big Data and Analytics
Robert L. Grossman
2014-04-01
Full Text Available In this article, we introduce a framework for determining how analytics capability should be distributed within an organization. Our framework stresses the importance of building a critical mass of analytics staff, centralizing or decentralizing the analytics staff to support business processes, and establishing an analytics governance structure to ensure that analytics processes are supported by the organization as a whole.
Analytical performance modeling for computer systems
Tay, Y C
2013-01-01
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems that they are interested in.Describing a complicated system abstractly with mathematical equations requires a careful choice of assumpti
An analytical model for interactive failures
Sun Yong; Ma Lin; Mathew, Joseph; Zhang Sheng
2006-01-01
In some systems, failures of certain components can interact with each other, and accelerate the failure rates of these components. These failures are defined as interactive failure. Interactive failure is a prevalent cause of failure associated with complex systems, particularly in mechanical systems. The failure risk of an asset will be underestimated if the interactive effect is ignored. When failure risk is assessed, interactive failures of an asset need to be considered. However, the literature is silent on previous research work in this field. This paper introduces the concepts of interactive failure, develops an analytical model to analyse this type of failure quantitatively, and verifies the model using case studies and experiments
Analytical model of the optical vortex microscope.
Płocinniczak, Łukasz; Popiołek-Masajada, Agnieszka; Masajada, Jan; Szatkowski, Mateusz
2016-04-20
This paper presents an analytical model of the optical vortex scanning microscope. In this microscope the Gaussian beam with an embedded optical vortex is focused into the sample plane. Additionally, the optical vortex can be moved inside the beam, which allows fine scanning of the sample. We provide an analytical solution of the whole path of the beam in the system (within paraxial approximation)-from the vortex lens to the observation plane situated on the CCD camera. The calculations are performed step by step from one optical element to the next. We show that at each step, the expression for light complex amplitude has the same form with only four coefficients modified. We also derive a simple expression for the vortex trajectory of small vortex displacements.
Building analytical three-field cosmological models
Santos, J.R.L. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Moraes, P.H.R.S. [ITA-Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP (Brazil); Ferreira, D.A. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, PB (Brazil); Neta, D.C.V. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Universidade Estadual da Paraiba, Departamento de Fisica, Campina Grande, PB (Brazil)
2018-02-15
A difficult task to deal with is the analytical treatment of models composed of three real scalar fields, as their equations of motion are in general coupled and hard to integrate. In order to overcome this problem we introduce a methodology to construct three-field models based on the so-called ''extension method''. The fundamental idea of the procedure is to combine three one-field systems in a non-trivial way, to construct an effective three scalar field model. An interesting scenario where the method can be implemented is with inflationary models, where the Einstein-Hilbert Lagrangian is coupled with the scalar field Lagrangian. We exemplify how a new model constructed from our method can lead to non-trivial behaviors for cosmological parameters. (orig.)
Analytical modelling of hydrogen transport in reactor containments
Manno, V.P.
1983-09-01
A versatile computational model of hydrogen transport in nuclear plant containment buildings is developed. The background and significance of hydrogen-related nuclear safety issues are discussed. A computer program is constructed that embodies the analytical models. The thermofluid dynamic formulation spans a wide applicability range from rapid two-phase blowdown transients to slow incompressible hydrogen injection. Detailed ancillary models of molecular and turbulent diffusion, mixture transport properties, multi-phase multicomponent thermodynamics and heat sink modelling are addressed. The numerical solution of the continuum equations emphasizes both accuracy and efficiency in the employment of relatively coarse discretization and long time steps. Reducing undesirable numerical diffusion is addressed. Problem geometry options include lumped parameter zones, one dimensional meshs, two dimensional Cartesian or axisymmetric coordinate systems and three dimensional Cartesian or cylindrical regions. An efficient lumped nodal model is included for simulation of events in which spatial resolution is not significant. Several validation calculations are reported
Cheng-Xiang Wang
2007-02-01
Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.
Analytical modeling of worldwide medical radiation use
Mettler, F.A. Jr.; Davis, M.; Kelsey, C.A.; Rosenberg, R.; Williams, A.
1987-01-01
An analytical model was developed to estimate the availability and frequency of medical radiation use on a worldwide basis. This model includes medical and dental x-ray, nuclear medicine, and radiation therapy. The development of an analytical model is necessary as the first step in estimating the radiation dose to the world's population from this source. Since there is no data about the frequency of medical radiation use in more than half the countries in the world and only fragmentary data in an additional one-fourth of the world's countries, such a model can be used to predict the uses of medical radiation in these countries. The model indicates that there are approximately 400,000 medical x-ray machines worldwide and that approximately 1.2 billion diagnostic medical x-ray examinations are performed annually. Dental x-ray examinations are estimated at 315 million annually and approximately 22 million in-vivo diagnostic nuclear medicine examinations. Approximately 4 million radiation therapy procedures or courses of treatment are undertaken annually
Analytic models of plausible gravitational lens potentials
Baltz, Edward A.; Marshall, Phil; Oguri, Masamune
2009-01-01
Gravitational lenses on galaxy scales are plausibly modelled as having ellipsoidal symmetry and a universal dark matter density profile, with a Sérsic profile to describe the distribution of baryonic matter. Predicting all lensing effects requires knowledge of the total lens potential: in this work we give analytic forms for that of the above hybrid model. Emphasising that complex lens potentials can be constructed from simpler components in linear combination, we provide a recipe for attaining elliptical symmetry in either projected mass or lens potential. We also provide analytic formulae for the lens potentials of Sérsic profiles for integer and half-integer index. We then present formulae describing the gravitational lensing effects due to smoothly-truncated universal density profiles in cold dark matter model. For our isolated haloes the density profile falls off as radius to the minus fifth or seventh power beyond the tidal radius, functional forms that allow all orders of lens potential derivatives to be calculated analytically, while ensuring a non-divergent total mass. We show how the observables predicted by this profile differ from that of the original infinite-mass NFW profile. Expressions for the gravitational flexion are highlighted. We show how decreasing the tidal radius allows stripped haloes to be modelled, providing a framework for a fuller investigation of dark matter substructure in galaxies and clusters. Finally we remark on the need for finite mass halo profiles when doing cosmological ray-tracing simulations, and the need for readily-calculable higher order derivatives of the lens potential when studying catastrophes in strong lenses
An analytical model of flagellate hydrodynamics
Dölger, Julia; Bohr, Tomas; Andersen, Anders Peter
2017-01-01
solution by Oseen for the low Reynolds number flow due to a point force outside a no-slip sphere. The no-slip sphere represents the cell and the point force a single flagellum. By superposition we are able to model a freely swimming flagellate with several flagella. For biflagellates with left......–right symmetric flagellar arrangements we determine the swimming velocity, and we show that transversal forces due to the periodic movements of the flagella can promote swimming. For a model flagellate with both a longitudinal and a transversal flagellum we determine radius and pitch of the helical swimming......Flagellates are unicellular microswimmers that propel themselves using one or several beating flagella. We consider a hydrodynamic model of flagellates and explore the effect of flagellar arrangement and beat pattern on swimming kinematics and near-cell flow. The model is based on the analytical...
Michael, J.R.; Williams, D.B.
1990-01-01
The X-ray microanalytical spatial resolution is determined experimentally in various analytical electron microscopes by measuring the degradation of an atomically discrete composition profile across an interphase interface in a thin-foil of Ni-Cr-Fe. The experimental spatial resolutions are then compared with calculated values. The calculated spatial resolutions are obtained by the mathematical convolution of the electron probe size with an assumed beam-broadening distribution and the single-scattering model of beam broadening. The probe size is measured directly from an image of the probe in a TEM/SETEM and indirectly from dark-field signal changes resulting from scanning the probe across the edge of an MgO crystal in a dedicated STEM. This study demonstrates the applicability of the convolution technique to the calculation of the microanalytical spatial resolution obtained in the analytical electron microscope. It is demonstrated that, contrary to popular opinion, the electron probe size has a major impact on the measured spatial resolution in foils < 150 nm thick. (author)
Analytical model of internally coupled ears
Vossen, Christine; Christensen-Dalsgaard, Jakob; Leo van Hemmen, J
2010-01-01
Lizards and many birds possess a specialized hearing mechanism: internally coupled ears where the tympanic membranes connect through a large mouth cavity so that the vibrations of the tympanic membranes influence each other. This coupling enhances the phase differences and creates amplitude...... additionally provides the opportunity to incorporate the effect of the asymmetrically attached columella, which leads to the activation of higher membrane vibration modes. Incorporating this effect, the analytical model can explain measurements taken from the tympanic membrane of a living lizard, for example...
An analytical model for climatic predictions
Njau, E.C.
1990-12-01
A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs
Continuous Spatial Process Models for Spatial Extreme Values
Sang, Huiyan
2010-01-28
We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ specified in the latent stage to reflect underlying spatio-temporal structure. The novelty here is that we relax the conditionally independence assumption in the first stage of the hierarchial model, an assumption which has been adopted in previous work. This assumption implies that realizations of the the surface of spatial maxima will be everywhere discontinuous. For many phenomena including, e. g., temperature and precipitation, this behavior is inappropriate. Instead, we offer a spatial process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters. In this sense, the first stage smoothing is viewed as fine scale or short range smoothing while the larger scale smoothing will be captured in the second stage of the modeling. In addition, as would be desired, we are able to implement spatial interpolation for extreme values based on this model. A simulation study and a study on actual annual maximum rainfall for a region in South Africa are used to illustrate the performance of the model. © 2009 International Biometric Society.
An analytical model for enantioseparation process in capillary electrophoresis
Ranzuglia, G. A.; Manzi, S. J.; Gomez, M. R.; Belardinelli, R. E.; Pereyra, V. D.
2017-12-01
An analytical model to explain the mobilities of enantiomer binary mixture in capillary electrophoresis experiment is proposed. The model consists in a set of kinetic equations describing the evolution of the populations of molecules involved in the enantioseparation process in capillary electrophoresis (CE) is proposed. These equations take into account the asymmetric driven migration of enantiomer molecules, chiral selector and the temporary diastomeric complexes, which are the products of the reversible reaction between the enantiomers and the chiral selector. The solution of these equations gives the spatial and temporal distribution of each species in the capillary, reproducing a typical signal of the electropherogram. The mobility, μ, of each specie is obtained by the position of the maximum (main peak) of their respective distributions. Thereby, the apparent electrophoretic mobility difference, Δμ, as a function of chiral selector concentration, [ C ] , can be measured. The behaviour of Δμ versus [ C ] is compared with the phenomenological model introduced by Wren and Rowe in J. Chromatography 1992, 603, 235. To test the analytical model, a capillary electrophoresis experiment for the enantiomeric separation of the (±)-chlorpheniramine β-cyclodextrin (β-CD) system is used. These data, as well as, other obtained from literature are in closed agreement with those obtained by the model. All these results are also corroborate by kinetic Monte Carlo simulation.
Spatial data quality and coastal spill modelling
Li, Y.; Brimicombe, A.J.; Ralphs, M.P.
1998-01-01
Issues of spatial data quality are central to the whole oil spill modelling process. Both model and data quality performance issues should be considered as indispensable parts of a complete oil spill model specification and testing procedure. This paper presents initial results of research that will emphasise to modeler and manager alike the practical issues of spatial data quality for coastal oil spill modelling. It is centred around a case study of Jiao Zhou Bay in the People's Republic of China. The implications for coastal oil spill modelling are discussed and some strategies for managing the effects of spatial data quality in the outputs of oil spill modelling are explored. (author)
Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam
2017-03-01
While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in
Vlacholia, Maria; Vosniadou, Stella; Roussos, Petros; Salta, Katerina; Kazi, Smaragda; Sigalas, Michael; Tzougraki, Chryssa
2017-01-01
We present two studies that investigated the adoption of visual/spatial and analytic strategies by individuals at different levels of expertise in the area of organic chemistry, using the Visual Analytic Chemistry Task (VACT). The VACT allows the direct detection of analytic strategy use without drawing inferences about underlying mental…
Quasi-analytical treatment of spatially averaged radiation transfer in complex terrain
LöWe, H.; Helbig, N.
2012-10-01
We provide a new quasi-analytical method to compute the subgrid topographic influences on the shortwave radiation fluxes and the effective albedo in complex terrain as required for large-scale meteorological, land surface, or climate models. We investigate radiative transfer in complex terrain via the radiosity equation on isotropic Gaussian random fields. Under controlled approximations we derive expressions for domain-averaged fluxes of direct, diffuse, and terrain radiation and the sky view factor. Domain-averaged quantities can be related to a type of level-crossing probability of the random field, which is approximated by long-standing results developed for acoustic scattering at ocean boundaries. This allows us to express all nonlocal horizon effects in terms of a local terrain parameter, namely, the mean-square slope. Emerging integrals are computed numerically, and fit formulas are given for practical purposes. As an implication of our approach, we provide an expression for the effective albedo of complex terrain in terms of the Sun elevation angle, mean-square slope, the area-averaged surface albedo, and the ratio of atmospheric direct beam to diffuse radiation. For demonstration we compute the decrease of the effective albedo relative to the area-averaged albedo in Switzerland for idealized snow-covered and clear-sky conditions at noon in winter. We find an average decrease of 5.8% and spatial patterns which originate from characteristics of the underlying relief. Limitations and possible generalizations of the method are discussed.
Bayesian Spatial Modelling with R-INLA
Finn Lindgren
2015-02-01
Full Text Available The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA approach proposed by Rue, Martino, and Chopin (2009 is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized linear mixed to spatial and spatio-temporal models. Combined with the stochastic partial differential equation approach (SPDE, Lindgren, Rue, and Lindstrm 2011, one can accommodate all kinds of geographically referenced data, including areal and geostatistical ones, as well as spatial point process data. The implementation interface covers stationary spatial mod- els, non-stationary spatial models, and also spatio-temporal models, and is applicable in epidemiology, ecology, environmental risk assessment, as well as general geostatistics.
Approximate analytical modeling of leptospirosis infection
Ismail, Nur Atikah; Azmi, Amirah; Yusof, Fauzi Mohamed; Ismail, Ahmad Izani
2017-11-01
Leptospirosis is an infectious disease carried by rodents which can cause death in humans. The disease spreads directly through contact with feces, urine or through bites of infected rodents and indirectly via water contaminated with urine and droppings from them. Significant increase in the number of leptospirosis cases in Malaysia caused by the recent severe floods were recorded during heavy rainfall season. Therefore, to understand the dynamics of leptospirosis infection, a mathematical model based on fractional differential equations have been developed and analyzed. In this paper an approximate analytical method, the multi-step Laplace Adomian decomposition method, has been used to conduct numerical simulations so as to gain insight on the spread of leptospirosis infection.
Simple Analytic Models of Gravitational Collapse
Adler, R.
2005-02-09
Most general relativity textbooks devote considerable space to the simplest example of a black hole containing a singularity, the Schwarzschild geometry. However only a few discuss the dynamical process of gravitational collapse, by which black holes and singularities form. We present here two types of analytic models for this process, which we believe are the simplest available; the first involves collapsing spherical shells of light, analyzed mainly in Eddington-Finkelstein coordinates; the second involves collapsing spheres filled with a perfect fluid, analyzed mainly in Painleve-Gullstrand coordinates. Our main goal is pedagogical simplicity and algebraic completeness, but we also present some results that we believe are new, such as the collapse of a light shell in Kruskal-Szekeres coordinates.
An analytical model of flagellate hydrodynamics
Dölger, Julia; Bohr, Tomas; Andersen, Anders
2017-01-01
Flagellates are unicellular microswimmers that propel themselves using one or several beating flagella. We consider a hydrodynamic model of flagellates and explore the effect of flagellar arrangement and beat pattern on swimming kinematics and near-cell flow. The model is based on the analytical solution by Oseen for the low Reynolds number flow due to a point force outside a no-slip sphere. The no-slip sphere represents the cell and the point force a single flagellum. By superposition we are able to model a freely swimming flagellate with several flagella. For biflagellates with left–right symmetric flagellar arrangements we determine the swimming velocity, and we show that transversal forces due to the periodic movements of the flagella can promote swimming. For a model flagellate with both a longitudinal and a transversal flagellum we determine radius and pitch of the helical swimming trajectory. We find that the longitudinal flagellum is responsible for the average translational motion whereas the transversal flagellum governs the rotational motion. Finally, we show that the transversal flagellum can lead to strong feeding currents to localized capture sites on the cell surface. (paper)
Core monitoring with analytical model adaption
Linford, R.B.; Martin, C.L.; Parkos, G.R.; Rahnema, F.; Williams, R.D.
1992-01-01
The monitoring of BWR cores has evolved rapidly due to more capable computer systems, improved analytical models and new types of core instrumentation. Coupling of first principles diffusion theory models such as applied to design to the core instrumentation has been achieved by GE with an adaptive methodology in the 3D Minicore system. The adaptive methods allow definition of 'leakage parameters' which are incorporated directly into the diffusion models to enhance monitoring accuracy and predictions. These improved models for core monitoring allow for substitution of traversing in-core probe (TIP) and local power range monitor (LPRM) with calculations to continue monitoring with no loss of accuracy or reduction of thermal limits. Experience in small BWR cores has shown that with one out of three TIP machines failed there was no operating limitation or impact from the substitute calculations. Other capabilities exist in 3D Monicore to align TIPs more accurately and accommodate other types of system measurements or anomalies. 3D Monicore also includes an accurate predictive capability which uses the adaptive results from previous monitoring calculations and is used to plan and optimize reactor maneuvers/operations to improve operating efficiency and reduce support requirements
Reducing Spatial Data Complexity for Classification Models
Ruta, Dymitr; Gabrys, Bogdan
2007-01-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Reducing Spatial Data Complexity for Classification Models
Ruta, Dymitr; Gabrys, Bogdan
2007-11-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Intelligent spatial ecosystem modeling using parallel processors
Maxwell, T.; Costanza, R.
1993-01-01
Spatial modeling of ecosystems is essential if one's modeling goals include developing a relatively realistic description of past behavior and predictions of the impacts of alternative management policies on future ecosystem behavior. Development of these models has been limited in the past by the large amount of input data required and the difficulty of even large mainframe serial computers in dealing with large spatial arrays. These two limitations have begun to erode with the increasing availability of remote sensing data and GIS systems to manipulate it, and the development of parallel computer systems which allow computation of large, complex, spatial arrays. Although many forms of dynamic spatial modeling are highly amenable to parallel processing, the primary focus in this project is on process-based landscape models. These models simulate spatial structure by first compartmentalizing the landscape into some geometric design and then describing flows within compartments and spatial processes between compartments according to location-specific algorithms. The authors are currently building and running parallel spatial models at the regional scale for the Patuxent River region in Maryland, the Everglades in Florida, and Barataria Basin in Louisiana. The authors are also planning a project to construct a series of spatially explicit linked ecological and economic simulation models aimed at assessing the long-term potential impacts of global climate change
Dynamic spatial panels : models, methods, and inferences
Elhorst, J. Paul
This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent
Ibmdbpy-spatial : An Open-source implementation of in-database geospatial analytics in Python
Roy, Avipsa; Fouché, Edouard; Rodriguez Morales, Rafael; Moehler, Gregor
2017-04-01
As the amount of spatial data acquired from several geodetic sources has grown over the years and as data infrastructure has become more powerful, the need for adoption of in-database analytic technology within geosciences has grown rapidly. In-database analytics on spatial data stored in a traditional enterprise data warehouse enables much faster retrieval and analysis for making better predictions about risks and opportunities, identifying trends and spot anomalies. Although there are a number of open-source spatial analysis libraries like geopandas and shapely available today, most of them have been restricted to manipulation and analysis of geometric objects with a dependency on GEOS and similar libraries. We present an open-source software package, written in Python, to fill the gap between spatial analysis and in-database analytics. Ibmdbpy-spatial provides a geospatial extension to the ibmdbpy package, implemented in 2015. It provides an interface for spatial data manipulation and access to in-database algorithms in IBM dashDB, a data warehouse platform with a spatial extender that runs as a service on IBM's cloud platform called Bluemix. Working in-database reduces the network overload, as the complete data need not be replicated into the user's local system altogether and only a subset of the entire dataset can be fetched into memory in a single instance. Ibmdbpy-spatial accelerates Python analytics by seamlessly pushing operations written in Python into the underlying database for execution using the dashDB spatial extender, thereby benefiting from in-database performance-enhancing features, such as columnar storage and parallel processing. The package is currently supported on Python versions from 2.7 up to 3.4. The basic architecture of the package consists of three main components - 1) a connection to the dashDB represented by the instance IdaDataBase, which uses a middleware API namely - pypyodbc or jaydebeapi to establish the database connection via
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.
2017-01-01
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture
Optimizing multi-pinhole SPECT geometries using an analytical model
Rentmeester, M C M; Have, F van der; Beekman, F J
2007-01-01
State-of-the-art multi-pinhole SPECT devices allow for sub-mm resolution imaging of radio-molecule distributions in small laboratory animals. The optimization of multi-pinhole and detector geometries using simulations based on ray-tracing or Monte Carlo algorithms is time-consuming, particularly because many system parameters need to be varied. As an efficient alternative we develop a continuous analytical model of a pinhole SPECT system with a stationary detector set-up, which we apply to focused imaging of a mouse. The model assumes that the multi-pinhole collimator and the detector both have the shape of a spherical layer, and uses analytical expressions for effective pinhole diameters, sensitivity and spatial resolution. For fixed fields-of-view, a pinhole-diameter adapting feedback loop allows for the comparison of the system resolution of different systems at equal system sensitivity, and vice versa. The model predicts that (i) for optimal resolution or sensitivity the collimator layer with pinholes should be placed as closely as possible around the animal given a fixed detector layer, (ii) with high-resolution detectors a resolution improvement up to 31% can be achieved compared to optimized systems, (iii) high-resolution detectors can be placed close to the collimator without significant resolution losses, (iv) interestingly, systems with a physical pinhole diameter of 0 mm can have an excellent resolution when high-resolution detectors are used
An analytical model of iceberg drift
Eisenman, I.; Wagner, T. J. W.; Dell, R.
2017-12-01
Icebergs transport freshwater from glaciers and ice shelves, releasing the freshwater into the upper ocean thousands of kilometers from the source. This influences ocean circulation through its effect on seawater density. A standard empirical rule-of-thumb for estimating iceberg trajectories is that they drift at the ocean surface current velocity plus 2% of the atmospheric surface wind velocity. This relationship has been observed in empirical studies for decades, but it has never previously been physically derived or justified. In this presentation, we consider the momentum balance for an individual iceberg, which includes nonlinear drag terms. Applying a series of approximations, we derive an analytical solution for the iceberg velocity as a function of time. In order to validate the model, we force it with surface velocity and temperature data from an observational state estimate and compare the results with iceberg observations in both hemispheres. We show that the analytical solution reduces to the empirical 2% relationship in the asymptotic limit of small icebergs (or strong winds), which approximately applies for typical Arctic icebergs. We find that the 2% value arises due to a term involving the drag coefficients for water and air and the densities of the iceberg, ocean, and air. In the opposite limit of large icebergs (or weak winds), which approximately applies for typical Antarctic icebergs with horizontal length scales greater than about 12 km, we find that the 2% relationship is not applicable and that icebergs instead move with the ocean current, unaffected by the wind. The two asymptotic regimes can be understood by considering how iceberg size influences the relative importance of the wind and ocean current drag terms compared with the Coriolis and pressure gradient force terms in the iceberg momentum balance.
Suarez Antola, R.
2005-01-01
It was proponed recently to apply an extension of Lyapunov's first method to the non-linear regime, known as non-linear modal analysis (NMA), to the study of space-time problems in nuclear reactor kinetics, nuclear power plant dynamics and nuclear power plant instrumentation and control(1). The present communication shows how to apply NMA to the study of Xenon spatial oscillations in large nuclear reactors. The set of non-linear modal equations derived by J. Lewins(2) for neutron flux, Xenon concentration and Iodine concentration are discussed, and a modified version of these equations is taken as a starting point. Using the methods of singular perturbation theory a slow manifold is constructed in the space of mode amplitudes. This allows the reduction of the original high dimensional dynamics to a low dimensional one. It is shown how the amplitudes of the first mode for neutron flux field, temperature field and concentrations of Xenon and Iodine fields can have a stable steady state value while the corresponding amplitudes of the second mode oscillates in a stable limit cycle. The extrapolated dimensions of the reactor's core are used as bifurcation parameters. Approximate analytical formulae are obtained for the critical values of this parameters( below which the onset of oscillations is produced), for the period and for the amplitudes of the above mentioned oscillations. These results are applied to the discussion of neutron flux and temperature excursions in critical locations of the reactor's core. The results of NMA can be validated from the results obtained applying suitable computer codes, using homogenization theory(3) to link the complex heterogeneous model of the codes with the simplified mathematical model used for NMA
Analytic modeling of axisymmetric disruption halo currents
Humphreys, D.A.; Kellman, A.G.
1999-01-01
Currents which can flow in plasma facing components during disruptions pose a challenge to the design of next generation tokamaks. Induced toroidal eddy currents and both induced and conducted poloidal ''halo'' currents can produce design-limiting electromagnetic loads. While induction of toroidal and poloidal currents in passive structures is a well-understood phenomenon, the driving terms and scalings for poloidal currents flowing on open field lines during disruptions are less well established. A model of halo current evolution is presented in which the current is induced in the halo by decay of the plasma current and change in enclosed toroidal flux while being convected into the halo from the core by plasma motion. Fundamental physical processes and scalings are described in a simplified analytic version of the model. The peak axisymmetric halo current is found to depend on halo and core plasma characteristics during the current quench, including machine and plasma dimensions, resistivities, safety factor, and vertical stability growth rate. Two extreme regimes in poloidal halo current amplitude are identified depending on the minimum halo safety factor reached during the disruption. A 'type I' disruption is characterized by a minimum safety factor that remains relatively high (typically 2 - 3, comparable to the predisruption safety factor), and a relatively low poloidal halo current. A 'type II' disruption is characterized by a minimum safety factor comparable to unity and a relatively high poloidal halo current. Model predictions for these two regimes are found to agree well with halo current measurements from vertical displacement event disruptions in DIII-D [T. S. Taylor, K. H. Burrell, D. R. Baker, G. L. Jackson, R. J. La Haye, M. A. Mahdavi, R. Prater, T. C. Simonen, and A. D. Turnbull, open-quotes Results from the DIII-D Scientific Research Program,close quotes in Proceedings of the 17th IAEA Fusion Energy Conference, Yokohama, 1998, to be published in
A random spatial network model based on elementary postulates
Karlinger, Michael R.; Troutman, Brent M.
1989-01-01
A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
Hierarchical modeling and analysis for spatial data
Banerjee, Sudipto; Gelfand, Alan E
2003-01-01
Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat
Location Aggregation of Spatial Population CTMC Models
Luca Bortolussi
2016-10-01
Full Text Available In this paper we focus on spatial Markov population models, describing the stochastic evolution of populations of agents, explicitly modelling their spatial distribution, representing space as a discrete, finite graph. More specifically, we present a heuristic approach to aggregating spatial locations, which is designed to preserve the dynamical behaviour of the model whilst reducing the computational cost of analysis. Our approach combines stochastic approximation ideas (moment closure, linear noise, with computational statistics (spectral clustering to obtain an efficient aggregation, which is experimentally shown to be reasonably accurate on two case studies: an instance of epidemic spreading and a London bike sharing scenario.
Analytic Ballistic Performance Model of Whipple Shields
Miller, J. E.; Bjorkman, M. D.; Christiansen, E. L.; Ryan, S. J.
2015-01-01
The dual-wall, Whipple shield is the shield of choice for lightweight, long-duration flight. The shield uses an initial sacrificial wall to initiate fragmentation and melt an impacting threat that expands over a void before hitting a subsequent shield wall of a critical component. The key parameters to this type of shield are the rear wall and its mass which stops the debris, as well as the minimum shock wave strength generated by the threat particle impact of the sacrificial wall and the amount of room that is available for expansion. Ensuring the shock wave strength is sufficiently high to achieve large scale fragmentation/melt of the threat particle enables the expansion of the threat and reduces the momentum flux of the debris on the rear wall. Three key factors in the shock wave strength achieved are the thickness of the sacrificial wall relative to the characteristic dimension of the impacting particle, the density and material cohesion contrast of the sacrificial wall relative to the threat particle and the impact speed. The mass of the rear wall and the sacrificial wall are desirable to minimize for launch costs making it important to have an understanding of the effects of density contrast and impact speed. An analytic model is developed here, to describe the influence of these three key factors. In addition this paper develops a description of a fourth key parameter related to fragmentation and its role in establishing the onset of projectile expansion.
A spatial structural derivative model for ultraslow diffusion
Xu Wei
2017-01-01
Full Text Available This study investigates the ultraslow diffusion by a spatial structural derivative, in which the exponential function ex is selected as the structural function to construct the local structural derivative diffusion equation model. The analytical solution of the diffusion equation is a form of Biexponential distribution. Its corresponding mean squared displacement is numerically calculated, and increases more slowly than the logarithmic function of time. The local structural derivative diffusion equation with the structural function ex in space is an alternative physical and mathematical modeling model to characterize a kind of ultraslow diffusion.
An analytical approach to the CMB polarization in a spatially closed background
Niazy, Pedram; Abbassi, Amir H.
2018-03-01
The scalar mode polarization of the cosmic microwave background is derived in a spatially closed universe from the Boltzmann equation using the line of sight integral method. The EE and TE multipole coefficients have been extracted analytically by considering some tolerable approximations such as considering the evolution of perturbation hydrodynamically and sudden transition from opacity to transparency at the time of last scattering. As the major advantage of analytic expressions, CEE,ℓS and CTE,ℓ explicitly show the dependencies on baryon density ΩB, matter density ΩM, curvature ΩK, primordial spectral index ns, primordial power spectrum amplitude As, Optical depth τreion, recombination width σt and recombination time tL. Using a realistic set of cosmological parameters taken from a fit to data from Planck, the closed universe EE and TE power spectrums in the scalar mode are compared with numerical results from the CAMB code and also latest observational data. The analytic results agree with the numerical ones on the big and moderate scales. The peak positions are in good agreement with the numerical result on these scales while the peak heights agree with that to within 20% due to the approximations have been considered for these derivations. Also, several interesting properties of CMB polarization are revealed by the analytic spectra.
Spatial occupancy models for large data sets
Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.
2013-01-01
Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.
Global sensitivity analysis for models with spatially dependent outputs
Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.
2011-01-01
The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)
Evaluating spatial patterns in hydrological modelling
Koch, Julian
the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...... is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...
Analytic Models of High-Temperature Hohlraums
Stygar, W.A.; Olson, R.E.; Spielman, R.B.; Leeper, R.J.
2000-01-01
A unified set of high-temperature-hohlraum models has been developed. For a simple hohlraum, P s = (A s +(1minusα W )A W +A H )σT R 4 + (4Vσ/c)(dT R r /dt) where P S is the total power radiated by the source, A s is the source area, A W is the area of the cavity wall excluding the source and holes in the wall, A H is the area of the holes, σ is the Stefan-Boltzmann constant, T R is the radiation brightness temperature, V is the hohlraum volume, and c is the speed of light. The wall albedo α W triple b ond (T W /T R ) 4 where T W is the brightness temperature of area A W . The net power radiated by the source P N = P S -A S σT R 4 , which suggests that for laser-driven hohlraums the conversion efficiency η CE be defined as P N /P LASER . The characteristic time required to change T R 4 in response to a change in P N is 4V/C((lminusα W )A W +A H ). Using this model, T R , α W , and η CE can be expressed in terms of quantities directly measurable in a hohlraum experiment. For a steady-state hohlraum that encloses a convex capsule, P N = {(1minusα W )A W +A H +((1minusα C )(A S +A W α W )A C /A T = )}σT RC 4 where α C is the capsule albedo, A C is the capsule area, A T triple b ond (A S +A W +A H ), and T RC is the brightness temperature of the radiation that drives the capsule. According to this relation, the capsule-coupling efficiency of the baseline National-Ignition-Facility (NIF) hohlraum is 15% higher than predicted by previous analytic expressions. A model of a hohlraum that encloses a z pinch is also presented
New integrable models and analytical solutions in f (R ) cosmology with an ideal gas
Papagiannopoulos, G.; Basilakos, Spyros; Barrow, John D.; Paliathanasis, Andronikos
2018-01-01
In the context of f (R ) gravity with a spatially flat FLRW metric containing an ideal fluid, we use the method of invariant transformations to specify families of models which are integrable. We find three families of f (R ) theories for which new analytical solutions are given and closed-form solutions are provided.
Crime Modeling using Spatial Regression Approach
Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.
2018-01-01
Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.
Modeling and analytical simulation of a smouldering carbonaceous ...
Modeling and analytical simulation of a smouldering carbonaceous rod. A.A. Mohammed, R.O. Olayiwola, M Eseyin, A.A. Wachin. Abstract. Modeling of pyrolysis and combustion in a smouldering fuel bed requires the solution of flow, heat and mass transfer through porous media. This paper presents an analytical method ...
Casey, Beth M.; Lombardi, Caitlin McPherran; Pollock, Amanda; Fineman, Bonnie; Pezaris, Elizabeth
2017-01-01
This study investigated longitudinal pathways leading from early spatial skills in first-grade girls to their fifth-grade analytical math reasoning abilities (N = 138). First-grade assessments included spatial skills, verbal skills, addition/subtraction skills, and frequency of choice of a decomposition or retrieval strategy on the…
A simplified spatial model for BWR stability
Berman, Y.; Lederer, Y.; Meron, E.
2012-01-01
A spatial reduced order model for the study of BWR stability, based on the phenomenological model of March-Leuba et al., is presented. As one dimensional spatial dependence of the neutron flux, fuel temperature and void fraction is introduced, it is possible to describe both global and regional oscillations of the reactor power. Both linear stability analysis and numerical analysis were applied in order to describe the parameters which govern the model stability. The results were found qualitatively similar to past results. Doppler reactivity feedback was found essential for the explanation of the different regions of the flow-power stability map. (authors)
Spatial scale separation in regional climate modelling
Feser, F.
2005-07-01
In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter
Nonparametric Bayesian models for a spatial covariance.
Reich, Brian J; Fuentes, Montserrat
2012-01-01
A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.
Analytical models for low-power rectenna design
Akkermans, J.A.G.; Beurden, van M.C.; Doodeman, G.J.N.; Visser, H.J.
2005-01-01
The design of a low-cost rectenna for low-power applications is presented. The rectenna is designed with the use of analytical models and closed-form analytical expressions. This allows for a fast design of the rectenna system. To acquire a small-area rectenna, a layered design is proposed.
Analytically solvable models of reaction-diffusion systems
Zemskov, E P; Kassner, K [Institut fuer Theoretische Physik, Otto-von-Guericke-Universitaet, Universitaetsplatz 2, 39106 Magdeburg (Germany)
2004-05-01
We consider a class of analytically solvable models of reaction-diffusion systems. An analytical treatment is possible because the nonlinear reaction term is approximated by a piecewise linear function. As particular examples we choose front and pulse solutions to illustrate the matching procedure in the one-dimensional case.
Analytical modeling of masonry infilled steel frames
Flanagan, R.D.; Jones, W.D.; Bennett, R.M.
1991-01-01
A comprehensive program is underway at the Oak Ridge Y-12 Plant to evaluate the seismic capacity of unreinforced hollow clay tile infilled steel frames. This program has three major parts. First, preliminary numerical analyses are conducted to predict behavior, initial cracking loads, ultimate capacity loads, and to identify important parameters. Second, in-situ and laboratory tests are performed to obtain constitutive parameters and confirm predicted behavior. Finally, the analytical techniques are refined based on experimental results. This paper summarizes the findings of the preliminary numerical analyses. A review of current analytical methods was conducted and a subset of these methods was applied to known experimental results. Parametric studies were used to find the sensitivity of the behavior to various parameters. Both in-plane and out-of-plane loads were examined. Two types of out-of-plane behavior were examined, the inertial forces resulting from the mass of the infill panel and the out-of-plane forces resulting from interstory drift. Cracking loads were estimated using linear elastic analysis and an elliptical failure criterion. Calculated natural frequencies were correlated with low amplitude vibration testing. Ultimate behavior under inertial loads was estimated using a modified yield line procedure accounting for membrane stresses. The initial stiffness and ultimate capacity under in-plane loadings were predicted using finite element analyses. Results were compared to experimental data and to failure loads obtained using plastic collapse theory
Landscape Modelling and Simulation Using Spatial Data
Amjed Naser Mohsin AL-Hameedawi
2017-08-01
Full Text Available In this paper a procedure was performed for engendering spatial model of landscape acclimated to reality simulation. This procedure based on combining spatial data and field measurements with computer graphics reproduced using Blender software. Thereafter that we are possible to form a 3D simulation based on VIS ALL packages. The objective was to make a model utilising GIS, including inputs to the feature attribute data. The objective of these efforts concentrated on coordinating a tolerable spatial prototype, circumscribing facilitation scheme and outlining the intended framework. Thus; the eventual result was utilized in simulation form. The performed procedure contains not only data gathering, fieldwork and paradigm providing, but extended to supply a new method necessary to provide the respective 3D simulation mapping production, which authorises the decision makers as well as investors to achieve permanent acceptance an independent navigation system for Geoscience applications.
Analytical model for local scour prediction around hydrokinetic turbine foundations
Musa, M.; Heisel, M.; Hill, C.; Guala, M.
2017-12-01
Marine and Hydrokinetic renewable energy is an emerging sustainable and secure technology which produces clean energy harnessing water currents from mostly tidal and fluvial waterways. Hydrokinetic turbines are typically anchored at the bottom of the channel, which can be erodible or non-erodible. Recent experiments demonstrated the interactions between operating turbines and an erodible surface with sediment transport, resulting in a remarkable localized erosion-deposition pattern significantly larger than those observed by static in-river construction such as bridge piers, etc. Predicting local scour geometry at the base of hydrokinetic devices is extremely important during foundation design, installation, operation, and maintenance (IO&M), and long-term structural integrity. An analytical modeling framework is proposed applying the phenomenological theory of turbulence to the flow structures that promote the scouring process at the base of a turbine. The evolution of scour is directly linked to device operating conditions through the turbine drag force, which is inferred to locally dictate the energy dissipation rate in the scour region. The predictive model is validated using experimental data obtained at the University of Minnesota's St. Anthony Falls Laboratory (SAFL), covering two sediment mobility regimes (clear water and live bed), different turbine designs, hydraulic parameters, grain size distribution and bedform types. The model is applied to a potential prototype scale deployment in the lower Mississippi River, demonstrating its practical relevance and endorsing the feasibility of hydrokinetic energy power plants in large sandy rivers. Multi-turbine deployments are further studied experimentally by monitoring both local and non-local geomorphic effects introduced by a twelve turbine staggered array model installed in a wide channel at SAFL. Local scour behind each turbine is well captured by the theoretical predictive model. However, multi
Spatial Modeling for Resources Framework (SMRF)
Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed...
The 3-D global spatial data model foundation of the spatial data infrastructure
Burkholder, Earl F
2008-01-01
Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements. Modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure offers a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This groundbreaking spatial model incorporates both a functional model and a stochastic model to connect the physical world to the ECEF rectangular system. Combining horizontal and vertical data into a single, three-dimensional database, this authoritative monograph provides a logical development of theoretical concepts and practical tools that can be used to handle spatial data mo...
Li, W.; Shao, H.
2017-12-01
For geospatial cyberinfrastructure enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for the vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: 1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance (ADT) to meet various visualization requirements, and at the same time speed up simplification efficiency; 2) a progressive attribute transmission method to reduce data size and therefore the service response time; 3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to widen the use of web service providing vector data to support real-time spatial feature sharing, visual analytics and decision-making.
Analytical dynamic modeling of fast trilayer polypyrrole bending actuators
Amiri Moghadam, Amir Ali; Moavenian, Majid; Tahani, Masoud; Torabi, Keivan
2011-01-01
Analytical modeling of conjugated polymer actuators with complicated electro-chemo-mechanical dynamics is an interesting area for research, due to the wide range of applications including biomimetic robots and biomedical devices. Although there have been extensive reports on modeling the electrochemical dynamics of polypyrrole (PPy) bending actuators, mechanical dynamics modeling of the actuators remains unexplored. PPy actuators can operate with low voltage while producing large displacement in comparison to robotic joints, they do not have friction or backlash, but they suffer from some disadvantages such as creep and hysteresis. In this paper, a complete analytical dynamic model for fast trilayer polypyrrole bending actuators has been proposed and named the analytical multi-domain dynamic actuator (AMDDA) model. First an electrical admittance model of the actuator will be obtained based on a distributed RC line; subsequently a proper mechanical dynamic model will be derived, based on Hamilton's principle. The purposed modeling approach will be validated based on recently published experimental results
Analytical and numerical modeling of sandbanks dynamics
Idier, Deborah; Astruc, Dominique
2003-01-01
Linear and nonlinear behavior of large-scale underwater bedform patterns like sandbanks are studied using linear stability analysis and numerical modeling. The model is based on depth-integrated hydrodynamics equations with a quadratic bottom friction law and a bed load sediment transport model
An analytical model for beaconing in VANETs
van Eenennaam, Martijn; Remke, Anne Katharina Ingrid; Heijenk, Geert
2012-01-01
IEEE 802.11 CSMA/CA is generally considered to be well-understood, and many detailed models are available. However, most models focus on Unicast in small-scale W-LAN scenarios. When modelling beaconing in VANETs, the Broadcast nature and the (potentially) large number of nodes cause phenomena
Analytic Models for Sunlight Charging of a Rapidly Spinning Satellite
Tautz, Maurice
2003-01-01
... photoelectrons can be blocked by local potential barriers. In this report, we discuss two analytic models for sunlight charging of a rapidly spinning spherical satellite, both of which are based on blocked photoelectron currents...
Analytical Models Development of Compact Monopole Vortex Flows
Pavlo V. Lukianov
2017-09-01
Conclusions. The article contains series of the latest analytical models that describe both laminar and turbulent dynamics of monopole vortex flows which have not been reflected in traditional publications up to the present. The further research must be directed to search of analytical models for the coherent vortical structures in flows of viscous fluids, particularly near curved surfaces, where known in hydromechanics “wall law” is disturbed and heat and mass transfer anomalies take place.
Analytical solution of dispersion relations for the nuclear optical model
VanderKam, J.M. [Center for Communications Research, Thanet Road, Princeton, NJ 08540 (United States); Weisel, G.J. [Triangle Universities Nuclear Laboratory, and Duke University, Box 90308, Durham, NC 27708-0308 (United States); Penn State Altoona, 3000 Ivyside Park, Altoona, PA 16601-3760 (United States); Tornow, W. [Triangle Universities Nuclear Laboratory, and Duke University, Box 90308, Durham, NC 27708-0308 (United States)
2000-12-01
Analytical solutions of dispersion integral relations, linking the real and imaginary parts of the nuclear optical model, have been derived. These are displayed for some widely used forms of the volume- and surface-absorptive nuclear potentials. When the analytical solutions are incorporated into the optical-model search code GENOA, replacing a numerical integration, the code runs three and a half to seven times faster, greatly aiding the analysis of direct-reaction, elastic scattering data. (author)
Empirically evaluating decision-analytic models.
Goldhaber-Fiebert, Jeremy D; Stout, Natasha K; Goldie, Sue J
2010-08-01
Model-based cost-effectiveness analyses support decision-making. To augment model credibility, evaluation via comparison to independent, empirical studies is recommended. We developed a structured reporting format for model evaluation and conducted a structured literature review to characterize current model evaluation recommendations and practices. As an illustration, we applied the reporting format to evaluate a microsimulation of human papillomavirus and cervical cancer. The model's outputs and uncertainty ranges were compared with multiple outcomes from a study of long-term progression from high-grade precancer (cervical intraepithelial neoplasia [CIN]) to cancer. Outcomes included 5 to 30-year cumulative cancer risk among women with and without appropriate CIN treatment. Consistency was measured by model ranges overlapping study confidence intervals. The structured reporting format included: matching baseline characteristics and follow-up, reporting model and study uncertainty, and stating metrics of consistency for model and study results. Structured searches yielded 2963 articles with 67 meeting inclusion criteria and found variation in how current model evaluations are reported. Evaluation of the cervical cancer microsimulation, reported using the proposed format, showed a modeled cumulative risk of invasive cancer for inadequately treated women of 39.6% (30.9-49.7) at 30 years, compared with the study: 37.5% (28.4-48.3). For appropriately treated women, modeled risks were 1.0% (0.7-1.3) at 30 years, study: 1.5% (0.4-3.3). To support external and projective validity, cost-effectiveness models should be iteratively evaluated as new studies become available, with reporting standardized to facilitate assessment. Such evaluations are particularly relevant for models used to conduct comparative effectiveness analyses.
Analytical Model for Fictitious Crack Propagation in Concrete Beams
Ulfkjær, J. P.; Krenk, Steen; Brincker, Rune
1995-01-01
An analytical model for load-displacement curves of concrete beams is presented. The load-displacement curve is obtained by combining two simple models. The fracture is modeled by a fictitious crack in an elastic layer around the midsection of the beam. Outside the elastic layer the deformations...... are modeled by beam theory. The state of stress in the elastic layer is assumed to depend bilinearly on local elongation corresponding to a linear softening relation for the fictitious crack. Results from the analytical model are compared with results from a more detailed model based on numerical methods...... for different beam sizes. The analytical model is shown to be in agreement with the numerical results if the thickness of the elastic layer is taken as half the beam depth. It is shown that the point on the load-displacement curve where the fictitious crack starts to develop and the point where the real crack...
Analytical Model for Fictitious Crack Propagation in Concrete Beams
Ulfkjær, J. P.; Krenk, S.; Brincker, Rune
An analytical model for load-displacement curves of unreinforced notched and un-notched concrete beams is presented. The load displacement-curve is obtained by combining two simple models. The fracture is modelled by a fictitious crack in an elastic layer around the mid-section of the beam. Outside...... the elastic layer the deformations are modelled by the Timoshenko beam theory. The state of stress in the elastic layer is assumed to depend bi-lineary on local elongation corresponding to a linear softening relation for the fictitious crack. For different beam size results from the analytical model...... is compared with results from a more accurate model based on numerical methods. The analytical model is shown to be in good agreement with the numerical results if the thickness of the elastic layer is taken as half the beam depth. Several general results are obtained. It is shown that the point on the load...
Spatially explicit modeling in ecology: A review
DeAngelis, Donald L.; Yurek, Simeon
2017-01-01
The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.
Control of spatial discretisation in coastal oil spill modelling
Li, Yang
2007-01-01
Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Searc...
Analytical system dynamics modeling and simulation
Fabien, Brian C
2008-01-01
This book offering a modeling technique based on Lagrange's energy method includes 125 worked examples. Using this technique enables one to model and simulate systems as diverse as a six-link, closed-loop mechanism or a transistor power amplifier.
Spatial Models and Networks of Living Systems
Juul, Jeppe Søgaard
When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...
Linking spatial and dynamic models for traffic maneuvers
Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal
2015-01-01
For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...
Analytic model of heat deposition in spallation neutron target
Findlay, D.J.S.
2015-01-01
A simple analytic model for estimating deposition of heat in a spallation neutron target is presented—a model that can readily be realised in an unambitious spreadsheet. The model is based on simple representations of the principal underlying physical processes, and is intended largely as a ‘sanity check’ on results from Monte Carlo codes such as FLUKA or MCNPX.
Analytic model of heat deposition in spallation neutron target
Findlay, D.J.S.
2015-12-11
A simple analytic model for estimating deposition of heat in a spallation neutron target is presented—a model that can readily be realised in an unambitious spreadsheet. The model is based on simple representations of the principal underlying physical processes, and is intended largely as a ‘sanity check’ on results from Monte Carlo codes such as FLUKA or MCNPX.
Developing a modelling for the spatial data infrastructure
Hjelmager, J
2005-07-01
Full Text Available The Commission on Spatial Data Standards of the International Cartographic Association (ICA) is working on defining spatial models and technical characteristics of a Spatial Data Infrastructure (SDI). To date, this work has been restricted...
Factor Copula Models for Replicated Spatial Data
Krupskii, Pavel
2016-12-19
We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.
Factor Copula Models for Replicated Spatial Data
Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.
2016-01-01
We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.
Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges
Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór
2010-01-01
restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...
Meta-analytic structural equation modelling
Jak, Suzanne
2015-01-01
This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.
Analytical modeling of inverted annular film boiling
Analytis, G.T.; Yadigaroglu, G.
1987-01-01
By employing a two-fluid formulation similar to the one used in the most recent LWR accident analysis codes, a model for the Inverted Annular Film Boiling region is developed. The conservation equations, together with appropriate closure relations are solved numerically. Successful comparisons are made between model predictions and heat transfer coefficient distributions measured in a series of single-tube reflooding experiments. Generally, the model predicts correctly the dependence of the heat transfer coefficient on liquid subcooling and flow rate; for some cases, however, heat transfer is still under-predicted, and an enhancement of the heat exchange from the liquid-vapour interface to the bulk of the liquid is required. The importance of the initial conditions at the quench front is also discussed. (orig.)
Analytical modeling of inverted annular film boiling
Analytis, G.T.; Yadigaroglu, G.
1985-01-01
By employing a two-fluid formulation similar to the one used in the most recent LWR accident analysis codes, a model for the Inverted Annular Film Boiling region is developed. The conservation equations, together with appropriate constitutive relations are solved numerically and successful comparisons are made between model predictions and heat transfer coefficient distributions measured in a series of single-tube reflooding experiments. The model predicts generally correctly the dependence of the heat transfer coefficient on liquid subcooling and flow rate, through, for some cases, heat transfer is still under-predicted, and an enhancement of the heat exchange from the liquid-vapour interface to the bulk of the liquid is required
Analytical study of anisotropic compact star models
Ivanov, B.V. [Bulgarian Academy of Science, Institute for Nuclear Research and Nuclear Energy, Sofia (Bulgaria)
2017-11-15
A simple classification is given of the anisotropic relativistic star models, resembling the one of charged isotropic solutions. On the ground of this database, and taking into account the conditions for physically realistic star models, a method is proposed for generating all such solutions. It is based on the energy density and the radial pressure as seeding functions. Numerous relations between the realistic conditions are found and the need for a graphic proof is reduced just to one pair of inequalities. This general formalism is illustrated with an example of a class of solutions with linear equation of state and simple energy density. It is found that the solutions depend on three free constants and concrete examples are given. Some other popular models are studied with the same method. (orig.)
Modeling spin magnetization transport in a spatially varying magnetic field
Picone, Rico A.R.; Garbini, Joseph L.; Sidles, John A.
2015-01-01
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of
Modeling spin magnetization transport in a spatially varying magnetic field
Picone, Rico A.R., E-mail: rpicone@stmartin.edu [Department of Mechanical Engineering, University of Washington, Seattle (United States); Garbini, Joseph L. [Department of Mechanical Engineering, University of Washington, Seattle (United States); Sidles, John A. [Department of Orthopædics, University of Washington, Seattle (United States)
2015-01-15
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]). - Highlights: • A framework for modeling the transport of conserved magnetic and thermodynamic quantities in any spatial configuration. • A thermodynamically grounded model of spin magnetization transport valid in new regimes, including high-polarization. • Analysis of the separative quality of
Analytical model for cable tray fires
Clarke, R.K.
1975-09-01
A model for cable tray fires based on buoyant plume theory is presented. Using the model in conjunction with empirical data on size of natural fires and burning rate of cellulosic materials, estimates are made of the heat flux as a function of vertical and horizontal distance from a tray fire. Both local fires and fires extending along a significant length of tray are considered. For the particular set of fire parameters assumed in the calculations, the current tray separation criteria of five feet vertical and three feet horizontal are found to be marginal for local fires and too small to prevent fire spread for extended tray fires. 8 references. (auth)
Oliveira, F.L. de; Maiorino, J.R.; Santos, R.S.
2007-01-01
This paper describes a closed form solution obtained by the expansion method for the general time dependent diffusion model with delayed emission for source transients in homogeneous media. In particular, starting from simple models, and increasing the complexity, numerical results were obtained for different types of source transients. Thus, first an analytical solution of the one group without precursors was solved, followed by considering one precursors family. The general case of G-groups with R families of precursor although having a closed form solution, cannot be solved analytically, since there are no explicit formulae for the eigenvalues, and numerical methods must be used to solve such problem. To illustrate the general solution, the multi-group (three groups) time-dependent without precursors was also solved and the results inter compared with results obtained by the previous one group models for a given fast homogeneous media, and different types of source transients. The results are being compared with the obtained by numerical methods. (author)
Analytical model of impedance in elliptical beam pipes
Pesah, Arthur Chalom
2017-01-01
Beam instabilities are among the main limitations in building higher intensity accelerators. Having a good impedance model for every accelerators is necessary in order to build components that minimize the probability of instabilities caused by the interaction beam-environment and to understand what piece to change in case of intensity increasing. Most of accelerator components have their impedance simulated with finite elements method (using softwares like CST Studio), but simple components such as circular or flat pipes are modeled analytically, with a decreasing computation time and an increasing precision compared to their simulated model. Elliptical beam pipes, while being a simple component present in some accelerators, still misses a good analytical model working for the hole range of velocities and frequencies. In this report, we present a general framework to study the impedance of elliptical pipes analytically. We developed a model for both longitudinal and transverse impedance, first in the case of...
Unjamming in models with analytic pairwise potentials
Kooij, S.; Lerner, E.
Canonical models for studying the unjamming scenario in systems of soft repulsive particles assume pairwise potentials with a sharp cutoff in the interaction range. The sharp cutoff renders the potential nonanalytic but makes it possible to describe many properties of the solid in terms of the
Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers
2006-01-01
Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...
Human Plague Risk: Spatial-Temporal Models
Pinzon, Jorge E.
2010-01-01
This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).
Analytical and numerical modeling for flexible pipes
Wang, Wei; Chen, Geng
2011-12-01
The unbonded flexible pipe of eight layers, in which all the layers except the carcass layer are assumed to have isotropic properties, has been analyzed. Specifically, the carcass layer shows the orthotropic characteristics. The effective elastic moduli of the carcass layer have been developed in terms of the influence of deformation to stiffness. With consideration of the effective elastic moduli, the structure can be properly analyzed. Also the relative movements of tendons and relative displacements of wires in helical armour layer have been investigated. A three-dimensional nonlinear finite element model has been presented to predict the response of flexible pipes under axial force and torque. Further, the friction and contact of interlayer have been considered. Comparison between the finite element model and experimental results obtained in literature has been given and discussed, which might provide practical and technical support for the application of unbonded flexible pipes.
The quantitative modelling of human spatial habitability
Wise, James A.
1988-01-01
A theoretical model for evaluating human spatial habitability (HuSH) in the proposed U.S. Space Station is developed. Optimizing the fitness of the space station environment for human occupancy will help reduce environmental stress due to long-term isolation and confinement in its small habitable volume. The development of tools that operationalize the behavioral bases of spatial volume for visual kinesthetic, and social logic considerations is suggested. This report further calls for systematic scientific investigations of how much real and how much perceived volume people need in order to function normally and with minimal stress in space-based settings. The theoretical model presented in this report can be applied to any size or shape interior, at any scale of consideration, for the Space Station as a whole to an individual enclosure or work station. Using as a point of departure the Isovist model developed by Dr. Michael Benedikt of the U. of Texas, the report suggests that spatial habitability can become as amenable to careful assessment as engineering and life support concerns.
Haskell financial data modeling and predictive analytics
Ryzhov, Pavel
2013-01-01
This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner.This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential.
Unjamming in models with analytic pairwise potentials
Kooij, Stefan; Lerner, Edan
2017-06-01
Canonical models for studying the unjamming scenario in systems of soft repulsive particles assume pairwise potentials with a sharp cutoff in the interaction range. The sharp cutoff renders the potential nonanalytic but makes it possible to describe many properties of the solid in terms of the coordination number z , which has an unambiguous definition in these cases. Pairwise potentials without a sharp cutoff in the interaction range have not been studied in this context, but should in fact be considered to understand the relevance of the unjamming phenomenology in systems where such a cutoff is not present. In this work we explore two systems with such interactions: an inverse power law and an exponentially decaying pairwise potential, with the control parameters being the exponent (of the inverse power law) for the former and the number density for the latter. Both systems are shown to exhibit the characteristic features of the unjamming transition, among which are the vanishing of the shear-to-bulk modulus ratio and the emergence of an excess of low-frequency vibrational modes. We establish a relation between the pressure-to-bulk modulus ratio and the distance to unjamming in each of our model systems. This allows us to predict the dependence of other key observables on the distance to unjamming. Our results provide the means for a quantitative estimation of the proximity of generic glass-forming models to the unjamming transition in the absence of a clear-cut definition of the coordination number and highlight the general irrelevance of nonaffine contributions to the bulk modulus.
Analytical Model for High Impedance Fault Analysis in Transmission Lines
S. Maximov
2014-01-01
Full Text Available A high impedance fault (HIF normally occurs when an overhead power line physically breaks and falls to the ground. Such faults are difficult to detect because they often draw small currents which cannot be detected by conventional overcurrent protection. Furthermore, an electric arc accompanies HIFs, resulting in fire hazard, damage to electrical devices, and risk with human life. This paper presents an analytical model to analyze the interaction between the electric arc associated to HIFs and a transmission line. A joint analytical solution to the wave equation for a transmission line and a nonlinear equation for the arc model is presented. The analytical model is validated by means of comparisons between measured and calculated results. Several cases of study are presented which support the foundation and accuracy of the proposed model.
Analytical model for fast-shock ignition
Ghasemi, S. A.; Farahbod, A. H.; Sobhanian, S.
2014-01-01
A model and its improvements are introduced for a recently proposed approach to inertial confinement fusion, called fast-shock ignition (FSI). The analysis is based upon the gain models of fast ignition, shock ignition and considerations for the fast electrons penetration into the pre-compressed fuel to examine the formation of an effective central hot spot. Calculations of fast electrons penetration into the dense fuel show that if the initial electron kinetic energy is of the order ∼4.5 MeV, the electrons effectively reach the central part of the fuel. To evaluate more realistically the performance of FSI approach, we have used a quasi-two temperature electron energy distribution function of Strozzi (2012) and fast ignitor energy formula of Bellei (2013) that are consistent with 3D PIC simulations for different values of fast ignitor laser wavelength and coupling efficiency. The general advantages of fast-shock ignition in comparison with the shock ignition can be estimated to be better than 1.3 and it is seen that the best results can be obtained for the fuel mass around 1.5 mg, fast ignitor laser wavelength ∼0.3 micron and the shock ignitor energy weight factor about 0.25
Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar
2017-09-01
Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.
Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python
Laura, Jason R.; Rey, Sergio J.
2017-01-01
Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.
The quantitative modelling of human spatial habitability
Wise, J. A.
1985-01-01
A model for the quantitative assessment of human spatial habitability is presented in the space station context. The visual aspect assesses how interior spaces appear to the inhabitants. This aspect concerns criteria such as sensed spaciousness and the affective (emotional) connotations of settings' appearances. The kinesthetic aspect evaluates the available space in terms of its suitability to accommodate human movement patterns, as well as the postural and anthrometric changes due to microgravity. Finally, social logic concerns how the volume and geometry of available space either affirms or contravenes established social and organizational expectations for spatial arrangements. Here, the criteria include privacy, status, social power, and proxemics (the uses of space as a medium of social communication).
Modeling mental spatial reasoning about cardinal directions.
Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas
2014-01-01
This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions (i.e., are spatially underdetermined), at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. Copyright © 2014 Cognitive Science Society, Inc.
AN ANALYTIC MODEL OF DUSTY, STRATIFIED, SPHERICAL H ii REGIONS
Rodríguez-Ramírez, J. C.; Raga, A. C. [Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ap. 70-543, 04510 D.F., México (Mexico); Lora, V. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Cantó, J., E-mail: juan.rodriguez@nucleares.unam.mx [Instituto de Astronomía, Universidad Nacional Autónoma de México, Ap. 70-468, 04510 D. F., México (Mexico)
2016-12-20
We study analytically the effect of radiation pressure (associated with photoionization processes and with dust absorption) on spherical, hydrostatic H ii regions. We consider two basic equations, one for the hydrostatic balance between the radiation-pressure components and the gas pressure, and another for the balance among the recombination rate, the dust absorption, and the ionizing photon rate. Based on appropriate mathematical approximations, we find a simple analytic solution for the density stratification of the nebula, which is defined by specifying the radius of the external boundary, the cross section of dust absorption, and the luminosity of the central star. We compare the analytic solution with numerical integrations of the model equations of Draine, and find a wide range of the physical parameters for which the analytic solution is accurate.
Four-parameter analytical local model potential for atoms
Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang
2009-01-01
Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)
Analytic uncertainty and sensitivity analysis of models with input correlations
Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu
2018-03-01
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
Helbich, M; Griffith, D
2016-01-01
Real estate policies in urban areas require the recognition of spatial heterogeneity in housing prices to account for local settings. In response to the growing number of spatially varying coefficient models in housing applications, this study evaluated four models in terms of their spatial patterns
Spatial Economics Model Predicting Transport Volume
Lu Bo
2016-10-01
Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.
A Computational Model of Spatial Development
Hiraki, Kazuo; Sashima, Akio; Phillips, Steven
Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism underlying development is unknown. We propose a robot that learns to mentally track a target object (i.e., maintaining a representation of an object's position when outside the field-of-view) as a model for spatial development. Mental tracking is considered as prediction of an object's position given the previous environmental state and motor commands, and the current environment state resulting from movement. Following Jordan & Rumelhart's (1992) forward modeling architecture the system consists of two components: an inverse model of sensory input to desired motor commands; and a forward model of motor commands to desired sensory input (goals). The robot was tested on the `three cups' paradigm (where children are required to select the cup containing the hidden object under various movement conditions). Consistent with child development, without the capacity for self-locomotion the robot's errors are self-center based. When given the ability of self-locomotion the robot responds allocentrically.
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong
2017-11-28
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.
Latent spatial models and sampling design for landscape genetics
Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.
2016-01-01
We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
An analytical model of the HINT performance metric
Snell, Q.O.; Gustafson, J.L. [Scalable Computing Lab., Ames, IA (United States)
1996-10-01
The HINT benchmark was developed to provide a broad-spectrum metric for computers and to measure performance over the full range of memory sizes and time scales. We have extended our understanding of why HINT performance curves look the way they do and can now predict the curves using an analytical model based on simple hardware specifications as input parameters. Conversely, by fitting the experimental curves with the analytical model, hardware specifications such as memory performance can be inferred to provide insight into the nature of a given computer system.
Spatially varying dispersion to model breakthrough curves.
Li, Guangquan
2011-01-01
Often the water flowing in a karst conduit is a combination of contaminated water entering at a sinkhole and cleaner water released from the limestone matrix. Transport processes in the conduit are controlled by advection, mixing (dilution and dispersion), and retention-release. In this article, a karst transport model considering advection, spatially varying dispersion, and dilution (from matrix seepage) is developed. Two approximate Green's functions are obtained using transformation of variables, respectively, for the initial-value problem and for the boundary-value problem. A numerical example illustrates that mixing associated with strong spatially varying conduit dispersion can cause strong skewness and long tailing in spring breakthrough curves. Comparison of the predicted breakthrough curve against that measured from a dye-tracing experiment between Ames Sink and Indian Spring, Northwest Florida, shows that the conduit dispersivity can be as large as 400 m. Such a large number is believed to imply strong solute interaction between the conduit and the matrix and/or multiple flow paths in a conduit network. It is concluded that Taylor dispersion is not dominant in transport in a karst conduit, and the complicated retention-release process between mobile- and immobile waters may be described by strong spatially varying conduit dispersion. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.
Analytical Modelling and Simulation of Photovoltaic Panels and Arrays
H. Bourdoucen
2007-12-01
Full Text Available In this paper, an analytical model for PV panels and arrays based on extracted physical parameters of solar cells is developed. The proposed model has the advantage of simplifying mathematical modelling for different configurations of cells and panels without losing efficiency of PV system operation. The effects of external parameters, mainly temperature and solar irradiance have been considered in the modelling. Due to their critical effects on the operation of the panel, effects of series and shunt resistances were also studied. The developed analytical model has been easily implemented, simulated and validated using both Spice and Matlab packages for different series and parallel configurations of cells and panels. The results obtained with these two programs are in total agreement, which make the proposed model very useful for researchers and designers for quick and accurate sizing of PV panels and arrays.
An Evolutionary Model of Spatial Competition
Knudsen, Thorbjørn; Winter, Sidney G.
This paper sets forth an evolutionary model in which diverse businesses, with diverse offerings, compete in a stylized physical space. When a business firm attempts to expand its activity, so as to profit further from the capabilities it has developed, it necessarily does so in a "new location...... as well in the new environment as they did in the old; the firm may respond with effort to locate appropriate environments or by modification of its routines. Tradeoffs are presented between the complexity of a business model and its replication costs, as well as issues involving response....... Randomly generated firm policies are tested first by a local market environment, and then, if success leads the firm to grow spatially, in a gradually expanding environment. In the initial experiments reported here, we show that the model generates configurations that reflect features of the exogenous...
Elliptic-cylindrical analytical flux-rope model for ICMEs
Nieves-Chinchilla, T.; Linton, M.; Hidalgo, M. A. U.; Vourlidas, A.
2016-12-01
We present an analytical flux-rope model for realistic magnetic structures embedded in Interplanetary Coronal Mass Ejections. The framework of this model was established by Nieves-Chinchilla et al. (2016) with the circular-cylindrical analytical flux rope model and under the concept developed by Hidalgo et al. (2002). Elliptic-cylindrical geometry establishes the first-grade of complexity of a series of models. The model attempts to describe the magnetic flux rope topology with distorted cross-section as a possible consequence of the interaction with the solar wind. In this model, the flux rope is completely described in the non-euclidean geometry. The Maxwell equations are solved using tensor calculus consistently with the geometry chosen, invariance along the axial component, and with the only assumption of no radial current density. The model is generalized in terms of the radial dependence of the poloidal current density component and axial current density component. The misalignment between current density and magnetic field is studied in detail for the individual cases of different pairs of indexes for the axial and poloidal current density components. This theoretical analysis provides a map of the force distribution inside of the flux-rope. The reconstruction technique has been adapted to the model and compared with in situ ICME set of events with different in situ signatures. The successful result is limited to some cases with clear in-situ signatures of distortion. However, the model adds a piece in the puzzle of the physical-analytical representation of these magnetic structures. Other effects such as axial curvature, expansion and/or interaction could be incorporated in the future to fully understand the magnetic structure. Finally, the mathematical formulation of this model opens the door to the next model: toroidal flux rope analytical model.
Two analytical models for evaluating performance of Gigabit Ethernet Hosts
Salah, K.
2006-01-01
Two analytical models are developed to study the impact of interrupt overhead on operating system performance of network hosts when subjected to Gigabit network traffic. Under heavy network traffic, the system performance will be negatively affected due to interrupt overhead caused by incoming traffic. In particular, excessive latency and significant degradation in system throughput can be experienced. Also user application may livelock as the CPU power is mostly consumed by interrupt handling and protocol processing. In this paper we present and compare two analytical models that capture host behavior and evaluate its performance. The first model is based Markov processes and queuing theory, while the second, which is more accurate but more complex is a pure Markov process. For the most part both models give mathematically-equivalent closed-form solutions for a number of important system performance metrics. These metrics include throughput, latency and stability condition, CPU utilization of interrupt handling and protocol processing and CPU availability for user applications. The analysis yields insight into understanding and predicting the impact of system and network choices on the performance of interrupt-driven systems when subjected to light and heavy network loads. More, importantly, our analytical work can also be valuable in improving host performance. The paper gives guidelines and recommendations to address design and implementation issues. Simulation and reported experimental results show that our analytical models are valid and give a good approximation. (author)
Analytical Model for Hook Anchor Pull-Out
Brincker, Rune; Ulfkjær, Jens Peder; Adamsen, Peter
1995-01-01
A simple analytical model for the pull-out of a hook anchor is presented. The model is based on a simplified version of the fictitious crack model. It is assumed that the fracture process is the pull-off of a cone shaped concrete part, simplifying the problem by assuming pure rigid body motions...... allowing elastic deformations only in a layer between the pull-out cone and the concrete base. The derived model is in good agreement with experimental results, it predicts size effects and the model parameters found by calibration of the model on experimental data are in good agreement with what should...
Analytical Model for Hook Anchor Pull-out
Brincker, Rune; Ulfkjær, J. P.; Adamsen, P.
A simple analytical model for the pull-out of a hook anchor is presented. The model is based on a simplified version of the fictitious crack model. It is assumed that the fracture process is the pull-off of a cone shaped concrete part, simplifying the problem by assuming pure rigid body motions...... allowing elastic deformations only in a layer between the pull-out cone and the concrete base. The derived model is in good agreement with experimental results, it predicts size effects and the model parameters found by calibration of the model on experimental data are in good agreement with what should...
Evaluation of one dimensional analytical models for vegetation canopies
Goel, Narendra S.; Kuusk, Andres
1992-01-01
The SAIL model for one-dimensional homogeneous vegetation canopies has been modified to include the specular reflectance and hot spot effects. This modified model and the Nilson-Kuusk model are evaluated by comparing the reflectances given by them against those given by a radiosity-based computer model, Diana, for a set of canopies, characterized by different leaf area index (LAI) and leaf angle distribution (LAD). It is shown that for homogeneous canopies, the analytical models are generally quite accurate in the visible region, but not in the infrared region. For architecturally realistic heterogeneous canopies of the type found in nature, these models fall short. These shortcomings are quantified.
Analytical study on model tests of soil-structure interaction
Odajima, M.; Suzuki, S.; Akino, K.
1987-01-01
Since nuclear power plant (NPP) structures are stiff, heavy and partly-embedded, the behavior of those structures during an earthquake depends on the vibrational characteristics of not only the structure but also the soil. Accordingly, seismic response analyses considering the effects of soil-structure interaction (SSI) are extremely important for seismic design of NPP structures. Many studies have been conducted on analytical techniques concerning SSI and various analytical models and approaches have been proposed. Based on the studies, SSI analytical codes (computer programs) for NPP structures have been improved at JINS (Japan Institute of Nuclear Safety), one of the departments of NUPEC (Nuclear Power Engineering Test Center) in Japan. These codes are soil-spring lumped-mass code (SANLUM), finite element code (SANSSI), thin layered element code (SANSOL). In proceeding with the improvement of the analytical codes, in-situ large-scale forced vibration SSI tests were performed using models simulating light water reactor buildings, and simulation analyses were performed to verify the codes. This paper presents an analytical study to demonstrate the usefulness of the codes
Analytical models for the rewetting of hot surfaces
Olek, S.
1988-10-01
Some aspects concerning analytical models for the rewetting of hot surface are discussed. These include the problems with applying various forms of boundary conditions, compatibility of boundary conditions with the physics of the rewetting problems, recent analytical models, the use of the separation of variables method versus the Wiener-Hopf technique, and the use of transformations. The report includes an updated list of rewetting models as well as benchmark solutions in tabular form for several models. It should be emphasized that this report is not meant to cover the topic of rewetting models. It merely discusses some points which are less commonly referred to in the literature. 93 refs., 3 figs., 22 tabs
Analytic investigation of extended Heitler-Matthews model
Grimm, Stefan; Veberic, Darko; Engel, Ralph [KIT, IKP (Germany)
2016-07-01
Many features of extensive air showers are qualitatively well described by the Heitler cascade model and its extensions. The core of a shower is given by hadrons that interact with air nuclei. After each interaction some of these hadrons decay and feed the electromagnetic shower component. The most important parameters of such hadronic interactions are inelasticity, multiplicity, and the ratio of charged vs. neutral particles. However, in analytic considerations approximations are needed to include the characteristics of hadron production. We discuss extensions of the simple cascade model by analytic description of air showers by cascade models which include also the elasticity, and derive the number of produced muons. In a second step we apply this model to calculate the dependence of the shower center of gravity on model parameters. The depth of the center of gravity is closely related to that of the shower maximum, which is a commonly-used composition-sensitive observable.
Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable
Elhorst, J. Paul
2001-01-01
This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the
An analytical model for the assessment of airline expansion strategies
Mauricio Emboaba Moreira
2014-01-01
Full Text Available Purpose: The purpose of this article is to develop an analytical model to assess airline expansion strategies by combining generic business strategy models with airline business models. Methodology and approach: A number of airline business models are examined, as are Porter’s (1983 industry five forces that drive competition, complemented by Nalebuff/ Brandenburger’s (1996 sixth force, and the basic elements of the general environment in which the expansion process takes place. A system of points and weights is developed to create a score among the 904,736 possible combinations considered. The model’s outputs are generic expansion strategies with quantitative assessments for each specific combination of elements inputted. Originality and value: The analytical model developed is original because it combines for the first time and explicitly elements of the general environment, industry environment, airline business models and the generic expansion strategy types. Besides it creates a system of scores that may be used to drive the decision process toward the choice of a specific strategic expansion path. Research implications: The analytical model may be adapted to other industries apart from the airline industry by substituting the element “airline business model” by other industries corresponding elements related to the different specific business models.
Piezoresistive Cantilever Performance-Part I: Analytical Model for Sensitivity.
Park, Sung-Jin; Doll, Joseph C; Pruitt, Beth L
2010-02-01
An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors.
Piezoresistive Cantilever Performance—Part I: Analytical Model for Sensitivity
Park, Sung-Jin; Doll, Joseph C.; Pruitt, Beth L.
2010-01-01
An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors. PMID:20336183
Bubbles in inkjet printheads: analytical and numerical models
Jeurissen, R.J.M.
2009-01-01
The phenomenon of nozzle failure of an inkjet printhead due to entrainment of air bubbles was studies using analytical and numerical models. The studied inkjet printheads consist of many channels in which an acoustic field is generated to eject a droplet. When an air bubble is entrained, it disrupts
Bubbles in inkjet printheads : analytical and numerical models
Jeurissen, R.J.M.
2009-01-01
The phenomenon of nozzle failure of an inkjet printhead due to entrainment of air bubbles was studies using analytical and numerical models. The studied inkjet printheads consist of many channels in which an acoustic field is generated to eject a droplet. When an air bubble is entrained, it disrupts
Analytic processor model for fast design-space exploration
Jongerius, R.; Mariani, G.; Anghel, A.; Dittmann, G.; Vermij, E.; Corporaal, H.
2015-01-01
In this paper, we propose an analytic model that takes as inputs a) a parametric microarchitecture-independent characterization of the target workload, and b) a hardware configuration of the core and the memory hierarchy, and returns as output an estimation of processor-core performance. To validate
Models for the analytic estimation of low energy photon albedo
Simovic, R.; Markovic, S.; Ljubenov, V.
2005-01-01
This paper shows some monoenergetic models for estimation of photon reflection in the energy range from 20 keV to 80 keV. Using the DP0 approximation of the H-function we have derived the analytic expressions of the η and R functions in purpose to facilitate photon reflection analyses as well as the radiation shield designee. (author) [sr
An analytical excitation model for an ionizing plasma
Mullen, van der J.J.A.M.; Sijde, van der B.; Schram, D.C.
1983-01-01
From an analytical model for the population of high-lying excited levels in ionizing plasmas it appears that the distribution is a superposition of the equilibrium (Saha) value and an overpopulation. This overpopulation takes the form of a Maxwell distribution for free electrons. Experiments for He
MODEL ANALYTICAL NETWORK PROCESS (ANP DALAM PENGEMBANGAN PARIWISATA DI JEMBER
Sukidin Sukidin
2015-04-01
Full Text Available Abstrak : Model Analytical Network Process (ANP dalam Pengembangan Pariwisata di Jember. Penelitian ini mengkaji kebijakan pengembangan pariwisata di Jember, terutama kebijakan pengembangan agrowisata perkebunan kopi dengan menggunakan Jember Fashion Carnival (JFC sebagai event marketing. Metode yang digunakan adalah soft system methodology dengan menggunakan metode analitis jaringan (Analytical Network Process. Penelitian ini menemukan bahwa pengembangan pariwisata di Jember masih dilakukan dengan menggunakan pendekatan konvensional, belum terkoordinasi dengan baik, dan lebih mengandalkan satu even (atraksi pariwisata, yakni JFC, sebagai lokomotif daya tarik pariwisata Jember. Model pengembangan konvensional ini perlu dirancang kembali untuk memperoleh pariwisata Jember yang berkesinambungan. Kata kunci: pergeseran paradigma, industry pariwisata, even pariwisata, agrowisata Abstract: Analytical Network Process (ANP Model in the Tourism Development in Jember. The purpose of this study is to conduct a review of the policy of tourism development in Jember, especially development policies for coffee plantation agro-tourism by using Jember Fashion Carnival (JFC as event marketing. The research method used is soft system methodology using Analytical Network Process. The result shows that the tourism development in Jember is done using a conventional approach, lack of coordination, and merely focus on a single event tourism, i.e. the JFC, as locomotive tourism attraction in Jember. This conventional development model needs to be redesigned to reach Jember sustainable tourism development. Keywords: paradigm shift, tourism industry, agro-tourism
Foam for Enhanced Oil Recovery : Modeling and Analytical Solutions
Ashoori, E.
2012-01-01
Foam increases sweep in miscible- and immiscible-gas enhanced oil recovery by decreasing the mobility of gas enormously. This thesis is concerned with the simulations and analytical solutions for foam flow for the purpose of modeling foam EOR in a reservoir. For the ultimate goal of upscaling our
Learning, Learning Analytics, Activity Visualisation and Open learner Model
Bull, Susan; Kickmeier-Rust, Michael; Vatrapu, Ravi
2013-01-01
This paper draws on visualisation approaches in learning analytics, considering how classroom visualisations can come together in practice. We suggest an open learner model in situations where many tools and activity visualisations produce more visual information than can be readily interpreted....
Evaluating Modeling Sessions Using the Analytic Hierarchy Process
Ssebuggwawo, D.; Hoppenbrouwers, S.J.B.A.; Proper, H.A.; Persson, A.; Stirna, J.
2008-01-01
In this paper, which is methodological in nature, we propose to use an established method from the field of Operations Research, the Analytic Hierarchy Process (AHP), in the integrated, stakeholder- oriented evaluation of enterprise modeling sessions: their language, pro- cess, tool (medium), and
Spatial Stochastic Point Models for Reservoir Characterization
Syversveen, Anne Randi
1997-12-31
The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.
Theoretical aspects of spatial-temporal modeling
Matsui, Tomoko
2015-01-01
This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alph...
A semi-analytical stationary model of a point-to-plane corona discharge
Yanallah, K; Pontiga, F
2012-01-01
A semi-analytical model of a dc corona discharge is formulated to determine the spatial distribution of charged particles (electrons, negative ions and positive ions) and the electric field in pure oxygen using a point-to-plane electrode system. A key point in the modeling is the integration of Gauss' law and the continuity equation of charged species along the electric field lines, and the use of Warburg's law and the corona current–voltage characteristics as input data in the boundary conditions. The electric field distribution predicted by the model is compared with the numerical solution obtained using a finite-element technique. The semi-analytical solutions are obtained at a negligible computational cost, and provide useful information to characterize and control the corona discharge in different technological applications. (paper)
Analytical model spectrum for electrostatic turbulence in tokamaks
Fiedler-Ferrari, N.; Misguich, J.H.
1990-04-01
In this work we present an analytical model spectrum, for three-dimensional electrostatic turbulence (homogeneous, stationary and locally isotropic in the plane perpendicular to the magnetic field), constructed by using experimental results from TFR and TEXT Tokamaks, and satisfying basic symmetry and parity conditions. The proposed spectrum seems to be tractable for explicit analytical calculations of transport processes, and consistent with experimental data. Additional experimental measurements in the bulk plasma remain however necessary in order to determine some unknown spectral properties of parallel propagation
The Greenhouse effect within an analytic model of the atmosphere
Dehnen, Heinz [Konstanz Univ. (Germany). Fachbereich Physik
2009-01-15
Within a simplified atmospheric model the greenhouse effect is treated by analytical methods starting from physical first principles. The influence of solar radiation, absorption cross sections of the greenhouse molecules, and cloud formation on the earth's temperature is shown and discussed explicitly by mathematical formulae in contrast to the climate simulations. The application of our analytical results on the production of 20 .10{sup 9} t of CO{sub 2} per year yields an enlargement of the earth's surface temperature of 2.3 .10{sup -2} C per year in agreement with other estimations. (orig.)
An analytically solvable model for rapid evolution of modular structure.
Nadav Kashtan
2009-04-01
Full Text Available Biological systems often display modularity, in the sense that they can be decomposed into nearly independent subsystems. Recent studies have suggested that modular structure can spontaneously emerge if goals (environments change over time, such that each new goal shares the same set of sub-problems with previous goals. Such modularly varying goals can also dramatically speed up evolution, relative to evolution under a constant goal. These studies were based on simulations of model systems, such as logic circuits and RNA structure, which are generally not easy to treat analytically. We present, here, a simple model for evolution under modularly varying goals that can be solved analytically. This model helps to understand some of the fundamental mechanisms that lead to rapid emergence of modular structure under modularly varying goals. In particular, the model suggests a mechanism for the dramatic speedup in evolution observed under such temporally varying goals.
Experimental evaluation of analytical penumbra calculation model for wobbled beams
Kohno, Ryosuke; Kanematsu, Nobuyuki; Yusa, Ken; Kanai, Tatsuaki
2004-01-01
The goal of radiotherapy is not only to apply a high radiation dose to a tumor, but also to avoid side effects in the surrounding healthy tissue. Therefore, it is important for carbon-ion treatment planning to calculate accurately the effects of the lateral penumbra. In this article, for wobbled beams under various irradiation conditions, we focus on the lateral penumbras at several aperture positions of one side leaf of the multileaf collimator. The penumbras predicted by an analytical penumbra calculation model were compared with the measured results. The results calculated by the model for various conditions agreed well with the experimental ones. In conclusion, we found that the analytical penumbra calculation model could predict accurately the measured results for wobbled beams and it was useful for carbon-ion treatment planning to apply the model
Quantum decay model with exact explicit analytical solution
Marchewka, Avi; Granot, Er'El
2009-01-01
A simple decay model is introduced. The model comprises a point potential well, which experiences an abrupt change. Due to the temporal variation, the initial quantum state can either escape from the well or stay localized as a new bound state. The model allows for an exact analytical solution while having the necessary features of a decay process. The results show that the decay is never exponential, as classical dynamics predicts. Moreover, at short times the decay has a fractional power law, which differs from perturbation quantum method predictions. At long times the decay includes oscillations with an envelope that decays algebraically. This is a model where the final state can be either continuous or localized, and that has an exact analytical solution.
Models and Inference for Multivariate Spatial Extremes
Vettori, Sabrina
2017-12-07
The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical
Modeling spin magnetization transport in a spatially varying magnetic field
Picone, Rico A. R.; Garbini, Joseph L.; Sidles, John A.
2015-01-01
We present a framework for modeling the transport of any number of globally conserved quantities in any spatial configuration and apply it to obtain a model of magnetization transport for spin-systems that is valid in new regimes (including high-polarization). The framework allows an entropy function to define a model that explicitly respects the laws of thermodynamics. Three facets of the model are explored. First, it is expressed as nonlinear partial differential equations that are valid for the new regime of high dipole-energy and polarization. Second, the nonlinear model is explored in the limit of low dipole-energy (semi-linear), from which is derived a physical parameter characterizing separative magnetization transport (SMT). It is shown that the necessary and sufficient condition for SMT to occur is that the parameter is spatially inhomogeneous. Third, the high spin-temperature (linear) limit is shown to be equivalent to the model of nuclear spin transport of Genack and Redfield (1975) [1]. Differences among the three forms of the model are illustrated by numerical solution with parameters corresponding to a magnetic resonance force microscopy (MRFM) experiment (Degen et al., 2009 [2]; Kuehn et al., 2008 [3]; Sidles et al., 2003 [4]; Dougherty et al., 2000 [5]). A family of analytic, steady-state solutions to the nonlinear equation is derived and shown to be the spin-temperature analog of the Langevin paramagnetic equation and Curie's law. Finally, we analyze the separative quality of magnetization transport, and a steady-state solution for the magnetization is shown to be compatible with Fenske's separative mass transport equation (Fenske, 1932 [6]).
Collaborative data analytics for smart buildings: opportunities and models
Lazarova-Molnar, Sanja; Mohamed, Nader
2018-01-01
of collaborative data analytics for smart buildings, its benefits, as well as presently possible models of carrying it out. Furthermore, we present a framework for collaborative fault detection and diagnosis as a case of collaborative data analytics for smart buildings. We also provide a preliminary analysis...... of the energy efficiency benefit of such collaborative framework for smart buildings. The result shows that significant energy savings can be achieved for smart buildings using collaborative data analytics.......Smart buildings equipped with state-of-the-art sensors and meters are becoming more common. Large quantities of data are being collected by these devices. For a single building to benefit from its own collected data, it will need to wait for a long time to collect sufficient data to build accurate...
Analytical model for nonlinear piezoelectric energy harvesting devices
Neiss, S; Goldschmidtboeing, F; M Kroener; Woias, P
2014-01-01
In this work we propose analytical expressions for the jump-up and jump-down point of a nonlinear piezoelectric energy harvester. In addition, analytical expressions for the maximum power output at optimal resistive load and the 3 dB-bandwidth are derived. So far, only numerical models have been used to describe the physics of a piezoelectric energy harvester. However, this approach is not suitable to quickly evaluate different geometrical designs or piezoelectric materials in the harvester design process. In addition, the analytical expressions could be used to predict the jump-frequencies of a harvester during operation. In combination with a tuning mechanism, this would allow the design of an efficient control algorithm to ensure that the harvester is always working on the oscillator's high energy attractor. (paper)
Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models
Haslauer, C. P.; Bárdossy, A.
2017-12-01
A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.
Analytic models for the evolution of semilocal string networks
Nunes, A. S.; Martins, C. J. A. P.; Avgoustidis, A.; Urrestilla, J.
2011-01-01
We revisit previously developed analytic models for defect evolution and adapt them appropriately for the study of semilocal string networks. We thus confirm the expectation (based on numerical simulations) that linear scaling evolution is the attractor solution for a broad range of model parameters. We discuss in detail the evolution of individual semilocal segments, focusing on the phenomenology of segment growth, and also provide a preliminary comparison with existing numerical simulations.
Analytic regularization of the Yukawa model at finite temperature
Malbouisson, A.P.C.; Svaiter, N.F.; Svaiter, B.F.
1996-07-01
It is analysed the one-loop fermionic contribution for the scalar effective potential in the temperature dependent Yukawa model. Ir order to regularize the model a mix between dimensional and analytic regularization procedures is used. It is found a general expression for the fermionic contribution in arbitrary spacetime dimension. It is also found that in D = 3 this contribution is finite. (author). 19 refs
Modeling strategic investment decisions in spatial markets
Lorenczik, Stefan; Malischek, Raimund
2014-01-01
Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.
Spatially explicit modelling of cholera epidemics
Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.
2013-12-01
Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.
Modeling strategic investment decisions in spatial markets
Lorenczik, Stefan; Malischek, Raimund [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Trueby, Johannes [International Energy Agency, 75 - Paris (France)
2014-04-15
Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.
Toward Accessing Spatial Structure from Building Information Models
Schultz, C.; Bhatt, M.
2011-08-01
Data about building designs and layouts is becoming increasingly more readily available. In the near future, service personal (such as maintenance staff or emergency rescue workers) arriving at a building site will have immediate real-time access to enormous amounts of data relating to structural properties, utilities, materials, temperature, and so on. The critical problem for users is the taxing and error prone task of interpreting such a large body of facts in order to extract salient information. This is necessary for comprehending a situation and deciding on a plan of action, and is a particularly serious issue in time-critical and safety-critical activities such as firefighting. Current unifying building models such as the Industry Foundation Classes (IFC), while being comprehensive, do not directly provide data structures that focus on spatial reasoning and spatial modalities that are required for high-level analytical tasks. The aim of the research presented in this paper is to provide computational tools for higher level querying and reasoning that shift the cognitive burden of dealing with enormous amounts of data away from the user. The user can then spend more energy and time in planning and decision making in order to accomplish the tasks at hand. We present an overview of our framework that provides users with an enhanced model of "built-up space". In order to test our approach using realistic design data (in terms of both scale and the nature of the building models) we describe how our system interfaces with IFC, and we conduct timing experiments to determine the practicality of our approach. We discuss general computational approaches for deriving higher-level spatial modalities by focusing on the example of route graphs. Finally, we present a firefighting scenario with alternative route graphs to motivate the application of our framework.
Analytical dose modeling for preclinical proton irradiation of millimetric targets.
Vanstalle, Marie; Constanzo, Julie; Karakaya, Yusuf; Finck, Christian; Rousseau, Marc; Brasse, David
2018-01-01
Due to the considerable development of proton radiotherapy, several proton platforms have emerged to irradiate small animals in order to study the biological effectiveness of proton radiation. A dedicated analytical treatment planning tool was developed in this study to accurately calculate the delivered dose given the specific constraints imposed by the small dimensions of the irradiated areas. The treatment planning system (TPS) developed in this study is based on an analytical formulation of the Bragg peak and uses experimental range values of protons. The method was validated after comparison with experimental data from the literature and then compared to Monte Carlo simulations conducted using Geant4. Three examples of treatment planning, performed with phantoms made of water targets and bone-slab insert, were generated with the analytical formulation and Geant4. Each treatment planning was evaluated using dose-volume histograms and gamma index maps. We demonstrate the value of the analytical function for mouse irradiation, which requires a targeting accuracy of 0.1 mm. Using the appropriate database, the analytical modeling limits the errors caused by misestimating the stopping power. For example, 99% of a 1-mm tumor irradiated with a 24-MeV beam receives the prescribed dose. The analytical dose deviations from the prescribed dose remain within the dose tolerances stated by report 62 of the International Commission on Radiation Units and Measurements for all tested configurations. In addition, the gamma index maps show that the highly constrained targeting accuracy of 0.1 mm for mouse irradiation leads to a significant disagreement between Geant4 and the reference. This simulated treatment planning is nevertheless compatible with a targeting accuracy exceeding 0.2 mm, corresponding to rat and rabbit irradiations. Good dose accuracy for millimetric tumors is achieved with the analytical calculation used in this work. These volume sizes are typical in mouse
Analytical fitting model for rough-surface BRDF.
Renhorn, Ingmar G E; Boreman, Glenn D
2008-08-18
A physics-based model is developed for rough surface BRDF, taking into account angles of incidence and scattering, effective index, surface autocovariance, and correlation length. Shadowing is introduced on surface correlation length and reflectance. Separate terms are included for surface scatter, bulk scatter and retroreflection. Using the FindFit function in Mathematica, the functional form is fitted to BRDF measurements over a wide range of incident angles. The model has fourteen fitting parameters; once these are fixed, the model accurately describes scattering data over two orders of magnitude in BRDF without further adjustment. The resulting analytical model is convenient for numerical computations.
Zlotnik, V. A.; Ledder, G.; Kacimov, A. R.
2014-12-01
Disposal of excessive runoff or treated sewage into wadis and ephemeral streams is a common practice and an important hydrological problem in many Middle Eastern countries. While chemical and biological properties of the injected treated wastewater may be different from those of the receiving aquifer, the density contrast between the two fluids can be small. Therefore, studies of the fluid interface for variable density fluids or water intrusion are not directly relevant in many Managed Aquifer Recharge (MAR) problems. Other factors, such as the transient nature of injection and lack of detailed aquifer information must be considered. The disposed water reaching the water table through the vadose zone creates groundwater mounds, deforms the original water table, and develops finite-size convex-concave lenses of treated water over receiving water. After cessation of infiltration, these mounds flatten, water levels become horizontal, and infiltrated water becomes fully embedded in the receiving aquifer. The shape of the treated water body is controlled by the aquifer parameters, the magnitude of ambient flow, and the duration, rate, and cyclicity of infiltration. In case of limited aquifer data, advective transport modeling offers the most appropriate tools for predicting plume shapes over time, but surprisingly little work has been done on this important 3D flow problem. We investigate the lateral and vertical spreading of infiltrated water combining techniques of spatial velocity analyses by Zlotnik and Ledder (1992, 1993) with particle tracking. This approach allows for evaluating the geometry of the plume and the protection zone, the flow development phases, and other temporal and spatial effects and results can be used in conditions of limited data availability and quality. (Funding was provided by the USAID, DAI Subcontract 1001624-12S-19745)
Spatial and Social Media Data Analytics of Housing Prices in Shenzhen, China.
Wu, Chao; Ye, Xinyue; Ren, Fu; Wan, You; Ning, Pengfei; Du, Qingyun
2016-01-01
Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big data perspective to determine the willingness of buyers to pay for various factors. The opinions and geographical preferences of individuals for places can be represented by visit frequencies given different motivations. Check-in data from the social media platform Sina Visitor System is used in this article. Here, we use kernel density estimation (KDE) to analyse the spatial patterns of check-in spots (or places of interest, POIs) and employ the Getis-Ord [Formula: see text] method to identify the hot spots for different types of POIs in Shenzhen, China. New indexes are then proposed based on the hot-spot results as measured by check-in data to analyse the effects of these locations on housing prices. This modelling is performed using the hedonic price method (HPM) and the geographically weighted regression (GWR) method. The results show that the degree of clustering of POIs has a significant influence on housing values. Meanwhile, the GWR method has a better interpretive capacity than does the HPM because of the former method's ability to capture spatial heterogeneity. This article integrates big social media data to expand the scope (new study content) and depth (study scale) of housing price research to an unprecedented degree.
Spatial and Social Media Data Analytics of Housing Prices in Shenzhen, China.
Chao Wu
Full Text Available Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big data perspective to determine the willingness of buyers to pay for various factors. The opinions and geographical preferences of individuals for places can be represented by visit frequencies given different motivations. Check-in data from the social media platform Sina Visitor System is used in this article. Here, we use kernel density estimation (KDE to analyse the spatial patterns of check-in spots (or places of interest, POIs and employ the Getis-Ord [Formula: see text] method to identify the hot spots for different types of POIs in Shenzhen, China. New indexes are then proposed based on the hot-spot results as measured by check-in data to analyse the effects of these locations on housing prices. This modelling is performed using the hedonic price method (HPM and the geographically weighted regression (GWR method. The results show that the degree of clustering of POIs has a significant influence on housing values. Meanwhile, the GWR method has a better interpretive capacity than does the HPM because of the former method's ability to capture spatial heterogeneity. This article integrates big social media data to expand the scope (new study content and depth (study scale of housing price research to an unprecedented degree.
Analytical heat transfer modeling of a new radiation calorimeter
Obame Ndong, Elysée [Department of Industrial Engineering and Maintenance, University of Sciences and Technology of Masuku (USTM), BP 941 Franceville (Gabon); Grenoble Electrical Engineering Laboratory (G2Elab), University Grenoble Alpes and CNRS, G2Elab, F38000 Grenoble (France); Gallot-Lavallée, Olivier [Grenoble Electrical Engineering Laboratory (G2Elab), University Grenoble Alpes and CNRS, G2Elab, F38000 Grenoble (France); Aitken, Frédéric, E-mail: frederic.aitken@g2elab.grenoble-inp.fr [Grenoble Electrical Engineering Laboratory (G2Elab), University Grenoble Alpes and CNRS, G2Elab, F38000 Grenoble (France)
2016-06-10
Highlights: • Design of a new calorimeter for measuring heat power loss in electrical components. • The calorimeter can operate in a temperature range from −50 °C to 150 °C. • An analytical model of heat transfers for this new calorimeter is presented. • The theoretical sensibility of the new apparatus is estimated at ±1 mW. - Abstract: This paper deals with an analytical modeling of heat transfers simulating a new radiation calorimeter operating in a temperature range from −50 °C to 150 °C. The aim of this modeling is the evaluation of the feasibility and performance of the calorimeter by assessing the measurement of power losses of some electrical devices by radiation, the influence of the geometry and materials. Finally a theoretical sensibility of the new apparatus is estimated at ±1 mW. From these results the calorimeter has been successfully implemented and patented.
Analytical heat transfer modeling of a new radiation calorimeter
Obame Ndong, Elysée; Gallot-Lavallée, Olivier; Aitken, Frédéric
2016-01-01
Highlights: • Design of a new calorimeter for measuring heat power loss in electrical components. • The calorimeter can operate in a temperature range from −50 °C to 150 °C. • An analytical model of heat transfers for this new calorimeter is presented. • The theoretical sensibility of the new apparatus is estimated at ±1 mW. - Abstract: This paper deals with an analytical modeling of heat transfers simulating a new radiation calorimeter operating in a temperature range from −50 °C to 150 °C. The aim of this modeling is the evaluation of the feasibility and performance of the calorimeter by assessing the measurement of power losses of some electrical devices by radiation, the influence of the geometry and materials. Finally a theoretical sensibility of the new apparatus is estimated at ±1 mW. From these results the calorimeter has been successfully implemented and patented.
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J
2010-12-01
Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies
Yamamoto, Akio; Tatsumi, Masahiro
2006-01-01
In this paper, the scattered source subtraction (SSS) method is newly proposed to improve the spatial discretization error of the semi-analytic nodal method with the flat-source approximation. In the SSS method, the scattered source is subtracted from both side of the diffusion or the transport equation to make spatial variation of the source term to be small. The same neutron balance equation is still used in the SSS method. Since the SSS method just modifies coefficients of node coupling equations (those used in evaluation for the response of partial currents), its implementation is easy. Validity of the present method is verified through test calculations that are carried out in PWR multi-assemblies configurations. The calculation results show that the SSS method can significantly improve the spatial discretization error. Since the SSS method does not have any negative impact on execution time, convergence behavior and memory requirement, it will be useful to reduce the spatial discretization error of the semi-analytic nodal method with the flat-source approximation. (author)
Using Learning Analytics to Understand Scientific Modeling in the Classroom
David Quigley
2017-11-01
Full Text Available Scientific models represent ideas, processes, and phenomena by describing important components, characteristics, and interactions. Models are constructed across various scientific disciplines, such as the food web in biology, the water cycle in Earth science, or the structure of the solar system in astronomy. Models are central for scientists to understand phenomena, construct explanations, and communicate theories. Constructing and using models to explain scientific phenomena is also an essential practice in contemporary science classrooms. Our research explores new techniques for understanding scientific modeling and engagement with modeling practices. We work with students in secondary biology classrooms as they use a web-based software tool—EcoSurvey—to characterize organisms and their interrelationships found in their local ecosystem. We use learning analytics and machine learning techniques to answer the following questions: (1 How can we automatically measure the extent to which students’ scientific models support complete explanations of phenomena? (2 How does the design of student modeling tools influence the complexity and completeness of students’ models? (3 How do clickstreams reflect and differentiate student engagement with modeling practices? We analyzed EcoSurvey usage data collected from two different deployments with over 1,000 secondary students across a large urban school district. We observe large variations in the completeness and complexity of student models, and large variations in their iterative refinement processes. These differences reveal that certain key model features are highly predictive of other aspects of the model. We also observe large differences in student modeling practices across different classrooms and teachers. We can predict a student’s teacher based on the observed modeling practices with a high degree of accuracy without significant tuning of the predictive model. These results highlight
An Analytical Tire Model with Flexible Carcass for Combined Slips
Nan Xu
2014-01-01
Full Text Available The tire mechanical characteristics under combined cornering and braking/driving situations have significant effects on vehicle directional controls. The objective of this paper is to present an analytical tire model with flexible carcass for combined slip situations, which can describe tire behavior well and can also be used for studying vehicle dynamics. The tire forces and moments come mainly from the shear stress and sliding friction at the tread-road interface. In order to describe complicated tire characteristics and tire-road friction, some key factors are considered in this model: arbitrary pressure distribution; translational, bending, and twisting compliance of the carcass; dynamic friction coefficient; anisotropic stiffness properties. The analytical tire model can describe tire forces and moments accurately under combined slip conditions. Some important properties induced by flexible carcass can also be reflected. The structural parameters of a tire can be identified from tire measurements and the computational results using the analytical model show good agreement with test data.
SINGLE PHASE ANALYTICAL MODELS FOR TERRY TURBINE NOZZLE
Zhao, Haihua; Zhang, Hongbin; Zou, Ling; O' Brien, James
2016-11-01
All BWR RCIC (Reactor Core Isolation Cooling) systems and PWR AFW (Auxiliary Feed Water) systems use Terry turbine, which is composed of the wheel with turbine buckets and several groups of fixed nozzles and reversing chambers inside the turbine casing. The inlet steam is accelerated through the turbine nozzle and impacts on the wheel buckets, generating work to drive the RCIC pump. As part of the efforts to understand the unexpected “self-regulating” mode of the RCIC systems in Fukushima accidents and extend BWR RCIC and PWR AFW operational range and flexibility, mechanistic models for the Terry turbine, based on Sandia National Laboratories’ original work, has been developed and implemented in the RELAP-7 code to simulate the RCIC system. RELAP-7 is a new reactor system code currently under development with the funding support from U.S. Department of Energy. The RELAP-7 code is a fully implicit code and the preconditioned Jacobian-free Newton-Krylov (JFNK) method is used to solve the discretized nonlinear system. This paper presents a set of analytical models for simulating the flow through the Terry turbine nozzles when inlet fluid is pure steam. The implementation of the models into RELAP-7 will be briefly discussed. In the Sandia model, the turbine bucket inlet velocity is provided according to a reduced-order model, which was obtained from a large number of CFD simulations. In this work, we propose an alternative method, using an under-expanded jet model to obtain the velocity and thermodynamic conditions for the turbine bucket inlet. The models include both adiabatic expansion process inside the nozzle and free expansion process out of the nozzle to reach the ambient pressure. The combined models are able to predict the steam mass flow rate and supersonic velocity to the Terry turbine bucket entrance, which are the necessary input conditions for the Terry Turbine rotor model. The nozzle analytical models were validated with experimental data and
Spatial Data Web Services Pricing Model Infrastructure
Ozmus, L.; Erkek, B.; Colak, S.; Cankurt, I.; Bakıcı, S.
2013-08-01
most important law with related NSDI is the establishment of General Directorate of Geographic Information System under the Ministry of Environment and Urbanism. due to; to do or to have do works and activities with related to the establishment of National Geographic Information Systems (NGIS), usage of NGIS and improvements of NGIS. Outputs of these projects are served to not only public administration but also to Turkish society. Today for example, TAKBIS data (cadastre services) are shared more than 50 institutions by Web services, Tusaga-Aktif system has more than 3800 users who are having real-time GPS data correction, Orthophoto WMS services has been started for two years as a charge of free. Today there is great discussion about data pricing among the institutions. Some of them think that the pricing is storage of the data. Some of them think that the pricing is value of data itself. There is no certain rule about pricing. On this paper firstly, pricing of data storage and later on spatial data pricing models in different countries are investigated to improve institutional understanding in Turkey.
ANALYTICAL AND SIMULATION PLANNING MODEL OF URBAN PASSENGER TRANSPORT
Andrey Borisovich Nikolaev
2017-09-01
Full Text Available The article described the structure of the analytical and simulation models to make informed decisions in the planning of urban passenger transport. Designed UML diagram that describes the relationship of classes of the proposed model. A description of the main agents of the model developed in the simulation AnyLogic. Designed user interface integration with GIS map. Also provides simulation results that allow concluding about her health and the possibility of its use in solving planning problems of urban passenger transport.
Analytical and finite element modeling of grounding systems
Luz, Mauricio Valencia Ferreira da [University of Santa Catarina (UFSC), Florianopolis, SC (Brazil)], E-mail: mauricio@grucad.ufsc.br; Dular, Patrick [University of Liege (Belgium). Institut Montefiore], E-mail: Patrick.Dular@ulg.ac.be
2007-07-01
Grounding is the art of making an electrical connection to the earth. This paper deals with the analytical and finite element modeling of grounding systems. An electrokinetic formulation using a scalar potential can benefit from floating potentials to define global quantities such as electric voltages and currents. The application concerns a single vertical grounding with one, two and three-layer soil, where the superior extremity stays in the surface of the soil. This problem has been modeled using a 2D axi-symmetric electrokinetic formulation. The grounding resistance obtained by finite element method is compared with the analytical one for one-layer soil. With the results of this paper it is possible to show that finite element method is a powerful tool in the analysis of the grounding systems in low frequencies. (author)
A simple stationary semi-analytical wake model
Larsen, Gunner Chr.
We present an idealized simple, but fast, semi-analytical algorithm for computation of stationary wind farm wind fields with a possible potential within a multi-fidelity strategy for wind farm topology optimization. Basically, the model considers wakes as linear perturbations on the ambient non......-linear. With each of these approached, a parabolic system are described, which is initiated by first considering the most upwind located turbines and subsequently successively solved in the downstream direction. Algorithms for the resulting wind farm flow fields are proposed, and it is shown that in the limit......-uniform mean wind field, although the modelling of the individual stationary wake flow fields includes non-linear terms. The simulation of the individual wake contributions are based on an analytical solution of the thin shear layer approximation of the NS equations. The wake flow fields are assumed...
Human performance modeling for system of systems analytics.
Dixon, Kevin R.; Lawton, Craig R.; Basilico, Justin Derrick; Longsine, Dennis E. (INTERA, Inc., Austin, TX); Forsythe, James Chris; Gauthier, John Henry; Le, Hai D.
2008-10-01
A Laboratory-Directed Research and Development project was initiated in 2005 to investigate Human Performance Modeling in a System of Systems analytic environment. SAND2006-6569 and SAND2006-7911 document interim results from this effort; this report documents the final results. The problem is difficult because of the number of humans involved in a System of Systems environment and the generally poorly defined nature of the tasks that each human must perform. A two-pronged strategy was followed: one prong was to develop human models using a probability-based method similar to that first developed for relatively well-understood probability based performance modeling; another prong was to investigate more state-of-art human cognition models. The probability-based modeling resulted in a comprehensive addition of human-modeling capability to the existing SoSAT computer program. The cognitive modeling resulted in an increased understanding of what is necessary to incorporate cognition-based models to a System of Systems analytic environment.
Two dimensional analytical model for a reconfigurable field effect transistor
Ranjith, R.; Jayachandran, Remya; Suja, K. J.; Komaragiri, Rama S.
2018-02-01
This paper presents two-dimensional potential and current models for a reconfigurable field effect transistor (RFET). Two potential models which describe subthreshold and above-threshold channel potentials are developed by solving two-dimensional (2D) Poisson's equation. In the first potential model, 2D Poisson's equation is solved by considering constant/zero charge density in the channel region of the device to get the subthreshold potential characteristics. In the second model, accumulation charge density is considered to get above-threshold potential characteristics of the device. The proposed models are applicable for the device having lightly doped or intrinsic channel. While obtaining the mathematical model, whole body area is divided into two regions: gated region and un-gated region. The analytical models are compared with technology computer-aided design (TCAD) simulation results and are in complete agreement for different lengths of the gated regions as well as at various supply voltage levels.
New analytically solvable models of relativistic point interactions
Gesztesy, F.; Seba, P.
1987-01-01
Two new analytically solvable models of relativistic point interactions in one dimension (being natural extensions of the nonrelativistic δ-resp, δ'-interaction) are considered. Their spectral properties in the case of finitely many point interactions as well as in the periodic case are fully analyzed. Moreover the spectrum is explicitely determined in the case of independent, identically distributed random coupling constants and the analog of the Saxon and Huther conjecture concerning gaps in the energy spectrum of such systems is derived
Panchromatic SED modelling of spatially resolved galaxies
Smith, Daniel J. B.; Hayward, Christopher C.
2018-05-01
We test the efficacy of the energy-balance spectral energy distribution (SED) fitting code MAGPHYS for recovering the spatially resolved properties of a simulated isolated disc galaxy, for which it was not designed. We perform 226 950 MAGPHYS SED fits to regions between 0.2 and 25 kpc in size across the galaxy's disc, viewed from three different sight-lines, to probe how well MAGPHYS can recover key galaxy properties based on 21 bands of UV-far-infrared model photometry. MAGPHYS yields statistically acceptable fits to >99 per cent of the pixels within the r-band effective radius and between 59 and 77 percent of pixels within 20 kpc of the nucleus. MAGPHYS is able to recover the distribution of stellar mass, star formation rate (SFR), specific SFR, dust luminosity, dust mass, and V-band attenuation reasonably well, especially when the pixel size is ≳ 1 kpc, whereas non-standard outputs (stellar metallicity and mass-weighted age) are recovered less well. Accurate recovery is more challenging in the smallest sub-regions of the disc (pixel scale ≲ 1 kpc), where the energy balance criterion becomes increasingly incorrect. Estimating integrated galaxy properties by summing the recovered pixel values, the true integrated values of all parameters considered except metallicity and age are well recovered at all spatial resolutions, ranging from 0.2 kpc to integrating across the disc, albeit with some evidence for resolution-dependent biases. These results must be considered when attempting to analyse the structure of real galaxies with actual observational data, for which the `ground truth' is unknown.
Vibration Based Diagnosis for Planetary Gearboxes Using an Analytical Model
Liu Hong
2016-01-01
Full Text Available The application of conventional vibration based diagnostic techniques to planetary gearboxes is a challenge because of the complexity of frequency components in the measured spectrum, which is the result of relative motions between the rotary planets and the fixed accelerometer. In practice, since the fault signatures are usually contaminated by noises and vibrations from other mechanical components of gearboxes, the diagnostic efficacy may further deteriorate. Thus, it is essential to develop a novel vibration based scheme to diagnose gear failures for planetary gearboxes. Following a brief literature review, the paper begins with the introduction of an analytical model of planetary gear-sets developed by the authors in previous works, which can predict the distinct behaviors of fault introduced sidebands. This analytical model is easy to implement because the only prerequisite information is the basic geometry of the planetary gear-set. Afterwards, an automated diagnostic scheme is proposed to cope with the challenges associated with the characteristic configuration of planetary gearboxes. The proposed vibration based scheme integrates the analytical model, a denoising algorithm, and frequency domain indicators into one synergistic system for the detection and identification of damaged gear teeth in planetary gearboxes. Its performance is validated with the dynamic simulations and the experimental data from a planetary gearbox test rig.
Hiebeler, David E; Millett, Nicholas E
2011-06-21
We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.
AN ANALYTIC RADIATIVE-CONVECTIVE MODEL FOR PLANETARY ATMOSPHERES
Robinson, Tyler D.; Catling, David C.
2012-01-01
We present an analytic one-dimensional radiative-convective model of the thermal structure of planetary atmospheres. Our model assumes that thermal radiative transfer is gray and can be represented by the two-stream approximation. Model atmospheres are assumed to be in hydrostatic equilibrium, with a power-law scaling between the atmospheric pressure and the gray thermal optical depth. The convective portions of our models are taken to follow adiabats that account for condensation of volatiles through a scaling parameter to the dry adiabat. By combining these assumptions, we produce simple, analytic expressions that allow calculations of the atmospheric-pressure-temperature profile, as well as expressions for the profiles of thermal radiative flux and convective flux. We explore the general behaviors of our model. These investigations encompass (1) worlds where atmospheric attenuation of sunlight is weak, which we show tend to have relatively high radiative-convective boundaries; (2) worlds with some attenuation of sunlight throughout the atmosphere, which we show can produce either shallow or deep radiative-convective boundaries, depending on the strength of sunlight attenuation; and (3) strongly irradiated giant planets (including hot Jupiters), where we explore the conditions under which these worlds acquire detached convective regions in their mid-tropospheres. Finally, we validate our model and demonstrate its utility through comparisons to the average observed thermal structure of Venus, Jupiter, and Titan, and by comparing computed flux profiles to more complex models.
A simple analytical infiltration model for short-duration rainfall
Wang, Kaiwen; Yang, Xiaohua; Liu, Xiaomang; Liu, Changming
2017-12-01
Many infiltration models have been proposed to simulate infiltration process. Different initial soil conditions and non-uniform initial water content can lead to infiltration simulation errors, especially for short-duration rainfall (SHR). Few infiltration models are specifically derived to eliminate the errors caused by the complex initial soil conditions. We present a simple analytical infiltration model for SHR infiltration simulation, i.e., Short-duration Infiltration Process model (SHIP model). The infiltration simulated by 5 models (i.e., SHIP (high) model, SHIP (middle) model, SHIP (low) model, Philip model and Parlange model) were compared based on numerical experiments and soil column experiments. In numerical experiments, SHIP (middle) and Parlange models had robust solutions for SHR infiltration simulation of 12 typical soils under different initial soil conditions. The absolute values of percent bias were less than 12% and the values of Nash and Sutcliffe efficiency were greater than 0.83. Additionally, in soil column experiments, infiltration rate fluctuated in a range because of non-uniform initial water content. SHIP (high) and SHIP (low) models can simulate an infiltration range, which successfully covered the fluctuation range of the observed infiltration rate. According to the robustness of solutions and the coverage of fluctuation range of infiltration rate, SHIP model can be integrated into hydrologic models to simulate SHR infiltration process and benefit the flood forecast.
Analytical model of tilted driver–pickup coils for eddy current nondestructive evaluation
Cao, Bing-Hua; Li, Chao; Fan, Meng-Bao; Ye, Bo; Tian, Gui-Yun
2018-03-01
A driver-pickup probe possesses better sensitivity and flexibility due to individual optimization of a coil. It is frequently observed in an eddy current (EC) array probe. In this work, a tilted non-coaxial driver-pickup probe above a multilayered conducting plate is analytically modeled with spatial transformation for eddy current nondestructive evaluation. Basically, the core of the formulation is to obtain the projection of magnetic vector potential (MVP) from the driver coil onto the vector along the tilted pickup coil, which is divided into two key steps. The first step is to make a projection of MVP along the pickup coil onto a horizontal plane, and the second one is to build the relationship between the projected MVP and the MVP along the driver coil. Afterwards, an analytical model for the case of a layered plate is established with the reflection and transmission theory of electromagnetic fields. The calculated values from the resulting model indicate good agreement with those from the finite element model (FEM) and experiments, which validates the developed analytical model. Project supported by the National Natural Science Foundation of China (Grant Nos. 61701500, 51677187, and 51465024).
Fractal approach to computer-analytical modelling of tree crown
Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.
1993-09-01
In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs
Challenges in the development of analytical soil compaction models
Keller, Thomas; Lamandé, Mathieu
2010-01-01
and recommendations for the prevention of soil compaction often rely on simulation models. This paper highlights some issues that need further consideration in order to improve soil compaction modelling, with the focus on analytical models. We discuss the different issues based on comparisons between experimental......Soil compaction can cause a number of environmental and agronomic problems (e.g. flooding, erosion, leaching of agrochemicals to recipient waters, emission of greenhouse gases to the atmosphere, crop yield losses), resulting in significant economic damage to society and agriculture. Strategies...... data and model simulations. The upper model boundary condition (i.e. contact area and stresses at the tyre-soil interface) is highly influential in stress propagation, but knowledge on the effects of loading and soil conditions on the upper model boundary condition is inadequate. The accuracy of stress...
Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M
2008-11-07
Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of
Consequences of spatial autocorrelation for niche-based models
Segurado, P.; Araújo, Miguel B.; Kunin, W. E.
2006-01-01
1. Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2. Analyses were based o...
Spatial Econometric data analysis: moving beyond traditional models
Florax, R.J.G.M.; Vlist, van der A.J.
2003-01-01
This article appraises recent advances in the spatial econometric literature. It serves as the introduction too collection of new papers on spatial econometric data analysis brought together in this special issue, dealing specifically with new extensions to the spatial econometric modeling
Analytical properties of a three-compartmental dynamical demographic model
Postnikov, E. B.
2015-07-01
The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.
Model and Analytic Processes for Export License Assessments
Thompson, Sandra E.; Whitney, Paul D.; Weimar, Mark R.; Wood, Thomas W.; Daly, Don S.; Brothers, Alan J.; Sanfilippo, Antonio P.; Cook, Diane; Holder, Larry
2011-09-29
This paper represents the Department of Energy Office of Nonproliferation Research and Development (NA-22) Simulations, Algorithms and Modeling (SAM) Program's first effort to identify and frame analytical methods and tools to aid export control professionals in effectively predicting proliferation intent; a complex, multi-step and multi-agency process. The report focuses on analytical modeling methodologies that alone, or combined, may improve the proliferation export control license approval process. It is a follow-up to an earlier paper describing information sources and environments related to international nuclear technology transfer. This report describes the decision criteria used to evaluate modeling techniques and tools to determine which approaches will be investigated during the final 2 years of the project. The report also details the motivation for why new modeling techniques and tools are needed. The analytical modeling methodologies will enable analysts to evaluate the information environment for relevance to detecting proliferation intent, with specific focus on assessing risks associated with transferring dual-use technologies. Dual-use technologies can be used in both weapons and commercial enterprises. A decision-framework was developed to evaluate which of the different analytical modeling methodologies would be most appropriate conditional on the uniqueness of the approach, data availability, laboratory capabilities, relevance to NA-22 and Office of Arms Control and Nonproliferation (NA-24) research needs and the impact if successful. Modeling methodologies were divided into whether they could help micro-level assessments (e.g., help improve individual license assessments) or macro-level assessment. Macro-level assessment focuses on suppliers, technology, consumers, economies, and proliferation context. Macro-level assessment technologies scored higher in the area of uniqueness because less work has been done at the macro level. An
Gas Atomization of Aluminium Melts: Comparison of Analytical Models
Georgios Antipas
2012-06-01
Full Text Available A number of analytical models predicting the size distribution of particles during atomization of Al-based alloys by N2, He and Ar gases were compared. Simulations of liquid break up in a close coupled atomizer revealed that the finer particles are located near the center of the spray cone. Increasing gas injection pressures led to an overall reduction of particle diameters and caused a migration of the larger powder particles towards the outer boundary of the flow. At sufficiently high gas pressures the spray became monodisperse. The models also indicated that there is a minimum achievable mean diameter for any melt/gas system.
A simple analytical model for reactive particle ignition in explosives
Tanguay, Vincent [Defence Research and Development Canada - Valcartier, 2459 Pie XI Blvd. North, Quebec, QC, G3J 1X5 (Canada); Higgins, Andrew J. [Department of Mechanical Engineering, McGill University, 817 Sherbrooke St. West, Montreal, QC, H3A 2K6 (Canada); Zhang, Fan [Defence Research and Development Canada - Suffield, P. O. Box 4000, Stn Main, Medicine Hat, AB, T1A 8K6 (Canada)
2007-10-15
A simple analytical model is developed to predict ignition of magnesium particles in nitromethane detonation products. The flow field is simplified by considering the detonation products as a perfect gas expanding in a vacuum in a planar geometry. This simplification allows the flow field to be solved analytically. A single particle is then introduced in this flow field. Its trajectory and heating history are computed. It is found that most of the particle heating occurs in the Taylor wave and in the quiescent flow region behind it, shortly after which the particle cools. By considering only these regions, thereby considerably simplifying the problem, the flow field can be solved analytically with a more realistic equation of state (such as JWL) and a spherical geometry. The model is used to compute the minimum charge diameter for particle ignition to occur. It is found that the critical charge diameter for particle ignition increases with particle size. These results are compared to experimental data and show good agreement. (Abstract Copyright [2007], Wiley Periodicals, Inc.)
HTS axial flux induction motor with analytic and FEA modeling
Li, S., E-mail: alexlee.zn@gmail.com; Fan, Y.; Fang, J.; Qin, W.; Lv, G.; Li, J.H.
2013-11-15
Highlights: •A high temperature superconductor axial flux induction motor and a novel maglev scheme are presented. •Analytic method and finite element method have been adopted to model the motor and to calculate the force. •Magnetic field distribution in HTS coil is calculated by analytic method. •An effective method to improve the critical current of HTS coil is presented. •AC losses of HTS coils in the HTS axial flux induction motor are estimated and tested. -- Abstract: This paper presents a high-temperature superconductor (HTS) axial-flux induction motor, which can output levitation force and torque simultaneously. In order to analyze the character of the force, analytic method and finite element method are adopted to model the motor. To make sure the HTS can carry sufficiently large current and work well, the magnetic field distribution in HTS coil is calculated. An effective method to improve the critical current of HTS coil is presented. Then, AC losses in HTS windings in the motor are estimated and tested.
HTS axial flux induction motor with analytic and FEA modeling
Li, S.; Fan, Y.; Fang, J.; Qin, W.; Lv, G.; Li, J.H.
2013-01-01
Highlights: •A high temperature superconductor axial flux induction motor and a novel maglev scheme are presented. •Analytic method and finite element method have been adopted to model the motor and to calculate the force. •Magnetic field distribution in HTS coil is calculated by analytic method. •An effective method to improve the critical current of HTS coil is presented. •AC losses of HTS coils in the HTS axial flux induction motor are estimated and tested. -- Abstract: This paper presents a high-temperature superconductor (HTS) axial-flux induction motor, which can output levitation force and torque simultaneously. In order to analyze the character of the force, analytic method and finite element method are adopted to model the motor. To make sure the HTS can carry sufficiently large current and work well, the magnetic field distribution in HTS coil is calculated. An effective method to improve the critical current of HTS coil is presented. Then, AC losses in HTS windings in the motor are estimated and tested
Analytical local electron-electron interaction model potentials for atoms
Neugebauer, Johannes; Reiher, Markus; Hinze, Juergen
2002-01-01
Analytical local potentials for modeling the electron-electron interaction in an atom reduce significantly the computational effort in electronic structure calculations. The development of such potentials has a long history, but some promising ideas have not yet been taken into account for further improvements. We determine a local electron-electron interaction potential akin to those suggested by Green et al. [Phys. Rev. 184, 1 (1969)], which are widely used in atom-ion scattering calculations, electron-capture processes, and electronic structure calculations. Generalized Yukawa-type model potentials are introduced. This leads, however, to shell-dependent local potentials, because the origin behavior of such potentials is different for different shells as has been explicated analytically [J. Neugebauer, M. Reiher, and J. Hinze, Phys. Rev. A 65, 032518 (2002)]. It is found that the parameters that characterize these local potentials can be interpolated and extrapolated reliably for different nuclear charges and different numbers of electrons. The analytical behavior of the corresponding localized Hartree-Fock potentials at the origin and at long distances is utilized in order to reduce the number of fit parameters. It turns out that the shell-dependent form of Green's potential, which we also derive, yields results of comparable accuracy using only one shell-dependent parameter
The spatial limitations of current neutral models of biodiversity.
Rampal S Etienne
Full Text Available The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a 'fat-tailed' distribution. Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.
Analytical models of optical response in one-dimensional semiconductors
Pedersen, Thomas Garm
2015-01-01
The quantum mechanical description of the optical properties of crystalline materials typically requires extensive numerical computation. Including excitonic and non-perturbative field effects adds to the complexity. In one dimension, however, the analysis simplifies and optical spectra can be computed exactly. In this paper, we apply the Wannier exciton formalism to derive analytical expressions for the optical response in four cases of increasing complexity. Thus, we start from free carriers and, in turn, switch on electrostatic fields and electron–hole attraction and, finally, analyze the combined influence of these effects. In addition, the optical response of impurity-localized excitons is discussed. - Highlights: • Optical response of one-dimensional semiconductors including excitons. • Analytical model of excitonic Franz–Keldysh effect. • Computation of optical response of impurity-localized excitons
Analytical expressions for transition edge sensor excess noise models
Brandt, Daniel; Fraser, George W.
2010-01-01
Transition edge sensors (TESs) are high-sensitivity thermometers used in cryogenic microcalorimeters which exploit the steep gradient in resistivity with temperature during the superconducting phase transition. Practical TES devices tend to exhibit a white noise of uncertain origin, arising inside the device. We discuss two candidate models for this excess noise, phase slip shot noise (PSSN) and percolation noise. We extend the existing PSSN model to include a magnetic field dependence and derive a basic analytical model for percolation noise. We compare the predicted functional forms of the noise current vs. resistivity curves of both models with experimental data and provide a set of equations for both models to facilitate future experimental efforts to clearly identify the source of excess noise.
Model for Atmospheric Propagation of Spatially Combined Laser Beams
2016-09-01
NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS by Kum Leong Lee September...MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS 5. FUNDING NUMBERS 6. AUTHOR(S) Kum Leong Lee 7. PERFORMING ORGANIZATION NAME(S) AND...BLANK ii Approved for public release. Distribution is unlimited. MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS Kum Leong Lee
Analytical modeling of glucose biosensors based on carbon nanotubes.
Pourasl, Ali H; Ahmadi, Mohammad Taghi; Rahmani, Meisam; Chin, Huei Chaeng; Lim, Cheng Siong; Ismail, Razali; Tan, Michael Loong Peng
2014-01-15
In recent years, carbon nanotubes have received widespread attention as promising carbon-based nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal conductivity, carbon nanotubes can be used effectively as electrochemical sensors. The integration of carbon nanotubes with a functional group provides a good and solid support for the immobilization of enzymes. The determination of glucose levels using biosensors, particularly in the medical diagnostics and food industries, is gaining mass appeal. Glucose biosensors detect the glucose molecule by catalyzing glucose to gluconic acid and hydrogen peroxide in the presence of oxygen. This action provides high accuracy and a quick detection rate. In this paper, a single-wall carbon nanotube field-effect transistor biosensor for glucose detection is analytically modeled. In the proposed model, the glucose concentration is presented as a function of gate voltage. Subsequently, the proposed model is compared with existing experimental data. A good consensus between the model and the experimental data is reported. The simulated data demonstrate that the analytical model can be employed with an electrochemical glucose sensor to predict the behavior of the sensing mechanism in biosensors.
A Spatial Model of the Mere Exposure Effect.
Fink, Edward L.; And Others
1989-01-01
Uses a spatial model to examine the relationship between stimulus exposure, cognition, and affect. Notes that this model accounts for cognitive changes that a stimulus may acquire as a result of exposure. Concludes that the spatial model is useful for evaluating the mere exposure effect and that affective change does not require cognitive change.…
Chaogui Kang
Full Text Available We generalized the recently introduced "radiation model", as an analog to the generalization of the classic "gravity model", to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses.
A semi-analytic model of magnetized liner inertial fusion
McBride, Ryan D.; Slutz, Stephen A. [Sandia National Laboratories, Albuquerque, New Mexico 87185 (United States)
2015-05-15
Presented is a semi-analytic model of magnetized liner inertial fusion (MagLIF). This model accounts for several key aspects of MagLIF, including: (1) preheat of the fuel (optionally via laser absorption); (2) pulsed-power-driven liner implosion; (3) liner compressibility with an analytic equation of state, artificial viscosity, internal magnetic pressure, and ohmic heating; (4) adiabatic compression and heating of the fuel; (5) radiative losses and fuel opacity; (6) magnetic flux compression with Nernst thermoelectric losses; (7) magnetized electron and ion thermal conduction losses; (8) end losses; (9) enhanced losses due to prescribed dopant concentrations and contaminant mix; (10) deuterium-deuterium and deuterium-tritium primary fusion reactions for arbitrary deuterium to tritium fuel ratios; and (11) magnetized α-particle fuel heating. We show that this simplified model, with its transparent and accessible physics, can be used to reproduce the general 1D behavior presented throughout the original MagLIF paper [S. A. Slutz et al., Phys. Plasmas 17, 056303 (2010)]. We also discuss some important physics insights gained as a result of developing this model, such as the dependence of radiative loss rates on the radial fraction of the fuel that is preheated.
An analytical model for an input/output-subsystem
Roemgens, J.
1983-05-01
An input/output-subsystem of one or several computers if formed by the external memory units and the peripheral units of a computer system. For these subsystems mathematical models are established, taking into account the special properties of the I/O-subsystems, in order to avoid planning errors and to allow for predictions of the capacity of such systems. Here an analytical model is presented for the magnetic discs of a I/O-subsystem, using analytical methods for the individual waiting queues or waiting queue networks. Only I/O-subsystems of IBM-computer configurations are considered, which can be controlled by the MVS operating system. After a description of the hardware and software components of these I/O-systems, possible solutions from the literature are presented and discussed with respect to their applicability in IBM-I/O-subsystems. Based on these models a special scheme is developed which combines the advantages of the literature models and avoids the disadvantages in part. (orig./RW) [de
Target normal sheath acceleration analytical modeling, comparative study and developments
Perego, C.; Batani, D.; Zani, A.; Passoni, M.
2012-01-01
Ultra-intense laser interaction with solid targets appears to be an extremely promising technique to accelerate ions up to several MeV, producing beams that exhibit interesting properties for many foreseen applications. Nowadays, most of all the published experimental results can be theoretically explained in the framework of the target normal sheath acceleration (TNSA) mechanism proposed by Wilks et al. [Phys. Plasmas 8(2), 542 (2001)]. As an alternative to numerical simulation various analytical or semi-analytical TNSA models have been published in the latest years, each of them trying to provide predictions for some of the ion beam features, given the initial laser and target parameters. However, the problem of developing a reliable model for the TNSA process is still open, which is why the purpose of this work is to enlighten the present situation of TNSA modeling and experimental results, by means of a quantitative comparison between measurements and theoretical predictions of the maximum ion energy. Moreover, in the light of such an analysis, some indications for the future development of the model proposed by Passoni and Lontano [Phys. Plasmas 13(4), 042102 (2006)] are then presented.
A workflow learning model to improve geovisual analytics utility.
Roth, Robert E; Maceachren, Alan M; McCabe, Craig A
2009-01-01
INTRODUCTION: This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. OBJECTIVES: The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. METHODOLOGY: The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on
Bakker, Mark
2010-08-01
A new analytic solution approach is presented for the modeling of steady flow to pumping wells near rivers in strip aquifers; all boundaries of the river and strip aquifer may be curved. The river penetrates the aquifer only partially and has a leaky stream bed. The water level in the river may vary spatially. Flow in the aquifer below the river is semi-confined while flow in the aquifer adjacent to the river is confined or unconfined and may be subject to areal recharge. Analytic solutions are obtained through superposition of analytic elements and Fourier series. Boundary conditions are specified at collocation points along the boundaries. The number of collocation points is larger than the number of coefficients in the Fourier series and a solution is obtained in the least squares sense. The solution is analytic while boundary conditions are met approximately. Very accurate solutions are obtained when enough terms are used in the series. Several examples are presented for domains with straight and curved boundaries, including a well pumping near a meandering river with a varying water level. The area of the river bottom where water infiltrates into the aquifer is delineated and the fraction of river water in the well water is computed for several cases.
Untangling Slab Dynamics Using 3-D Numerical and Analytical Models
Holt, A. F.; Royden, L.; Becker, T. W.
2016-12-01
Increasingly sophisticated numerical models have enabled us to make significant strides in identifying the key controls on how subducting slabs deform. For example, 3-D models have demonstrated that subducting plate width, and the related strength of toroidal flow around the plate edge, exerts a strong control on both the curvature and the rate of migration of the trench. However, the results of numerical subduction models can be difficult to interpret, and many first order dynamics issues remain at least partially unresolved. Such issues include the dominant controls on trench migration, the interdependence of asthenospheric pressure and slab dynamics, and how nearby slabs influence each other's dynamics. We augment 3-D, dynamically evolving finite element models with simple, analytical force-balance models to distill the physics associated with subduction into more manageable parts. We demonstrate that for single, isolated subducting slabs much of the complexity of our fully numerical models can be encapsulated by simple analytical expressions. Rates of subduction and slab dip correlate strongly with the asthenospheric pressure difference across the subducting slab. For double subduction, an additional slab gives rise to more complex mantle pressure and flow fields, and significantly extends the range of plate kinematics (e.g., convergence rate, trench migration rate) beyond those present in single slab models. Despite these additional complexities, we show that much of the dynamics of such multi-slab systems can be understood using the physics illuminated by our single slab study, and that a force-balance method can be used to relate intra-plate stress to viscous pressure in the asthenosphere and coupling forces at plate boundaries. This method has promise for rapid modeling of large systems of subduction zones on a global scale.
Spatial data modelling and maximum entropy theory
Klimešová, Dana; Ocelíková, E.
2005-01-01
Roč. 51, č. 2 (2005), s. 80-83 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : spatial data classification * distribution function * error distribution Subject RIV: BD - Theory of Information
"Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process
Sanfilippo, Antonio P.; Nibbs, Faith G.
2007-08-24
While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.
Analytic modeling of the feedback stabilization of resistive wall modes
Pustovitov, Vladimir D.
2003-01-01
Feedback suppression of resistive wall modes (RWM) is studied analytically using a model based on a standard cylindrical approximation. Optimal choice of the input signal for the feedback, effects related to the geometry of the feedback active coils, RWM suppression in a configuration with ITER-like double wall, are considered here. The widespread opinion that the feedback with poloidal sensors is better than that with radial sensors is discussed. It is shown that for an ideal feedback system the best input signal would be a combination of radial and poloidal perturbations measured inside the vessel. (author)
An analytic model for flow reversal in divertor plasmas
Cooke, P.I.H.; Prinja, A.K.
1987-04-01
An analytic model is developed and used to study the phenomenon of flow reversal which is observed in two-dimensional simulations of divertor plasmas. The effect is shown to be caused by the radial spread of neutral particles emitted from the divertor target which can lead to a strong peaking of the ionization source at certain radial locations. The results indicate that flow reversal over a portion of the width of the scrape-off layer is inevitable in high recycling conditions. Implications for impurity transport and particle removal in reactors are discussed
Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Carl C. Trettin
2015-01-01
Mangrove forests are highly productive and have large carbon sinks while also providing numerous goods and ecosystem services. However, effective management and conservation of the mangrove forests are often dependent on spatially explicit assessments of the resource. Given the remote and highly dispersed nature of mangroves, estimation of biomass and carbon...
Analytic model of Applied-B ion diode impedance behavior
Miller, P.A.; Mendel, C.W. Jr.
1987-01-01
An empirical analysis of impedance data from Applied-B ion diodes used in seven inertial confinement fusion research experiments was published recently. The diodes all operated with impedance values well below the Child's-law value. The analysis uncovered an unusual unifying relationship among data from the different experiments. The analysis suggested that closure of the anode-cathode gap by electrode plasma was not a dominant factor in the experiments, but was not able to elaborate the underlying physics. Here we present a new analytic model of Applied-B ion diodes coupled to accelerators. A critical feature of the diode model is based on magnetic insulation theory. The model successfully describes impedance behavior of these diodes and supports stimulating new viewpoints of the physics of Applied-B ion diode operation
Simplified analytical model for radionuclide transport simulation in the geosphere
Hiromoto, G.
1996-01-01
In order to evaluate postclosure off-site doses from a low-level radioactive waste disposal facilities, an integrated safety assessment methodology has being developed at Instituto de Pesquisas Energeticas e Nucleares. The source-term modelling approach adopted in this system is described and the results obtained in the IAEA NSARS 'The Safety Assessment of Near-Surface Radioactive Waste Disposal Facilities' programme for model intercomparison studies are presented. The radionuclides released from the waste are calculated using a simple first order kinetics model, and the transport, through porous media below the waste is determined by using an analytical solution of the mass transport equation. The methodology and the results obtained in this work are compared with those reported by others participants of the NSARS programme. (author). 4 refs., 4 figs
Getis, Arthur
1997-01-01
In recent years, spatial analysis has become an increasingly active field, as evidenced by the establishment of educational and research programs at many universities. Its popularity is due mainly to new technologies and the development of spatial data infrastructures. This book illustrates some recent developments in spatial analysis, behavioural modelling, and computational intelligence. World renown spatial analysts explain and demonstrate their new and insightful models and methods. The applications are in areas of societal interest such as the spread of infectious diseases, migration behaviour, and retail and agricultural location strategies. In addition, there is emphasis on the uses of new technologoies for the analysis of spatial data through the application of neural network concepts.
Danesh Yazdi, M.; Klaus, J.; Condon, L. E.; Maxwell, R. M.
2017-12-01
Recent advancements in analytical solutions to quantify water and solute time-variant travel time distributions (TTDs) and the related StorAge Selection (SAS) functions synthesize catchment complexity into a simplified, lumped representation. While these analytical approaches are easy and efficient in application, they require high frequency hydrochemical data for parameter estimation. Alternatively, integrated hydrologic models coupled to Lagrangian particle-tracking approaches can directly simulate age under different catchment geometries and complexity at a greater computational expense. Here, we compare and contrast the two approaches by exploring the influence of the spatial distribution of subsurface heterogeneity, interactions between distinct flow domains, diversity of flow pathways, and recharge rate on the shape of TTDs and the relating SAS functions. To this end, we use a parallel three-dimensional variably saturated groundwater model, ParFlow, to solve for the velocity fields in the subsurface. A particle-tracking model, SLIM, is then implemented to determine the age distributions at every real time and domain location, facilitating a direct characterization of the SAS functions as opposed to analytical approaches requiring calibration of such functions. Steady-state results reveal that the assumption of random age sampling scheme might only hold in the saturated region of homogeneous catchments resulting in an exponential TTD. This assumption is however violated when the vadose zone is included as the underlying SAS function gives a higher preference to older ages. The dynamical variability of the true SAS functions is also shown to be largely masked by the smooth analytical SAS functions. As the variability of subsurface spatial heterogeneity increases, the shape of TTD approaches a power-law distribution function, including a broader distribution of shorter and longer travel times. We further found that larger (smaller) magnitude of effective
Analytic Models of Brown Dwarfs and the Substellar Mass Limit
Sayantan Auddy
2016-01-01
Full Text Available We present the analytic theory of brown dwarf evolution and the lower mass limit of the hydrogen burning main-sequence stars and introduce some modifications to the existing models. We give an exact expression for the pressure of an ideal nonrelativistic Fermi gas at a finite temperature, therefore allowing for nonzero values of the degeneracy parameter. We review the derivation of surface luminosity using an entropy matching condition and the first-order phase transition between the molecular hydrogen in the outer envelope and the partially ionized hydrogen in the inner region. We also discuss the results of modern simulations of the plasma phase transition, which illustrate the uncertainties in determining its critical temperature. Based on the existing models and with some simple modification, we find the maximum mass for a brown dwarf to be in the range 0.064M⊙–0.087M⊙. An analytic formula for the luminosity evolution allows us to estimate the time period of the nonsteady state (i.e., non-main-sequence nuclear burning for substellar objects. We also calculate the evolution of very low mass stars. We estimate that ≃11% of stars take longer than 107 yr to reach the main sequence, and ≃5% of stars take longer than 108 yr.
Analytical Modeling for Underground Risk Assessment in Smart Cities
Israr Ullah
2018-06-01
Full Text Available In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a simple linear approximation based on multiple linear regression analysis; (b hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c hybrid approximation approach which is a combination of (a and (b. Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.
An analytically tractable model for community ecology with many species
Dickens, Benjamin; Fisher, Charles; Mehta, Pankaj; Pankaj Mehta Biophysics Theory Group Team
A fundamental problem in community ecology is to understand how ecological processes such as selection, drift, and immigration yield observed patterns in species composition and diversity. Here, we present an analytically tractable, presence-absence (PA) model for community assembly and use it to ask how ecological traits such as the strength of competition, diversity in competition, and stochasticity affect species composition in a community. In our PA model, we treat species as stochastic binary variables that can either be present or absent in a community: species can immigrate into the community from a regional species pool and can go extinct due to competition and stochasticity. Despite its simplicity, the PA model reproduces the qualitative features of more complicated models of community assembly. In agreement with recent work on large, competitive Lotka-Volterra systems, the PA model exhibits distinct ecological behaviors organized around a special (``critical'') point corresponding to Hubbell's neutral theory of biodiversity. Our results suggest that the concepts of ``phases'' and phase diagrams can provide a powerful framework for thinking about community ecology and that the PA model captures the essential ecological dynamics of community assembly. Pm was supported by a Simons Investigator in the Mathematical Modeling of Living Systems and a Sloan Research Fellowship.
Garrido, Eva; Camacho-Muñoz, Dolores; Martín, Julia; Santos, Antonio; Santos, Juan Luis; Aparicio, Irene; Alonso, Esteban
2016-12-01
Guadiamar River is located in the southwest of the Iberian Peninsula and connects two protected areas in the South of Spain: Sierra Morena and Doñana National Park. It is sited in an area affected by urban, industrial and agriculture sewage pollution and with tradition on intensive mining activities. Most of the studies performed in this area have been mainly focused on the presence of heavy metals and, until now, little is known about the occurrence of other contaminants such as emerging organic pollutants (EOPs). In this work, an analytical method has been optimized and validated for monitoring of forty-seven EOPs in surface water. The analytical method has been applied to study the distribution and environmental risk of these pollutants in Guadiamar River basin. The analytical method was based on solid-phase extraction and determination by liquid chromatography-triple quadrupole-tandem mass spectrometry. The 60 % of the target compounds were found in the analyzed samples. The highest concentrations were found for two plasticizers (bisphenol A and di(2-ethyhexyl)phthalate, mean concentration up to 930 ng/L) and two pharmaceutical compounds (caffeine (up to 623 ng/L) and salicylic acid (up to 318 ng/L)). This study allowed to evaluate the potential sources (industrial or urban) of the studied compounds and the spatial distribution of their concentrations along the river. Environmental risk assessment showed a major risk on the south of the river, mainly due to discharges of wastewater effluents.
Modeling spatial processes with unknown extremal dependence class
Huser, Raphaë l G.; Wadsworth, Jennifer L.
2017-01-01
Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models
Spatial structures in a simple model of population dynamics for parasite-host interactions
Dong, J. J.; Skinner, B.; Breecher, N.; Schmittmann, B.; Zia, R. K. P.
2015-08-01
Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the populations long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocity generally increases the parasite population.
Modeling the spatial reach of the LFP
Lindén, Henrik; Tetzlaff, Tom; Potjans, Tobias C
2011-01-01
The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent ...
Spatial modeling of potential woody biomass flow
Woodam Chung; Nathaniel Anderson
2012-01-01
The flow of woody biomass to end users is determined by economic factors, especially the amount available across a landscape and delivery costs of bioenergy facilities. The objective of this study develop methodology to quantify landscape-level stocks and potential biomass flows using the currently available spatial database road network analysis tool. We applied this...
Modeling fixation locations using spatial point processes.
Barthelmé, Simon; Trukenbrod, Hans; Engbert, Ralf; Wichmann, Felix
2013-10-01
Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.
Analytical model for macromolecular partitioning during yeast cell division
Kinkhabwala, Ali; Khmelinskii, Anton; Knop, Michael
2014-01-01
Asymmetric cell division, whereby a parent cell generates two sibling cells with unequal content and thereby distinct fates, is central to cell differentiation, organism development and ageing. Unequal partitioning of the macromolecular content of the parent cell — which includes proteins, DNA, RNA, large proteinaceous assemblies and organelles — can be achieved by both passive (e.g. diffusion, localized retention sites) and active (e.g. motor-driven transport) processes operating in the presence of external polarity cues, internal asymmetries, spontaneous symmetry breaking, or stochastic effects. However, the quantitative contribution of different processes to the partitioning of macromolecular content is difficult to evaluate. Here we developed an analytical model that allows rapid quantitative assessment of partitioning as a function of various parameters in the budding yeast Saccharomyces cerevisiae. This model exposes quantitative degeneracies among the physical parameters that govern macromolecular partitioning, and reveals regions of the solution space where diffusion is sufficient to drive asymmetric partitioning and regions where asymmetric partitioning can only be achieved through additional processes such as motor-driven transport. Application of the model to different macromolecular assemblies suggests that partitioning of protein aggregates and episomes, but not prions, is diffusion-limited in yeast, consistent with previous reports. In contrast to computationally intensive stochastic simulations of particular scenarios, our analytical model provides an efficient and comprehensive overview of partitioning as a function of global and macromolecule-specific parameters. Identification of quantitative degeneracies among these parameters highlights the importance of their careful measurement for a given macromolecular species in order to understand the dominant processes responsible for its observed partitioning
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
Cheung, Mike W.-L.; Cheung, Shu Fai
2016-01-01
Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…
Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu
2005-01-01
Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...
A theoretical study of CsI:Tl columnar scintillator image quality parameters by analytical modeling
Kalyvas, N., E-mail: nkalyvas@teiath.gr; Valais, I.; Michail, C.; Fountos, G.; Kandarakis, I.; Cavouras, D.
2015-04-11
Medical X-ray digital imaging systems such as mammography, radiography and computed tomography (CT), are composed from efficient radiation detectors, which can transform the X-rays to electron signal. Scintillators are materials that emit light when excited by X-rays and incorporated in X-ray medical imaging detectors. Columnar scintillator, like CsI:T1 is very often used for X-ray detection due to its higher performance. The columnar form limits the lateral spread of the optical photons to the scintillator output, thus it demonstrates superior spatial resolution compared to granular scintillators. The aim of this work is to provide an analytical model for calculating the MTF, the DQE and the emission efficiency of a columnar scintillator. The model parameters were validated against published Monte Carlo data. The model was able to predict the overall performance of CsI:Tl scintillators and suggested an optimum thickness of 300 μm for radiography applications. - Highlights: • An analytical model for calculating MTF, DQE and Detector Optical Gain (DOG) of columnar phosphors was developed. • The model was fitted to published efficiency and MTF Monte Carlo data. • A good fit was observed for 300 µm columnar CsI:Tl thickness. • The performance of the 300 µm column thickness CsI:Tl was better in terms of MTF and DOG for radiographic applications.
A hidden analytic structure of the Rabi model
Moroz, Alexander
2014-01-01
The Rabi model describes the simplest interaction between a cavity mode with a frequency ω c and a two-level system with a resonance frequency ω 0 . It is shown here that the spectrum of the Rabi model coincides with the support of the discrete Stieltjes integral measure in the orthogonality relations of recently introduced orthogonal polynomials. The exactly solvable limit of the Rabi model corresponding to Δ=ω 0 /(2ω c )=0, which describes a displaced harmonic oscillator, is characterized by the discrete Charlier polynomials in normalized energy ϵ, which are orthogonal on an equidistant lattice. A non-zero value of Δ leads to non-classical discrete orthogonal polynomials ϕ k (ϵ) and induces a deformation of the underlying equidistant lattice. The results provide a basis for a novel analytic method of solving the Rabi model. The number of ca. 1350 calculable energy levels per parity subspace obtained in double precision (cca 16 digits) by an elementary stepping algorithm is up to two orders of magnitude higher than is possible to obtain by Braak’s solution. Any first n eigenvalues of the Rabi model arranged in increasing order can be determined as zeros of ϕ N (ϵ) of at least the degree N=n+n t . The value of n t >0, which is slowly increasing with n, depends on the required precision. For instance, n t ≃26 for n=1000 and dimensionless interaction constant κ=0.2, if double precision is required. Given that the sequence of the lth zeros x nl ’s of ϕ n (ϵ)’s defines a monotonically decreasing discrete flow with increasing n, the Rabi model is indistinguishable from an algebraically solvable model in any finite precision. Although we can rigorously prove our results only for dimensionless interaction constant κ<1, numerics and exactly solvable example suggest that the main conclusions remain to be valid also for κ≥1. -- Highlights: •A significantly simplified analytic solution of the Rabi model. •The spectrum is the lattice of discrete
Analytical model of diffuse reflectance spectrum of skin tissue
Lisenko, S A; Kugeiko, M M; Firago, V A [Belarusian State University, Minsk (Belarus); Sobchuk, A N [B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk (Belarus)
2014-01-31
We have derived simple analytical expressions that enable highly accurate calculation of diffusely reflected light signals of skin in the spectral range from 450 to 800 nm at a distance from the region of delivery of exciting radiation. The expressions, taking into account the dependence of the detected signals on the refractive index, transport scattering coefficient, absorption coefficient and anisotropy factor of the medium, have been obtained in the approximation of a two-layer medium model (epidermis and dermis) for the same parameters of light scattering but different absorption coefficients of layers. Numerical experiments on the retrieval of the skin biophysical parameters from the diffuse reflectance spectra simulated by the Monte Carlo method show that commercially available fibre-optic spectrophotometers with a fixed distance between the radiation source and detector can reliably determine the concentration of bilirubin, oxy- and deoxyhaemoglobin in the dermis tissues and the tissue structure parameter characterising the size of its effective scatterers. We present the examples of quantitative analysis of the experimental data, confirming the correctness of estimates of biophysical parameters of skin using the obtained analytical expressions. (biophotonics)
Exploring Higher Education Governance: Analytical Models and Heuristic Frameworks
Burhan FINDIKLI
2017-08-01
Full Text Available Governance in higher education, both at institutional and systemic levels, has experienced substantial changes within recent decades because of a range of world-historical processes such as massification, growth, globalization, marketization, public sector reforms, and the emergence of knowledge economy and society. These developments have made governance arrangements and decision-making processes in higher education more complex and multidimensional more than ever and forced scholars to build new analytical and heuristic tools and strategies to grasp the intricacy and diversity of higher education governance dynamics. This article provides a systematic discussion of how and through which tools prominent scholars of higher education have analyzed governance in this sector by examining certain heuristic frameworks and analytical models. Additionally, the article shows how social scientific analysis of governance in higher education has proceeded in a cumulative way with certain revisions and syntheses rather than radical conceptual and theoretical ruptures from Burton R. Clark’s seminal work to the present, revealing conceptual and empirical junctures between them.
. Redundancy and blocking in the spatial domain: A connectionist model
I. P. L. Mc Laren
2002-01-01
Full Text Available How can the observations of spatial blocking (Rodrigo, Chamizo, McLaren & Mackintosh, 1997 and cue redundancy (OKeefe and Conway, 1978 be reconciled within the framework provided by an error-correcting, connectionist account of spatial navigation? I show that an implementation of McLarens (1995 better beta model can serve this purpose, and examine some of the implications for spatial learning and memory.
Finite element and analytical models for twisted and coiled actuator
Tang, Xintian; Liu, Yingxiang; Li, Kai; Chen, Weishan; Zhao, Jianguo
2018-01-01
Twisted and coiled actuator (TCA) is a class of recently discovered artificial muscle, which is usually made by twisting and coiling polymer fibers into spring-like structures. It has been widely studied since discovery due to its impressive output characteristics and bright prospects. However, its mathematical models describing the actuation in response to the temperature are still not fully developed. It is known that the large tensile stroke is resulted from the untwisting of the twisted fiber when heated. Thus, the recovered torque during untwisting is a key parameter in the mathematical model. This paper presents a simplified model for the recovered torque of TCA. Finite element method is used for evaluating the thermal stress of the twisted fiber. Based on the results of the finite element analyses, the constitutive equations of twisted fibers are simplified to develop an analytic model of the recovered torque. Finally, the model of the recovered torque is used to predict the deformation of TCA under varying temperatures and validated against experimental results. This work will enhance our understanding of the deformation mechanism of TCAs, which will pave the way for the closed-loop position control.
Fuzzy modeling of analytical redundancy for sensor failure detection
Tsai, T.M.; Chou, H.P.
1991-01-01
Failure detection and isolation (FDI) in dynamic systems may be accomplished by testing the consistency of the system via analytically redundant relations. The redundant relation is basically a mathematical model relating system inputs and dissimilar sensor outputs from which information is extracted and subsequently examined for the presence of failure signatures. Performance of the approach is often jeopardized by inherent modeling error and noise interference. To mitigate such effects, techniques such as Kalman filtering, auto-regression-moving-average (ARMA) modeling in conjunction with probability tests are often employed. These conventional techniques treat the stochastic nature of uncertainties in a deterministic manner to generate best-estimated model and sensor outputs by minimizing uncertainties. In this paper, the authors present a different approach by treating the effect of uncertainties with fuzzy numbers. Coefficients in redundant relations derived from first-principle physical models are considered as fuzzy parameters and on-line updated according to system behaviors. Failure detection is accomplished by examining the possibility that a sensor signal occurred in an estimated fuzzy domain. To facilitate failure isolation, individual FDI monitors are designed for each interested sensor
Guo, Y.; Keppens, R. [School of Astronomy and Space Science, Nanjing University, Nanjing 210023 (China); Xia, C. [Centre for mathematical Plasma-Astrophysics, Department of Mathematics, KU Leuven, B-3001 Leuven (Belgium); Valori, G., E-mail: guoyang@nju.edu.cn [University College London, Mullard Space Science Laboratory, Holmbury St. Mary, Dorking, Surrey RH5 6NT (United Kingdom)
2016-09-10
We report our implementation of the magneto-frictional method in the Message Passing Interface Adaptive Mesh Refinement Versatile Advection Code (MPI-AMRVAC). The method aims at applications where local adaptive mesh refinement (AMR) is essential to make follow-up dynamical modeling affordable. We quantify its performance in both domain-decomposed uniform grids and block-adaptive AMR computations, using all frequently employed force-free, divergence-free, and other vector comparison metrics. As test cases, we revisit the semi-analytic solution of Low and Lou in both Cartesian and spherical geometries, along with the topologically challenging Titov–Démoulin model. We compare different combinations of spatial and temporal discretizations, and find that the fourth-order central difference with a local Lax–Friedrichs dissipation term in a single-step marching scheme is an optimal combination. The initial condition is provided by the potential field, which is the potential field source surface model in spherical geometry. Various boundary conditions are adopted, ranging from fully prescribed cases where all boundaries are assigned with the semi-analytic models, to solar-like cases where only the magnetic field at the bottom is known. Our results demonstrate that all the metrics compare favorably to previous works in both Cartesian and spherical coordinates. Cases with several AMR levels perform in accordance with their effective resolutions. The magneto-frictional method in MPI-AMRVAC allows us to model a region of interest with high spatial resolution and large field of view simultaneously, as required by observation-constrained extrapolations using vector data provided with modern instruments. The applications of the magneto-frictional method to observations are shown in an accompanying paper.
Spatial Uncertainty Model for Visual Features Using a Kinect™ Sensor
Jae-Han Park
2012-06-01
Full Text Available This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.
Spatial uncertainty model for visual features using a Kinect™ sensor.
Park, Jae-Han; Shin, Yong-Deuk; Bae, Ji-Hun; Baeg, Moon-Hong
2012-01-01
This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.
Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model
Chengcheng Xu
2017-08-01
Full Text Available Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.
A spatial Mankiw-Romer-Weil model: Theory and evidence
Fischer, Manfred M.
2009-01-01
This paper presents a theoretical growth model that extends the Mankiw-Romer-Weil [MRW] model by accounting for technological interdependence among regional economies. Interdependence is assumed to work through spatial externalities caused by disembodied knowledge diffusion. The transition from theory to econometrics leads to a reduced-form empirical spatial Durbin model specification that explains the variation in regional levels of per worker output at steady state. A system ...
Spatial Modeling of Deforestation in FMU of Poigar, North Sulawesi
Ahmad, Afandi; Saleh, Muhammad Buce; Rusolono, Teddy
2016-01-01
Forest is a part of the ecosystem that provides environmental services. Deforestation may decrease forest function in an ecosystem. This study aims to build a spatial model of deforestation in a forest management unit (FMU) of Poigar. Deforestation analysis carried out by analyze the change of forest cover into non-forest cover with post classification comparison technique. Driving forces of deforestation carried out by spatial modeling using binary logistic regression models (LRM). Result of...
A model relating Eulerian spatial and temporal velocity correlations
Cholemari, Murali R.; Arakeri, Jaywant H.
2006-03-01
In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.
An Analytical Model of Joule Heating in Piezoresistive Microcantilevers
Chongdu Cho
2010-11-01
Full Text Available The present study investigates Joule heating in piezoresistive microcantilever sensors. Joule heating and thermal deflections are a major source of noise in such sensors. This work uses analytical and numerical techniques to characterise the Joule heating in 4-layer piezoresistive microcantilevers made of silicon and silicon dioxide substrates but with the same U-shaped silicon piezoresistor. A theoretical model for predicting the temperature generated due to Joule heating is developed. The commercial finite element software ANSYS Multiphysics was used to study the effect of electrical potential on temperature and deflection produced in the cantilevers. The effect of piezoresistor width on Joule heating is also studied. Results show that Joule heating strongly depends on the applied potential and width of piezoresistor and that a silicon substrate cantilever has better thermal characteristics than a silicon dioxide cantilever.
An analytical model of joule heating in piezoresistive microcantilevers.
Ansari, Mohd Zahid; Cho, Chongdu
2010-01-01
The present study investigates Joule heating in piezoresistive microcantilever sensors. Joule heating and thermal deflections are a major source of noise in such sensors. This work uses analytical and numerical techniques to characterise the Joule heating in 4-layer piezoresistive microcantilevers made of silicon and silicon dioxide substrates but with the same U-shaped silicon piezoresistor. A theoretical model for predicting the temperature generated due to Joule heating is developed. The commercial finite element software ANSYS Multiphysics was used to study the effect of electrical potential on temperature and deflection produced in the cantilevers. The effect of piezoresistor width on Joule heating is also studied. Results show that Joule heating strongly depends on the applied potential and width of piezoresistor and that a silicon substrate cantilever has better thermal characteristics than a silicon dioxide cantilever.
Analytical modeling of wet compression of gas turbine systems
Kim, Kyoung Hoon; Ko, Hyung-Jong; Perez-Blanco, Horacio
2011-01-01
Evaporative gas turbine cycles (EvGT) are of importance to the power generation industry because of the potential of enhanced cycle efficiencies with moderate incremental cost. Humidification of the working fluid to result in evaporative cooling during compression is a key operation in these cycles. Previous simulations of this operation were carried out via numerical integration. The present work is aimed at modeling the wet-compression process with approximate analytical solutions instead. A thermodynamic analysis of the simultaneous heat and mass transfer processes that occur during evaporation is presented. The transient behavior of important variables in wet compression such as droplet diameter, droplet mass, gas and droplet temperature, and evaporation rate is investigated. The effects of system parameters on variables such as droplet evaporation time, compressor outlet temperature and input work are also considered. Results from this work exhibit good agreement with those of previous numerical work.
Analytical Modelling Of Milling For Tool Design And Selection
Fontaine, M.; Devillez, A.; Dudzinski, D.
2007-01-01
This paper presents an efficient analytical model which allows to simulate a large panel of milling operations. A geometrical description of common end mills and of their engagement in the workpiece material is proposed. The internal radius of the rounded part of the tool envelope is used to define the considered type of mill. The cutting edge position is described for a constant lead helix and for a constant local helix angle. A thermomechanical approach of oblique cutting is applied to predict forces acting on the tool and these results are compared with experimental data obtained from milling tests on a 42CrMo4 steel for three classical types of mills. The influence of some tool's geometrical parameters on predicted cutting forces is presented in order to propose optimisation criteria for design and selection of cutting tools
Kaminskyj, S.; Konstantin, J.; Szeghalmi, A.; Gough, K.
2008-01-01
Fungi impact humans and the environment in many ways, for good and ill. Some fungi support the growth of terrestrial plants or are used in biotechnology, and yet others are established or emerging pathogens. In some cases, the same organism may play different roles depending on the context or the circumstance. A better understanding of the relationship between fungal biochemical composition as related to the fungal growth environment is essential if we are to support or control their activities. Synchrotron FTIR (sFTIR) spectromicroscopy of fungal hyphae is a major new tool for exploring cell composition at a high spatial resolution. Brilliant synchrotron light is essential for this analysis due to the small size of fungal hyphae. sFTIR biochemical characterization of subcellular variation in hyphal composition will allow detailed exploration of fungal responses to experimental treatments and to environmental factors.
Fractal analytical approach of urban form based on spatial correlation function
Chen, Yanguang
2013-01-01
Highlights: ► Many fractal parameter relations of cities can be derived by scaling analysis. ► The area-radius scaling of cities suggests a spatial correlation function. ► Spectral analysis can be used to estimate fractal dimension values of urban form. ► The valid range of fractal dimension of urban form comes between 1.5 and 2. ► The traditional scale concept will be replaced by scaling concept in geography. -- Abstract: Urban form has been empirically demonstrated to be of scaling invariance and can be described with fractal geometry. However, the rational range of fractal dimension value and the relationships between various fractal indicators of cities are not yet revealed in theory. By mathematical deduction and transform (e.g., Fourier transform), I find that scaling analysis, spectral analysis, and spatial correlation analysis are all associated with fractal concepts and can be integrated into a new approach to fractal analysis of cities. This method can be termed ‘3S analyses’ of urban form. Using the 3S analysis, I derived a set of fractal parameter equations, by which different fractal parameters of cities can be linked up with one another. Each fractal parameter has its own reasonable extent of values. According to the fractal parameter equations, the intersection of the rational ranges of different fractal parameters suggests the proper scale of the fractal dimension of urban patterns, which varies from 1.5 to 2. The fractal dimension equations based on the 3S analysis and the numerical relationships between different fractal parameters are useful for geographers to understand urban evolution and potentially helpful for future city planning
Tercariol, Cesar Augusto Sangaletti; Kiipper, Felipe de Moura; Martinez, Alexandre Souto
2007-01-01
Consider that the coordinates of N points are randomly generated along the edges of a d-dimensional hypercube (random point problem). The probability P (d,N) m,n that an arbitrary point is the mth nearest neighbour to its own nth nearest neighbour (Cox probabilities) plays an important role in spatial statistics. Also, it has been useful in the description of physical processes in disordered media. Here we propose a simpler derivation of Cox probabilities, where we stress the role played by the system dimensionality d. In the limit d → ∞, the distances between pair of points become independent (random link model) and closed analytical forms for the neighbourhood probabilities are obtained both for the thermodynamic limit and finite-size system. Breaking the distance symmetry constraint drives us to the random map model, for which the Cox probabilities are obtained for two cases: whether a point is its own nearest neighbour or not
Stochastic Spatial Models in Ecology: A Statistical Physics Approach
Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.
2017-11-01
Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.
Design of homogeneous trench-assisted multi-core fibers based on analytical model
Ye, Feihong; Tu, Jiajing; Saitoh, Kunimasa
2016-01-01
We present a design method of homogeneous trench-assisted multicore fibers (TA-MCFs) based on an analytical model utilizing an analytical expression for the mode coupling coefficient between two adjacent cores. The analytical model can also be used for crosstalk (XT) properties analysis, such as ...
33 CFR 385.33 - Revisions to models and analytical tools.
2010-07-01
... on a case-by-case basis what documentation is appropriate for revisions to models and analytic tools... analytical tools. 385.33 Section 385.33 Navigation and Navigable Waters CORPS OF ENGINEERS, DEPARTMENT OF THE... Incorporating New Information Into the Plan § 385.33 Revisions to models and analytical tools. (a) In carrying...
Updates to the Demographic and Spatial Allocation Models to ...
EPA announced the availability of the draft report, Updates to the Demographic and Spatial Allocation Models to Produce Integrated Climate and Land Use Scenarios (ICLUS) for a 30-day public comment period. The ICLUS version 2 (v2) modeling tool furthered land change modeling by providing nationwide housing development scenarios up to 2100. ICLUS V2 includes updated population and land use data sets and addressing limitations identified in ICLUS v1 in both the migration and spatial allocation models. The companion user guide describes the development of ICLUS v2 and the updates that were made to the original data sets and the demographic and spatial allocation models. [2017 UPDATE] Get the latest version of ICLUS and stay up-to-date by signing up to the ICLUS mailing list. The GIS tool enables users to run SERGoM with the population projections developed for the ICLUS project and allows users to modify the spatial allocation housing density across the landscape.
An API for Integrating Spatial Context Models with Spatial Reasoning Algorithms
Kjærgaard, Mikkel Baun
2006-01-01
The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible...... and can help reduce the complexity of algorithms making them easier to maintain and develop. This paper propose an object-oriented API for context models of the physical environment and extensions to a location modeling approach called geometric space trees for it to provide adequate support for location...... modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms....
Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.
Sarker, M Mizanur Rahman
2012-04-01
Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.
Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel
2017-03-01
Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.
TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction
Li, G; Yuan, A; Wei, J
2014-01-01
Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation. The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no
A simulation-based analytic model of radio galaxies
Hardcastle, M. J.
2018-04-01
I derive and discuss a simple semi-analytical model of the evolution of powerful radio galaxies which is not based on assumptions of self-similar growth, but rather implements some insights about the dynamics and energetics of these systems derived from numerical simulations, and can be applied to arbitrary pressure/density profiles of the host environment. The model can qualitatively and quantitatively reproduce the source dynamics and synchrotron light curves derived from numerical modelling. Approximate corrections for radiative and adiabatic losses allow it to predict the evolution of radio spectral index and of inverse-Compton emission both for active and `remnant' sources after the jet has turned off. Code to implement the model is publicly available. Using a standard model with a light relativistic (electron-positron) jet, subequipartition magnetic fields, and a range of realistic group/cluster environments, I simulate populations of sources and show that the model can reproduce the range of properties of powerful radio sources as well as observed trends in the relationship between jet power and radio luminosity, and predicts their dependence on redshift and environment. I show that the distribution of source lifetimes has a significant effect on both the source length distribution and the fraction of remnant sources expected in observations, and so can in principle be constrained by observations. The remnant fraction is expected to be low even at low redshift and low observing frequency due to the rapid luminosity evolution of remnants, and to tend rapidly to zero at high redshift due to inverse-Compton losses.
Analytical thermal model validation for Cassini radioisotope thermoelectric generator
Lin, E.I.
1997-01-01
The Saturn-bound Cassini spacecraft is designed to rely, without precedent, on the waste heat from its three radioisotope thermoelectric generators (RTGs) to warm the propulsion module subsystem, and the RTG end dome temperature is a key determining factor of the amount of waste heat delivered. A previously validated SINDA thermal model of the RTG was the sole guide to understanding its complex thermal behavior, but displayed large discrepancies against some initial thermal development test data. A careful revalidation effort led to significant modifications and adjustments of the model, which result in a doubling of the radiative heat transfer from the heat source support assemblies to the end domes and bring up the end dome and flange temperature predictions to within 2 C of the pertinent test data. The increased inboard end dome temperature has a considerable impact on thermal control of the spacecraft central body. The validation process offers an example of physically-driven analytical model calibration with test data from not only an electrical simulator but also a nuclear-fueled flight unit, and has established the end dome temperatures of a flight RTG where no in-flight or ground-test data existed before
Analytical modelling for ultrasonic surface mechanical attrition treatment
Guan-Rong Huang
2015-07-01
Full Text Available The grain refinement, gradient structure, fatigue limit, hardness, and tensile strength of metallic materials can be effectively enhanced by ultrasonic surface mechanical attrition treatment (SMAT, however, never before has SMAT been treated with rigorous analytical modelling such as the connection among the input energy and power and resultant temperature of metallic materials subjected to SMAT. Therefore, a systematic SMAT model is actually needed. In this article, we have calculated the averaged speed, duration time of a cycle, kinetic energy and kinetic energy loss of flying balls in SMAT for structural metallic materials. The connection among the quantities such as the frequency and amplitude of attrition ultrasonic vibration motor, the diameter, mass and density of balls, the sample mass, and the height of chamber have been considered and modelled in details. And we have introduced the one-dimensional heat equation with heat source within uniform-distributed depth in estimating the temperature distribution and heat energy of sample. In this approach, there exists a condition for the frequency of flying balls reaching a steady speed. With these known quantities, we can estimate the strain rate, hardness, and grain size of sample.
Analytic models of NH4+ uptake and regeneration experiments
Laws, E.A.
1985-01-01
Differential equations describing the uptake and regeneration of NH 4 + in both laboratory and field experiments are shown to have analytic solutions which can easily be inverted to determine the rate constants of interest. The solutions are used to study the descriptive ability of two fundamentally different models of NH 4 + cycling, one in which NH 4 + regeneration is regarded as a process that transfers N from participate N to NH 4 + , the other in which regeneration is regarded as a process that introduced NH 4 + to the dissolved phase without removing N from the particulate phase. The former model was found to give a good description of experimental field data and reasonable parameter values in all cases studied. The latter model was much less successful in describing the data and in producing reasonable parameter values. It is concluded that transfer of nitrogen from particulate N to NH 4 + is a process which must be taken into account in analyzing NH 4 + uptake and regeneration experiments
Analytical modeling of bwr safety relief valve blowdown phenomenon
Hwang, J.G.; Singh, A.
1984-01-01
An analytical, qualitative understanding of the pool pressures measured during safety relief valve discharge in boiling water reactors equipped with X-quenchers has been developed and compared to experimental data. A pressure trace typically consists of a brief 25-35 Hz. oscillation followed by longer 5-15 Hz. oscillation. In order to explain the pressure response, a discharge line vent clearing model has been coupled with a Rayleigh bubble dynamic model. The local conditions inside the safety relief valve discharge lines and inside of the X-quencher were simulated successfully with RELAP5. The simulation allows one to associate the peak pressure inside the quencher arm with the onset of air discharge into the suppression pool. Using the pressure and thermodynamic quality at quencher exit of RELAP5 calculation as input, a Rayleigh model of pool bubble dynamics has successfully explained both the higher and lower frequency pressure oscillations. The higher frequency oscillations are characteristic of an air bubble emanating from a single row of quencher holes. The lower frequency pressure oscillations are characteristic of a larger air bubble containing all the air expelled from one side of an X-quencher arm
Applying fuzzy analytic network process in quality function deployment model
Mohammad Ali Afsharkazemi
2012-08-01
Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.
More on analytic bootstrap for O(N) models
Dey, Parijat; Kaviraj, Apratim; Sen, Kallol [Centre for High Energy Physics, Indian Institute of Science,C.V. Raman Avenue, Bangalore 560012 (India)
2016-06-22
This note is an extension of a recent work on the analytical bootstrapping of O(N) models. An additonal feature of the O(N) model is that the OPE contains trace and antisymmetric operators apart from the symmetric-traceless objects appearing in the OPE of the singlet sector. This in addition to the stress tensor (T{sub μν}) and the ϕ{sub i}ϕ{sup i} scalar, we also have other minimal twist operators as the spin-1 current J{sub μ} and the symmetric-traceless scalar in the case of O(N). We determine the effect of these additional objects on the anomalous dimensions of the corresponding trace, symmetric-traceless and antisymmetric operators in the large spin sector of the O(N) model, in the limit when the spin is much larger than the twist. As an observation, we also verified that the leading order results for the large spin sector from the ϵ−expansion are an exact match with our n=0 case. A plausible holographic setup for the special case when N=2 is also mentioned which mimics the calculation in the CFT.
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
Lawson, Andrew
2013-01-01
Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
Lawson, Andrew
2013-01-01
.... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...
Testing spatial heterogeneity with stock assessment models
Jardim, Ernesto; Eero, Margit; Silva, Alexandra
2018-01-01
sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub......, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine...... exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis....
Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy
2014-10-01
The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.
On Angular Sampling Methods for 3-D Spatial Channel Models
Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum
2015-01-01
This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....
INCAS: an analytical model to describe displacement cascades
Jumel, Stephanie E-mail: stephanie.jumel@edf.fr; Claude Van-Duysen, Jean E-mail: jean-claude.van-duysen@edf.fr
2004-07-01
REVE (REactor for Virtual Experiments) is an international project aimed at developing tools to simulate neutron irradiation effects in Light Water Reactor materials (Fe, Ni or Zr-based alloys). One of the important steps of the project is to characterise the displacement cascades induced by neutrons. Accordingly, the Department of Material Studies of Electricite de France developed an analytical model based on the binary collision approximation. This model, called INCAS (INtegration of CAScades), was devised to be applied on pure elements; however, it can also be used on diluted alloys (reactor pressure vessel steels, etc.) or alloys composed of atoms with close atomic numbers (stainless steels, etc.). INCAS describes displacement cascades by taking into account the nuclear collisions and electronic interactions undergone by the moving atoms. In particular, it enables to determine the mean number of sub-cascades induced by a PKA (depending on its energy) as well as the mean energy dissipated in each of them. The experimental validation of INCAS requires a large effort and could not be carried out in the framework of the study. However, it was verified that INCAS results are in conformity with those obtained from other approaches. As a first application, INCAS was applied to determine the sub-cascade spectrum induced in iron by the neutron spectrum corresponding to the central channel of the High Flux Irradiation Reactor of Oak Ridge National Laboratory.
INCAS: an analytical model to describe displacement cascades
Jumel, Stéphanie; Claude Van-Duysen, Jean
2004-07-01
REVE (REactor for Virtual Experiments) is an international project aimed at developing tools to simulate neutron irradiation effects in Light Water Reactor materials (Fe, Ni or Zr-based alloys). One of the important steps of the project is to characterise the displacement cascades induced by neutrons. Accordingly, the Department of Material Studies of Electricité de France developed an analytical model based on the binary collision approximation. This model, called INCAS (INtegration of CAScades), was devised to be applied on pure elements; however, it can also be used on diluted alloys (reactor pressure vessel steels, etc.) or alloys composed of atoms with close atomic numbers (stainless steels, etc.). INCAS describes displacement cascades by taking into account the nuclear collisions and electronic interactions undergone by the moving atoms. In particular, it enables to determine the mean number of sub-cascades induced by a PKA (depending on its energy) as well as the mean energy dissipated in each of them. The experimental validation of INCAS requires a large effort and could not be carried out in the framework of the study. However, it was verified that INCAS results are in conformity with those obtained from other approaches. As a first application, INCAS was applied to determine the sub-cascade spectrum induced in iron by the neutron spectrum corresponding to the central channel of the High Flux Irradiation Reactor of Oak Ridge National Laboratory.
INCAS: an analytical model to describe displacement cascades
Jumel, Stephanie; Claude Van-Duysen, Jean
2004-01-01
REVE (REactor for Virtual Experiments) is an international project aimed at developing tools to simulate neutron irradiation effects in Light Water Reactor materials (Fe, Ni or Zr-based alloys). One of the important steps of the project is to characterise the displacement cascades induced by neutrons. Accordingly, the Department of Material Studies of Electricite de France developed an analytical model based on the binary collision approximation. This model, called INCAS (INtegration of CAScades), was devised to be applied on pure elements; however, it can also be used on diluted alloys (reactor pressure vessel steels, etc.) or alloys composed of atoms with close atomic numbers (stainless steels, etc.). INCAS describes displacement cascades by taking into account the nuclear collisions and electronic interactions undergone by the moving atoms. In particular, it enables to determine the mean number of sub-cascades induced by a PKA (depending on its energy) as well as the mean energy dissipated in each of them. The experimental validation of INCAS requires a large effort and could not be carried out in the framework of the study. However, it was verified that INCAS results are in conformity with those obtained from other approaches. As a first application, INCAS was applied to determine the sub-cascade spectrum induced in iron by the neutron spectrum corresponding to the central channel of the High Flux Irradiation Reactor of Oak Ridge National Laboratory
Simplified analytical model for thermal transfer in vertical hollow brick
Lorente, S [Lab. d` Etudes Thermiques et Mecaniques, INSA, UPS, Toulouse (France); Petit, M [Lab. d` Etudes Thermiques et Mecaniques, INSA, UPS, Toulouse (France); Javelas, R [Lab. d` Etudes Thermiques et Mecaniques, INSA, UPS, Toulouse (France)
1996-12-01
A modern building envelope has a lot of little cavities. Most of them are vertical with a high height to thickness ratio. We present here the conception of a software to determine heat transfer through terra-cotta bricks full of large vertical cavities. After a bibliographic study on convective heat transfer in such cavities, we made an analytical model based on Karman-Polhausen`s method for convection and on the radiosity method for radiative heat transfer. We used a test apparatus of a single cavity to determine the temperature field inside the cavity. Using these experimental results, we showed that the exchange was two-dimensional. We also realised heat flux measurements. Then we expose our theoretical study: We propose relations between central core temperatures and active face temperatures, then between outside and inside active face temperatures. We calculate convective superficial heat transfer because we noticed we have boundary layers along the active faces. We realise a heat flux balance between convective plus radiative heat transfer and conductive heat transfer, so we propose an algorithm to calculate global heat transfer through a single cavity. Finally, we extend our model to a whole hollow brick with lined-up cavities and propose an algorithm to calculate heat flux and thermal resistance with a good accuracy ({approx}7.5%) compared to previous experimental results. (orig.)
Analytical model for an electrostatically actuated miniature diaphragm compressor
Sathe, Abhijit A; Groll, Eckhard A; Garimella, Suresh V
2008-01-01
This paper presents a new analytical approach for quasi-static modeling of an electrostatically actuated diaphragm compressor that could be employed in a miniature scale refrigeration system. The compressor consists of a flexible circular diaphragm clamped at its circumference. A conformal chamber encloses the diaphragm completely. The membrane and the chamber surfaces are coated with metallic electrodes. A potential difference applied between the diaphragm and the chamber pulls the diaphragm toward the chamber surface progressively from the outer circumference toward the center. This zipping actuation reduces the volume available to the refrigerant gas, thereby increasing its pressure. A segmentation technique is proposed for analysis of the compressor by which the domain is divided into multiple segments for each of which the forces acting on the diaphragm are estimated. The pull-down voltage to completely zip each individual segment is thus obtained. The required voltage for obtaining a specific pressure rise in the chamber can thus be determined. Predictions from the model compare well with other simulation results from the literature, as well as to experimental measurements of the diaphragm displacement and chamber pressure rise in a custom-built setup
How does spatial study design influence density estimates from spatial capture-recapture models?
Rahel Sollmann
Full Text Available When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.
Spatial Epidemic Modelling in Social Networks
Simoes, Joana Margarida
2005-06-01
The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.
Analytic Intermodel Consistent Modeling of Volumetric Human Lung Dynamics.
Ilegbusi, Olusegun; Seyfi, Behnaz; Neylon, John; Santhanam, Anand P
2015-10-01
Human lung undergoes breathing-induced deformation in the form of inhalation and exhalation. Modeling the dynamics is numerically complicated by the lack of information on lung elastic behavior and fluid-structure interactions between air and the tissue. A mathematical method is developed to integrate deformation results from a deformable image registration (DIR) and physics-based modeling approaches in order to represent consistent volumetric lung dynamics. The computational fluid dynamics (CFD) simulation assumes the lung is a poro-elastic medium with spatially distributed elastic property. Simulation is performed on a 3D lung geometry reconstructed from four-dimensional computed tomography (4DCT) dataset of a human subject. The heterogeneous Young's modulus (YM) is estimated from a linear elastic deformation model with the same lung geometry and 4D lung DIR. The deformation obtained from the CFD is then coupled with the displacement obtained from the 4D lung DIR by means of the Tikhonov regularization (TR) algorithm. The numerical results include 4DCT registration, CFD, and optimal displacement data which collectively provide consistent estimate of the volumetric lung dynamics. The fusion method is validated by comparing the optimal displacement with the results obtained from the 4DCT registration.
Spatial modelling with R-INLA: A review
Bakka, Haakon; Rue, Haavard; Fuglstad, Geir-Arne; Riebler, Andrea; Bolin, David; Krainski, Elias; Simpson, Daniel; Lindgren, Finn
2018-01-01
Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are made to the model, there is little guarantee that the code performs well. The key advantages of R-INLA are the ease with which complex models can be created and modified, without the need to write complex code, and the speed at which inference can be done even for spatial problems with hundreds of thousands of observations. R-INLA handles latent Gaussian models, where fixed effects, structured and unstructured Gaussian random effects are combined linearly in a linear predictor, and the elements of the linear predictor are observed through one or more likelihoods. The structured random effects can be both standard areal model such as the Besag and the BYM models, and geostatistical models from a subset of the Mat\\'ern Gaussian random fields. In this review, we discuss the large success of spatial modelling with R-INLA and the types of spatial models that can be fitted, we give an overview of recent developments for areal models, and we give an overview of the stochastic partial differential equation (SPDE) approach and some of the ways it can be extended beyond the assumptions of isotropy and separability. In particular, we describe how slight changes to the SPDE approach leads to straight-forward approaches for non-stationary spatial models and non-separable space-time models.
Spatial modelling with R-INLA: A review
Bakka, Haakon
2018-02-18
Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are made to the model, there is little guarantee that the code performs well. The key advantages of R-INLA are the ease with which complex models can be created and modified, without the need to write complex code, and the speed at which inference can be done even for spatial problems with hundreds of thousands of observations. R-INLA handles latent Gaussian models, where fixed effects, structured and unstructured Gaussian random effects are combined linearly in a linear predictor, and the elements of the linear predictor are observed through one or more likelihoods. The structured random effects can be both standard areal model such as the Besag and the BYM models, and geostatistical models from a subset of the Mat\\\\\\'ern Gaussian random fields. In this review, we discuss the large success of spatial modelling with R-INLA and the types of spatial models that can be fitted, we give an overview of recent developments for areal models, and we give an overview of the stochastic partial differential equation (SPDE) approach and some of the ways it can be extended beyond the assumptions of isotropy and separability. In particular, we describe how slight changes to the SPDE approach leads to straight-forward approaches for non-stationary spatial models and non-separable space-time models.
Modeling structural change in spatial system dynamics: A Daisyworld example.
Neuwirth, C; Peck, A; Simonović, S P
2015-03-01
System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed.
A Structural Equation Approach to Models with Spatial Dependence
Oud, Johan H. L.; Folmer, Henk
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
A structural equation approach to models with spatial dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
A Structural Equation Approach to Models with Spatial Dependence
Oud, J.H.L.; Folmer, H.
2008-01-01
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it
A fast semi-analytical model for the slotted structure of induction motors
Sprangers, R.L.J.; Paulides, J.J.H.; Gysen, B.L.J.; Lomonova, E.A.
A fast, semi-analytical model for induction motors (IMs) is presented. In comparison to traditional analytical models for IMs, such as lumped parameter, magnetic equivalent circuit and anisotropic layer models, the presented model calculates a continuous distribution of the magnetic flux density in
Can spatial statistical river temperature models be transferred between catchments?
Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.
2017-09-01
There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across
Spatial Modeling Tools for Cell Biology
Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick
2006-01-01
.... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...
Semi-analytical modelling of positive corona discharge in air
Pontiga, Francisco; Yanallah, Khelifa; Chen, Junhong
2013-09-01
Semianalytical approximate solutions of the spatial distribution of electric field and electron and ion densities have been obtained by solving Poisson's equations and the continuity equations for the charged species along the Laplacian field lines. The need to iterate for the correct value of space charge on the corona electrode has been eliminated by using the corona current distribution over the grounded plane derived by Deutsch, which predicts a cos m θ law similar to Warburg's law. Based on the results of the approximated model, a parametric study of the influence of gas pressure, the corona wire radius, and the inter-electrode wire-plate separation has been carried out. Also, the approximate solutions of the electron number density has been combined with a simplified plasma chemistry model in order to compute the ozone density generated by the corona discharge in the presence of a gas flow. This work was supported by the Consejeria de Innovacion, Ciencia y Empresa (Junta de Andalucia) and by the Ministerio de Ciencia e Innovacion, Spain, within the European Regional Development Fund contracts FQM-4983 and FIS2011-25161.
Analytical models for total dose ionization effects in MOS devices.
Campbell, Phillip Montgomery; Bogdan, Carolyn W.
2008-08-01
MOS devices are susceptible to damage by ionizing radiation due to charge buildup in gate, field and SOI buried oxides. Under positive bias holes created in the gate oxide will transport to the Si / SiO{sub 2} interface creating oxide-trapped charge. As a result of hole transport and trapping, hydrogen is liberated in the oxide which can create interface-trapped charge. The trapped charge will affect the threshold voltage and degrade the channel mobility. Neutralization of oxidetrapped charge by electron tunneling from the silicon and by thermal emission can take place over long periods of time. Neutralization of interface-trapped charge is not observed at room temperature. Analytical models are developed that account for the principal effects of total dose in MOS devices under different gate bias. The intent is to obtain closed-form solutions that can be used in circuit simulation. Expressions are derived for the aging effects of very low dose rate radiation over long time periods.
Small-scale engagement model with arrivals: analytical solutions
Engi, D.
1977-04-01
This report presents an analytical model of small-scale battles. The specific impetus for this effort was provided by a need to characterize hypothetical battles between guards at a nuclear facility and their potential adversaries. The solution procedure can be used to find measures of a number of critical parameters; for example, the win probabilities and the expected duration of the battle. Numerical solutions are obtainable if the total number of individual combatants on the opposing sides is less than 10. For smaller force size battles, with one or two combatants on each side, symbolic solutions can be found. The symbolic solutions express the output parameters abstractly in terms of symbolic representations of the input parameters while the numerical solutions are expressed as numerical values. The input parameters are derived from the probability distributions of the attrition and arrival processes. The solution procedure reduces to solving sets of linear equations that have been constructed from the input parameters. The approach presented in this report does not address the problems associated with measuring the inputs. Rather, this report attempts to establish a relatively simple structure within which small-scale battles can be studied
An analytical study of various telecomminication networks using Markov models
Ramakrishnan, M; Jayamani, E; Ezhumalai, P
2015-01-01
The main aim of this paper is to examine issues relating to the performance of various Telecommunication networks, and applied queuing theory for better design and improved efficiency. Firstly, giving an analytical study of queues deals with quantifying the phenomenon of waiting lines using representative measures of performances, such as average queue length (on average number of customers in the queue), average waiting time in queue (on average time to wait) and average facility utilization (proportion of time the service facility is in use). In the second, using Matlab simulator, summarizes the finding of the investigations, from which and where we obtain results and describing methodology for a) compare the waiting time and average number of messages in the queue in M/M/1 and M/M/2 queues b) Compare the performance of M/M/1 and M/D/1 queues and study the effect of increasing the number of servers on the blocking probability M/M/k/k queue model. (paper)
Optimization of turning process through the analytic flank wear modelling
Del Prete, A.; Franchi, R.; De Lorenzis, D.
2018-05-01
In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.
Analytical and numerical models of transport in porous cementitious materials
Garboczi, E.J.; Bentz, D.P.
1990-01-01
Most chemical and physical processes that degrade cementitious materials are dependent on an external source of either water or ions or both. Understanding the rates of these processes at the microstructural level is necessary in order to develop a sound scientific basis for the prediction and control of the service life of cement-based materials, especially for radioactive-waste containment materials that are required to have service lives on the order of hundreds of years. An important step in developing this knowledge is to understand how transport coefficients, such as diffusivity and permeability, depend on the pore structure. Fluid flow under applied pressure gradients and ionic diffusion under applied concentration gradients are important transport mechanisms that take place in the pore space of cementitious materials. This paper describes: (1) a new analytical percolation-theory-based equation for calculating the permeability of porous materials, (2) new computational methods for computing effective diffusivities of microstructural models or digitized images of actual porous materials, and (3) a new digitized-image mercury intrusion simulation technique
Bayesian spatial transformation models with applications in neuroimaging data.
Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G
2013-12-01
The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.
Crash rates analysis in China using a spatial panel model
Wonmongo Lacina Soro
2017-10-01
Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.
Linear multivariate evaluation models for spatial perception of soundscape.
Deng, Zhiyong; Kang, Jian; Wang, Daiwei; Liu, Aili; Kang, Joe Zhengyu
2015-11-01
Soundscape is a sound environment that emphasizes the awareness of auditory perception and social or cultural understandings. The case of spatial perception is significant to soundscape. However, previous studies on the auditory spatial perception of the soundscape environment have been limited. Based on 21 native binaural-recorded soundscape samples and a set of auditory experiments for subjective spatial perception (SSP), a study of the analysis among semantic parameters, the inter-aural-cross-correlation coefficient (IACC), A-weighted-equal sound-pressure-level (L(eq)), dynamic (D), and SSP is introduced to verify the independent effect of each parameter and to re-determine some of their possible relationships. The results show that the more noisiness the audience perceived, the worse spatial awareness they received, while the closer and more directional the sound source image variations, dynamics, and numbers of sound sources in the soundscape are, the better the spatial awareness would be. Thus, the sensations of roughness, sound intensity, transient dynamic, and the values of Leq and IACC have a suitable range for better spatial perception. A better spatial awareness seems to promote the preference slightly for the audience. Finally, setting SSPs as functions of the semantic parameters and Leq-D-IACC, two linear multivariate evaluation models of subjective spatial perception are proposed.
SPATIAL MODELLING FOR DESCRIBING SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN EASTERN CROATIA
Igor Bogunović
2016-06-01
Full Text Available The objectives of this study were to characterize the field-scale spatial variability and test several interpolation methods to identify the best spatial predictor of penetration resistance (PR, bulk density (BD and gravimetric water content (GWC in the silty loam soil in Eastern Croatia. The measurements were made on a 25 x 25-m grid which created 40 individual grid cells. Soil properties were measured at the center of the grid cell deep 0-10 cm and 10-20 cm. Results demonstrated that PR and GWC displayed strong spatial dependence at 0-10 cm BD, while there was moderate and weak spatial dependence of PR, BD and GWC at depth of 10-20 cm. Semi-variogram analysis suggests that future sampling intervals for investigated parameters can be increased to 35 m in order to reduce research costs. Additionally, interpolation models recorded similar root mean square values with high predictive accuracy. Results suggest that investigated properties do not have uniform interpolation method implying the need for spatial modelling in the evaluation of these soil properties in Eastern Croatia.
Empirical spatial econometric modelling of small scale neighbourhood
Gerkman, Linda
2012-07-01
The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.
Spatial memory tasks in rodents: what do they model?
Morellini, Fabio
2013-10-01
The analysis of spatial learning and memory in rodents is commonly used to investigate the mechanisms underlying certain forms of human cognition and to model their dysfunction in neuropsychiatric and neurodegenerative diseases. Proper interpretation of rodent behavior in terms of spatial memory and as a model of human cognitive functions is only possible if various navigation strategies and factors controlling the performance of the animal in a spatial task are taken into consideration. The aim of this review is to describe the experimental approaches that are being used for the study of spatial memory in rats and mice and the way that they can be interpreted in terms of general memory functions. After an introduction to the classification of memory into various categories and respective underlying neuroanatomical substrates, I explain the concept of spatial memory and its measurement in rats and mice by analysis of their navigation strategies. Subsequently, I describe the most common paradigms for spatial memory assessment with specific focus on methodological issues relevant for the correct interpretation of the results in terms of cognitive function. Finally, I present recent advances in the use of spatial memory tasks to investigate episodic-like memory in mice.
Unleashing spatially distributed ecohydrology modeling using Big Data tools
Miles, B.; Idaszak, R.
2015-12-01
Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well
Modelling the effects of spatial variability on radionuclide migration
1998-01-01
The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)
Spatial distance in a technology gap model
Verspagen, B.; Caniëls, M.C.J.
1999-01-01
This paper analyses the effect of locally bounded knowledge spillovers on regional differences in growth. A model will be developed that allows spillovers to take place across regions. Certain conditions determine the amount of spillovers a region receives. By use of simulations (with randomised
Properties of spatial Cox process models
Møller, Jesper
Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties...... and point process operations such as thinning, displacements, and superpositioning. We also discuss how to simulate specific Cox processes....
Spatial-temporal modeling of malware propagation in networks.
Chen, Zesheng; Ji, Chuanyi
2005-09-01
Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.
An analytical model for annular flow boiling heat transfer in microchannel heat sinks
Megahed, A.; Hassan, I.
2009-01-01
An analytical model has been developed to predict flow boiling heat transfer coefficient in microchannel heat sinks. The new analytical model is proposed to predict the two-phase heat transfer coefficient during annular flow regime based on the separated model. Opposing to the majority of annular flow heat transfer models, the model is based on fundamental conservation principles. The model considers the characteristics of microchannel heat sink during annular flow and eliminates using any empirical closure relations. Comparison with limited experimental data was found to validate the usefulness of this analytical model. The model predicts the experimental data with a mean absolute error 8%. (author)
Spatial analysis and modelling based on activities
Conradie, Dirk CU
2010-01-01
Full Text Available (deliberative attitudes) (Pokahr, 2005). The BDI model does not cover emotional and other ‘higher’ human attitudes. KRONOS is a generic Computational Building Simulation (CBS) tool that was developed over the past three years to work on advanced... featured, stable, mature and platform independent with an easy to use C/C++ Application Program Interface (API). It has advanced joint types and integrated collision detection with friction. ODE is particularly useful for simulating vehicles, objects...
Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D
2017-09-11
Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.
Uncertainty in a spatial evacuation model
Mohd Ibrahim, Azhar; Venkat, Ibrahim; Wilde, Philippe De
2017-08-01
Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive with certainty the strategies of opponents (other agents) owing to the dynamic changes entailed by the neighborhood of opponents. In such uncertain scenarios, agents will try to update their strategy based on their own rules or their intrinsic behavior. We study risk seeking, risk averse and risk neutral behaviors of such agents via certain game theory notions. We found that risk averse agents tend to achieve faster evacuation time whenever the time delay in conflicts appears to be longer. The results of our simulations also comply with previous work and conform to the fact that evacuation time of agents becomes shorter once mutual cooperation among agents is achieved. Although the impatient strategy appears to be the rational strategy that might lead to faster evacuation times, our study scientifically shows that the more the agents are impatient, the slower is the egress time.
Stability of a spatial model of social interactions
Bragard, Jean; Mossay, Pascal
2016-01-01
We study a spatial model of social interactions. Though the properties of the spatial equilibrium have been largely discussed in the existing literature, the stability of equilibrium remains an unaddressed issue. Our aim is to fill up this gap by introducing dynamics in the model and by determining the stability of equilibrium. First we derive a variational equation useful for the stability analysis. This allows to study the corresponding eigenvalue problem. While odd modes are shown to be always stable, there is a single even mode of which stability depends on the model parameters. Finally various numerical simulations illustrate our theoretical results.
McCormick, Keith; Wei, Bowen
2017-01-01
IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used to build predictive models and conduct other analytic tasks using IBM SPSS Modeler. From ...
Determining passive cooling limits in CPV using an analytical thermal model
Gualdi, Federico; Arenas, Osvaldo; Vossier, Alexis; Dollet, Alain; Aimez, Vincent; Arès, Richard
2013-09-01
We propose an original thermal analytical model aiming to predict the practical limits of passive cooling systems for high concentration photovoltaic modules. The analytical model is described and validated by comparison with a commercial 3D finite element model. The limiting performances of flat plate cooling systems in natural convection are then derived and discussed.
Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers
Khalil Al Handawi
2017-09-01
Full Text Available Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber’s modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature.
Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers.
Al Handawi, Khalil; Vahdati, Nader; Shiryayev, Oleg; Lawand, Lydia
2017-09-28
Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber's modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature.
Li, Ping; Jiang, Li Jun; Bagci, Hakan
2018-01-01
It is well known that graphene demonstrates spatial dispersion properties, i.e., its conductivity is nonlocal and a function of spectral wave number (momentum operator) q. In this paper, to account for effects of spatial dispersion on transmission of high speed signals along graphene nano-ribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically-thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time domain SIBC model cannot be derived. To overcome this problem, the conductivity is approximated by its Taylor series in spectral domain under low-q assumption. This approach permits expressing the time domain SIBC in the form of a second-order partial differential equation (PDE) in current density and electric field intensity. To permit easy incorporation of this PDE with the DGTD algorithm, three auxiliary variables, which degenerate the second-order (temporal and spatial) differential operators to first-order ones, are introduced. Regarding to the temporal dispersion effects, the auxiliary differential equation (ADE) method is utilized to eliminates the expensive temporal convolutions. To demonstrate the applicability of the proposed scheme, numerical results, which involve characterization of spatial dispersion effects on the transfer impedance matrix of GNR interconnects, are presented.
Li, Ping
2018-04-13
It is well known that graphene demonstrates spatial dispersion properties, i.e., its conductivity is nonlocal and a function of spectral wave number (momentum operator) q. In this paper, to account for effects of spatial dispersion on transmission of high speed signals along graphene nano-ribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically-thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time domain SIBC model cannot be derived. To overcome this problem, the conductivity is approximated by its Taylor series in spectral domain under low-q assumption. This approach permits expressing the time domain SIBC in the form of a second-order partial differential equation (PDE) in current density and electric field intensity. To permit easy incorporation of this PDE with the DGTD algorithm, three auxiliary variables, which degenerate the second-order (temporal and spatial) differential operators to first-order ones, are introduced. Regarding to the temporal dispersion effects, the auxiliary differential equation (ADE) method is utilized to eliminates the expensive temporal convolutions. To demonstrate the applicability of the proposed scheme, numerical results, which involve characterization of spatial dispersion effects on the transfer impedance matrix of GNR interconnects, are presented.
Dim, J. R.; Sakura, Y.; Fukami, H.; Miyakoshi, A.
2002-03-01
In porous sediments of the Ishikari Lowland, there is a gradual increase in the background geothermal gradient from the Ishikari River (3-4 °C 100 m-1) to the southwest highland area (10 °C 100 m-1). However, the geothermal gradient at shallow depths differs in detail from the background distribution. In spite of convective heat-flow loss generally associated with groundwater flow, heat flow remains high (100 mW m-2) in the recharge area in the southwestern part of the Ishikari basin, which is part of an active geothermal field. In the northeastern part of the lowland, heat flow locally reaches 140 mW m-2, probably due to upward water flow from the deep geothermal field. Between the two areas the heat flow is much lower. To examine the role of hydraulic flow in the distortion of the isotherms in this area, thermal gradient vs. temperature analyses were made, and they helped to define the major components of the groundwater-flow system of the region. Two-dimensional simulation modeling aided in understanding not only the cause of horizontal heat-flow variations in this field but also the contrast between thermal properties of shallow and deep groundwater reservoirs. Résumé. Dans les sédiments poreux des basses terres d'Ishikari, on observe une augmentation graduelle du gradient géothermal général depuis la rivière Ishikari (3-4 °C 100 m-1) vers la zone élevée située au sud-ouest (10 °C 100 m-1). Toutefois, le gradient géothermal aux faibles profondeurs diffère dans le détail de la distribution générale. Malgré la perte de flux de chaleur par convection, généralement associée aux écoulements souterrains, le flux de chaleur reste élevé (100 mW m-2) dans la zone de recharge de la partie sud-ouest du bassin de l'Ishikari, qui appartient à un champ géothermal actif. Dans la partie nord-est des basses terres, le flux de chaleur atteint localement 140 mW m-2, probablement à cause d'un écoulement souterrain ascendant depuis le champ g
Modeling individuals’ cognitive and affective responses in spatial learning behavior
Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.
2008-01-01
Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a
Modelling firm heterogeneity with spatial 'trends'
Sarmiento, C. [North Dakota State University, Fargo, ND (United States). Dept. of Agricultural Business & Applied Economics
2004-04-15
The hypothesis underlying this article is that firm heterogeneity can be captured by spatial characteristics of the firm (similar to the inclusion of a time trend in time series models). The hypothesis is examined in the context of modelling electric generation by coal powered plants in the presence of firm heterogeneity.
Appropriatie spatial scales to achieve model output uncertainty goals
Booij, Martijn J.; Melching, Charles S.; Chen, Xiaohong; Chen, Yongqin; Xia, Jun; Zhang, Hailun
2008-01-01
Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between
Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina
2018-01-01
The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.
Spatially adaptive mixture modeling for analysis of FMRI time series.
Vincent, Thomas; Risser, Laurent; Ciuciu, Philippe
2010-04-01
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni et aL, 2005 and Makni et aL, 2008, a detection-estimation framework has been proposed to tackle these problems jointly, since they are connected to one another. In the Bayesian formalism, detection is achieved by modeling activating and nonactivating voxels through independent mixture models (IMM) within each region while hemodynamic response estimation is performed at a regional scale in a nonparametric way. Instead of IMMs, in this paper we take advantage of spatial mixture models (SMM) for their nonlinear spatial regularizing properties. The proposed method is unsupervised and spatially adaptive in the sense that the amount of spatial correlation is automatically tuned from the data and this setting automatically varies across brain regions. In addition, the level of regularization is specific to each experimental condition since both the signal-to-noise ratio and the activation pattern may vary across stimulus types in a given brain region. These aspects require the precise estimation of multiple partition functions of underlying Ising fields. This is addressed efficiently using first path sampling for a small subset of fields and then using a recently developed fast extrapolation technique for the large remaining set. Simulation results emphasize that detection relying on supervised SMM outperforms its IMM counterpart and that unsupervised spatial mixture models achieve similar results without any hand-tuning of the correlation parameter. On real datasets, the gain is illustrated in a localizer fMRI experiment: brain activations appear more spatially resolved using SMM in comparison with classical general linear model (GLM)-based approaches, while estimating a specific parcel-based HRF shape. Our approach therefore validates the treatment of unsmoothed fMRI data without fixed GLM
Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models
Duffy, Stephen F.
1997-01-01
Ceramic matrix composites (CMC) and intermetallic materials (e.g., single crystal nickel aluminide) are high performance materials that exhibit attractive mechanical, thermal and chemical properties. These materials are critically important in advancing certain performance aspects of gas turbine engines. From an aerospace engineer's perspective the new generation of ceramic composites and intermetallics offers a significant potential for raising the thrust/weight ratio and reducing NO(x) emissions of gas turbine engines. These aspects have increased interest in utilizing these materials in the hot sections of turbine engines. However, as these materials evolve and their performance characteristics improve a persistent need exists for state-of-the-art analytical methods that predict the response of components fabricated from CMC and intermetallic material systems. This need provided the motivation for the technology developed under this research effort. Continuous ceramic fiber composites exhibit an increase in work of fracture, which allows for "graceful" rather than catastrophic failure. When loaded in the fiber direction, these composites retain substantial strength capacity beyond the initiation of transverse matrix cracking despite the fact that neither of its constituents would exhibit such behavior if tested alone. As additional load is applied beyond first matrix cracking, the matrix tends to break in a series of cracks bridged by the ceramic fibers. Any additional load is born increasingly by the fibers until the ultimate strength of the composite is reached. Thus modeling efforts supported under this research effort have focused on predicting this sort of behavior. For single crystal intermetallics the issues that motivated the technology development involved questions relating to material behavior and component design. Thus the research effort supported by this grant had to determine the statistical nature and source of fracture in a high strength, Ni
An analytical model of a curved beam with a T shaped cross section
Hull, Andrew J.; Perez, Daniel; Cox, Donald L.
2018-03-01
This paper derives a comprehensive analytical dynamic model of a closed circular beam that has a T shaped cross section. The new model includes in-plane and out-of-plane vibrations derived using continuous media expressions which produces results that have a valid frequency range above those available from traditional lumped parameter models. The web is modeled using two-dimensional elasticity equations for in-plane motion and the classical flexural plate equation for out-of-plane motion. The flange is modeled using two sets of Donnell shell equations: one for the left side of the flange and one for the right side of the flange. The governing differential equations are solved with unknown wave propagation coefficients multiplied by spatial domain and time domain functions which are inserted into equilibrium and continuity equations at the intersection of the web and flange and into boundary conditions at the edges of the system resulting in 24 algebraic equations. These equations are solved to yield the wave propagation coefficients and this produces a solution to the displacement field in all three dimensions. An example problem is formulated and compared to results from finite element analysis.
A Statistical Toolbox For Mining And Modeling Spatial Data
D’Aubigny Gérard
2016-12-01
Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.
Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell
2017-01-01
In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.
Khalifa M. Al-Kindi
2017-08-01
Full Text Available In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.
A spatial model of mosquito host-seeking behavior.
Bree Cummins
Full Text Available Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions.
A study of spatial resolution in pollution exposure modelling
Gustafsson Susanna
2007-06-01
Full Text Available Abstract Background This study is part of several ongoing projects concerning epidemiological research into the effects on health of exposure to air pollutants in the region of Scania, southern Sweden. The aim is to investigate the optimal spatial resolution, with respect to temporal resolution, for a pollutant database of NOx-values which will be used mainly for epidemiological studies with durations of days, weeks or longer periods. The fact that a pollutant database has a fixed spatial resolution makes the choice critical for the future use of the database. Results The results from the study showed that the accuracy between the modelled concentrations of the reference grid with high spatial resolution (100 m, denoted the fine grid, and the coarser grids (200, 400, 800 and 1600 meters improved with increasing spatial resolution. When the pollutant values were aggregated in time (from hours to days and weeks the disagreement between the fine grid and the coarser grids were significantly reduced. The results also illustrate a considerable difference in optimal spatial resolution depending on the characteristic of the study area (rural or urban areas. To estimate the accuracy of the modelled values comparison were made with measured NOx values. The mean difference between the modelled and the measured value were 0.6 μg/m3 and the standard deviation 5.9 μg/m3 for the daily difference. Conclusion The choice of spatial resolution should not considerably deteriorate the accuracy of the modelled NOx values. Considering the comparison between modelled and measured values we estimate that an error due to coarse resolution greater than 1 μg/m3 is inadvisable if a time resolution of one day is used. Based on the study of different spatial resolutions we conclude that for urban areas a spatial resolution of 200–400 m is suitable; and for rural areas the spatial resolution could be coarser (about 1600 m. This implies that we should develop a pollutant
A genetic algorithm-based job scheduling model for big data analytics.
Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei
Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.
Toward micro-scale spatial modeling of gentrification
O'Sullivan, David
A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects.
Modeling Urban Spatial Growth in Mountainous Regions of Western China
Guoping Huang
2017-08-01
Full Text Available The scale and speed of urbanization in the mountainous regions of western China have received little attention from researchers. These cities are facing rapid population growth and severe environmental degradation. This study analyzed historical urban growth trends in this mountainous region to better understand the interaction between the spatial growth pattern and the mountainous topography. Three major factors—slope, accessibility, and land use type—were studied in light of their relationships with urban spatial growth. With the analysis of historical data as the basis, a conceptual urban spatial growth model was devised. In this model, slope, accessibility, and land use type together create resistance to urban growth, while accessibility controls the sequence of urban development. The model was tested and evaluated using historical data. It serves as a potential tool for planners to envision and assess future urban growth scenarios and their potential environmental impacts to make informed decisions.
Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard
2016-09-01
An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.
Hydrological model uncertainty due to spatial evapotranspiration estimation methods
Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub
2016-05-01
Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.
Spatial capture-recapture models for search-encounter data
Royle, J. Andrew; Kery, Marc; Guelat, Jerome
2011-01-01
1. Spatial capture–recapture models make use of auxiliary data on capture location to provide density estimates for animal populations. Previously, models have been developed primarily for fixed trap arrays which define the observable locations of individuals by a set of discrete points. 2. Here, we develop a class of models for 'search-encounter' data, i.e. for detections of recognizable individuals in continuous space, not restricted to trap locations. In our hierarchical model, detection probability is related to the average distance between individual location and the survey path. The locations are allowed to change over time owing to movements of individuals, and individual locations are related formally by a model describing individual activity or home range centre which is itself regarded as a latent variable in the model. We provide a Bayesian analysis of the model in WinBUGS, and develop a custom MCMC algorithm in the R language. 3. The model is applied to simulated data and to territory mapping data for the Willow Tit from the Swiss Breeding Bird Survey MHB. While the observed density was 15 territories per nominal 1 km2 plot of unknown effective sample area, the model produced a density estimate of 21∙12 territories per square km (95% posterior interval: 17–26). 4. Spatial capture–recapture models are relevant to virtually all animal population studies that seek to estimate population size or density, yet existing models have been proposed mainly for conventional sampling using arrays of traps. Our model for search-encounter data, where the spatial pattern of searching can be arbitrary and may change over occasions, greatly expands the scope and utility of spatial capture–recapture models.
Analysing earthquake slip models with the spatial prediction comparison test
Zhang, L.; Mai, Paul Martin; Thingbaijam, Kiran Kumar; Razafindrakoto, H. N. T.; Genton, Marc G.
2014-01-01
Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.
Analysing earthquake slip models with the spatial prediction comparison test
Zhang, L.
2014-11-10
Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.
Gaussian Process Regression Model in Spatial Logistic Regression
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.
Kim, Dohyeong; Galeano, M Alicia Overstreet; Hull, Andrew; Miranda, Marie Lynn
2008-12-01
Preventive approaches to childhood lead poisoning are critical for addressing this longstanding environmental health concern. Moreover, increasing evidence of cognitive effects of blood lead levels system-based childhood lead exposure risk models, especially if executed at highly resolved spatial scales, can help identify children most at risk of lead exposure, as well as prioritize and direct housing and health-protective intervention programs. However, developing highly resolved spatial data requires labor-and time-intensive geocoding and analytical processes. In this study we evaluated the benefit of increased effort spent geocoding in terms of improved performance of lead exposure risk models. We constructed three childhood lead exposure risk models based on established methods but using different levels of geocoded data from blood lead surveillance, county tax assessors, and the 2000 U.S. Census for 18 counties in North Carolina. We used the results to predict lead exposure risk levels mapped at the individual tax parcel unit. The models performed well enough to identify high-risk areas for targeted intervention, even with a relatively low level of effort on geocoding. This study demonstrates the feasibility of widespread replication of highly spatially resolved childhood lead exposure risk models. The models guide resource-constrained local health and housing departments and community-based organizations on how best to expend their efforts in preventing and mitigating lead exposure risk in their communities.
Spatial modeling of agricultural land use change at global scale
Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.
2014-11-01
Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling
Solution of the spatial neutral model yields new bounds on the Amazonian species richness
Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.
2017-02-01
Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).
Martin Gregory T
2004-11-01
Full Text Available Abstract Background Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. Methods We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1 surface contact heating and (2 spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42°C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. Results The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45°C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. Conclusions The heat transport system model of the
A spatial emergy model for Alachua County, Florida
Lambert, James David
A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method
Analytical Model-based Fault Detection and Isolation in Control Systems
Vukic, Z.; Ozbolt, H.; Blanke, M.
1998-01-01
The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...
Ethics, Big Data, and Analytics: A Model for Application.
Willis, James E, III
2013-01-01
The use of big data and analytics to predict student success presents unique ethical questions for higher education administrators relating to the nature of knowledge; in education, "to know" entails an obligation to act on behalf of the student. The Potter Box framework can help administrators address these questions and provide a framework for action.
An analytical model for soil-atmosphere feedback
Schaefli, B.; Van der Ent, R.J.; Woods, R.; Savenije, H.H.G.
2012-01-01
Soil-atmosphere feedback is a key for understanding the hydrological cycle and the direction of potential system changes. This paper presents an analytical framework to study the interplay between soil and atmospheric moisture, using as input only the boundary conditions at the upstream end of
Multivariate Receptor Models for Spatially Correlated Multipollutant Data
Jun, Mikyoung
2013-08-01
The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
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.
A Non-Gaussian Spatial Generalized Linear Latent Variable Model
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.
Practical likelihood analysis for spatial generalized linear mixed models
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
Drechsler, Martin; Ohl, Cornelia; Meyerhoff, Juergen; Eichhorn, Marcus; Monsees, Jan
2011-01-01
Although wind power is currently the most efficient source of renewable energy, the installation of wind turbines (WT) in landscapes often leads to conflicts in the affected communities. We propose that such conflicts can be mitigated by a welfare-optimal spatial allocation of WT in the landscape so that a given energy target is reached at minimum social costs. The energy target is motivated by the fact that wind power production is associated with relatively low CO 2 emissions. Social costs comprise energy production costs as well as external costs caused by harmful impacts on humans and biodiversity. We present a modeling approach that combines spatially explicit ecological-economic modeling and choice experiments to determine the welfare-optimal spatial allocation of WT in West Saxony, Germany. The welfare-optimal sites balance production and external costs. Results indicate that in the welfare-optimal allocation the external costs represent about 14% of the total costs (production costs plus external costs). Optimizing wind power production without consideration of the external costs would lead to a very different allocation of WT that would marginally reduce the production costs but strongly increase the external costs and thus lead to substantial welfare losses. - Highlights: → We combine modeling and economic valuation to optimally allocate wind turbines. → Welfare-optimal allocation balances energy production costs and external costs. → External costs (impacts on the environment) can be substantial. → Ignoring external costs leads to suboptimal allocations and welfare losses.
Towards a 3d Spatial Urban Energy Modelling Approach
Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.
2013-09-01
Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies
Modelling a flows in supply chain with analytical models: Case of a chemical industry
Benhida, Khalid; Azougagh, Yassine; Elfezazi, Said
2016-02-01
This study is interested on the modelling of the logistics flows in a supply chain composed on a production sites and a logistics platform. The contribution of this research is to develop an analytical model (integrated linear programming model), based on a case study of a real company operating in the phosphate field, considering a various constraints in this supply chain to resolve the planning problems for a better decision-making. The objectives of this model is to determine and define the optimal quantities of different products to route, to and from the various entities in the supply chain studied.
Spatially explicit models for inference about density in unmarked or partially marked populations
Chandler, Richard B.; Royle, J. Andrew
2013-01-01
Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating
Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A
2006-11-01
A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.
Analytical Model of Water Flow in Coal with Active Matrix
Siemek, Jakub; Stopa, Jerzy
2014-12-01
This paper presents new analytical model of gas-water flow in coal seams in one dimension with emphasis on interactions between water flowing in cleats and coal matrix. Coal as a flowing system, can be viewed as a solid organic material consisting of two flow subsystems: a microporous matrix and a system of interconnected macropores and fractures. Most of gas is accumulated in the microporous matrix, where the primary flow mechanism is diffusion. Fractures and cleats existing in coal play an important role as a transportation system for macro scale flow of water and gas governed by Darcy's law. The coal matrix can imbibe water under capillary forces leading to exchange of mass between fractures and coal matrix. In this paper new partial differential equation for water saturation in fractures has been formulated, respecting mass exchange between coal matrix and fractures. Exact analytical solution has been obtained using the method of characteristics. The final solution has very simple form that may be useful for practical engineering calculations. It was observed that the rate of exchange of mass between the fractures and the coal matrix is governed by an expression which is analogous to the Newton cooling law known from theory of heat exchange, but in present case the mass transfer coefficient depends not only on coal and fluid properties but also on time and position. The constant term of mass transfer coefficient depends on relation between micro porosity and macro porosity of coal, capillary forces, and microporous structure of coal matrix. This term can be expressed theoretically or obtained experimentally. W artykule zaprezentowano nowy model matematyczny przepływu wody i gazu w jednowymiarowej warstwie węglowej z uwzględnieniem wymiany masy między systemem szczelin i matrycą węglową. Węgiel jako system przepływowy traktowany jest jako układ o podwójnej porowatości i przepuszczalności, składający się z mikroporowatej matrycy węglowej oraz z
Tsivilskiy, I. V.; Nagulin, K. Yu.; Gilmutdinov, A. Kh.
2016-02-01
A full three-dimensional nonstationary numerical model of graphite electrothermal atomizers of various types is developed. The model is based on solution of a heat equation within solid walls of the atomizer with a radiative heat transfer and numerical solution of a full set of Navier-Stokes equations with an energy equation for a gas. Governing equations for the behavior of a discrete phase, i.e., atomic particles suspended in a gas (including gas-phase processes of evaporation and condensation), are derived from the formal equations molecular kinetics by numerical solution of the Hertz-Langmuir equation. The following atomizers test the model: a Varian standard heated electrothermal vaporizer (ETV), a Perkin Elmer standard THGA transversely heated graphite tube with integrated platform (THGA), and the original double-stage tube-helix atomizer (DSTHA). The experimental verification of computer calculations is carried out by a method of shadow spectral visualization of the spatial distributions of atomic and molecular vapors in an analytical space of an atomizer.
Modelling the Spatial Isotope Variability of Precipitation in Syria
Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)
2013-07-15
Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)
Design of spatial experiments: Model fitting and prediction
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Classifying and comparing spatial models of fire dynamics
Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan
2007-01-01
Wildland fire is a significant disturbance in many ecosystems worldwide and the interaction of fire with climate and vegetation over long time spans has major effects on vegetation dynamics, ecosystem carbon budgets, and patterns of biodiversity. Landscape-Fire-Succession Models (LFSMs) that simulate the linked processes of fire and vegetation development in a spatial...
Thinking Egyptian: Active Models for Understanding Spatial Representation.
Schiferl, Ellen
This paper highlights how introductory textbooks on Egyptian art inhibit understanding by reinforcing student preconceptions, and demonstrates another approach to discussing space with a classroom exercise and software. The alternative approach, an active model for spatial representation, introduced here was developed by adapting classroom…
Spatially Informed Plant PRA Models for Security Assessment
Wheeler, Timothy A.; Thomas, Willard; Thornsbury, Eric
2006-01-01
Traditional risk models can be adapted to evaluate plant response for situations where plant systems and structures are intentionally damaged, such as from sabotage or terrorism. This paper describes a process by which traditional risk models can be spatially informed to analyze the effects of compound and widespread harsh environments through the use of 'damage footprints'. A 'damage footprint' is a spatial map of regions of the plant (zones) where equipment could be physically destroyed or disabled as a direct consequence of an intentional act. The use of 'damage footprints' requires that the basic events from the traditional probabilistic risk assessment (PRA) be spatially transformed so that the failure of individual components can be linked to the destruction of or damage to specific spatial zones within the plant. Given the nature of intentional acts, extensive modifications must be made to the risk models to account for the special nature of the 'initiating events' associated with deliberate adversary actions. Intentional acts might produce harsh environments that in turn could subject components and structures to one or more insults, such as structural, fire, flood, and/or vibration and shock damage. Furthermore, the potential for widespread damage from some of these insults requires an approach that addresses the impacts of these potentially severe insults even when they occur in locations distant from the actual physical location of a component or structure modeled in the traditional PRA. (authors)
Rockfall hazard analysis using LiDAR and spatial modeling
Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho
2010-05-01
Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.
Individual based model of slug population and spatial dynamics
Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.
2006-01-01
The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field
Differences in spatial understanding between physical and virtual models
Lei Sun
2014-03-01
Full Text Available In the digital age, physical models are still used as major tools in architectural and urban design processes. The reason why designers still use physical models remains unclear. In addition, physical and 3D virtual models have yet to be differentiated. The answers to these questions are too complex to account for in all aspects. Thus, this study only focuses on the differences in spatial understanding between physical and virtual models. In particular, it emphasizes on the perception of scale. For our experiment, respondents were shown a physical model and a virtual model consecutively. A questionnaire was then used to ask the respondents to evaluate these models objectively and to establish which model was more accurate in conveying object size. Compared with the virtual model, the physical model tended to enable quicker and more accurate comparisons of building heights.
Spatial variability and parametric uncertainty in performance assessment models
Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo
2011-01-01
The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)
Spatial Development Modeling Methodology Application Possibilities in Vilnius
Lina Panavaitė
2017-05-01
Full Text Available In order to control the continued development of high-rise buildings and their irreversible visual impact on the overall silhouette of the city, the great cities of the world introduced new methodological principles to city’s spatial development models. These methodologies and spatial planning guidelines are focused not only on the controlled development of high-rise buildings, but on the spatial modelling of the whole city by defining main development criteria and estimating possible consequences. Vilnius city is no exception, however the re-establishment of independence of Lithuania caused uncontrolled urbanization process, so most of the city development regulations emerged as a consequence of unmanaged processes of investors’ expectations legalization. The importance of consistent urban fabric as well as conservation and representation of city’s most important objects gained attention only when an actual threat of overshadowing them with new architecture along with unmanaged urbanization in the city center or urban sprawl at suburbia, caused by land-use projects, had emerged. Current Vilnius’ spatial planning documents clearly define urban structure and key development principles, however the definitions are relatively abstract, causing uniform building coverage requirements for territories with distinct qualities and simplifying planar designs which do not meet quality standards. The overall quality of urban architecture is not regulated. The article deals with current spatial modeling methods, their individual parts, principles, the criteria for quality assessment and their applicability in Vilnius. The text contains an outline of possible building coverage regulations and impact assessment criteria for new development. The article contains a compendium of requirements for high-quality spatial planning and building design.
A spatial haplotype copying model with applications to genotype imputation.
Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan
2015-05-01
Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.
Marzieh Mokarrama
2018-04-01
Full Text Available The purpose of the present study is preparing a landform classification by using digital elevation model (DEM which has a high spatial resolution. To reach the mentioned aim, a sub-pixel spatial attraction model was used as a novel method for preparing DEM with a high spatial resolution in the north of Darab, Fars province, Iran. The sub-pixel attraction models convert the pixel into sub-pixels based on the neighboring pixels fraction values, which can only be attracted by a central pixel. Based on this approach, a mere maximum of eight neighboring pixels can be selected for calculating of the attraction value. In the mentioned model, other pixels are supposed to be far from the central pixel to receive any attraction. In the present study by using a sub-pixel attraction model, the spatial resolution of a DEM was increased. The design of the algorithm is accomplished by using a DEM with a spatial resolution of 30 m (the Advanced Space borne Thermal Emission and Reflection Radiometer; (ASTER and a 90 m (the Shuttle Radar Topography Mission; (SRTM. In the attraction model, scale factors of (S = 2, S = 3, and S = 4 with two neighboring methods of touching (T = 1 and quadrant (T = 2 are applied to the DEMs by using MATLAB software. The algorithm is evaluated by taking the best advantages of 487 sample points, which are measured by surveyors. The spatial attraction model with scale factor of (S = 2 gives better results compared to those scale factors which are greater than 2. Besides, the touching neighborhood method is turned to be more accurate than the quadrant method. In fact, dividing each pixel into more than two sub-pixels decreases the accuracy of the resulted DEM. On the other hand, in these cases DEM, is itself in charge of increasing the value of root-mean-square error (RMSE and shows that attraction models could not be used for S which is greater than 2. Thus considering results, the proposed model is highly capable of
Modern methodology and applications in spatial-temporal modeling
Matsui, Tomoko
2015-01-01
This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component an...
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
Lechevalier , David; Narayanan , Anantha; Rachuri , Sudarsan; Foufou , Sebti; Lee , Y Tina
2016-01-01
Part 3: Interoperability and Systems Integration; International audience; To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformatio...
Review of analytical models to stream depletion induced by pumping: Guide to model selection
Huang, Ching-Sheng; Yang, Tao; Yeh, Hund-Der
2018-06-01
Stream depletion due to groundwater extraction by wells may cause impact on aquatic ecosystem in streams, conflict over water rights, and contamination of water from irrigation wells near polluted streams. A variety of studies have been devoted to addressing the issue of stream depletion, but a fundamental framework for analytical modeling developed from aquifer viewpoint has not yet been found. This review shows key differences in existing models regarding the stream depletion problem and provides some guidelines for choosing a proper analytical model in solving the problem of concern. We introduce commonly used models composed of flow equations, boundary conditions, well representations and stream treatments for confined, unconfined, and leaky aquifers. They are briefly evaluated and classified according to six categories of aquifer type, flow dimension, aquifer domain, stream representation, stream channel geometry, and well type. Finally, we recommend promising analytical approaches that can solve stream depletion problem in reality with aquifer heterogeneity and irregular geometry of stream channel. Several unsolved stream depletion problems are also recommended.
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Analog model for analysis of spatial instability of neutron flux
Radanovic, Lj.
1964-12-01
The objective of this task was to develop a model for analysing spatial instability of the neutron flux and defining the optimum number and position of regulating rods. The developed model enables calculation of higher harmonics to be taken into account for each type of reactor, to define zones for regulation rods, position and number of points for detecting reactor state, and number and position of the regulating rods
Integrating remote sensing and spatially explicit epidemiological modeling
Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea
2015-04-01
Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.
Spatial Temporal Modelling of Particulate Matter for Health Effects Studies
Hamm, N. A. S.
2016-10-01
Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air quality monitoring stations in the Dutch city of Eindhoven, which make up the ILM (innovative air (quality) measurement system). These stations currently provide PM10 and PM2.5 (particulate matter less than 10 and 2.5 m in diameter), aggregated to hourly means. The data provide an unprecedented level of spatial and temporal detail for a city of this size. Despite these benefits the time series of measurements is characterized by missing values and noisy values. In this paper a space-time analysis is presented that is based on a dynamic model for the temporal component and a Gaussian process geostatistical for the spatial component. Spatial-temporal variability was dominated by the temporal component, although the spatial variability was also substantial. The model delivered accurate predictions for both isolated missing values and 24-hour periods of missing values (RMSE = 1.4 μg m-3 and 1.8 μg m-3 respectively). Outliers could be detected by comparison to the 95% prediction interval. The model shows promise for predicting missing values, outlier detection and for mapping to support health impact studies.
Spatial modelling and ecology of Echinococcus multilocularis transmission in China.
Danson, F Mark; Giraudoux, Patrick; Craig, Philip S
2006-01-01
Recent research in central China has suggested that the most likely transmission mechanism for Echinococcus multilocularis to humans is via domestic dogs which are allowed to roam freely and hunt (infected) small mammals within areas close to villages or in areas of tented pasture. This assertion has led to the hypothesis that there is a landscape control on transmission risk since the proximity of suitable habitat for susceptible small mammals appears to be the key. We have tested this hypothesis in a number of endemic areas in China, notably south Gansu Province and the Tibetan region of western Sichuan Province. The fundamental landscape control is its effect at a regional scale on small mammal species assemblages (susceptible species are not ubiquitous) and, at a local scale, the spatial distributions of small mammal populations. To date the research has examined relationships between landscape composition and patterns of human infection, landscape and small mammal distributions and recently the relationships between landscape and dog infection rates. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk. This paper reviews the progress that has been made so far in spatial modeling of the ecology of E. multilocularis with particular reference to China, outlines current research issues, and describes a framework for building a spatial-temporal model of transmission ecology.
IT vendor selection model by using structural equation model & analytical hierarchy process
Maitra, Sarit; Dominic, P. D. D.
2012-11-01
Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.
A minimal spatial cell lineage model of epithelium: tissue stratification and multi-stability
Yeh, Wei-Ting; Chen, Hsuan-Yi
2018-05-01
A minimal model which includes spatial and cell lineage dynamics for stratified epithelia is presented. The dependence of tissue steady state on cell differentiation models, cell proliferation rate, cell differentiation rate, and other parameters are studied numerically and analytically. Our minimal model shows some important features. First, we find that morphogen or mechanical stress mediated interaction is necessary to maintain a healthy stratified epithelium. Furthermore, comparing with tissues in which cell differentiation can take place only during cell division, tissues in which cell division and cell differentiation are decoupled can achieve relatively higher degree of stratification. Finally, our model also shows that in the presence of short-range interactions, it is possible for a tissue to have multiple steady states. The relation between our results and tissue morphogenesis or lesion is discussed.
Indoor 3D Route Modeling Based On Estate Spatial Data
Zhang, H.; Wen, Y.; Jiang, J.; Huang, W.
2014-04-01
Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.
Single Canonical Model of Reflexive Memory and Spatial Attention
Patel, Saumil S.; Red, Stuart; Lin, Eric; Sereno, Anne B.
2015-01-01
Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey’s task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes. PMID:26493949
Chaotic and stable perturbed maps: 2-cycles and spatial models
Braverman, E.; Haroutunian, J.
2010-06-01
As the growth rate parameter increases in the Ricker, logistic and some other maps, the models exhibit an irreversible period doubling route to chaos. If a constant positive perturbation is introduced, then the Ricker model (but not the classical logistic map) experiences period doubling reversals; the break of chaos finally gives birth to a stable two-cycle. We outline the maps which demonstrate a similar behavior and also study relevant discrete spatial models where the value in each cell at the next step is defined only by the values at the cell and its nearest neighbors. The stable 2-cycle in a scalar map does not necessarily imply 2-cyclic-type behavior in each cell for the spatial generalization of the map.
Single Canonical Model of Reflexive Memory and Spatial Attention.
Patel, Saumil S; Red, Stuart; Lin, Eric; Sereno, Anne B
2015-10-23
Many neurons in the dorsal and ventral visual stream have the property that after a brief visual stimulus presentation in their receptive field, the spiking activity in these neurons persists above their baseline levels for several seconds. This maintained activity is not always correlated with the monkey's task and its origin is unknown. We have previously proposed a simple neural network model, based on shape selective neurons in monkey lateral intraparietal cortex, which predicts the valence and time course of reflexive (bottom-up) spatial attention. In the same simple model, we demonstrate here that passive maintained activity or short-term memory of specific visual events can result without need for an external or top-down modulatory signal. Mutual inhibition and neuronal adaptation play distinct roles in reflexive attention and memory. This modest 4-cell model provides the first simple and unified physiologically plausible mechanism of reflexive spatial attention and passive short-term memory processes.
Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution
Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M
2007-01-01
Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus
Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model
Sahoo, Satiprasad; Dhar, Anirban; Kar, Amlanjyoti
2016-01-01
Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.
Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model
Sahoo, Satiprasad [School of Water Resources, Indian Institute of Technology Kharagpur (India); Dhar, Anirban, E-mail: anirban.dhar@gmail.com [Department of Civil Engineering, Indian Institute of Technology Kharagpur (India); Kar, Amlanjyoti [Central Ground Water Board, Bhujal Bhawan, Faridabad, Haryana (India)
2016-01-15
Environmental management of an area describes a policy for its systematic and sustainable environmental protection. In the present study, regional environmental vulnerability assessment in Hirakud command area of Odisha, India is envisaged based on Grey Analytic Hierarchy Process method (Grey–AHP) using integrated remote sensing (RS) and geographic information system (GIS) techniques. Grey–AHP combines the advantages of classical analytic hierarchy process (AHP) and grey clustering method for accurate estimation of weight coefficients. It is a new method for environmental vulnerability assessment. Environmental vulnerability index (EVI) uses natural, environmental and human impact related factors, e.g., soil, geology, elevation, slope, rainfall, temperature, wind speed, normalized difference vegetation index, drainage density, crop intensity, agricultural DRASTIC value, population density and road density. EVI map has been classified into four environmental vulnerability zones (EVZs) namely: ‘low’, ‘moderate’ ‘high’, and ‘extreme’ encompassing 17.87%, 44.44%, 27.81% and 9.88% of the study area, respectively. EVI map indicates that the northern part of the study area is more vulnerable from an environmental point of view. EVI map shows close correlation with elevation. Effectiveness of the zone classification is evaluated by using grey clustering method. General effectiveness is in between “better” and “common classes”. This analysis demonstrates the potential applicability of the methodology. - Highlights: • Environmental vulnerability zone identification based on Grey Analytic Hierarchy Process (AHP) • The effectiveness evaluation by means of a grey clustering method with support from AHP • Use of grey approach eliminates the excessive dependency on the experience of experts.
An analytical model on thermal performance evaluation of counter flow wet cooling tower
Wang Qian
2017-01-01
Full Text Available This paper proposes an analytical model for simultaneous heat and mass transfer processes in a counter flow wet cooling tower, with the assumption that the enthalpy of the saturated air is a linear function of the water surface temperature. The performance of the proposed analytical model is validated in some typical cases. The validation reveals that, when cooling range is in a certain interval, the proposed model is not only comparable with the accurate model, but also can reduce computational complexity. In addition, with the proposed analytical model, the thermal performance of the counter flow wet cooling towers in power plants is calculated. The results show that the proposed analytical model can be applied to evaluate and predict the thermal performance of counter flow wet cooling towers.
Cooperative effects in spherical spasers: Ab initio analytical model
Bordo, V. G.
2017-06-01
A fully analytical semiclassical theory of cooperative optical processes which occur in an ensemble of molecules embedded in a spherical core-shell nanoparticle is developed from first principles. Both the plasmonic Dicke effect and spaser generation are investigated for the designs in which a shell/core contains an arbitrarily large number of active molecules in the vicinity of a metallic core/shell. An essential aspect of the theory is an ab initio account of the feedback from the core/shell boundaries which significantly modifies the molecular dynamics. The theory provides rigorous, albeit simple and physically transparent, criteria for both plasmonic superradiance and surface plasmon generation.
Predictive analytics technology review: Similarity-based modeling and beyond
Herzog, James; Doan, Don; Gandhi, Devang; Nieman, Bill
2010-09-15
Over 11 years ago, SmartSignal introduced Predictive Analytics for eliminating equipment failures, using its patented SBM technology. SmartSignal continues to lead and dominate the market and, in 2010, went one step further and introduced Predictive Diagnostics. Now, SmartSignal is combining Predictive Diagnostics with RCM methodology and industry expertise. FMEA logic reengineers maintenance work management, eliminates unneeded inspections, and focuses efforts on the real issues. This integrated solution significantly lowers maintenance costs, protects against critical asset failures, and improves commercial availability, and reduces work orders 20-40%. Learn how.
Analytical models of optical refraction in the troposphere.
Nener, Brett D; Fowkes, Neville; Borredon, Laurent
2003-05-01
An extremely accurate but simple asymptotic description (with known error) is obtained for the path of a ray propagating over a curved Earth with radial variations in refractive index. The result is sufficiently simple that analytic solutions for the path can be obtained for linear and quadratic index profiles. As well as rendering the inverse problem trivial for these profiles, this formulation shows that images are uniformly magnified in the vertical direction when viewed through a quadratic refractive-index profile. Nonuniform vertical distortions occur for higher-order refractive-index profiles.
Modelling of packet traffic with matrix analytic methods
Andersen, Allan T.
1995-01-01
BISDN network. The heuristic formula did not seem to yield substantially better results than already available approximations. Finally, some results for the finite capacity BMAP/G/1 queue have been obtained. The steady state probability vector of the embedded chain is found by a direct method where...... process. A heuristic formula for the tail behaviour of a single server queue fed by a superposition of renewal processes has been evaluated. The evaluation was performed by applying Matrix Analytic methods. The heuristic formula has applications in the Call Admission Control (CAC) procedure of the future...
Analytical solution of a stochastic content-based network model
Mungan, Muhittin; Kabakoglu, Alkan; Balcan, Duygu; Erzan, Ayse
2005-01-01
We define and completely solve a content-based directed network whose nodes consist of random words and an adjacency rule involving perfect or approximate matches for an alphabet with an arbitrary number of letters. The analytic expression for the out-degree distribution shows a crossover from a leading power law behaviour to a log-periodic regime bounded by a different power law decay. The leading exponents in the two regions have a weak dependence on the mean word length, and an even weaker dependence on the alphabet size. The in-degree distribution, on the other hand, is much narrower and does not show any scaling behaviour
An Analytical Hierarchy Process Model for the Evaluation of College Experimental Teaching Quality
Yin, Qingli
2013-01-01
Taking into account the characteristics of college experimental teaching, through investigaton and analysis, evaluation indices and an Analytical Hierarchy Process (AHP) model of experimental teaching quality have been established following the analytical hierarchy process method, and the evaluation indices have been given reasonable weights. An…
An Analytic Hierarchy Process for School Quality and Inspection: Model Development and Application
Al Qubaisi, Amal; Badri, Masood; Mohaidat, Jihad; Al Dhaheri, Hamad; Yang, Guang; Al Rashedi, Asma; Greer, Kenneth
2016-01-01
Purpose: The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach: The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the…
John (Jack P. Riegel III
2016-04-01
Full Text Available Historically, there has been little correlation between the material properties used in (1 empirical formulae, (2 analytical formulations, and (3 numerical models. The various regressions and models may each provide excellent agreement for the depth of penetration into semi-infinite targets. But the input parameters for the empirically based procedures may have little in common with either the analytical model or the numerical model. This paper builds on previous work by Riegel and Anderson (2014 to show how the Effective Flow Stress (EFS strength model, based on empirical data, can be used as the average flow stress in the analytical Walker–Anderson Penetration model (WAPEN (Anderson and Walker, 1991 and how the same value may be utilized as an effective von Mises yield strength in numerical hydrocode simulations to predict the depth of penetration for eroding projectiles at impact velocities in the mechanical response regime of the materials. The method has the benefit of allowing the three techniques (empirical, analytical, and numerical to work in tandem. The empirical method can be used for many shot line calculations, but more advanced analytical or numerical models can be employed when necessary to address specific geometries such as edge effects or layering that are not treated by the simpler methods. Developing complete constitutive relationships for a material can be costly. If the only concern is depth of penetration, such a level of detail may not be required. The effective flow stress can be determined from a small set of depth of penetration experiments in many cases, especially for long penetrators such as the L/D = 10 ones considered here, making it a very practical approach. In the process of performing this effort, the authors considered numerical simulations by other researchers based on the same set of experimental data that the authors used for their empirical and analytical assessment. The goals were to establish a
An Analytical Model for the Evolution of the Protoplanetary Disks
Khajenabi, Fazeleh; Kazrani, Kimia; Shadmehri, Mohsen, E-mail: f.khajenabi@gu.ac.ir [Department of Physics, Faculty of Sciences, Golestan University, Gorgan 49138-15739 (Iran, Islamic Republic of)
2017-06-01
We obtain a new set of analytical solutions for the evolution of a self-gravitating accretion disk by holding the Toomre parameter close to its threshold and obtaining the stress parameter from the cooling rate. In agreement with the previous numerical solutions, furthermore, the accretion rate is assumed to be independent of the disk radius. Extreme situations where the entire disk is either optically thick or optically thin are studied independently, and the obtained solutions can be used for exploring the early or the final phases of a protoplanetary disk evolution. Our solutions exhibit decay of the accretion rate as a power-law function of the age of the system, with exponents −0.75 and −1.04 for optically thick and thin cases, respectively. Our calculations permit us to explore the evolution of the snow line analytically. The location of the snow line in the optically thick regime evolves as a power-law function of time with the exponent −0.16; however, when the disk is optically thin, the location of the snow line as a function of time with the exponent −0.7 has a stronger dependence on time. This means that in an optically thin disk inward migration of the snow line is faster than an optically thick disk.
Evaluation of Analytical Modeling Functions for the Phonation Onset Process
Simon Petermann
2016-01-01
Full Text Available The human voice originates from oscillations of the vocal folds in the larynx. The duration of the voice onset (VO, called the voice onset time (VOT, is currently under investigation as a clinical indicator for correct laryngeal functionality. Different analytical approaches for computing the VOT based on endoscopic imaging were compared to determine the most reliable method to quantify automatically the transient vocal fold oscillations during VO. Transnasal endoscopic imaging in combination with a high-speed camera (8000 fps was applied to visualize the phonation onset process. Two different definitions of VO interval were investigated. Six analytical functions were tested that approximate the envelope of the filtered or unfiltered glottal area waveform (GAW during phonation onset. A total of 126 recordings from nine healthy males and 210 recordings from 15 healthy females were evaluated. Three criteria were analyzed to determine the most appropriate computation approach: (1 reliability of the fit function for a correct approximation of VO; (2 consistency represented by the standard deviation of VOT; and (3 accuracy of the approximation of VO. The results suggest the computation of VOT by a fourth-order polynomial approximation in the interval between 32.2 and 67.8% of the saturation amplitude of the filtered GAW.
An analytic equation of state for Ising-like models
O'Connor, Denjoe; Santiago, J A; Stephens, C R
2007-01-01
Using an environmentally friendly renormalization we derive, from an underlying field theory representation, a formal expression for the equation of state, y = f(x), that exhibits all desired asymptotic and analyticity properties in the three limits x → 0, x → ∞ and x → -1. The only necessary inputs are the Wilson functions γ λ , γ ψ and γ φ 2 , associated with a renormalization of the transverse vertex functions. These Wilson functions exhibit a crossover between the Wilson-Fisher fixed point and the fixed point that controls the coexistence curve. Restricting to the case N = 1, we derive a one-loop equation of state for 2 < d < 4 naturally parameterized by a ratio of nonlinear scaling fields. For d = 3 we show that a non-parameterized analytic form can be deduced. Various asymptotic amplitudes are calculated directly from the equation of state in all three asymptotic limits of interest and comparison made with known results. By positing a scaling form for the equation of state inspired by the one-loop result, but adjusted to fit the known values of the critical exponents, we obtain better agreement with known asymptotic amplitudes
Design Evaluation of Wind Turbine Spline Couplings Using an Analytical Model: Preprint
Guo, Y.; Keller, J.; Wallen, R.; Errichello, R.; Halse, C.; Lambert, S.
2015-02-01
Articulated splines are commonly used in the planetary stage of wind turbine gearboxes for transmitting the driving torque and improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility. This paper presents an analytical model for the analysis of articulated spline coupling designs. For a given torque and shaft misalignment, this analytical model quickly yields insights into relationships between the spline design parameters and resulting loads; bending, contact, and shear stresses; and safety factors considering various heat treatment methods. Comparisons of this analytical model against previously published computational approaches are also presented.
Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon
2018-05-01
The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.
Modeling molecular mixing in a spatially inhomogeneous turbulent flow
Meyer, Daniel W.; Deb, Rajdeep
2012-02-01
Simulations of spatially inhomogeneous turbulent mixing in decaying grid turbulence with a joint velocity-concentration probability density function (PDF) method were conducted. The inert mixing scenario involves three streams with different compositions. The mixing model of Meyer ["A new particle interaction mixing model for turbulent dispersion and turbulent reactive flows," Phys. Fluids 22(3), 035103 (2010)], the interaction by exchange with the mean (IEM) model and its velocity-conditional variant, i.e., the IECM model, were applied. For reference, the direct numerical simulation data provided by Sawford and de Bruyn Kops ["Direct numerical simulation and lagrangian modeling of joint scalar statistics in ternary mixing," Phys. Fluids 20(9), 095106 (2008)] was used. It was found that velocity conditioning is essential to obtain accurate concentration PDF predictions. Moreover, the model of Meyer provides significantly better results compared to the IECM model at comparable computational expense.
A general modeling framework for describing spatially structured population dynamics
Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan
2017-01-01
Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance
Spatial distribution of emissions to air - the SPREAD model
Plejdrup, M S; Gyldenkaerne, S
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
Spatial distribution of emissions to air - the SPREAD model
Plejdrup, M.S.; Gyldenkaerne, S.
2011-04-15
The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Tapered composite likelihood for spatial max-stable models
Sang, Huiyan
2014-05-01
Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.
Database modeling to integrate macrobenthos data in Spatial Data Infrastructure
José Alberto Quintanilha
2012-08-01
Full Text Available Coastal zones are complex areas that include marine and terrestrial environments. Besides its huge environmental wealth, they also attracts humans because provides food, recreation, business, and transportation, among others. Some difficulties to manage these areas are related with their complexity, diversity of interests and the absence of standardization to collect and share data to scientific community, public agencies, among others. The idea to organize, standardize and share this information based on Web Atlas is essential to support planning and decision making issues. The construction of a spatial database integrating the environmental business, to be used on Spatial Data Infrastructure (SDI is illustrated by a bioindicator that indicates the quality of the sediments. The models show the phases required to build Macrobenthos spatial database based on Santos Metropolitan Region as a reference. It is concluded that, when working with environmental data the structuring of knowledge in a conceptual model is essential for their subsequent integration into the SDI. During the modeling process it can be noticed that methodological issues related to the collection process may obstruct or prejudice the integration of data from different studies of the same area. The development of a database model, as presented in this study, can be used as a reference for further research with similar goals.
Tapered composite likelihood for spatial max-stable models
Sang, Huiyan; Genton, Marc G.
2014-01-01
Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.
Spatial Modelling of Sediment Transport over the Upper Citarum Catchment
Poerbandono
2006-05-01
Full Text Available This paper discusses set up of a spatial model applied in Geographic Information System (GIS environment for predicting annual erosion rate and sediment yield of a watershed. The study area is situated in the Upper Citarum Catchment of West Java. Annual sediment yield is considered as product of erosion rate and sediment delivery ratio to be modelled under similar modeling tool. Sediment delivery ratio is estimated on the basis of sediment resident time. The modeling concept is based on the calculation of water flow velocity through sub-catchment surface, which is controlled by topography, rainfall, soil characteristics and various types of land use. Relating velocity to known distance across digital elevation model, sediment resident time can be estimated. Data from relevance authorities are used. Bearing in mind limited knowledge of some governing factors due to lack of observation, the result has shown the potential of GIS for spatially modeling regional sediment transport. Validation of model result is carried out by evaluating measured and computed total sediment yield at the main outlet. Computed total sediment yields for 1994 and 2001 are found to be 1.96×106 and 2.10×106tons/year. They deviate roughly 54 and 8% with respect to those measured in the field. Model response due to land use change observed in 2001 and 1994 is also recognised. Under presumably constant rainfall depth, an increase of overall average annual erosion rate of 11% resulted in an increase of overall average sediment yield of 7%.
Supplementary Material for: Factor Copula Models for Replicated Spatial Data
Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.
2016-01-01
We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.
Spatial modeling of HIV and HSV-2 among women in Kenya with spatially varying coefficients
Elphas Okango
2016-04-01
Full Text Available Abstract Background Disease mapping has become popular in the field of statistics as a method to explain the spatial distribution of disease outcomes and as a tool to help design targeted intervention strategies. Most of these models however have been implemented with assumptions that may be limiting or altogether lead to less meaningful results and hence interpretations. Some of these assumptions include the linearity, stationarity and normality assumptions. Studies have shown that the linearity assumption is not necessarily true for all covariates. Age for example has been found to have a non-linear relationship with HIV and HSV-2 prevalence. Other studies have made stationarity assumption in that one stimulus e.g. education, provokes the same response in all the regions under study and this is also quite restrictive. Responses to stimuli may vary from region to region due to aspects like culture, preferences and attitudes. Methods We perform a spatial modeling of HIV and HSV-2 among women in Kenya, while relaxing these assumptions i.e. the linearity assumption by allowing the covariate age to have a non-linear effect on HIV and HSV-2 prevalence using the random walk model of order 2 and the stationarity assumption by allowing the rest of the covariates to vary spatially using the conditional autoregressive model. The women data used in this study were derived from the 2007 Kenya AIDS indicator survey where women aged 15–49 years were surveyed. A full Bayesian approach was used and the models were implemented in R-INLA software. Results Age was found to have a non-linear relationship with both HIV and HSV-2 prevalence, and the spatially varying coefficient model provided a significantly better fit for HSV-2. Age-at first sex also had a greater effect on HSV-2 prevalence in the Coastal and some parts of North Eastern regions suggesting either early marriages or child prostitution. The effect of education on HIV prevalence among women was more
Models of chromatin spatial organisation in the cell nucleus
Nicodemi, Mario
2014-03-01
In the cell nucleus chromosomes have a complex architecture serving vital functional purposes. Recent experiments have started unveiling the interaction map of DNA sites genome-wide, revealing different levels of organisation at different scales. The principles, though, which orchestrate such a complex 3D structure remain still mysterious. I will overview the scenario emerging from some classical polymer physics models of the general aspect of chromatin spatial organisation. The available experimental data, which can be rationalised in a single framework, support a picture where chromatin is a complex mixture of differently folded regions, self-organised across spatial scales according to basic physical mechanisms. I will also discuss applications to specific DNA loci, e.g. the HoxB locus, where models informed with biological details, and tested against targeted experiments, can help identifying the determinants of folding.
Continuous spatial modelling to analyse planning and economic consequences of offshore wind energy
Moeller, Bernd
2011-01-01
Offshore wind resources appear abundant, but technological, economic and planning issues significantly reduce the theoretical potential. While massive investments are anticipated and planners and developers are scouting for viable locations and consider risk and impact, few studies simultaneously address potentials and costs together with the consequences of proposed planning in an analytical and continuous manner and for larger areas at once. Consequences may be investments short of efficiency and equity, and failed planning routines. A spatial resource economic model for the Danish offshore waters is presented, used to analyse area constraints, technological risks, priorities for development and opportunity costs of maintaining competing area uses. The SCREAM-offshore wind model (Spatially Continuous Resource Economic Analysis Model) uses raster-based geographical information systems (GIS) and considers numerous geographical factors, technology and cost data as well as planning information. Novel elements are weighted visibility analysis and geographically recorded shipping movements as variable constraints. A number of scenarios have been described, which include restrictions of using offshore areas, as well as alternative uses such as conservation and tourism. The results comprise maps, tables and cost-supply curves for further resource economic assessment and policy analysis. A discussion of parameter variations exposes uncertainties of technology development, environmental protection as well as competing area uses and illustrates how such models might assist in ameliorating public planning, while procuring decision bases for the political process. The method can be adapted to different research questions, and is largely applicable in other parts of the world. - Research Highlights: → A model for the spatially continuous evaluation of offshore wind resources. → Assessment of spatial constraints, costs and resources for each location. → Planning tool for
Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations
Le, Phuong Dong; Leonard, Michael; Westra, Seth
2018-03-01
Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.
Spatial Models of Prebiotic Evolution: Soup Before Pizza?
Scheuring, István; Czárán, Tamás; Szabó, Péter; Károlyi, György; Toroczkai, Zoltán
2003-10-01
The problem of information integration and resistance to the invasion of parasitic mutants in prebiotic replicator systems is a notorious issue of research on the origin of life. Almost all theoretical studies published so far have demonstrated that some kind of spatial structure is indispensable for the persistence and/or the parasite resistance of any feasible replicator system. Based on a detailed critical survey of spatial models on prebiotic information integration, we suggest a possible scenario for replicator system evolution leading to the emergence of the first protocells capable of independent life. We show that even the spatial versions of the hypercycle model are vulnerable to selfish parasites in heterogeneous habitats. Contrary, the metabolic system remains persistent and coexistent with its parasites both on heterogeneous surfaces and in chaotically mixing flowing media. Persistent metabolic parasites can be converted to metabolic cooperators, or they can gradually obtain replicase activity. Our simulations show that, once replicase activity emerged, a gradual and simultaneous evolutionary improvement of replicase functionality (speed and fidelity) and template efficiency is possible only on a surface that constrains the mobility of macromolecule replicators. Based on the results of the models reviewed, we suggest that open chaotic flows (`soup') and surface dynamics (`pizza') both played key roles in the sequence of evolutionary events ultimately concluding in the appearance of the first living cell on Earth.
Wang, D.; Cui, Y.
2015-12-01
The objectives of this paper are to validate the applicability of a multi-band quasi-analytical algorithm (QAA) in retrieval absorption coefficients of optically active constituents in turbid coastal waters, and to further improve the model using a proposed semi-analytical model (SAA). The ap(531) and ag(531) semi-analytically derived using SAA model are quite different from the retrievals procedures of QAA model that ap(531) and ag(531) are semi-analytically derived from the empirical retrievals results of a(531) and a(551). The two models are calibrated and evaluated against datasets taken from 19 independent cruises in West Florida Shelf in 1999-2003, provided by SeaBASS. The results indicate that the SAA model produces a superior performance to QAA model in absorption retrieval. Using of the SAA model in retrieving absorption coefficients of optically active constituents from West Florida Shelf decreases the random uncertainty of estimation by >23.05% from the QAA model. This study demonstrates the potential of the SAA model in absorption coefficients of optically active constituents estimating even in turbid coastal waters. Keywords: Remote sensing; Coastal Water; Absorption Coefficient; Semi-analytical Model
An Analytics Approach to Adaptive Maturity Models using Organizational Characteristics
Baars, T.; Mijnhardt, F.; Vlaanderen, K.; Spruit, M.
2016-01-01
Ever since the first incarnations of maturity models, critics have voiced several concerns with these frameworks. Indeed, a lack of model fit and oversimplification of the real world can be attributed to the rigidity of these models, which assumes that each organization that uses the framework is
Analytical Model of Planar Double Split Ring Resonator
Zhurbenko, Vitaliy; Jensen, Thomas; Krozer, Viktor
2007-01-01
This paper focuses on accurate modelling of microstrip double split ring resonators. The impedance matrix representation for coupled lines is applied for the first time to model the SRR, resulting in excellent model accuracy over a wide frequency range. Phase compensation is implemented to take i...
An analytical model for the prediction of rip spacing in intermediate ...
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study, an analytical model was presented to predict the spacing of channel rip currents (Srip) ... beach and normal wave incidence in two cases with the fixed breaking line and variable one .... On the other hand, in the above relations radiation.
Suresh V.
2016-02-01
Full Text Available In this paper, an analytical model is proposed to predict magnetic flux leakage (MFL signals from the surface defects in ferromagnetic tubes. The analytical expression consists of elliptic integrals of first kind based on the magnetic dipole model. The radial (Bz component of leakage fields is computed from the cylindrical holes in ferromagnetic tubes. The effectiveness of the model has been studied by analyzing MFL signals as a function of the defect parameters and lift-off. The model predicted results are verified with experimental results and a good agreement is observed between the analytical and the experimental results. This analytical expression could be used for quick prediction of MFL signals and also input data for defect reconstructions in inverse MFL problem.
Analytical model of a burst assembly algorithm for the VBR in the OBS networks
Shargabi, M.A.A.; Mellah, H.; Abid, A.
2008-01-01
This paper presents a proposed analytical model for the number of bursts aggregated in a period of time in OBS networks. The model considers the case of VBR traffic with two different sending rates, which are SCR and PCR. The model is validated using extensive simulations. Where results from simulations are in total agreement with the results obtained by the proposed model. (author)
Djordjević, Tijana; Radović, Ivan; Despoja, Vito; Lyon, Keenan; Borka, Duško; Mišković, Zoran L
2018-01-01
We present an analytical modeling of the electron energy loss (EEL) spectroscopy data for free-standing graphene obtained by scanning transmission electron microscope. The probability density for energy loss of fast electrons traversing graphene under normal incidence is evaluated using an optical approximation based on the conductivity of graphene given in the local, i.e., frequency-dependent form derived by both a two-dimensional, two-fluid extended hydrodynamic (eHD) model and an ab initio method. We compare the results for the real and imaginary parts of the optical conductivity in graphene obtained by these two methods. The calculated probability density is directly compared with the EEL spectra from three independent experiments and we find very good agreement, especially in the case of the eHD model. Furthermore, we point out that the subtraction of the zero-loss peak from the experimental EEL spectra has a strong influence on the analytical model for the EEL spectroscopy data. Copyright © 2017 Elsevier B.V. All rights reserved.
Modeling spatial invasion of Ebola in West Africa.
D'Silva, Jeremy P; Eisenberg, Marisa C
2017-09-07
The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics. Copyright © 2017 Elsevier Ltd. All rights reserved.
A modal approach to modeling spatially distributed vibration energy dissipation.
Segalman, Daniel Joseph
2010-08-01
The nonlinear behavior of mechanical joints is a confounding element in modeling the dynamic response of structures. Though there has been some progress in recent years in modeling individual joints, modeling the full structure with myriad frictional interfaces has remained an obstinate challenge. A strategy is suggested for structural dynamics modeling that can account for the combined effect of interface friction distributed spatially about the structure. This approach accommodates the following observations: (1) At small to modest amplitudes, the nonlinearity of jointed structures is manifest primarily in the energy dissipation - visible as vibration damping; (2) Correspondingly, measured vibration modes do not change significantly with amplitude; and (3) Significant coupling among the modes does not appear to result at modest amplitudes. The mathematical approach presented here postulates the preservation of linear modes and invests all the nonlinearity in the evolution of the modal coordinates. The constitutive form selected is one that works well in modeling spatially discrete joints. When compared against a mathematical truth model, the distributed dissipation approximation performs well.
Lumb, Matthew P. [The George Washington University, 2121 I Street NW, Washington, DC 20037 (United States); Naval Research Laboratory, Washington, DC 20375 (United States); Steiner, Myles A.; Geisz, John F. [National Renewable Energy Laboratory, Golden, Colorado 80401 (United States); Walters, Robert J. [Naval Research Laboratory, Washington, DC 20375 (United States)
2014-11-21
The analytical drift-diffusion formalism is able to accurately simulate a wide range of solar cell architectures and was recently extended to include those with back surface reflectors. However, as solar cells approach the limits of material quality, photon recycling effects become increasingly important in predicting the behavior of these cells. In particular, the minority carrier diffusion length is significantly affected by the photon recycling, with consequences for the solar cell performance. In this paper, we outline an approach to account for photon recycling in the analytical Hovel model and compare analytical model predictions to GaAs-based experimental devices operating close to the fundamental efficiency limit.
Analytical Solution for the Anisotropic Rabi Model: Effects of Counter-Rotating Terms
Zhang, Guofeng; Zhu, Hanjie
2015-01-01
The anisotropic Rabi model, which was proposed recently, differs from the original Rabi model: the rotating and counter-rotating terms are governed by two different coupling constants. This feature allows us to vary the counter-rotating interaction independently and explore the effects of it on some quantum properties. In this paper, we eliminate the counter-rotating terms approximately and obtain the analytical energy spectrums and wavefunctions. These analytical results agree well with the ...
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Propagation dynamics for a spatially periodic integrodifference competition model
Wu, Ruiwen; Zhao, Xiao-Qiang
2018-05-01
In this paper, we study the propagation dynamics for a class of integrodifference competition models in a periodic habitat. An interesting feature of such a system is that multiple spreading speeds can be observed, which biologically means different species may have different spreading speeds. We show that the model system admits a single spreading speed, and it coincides with the minimal wave speed of the spatially periodic traveling waves. A set of sufficient conditions for linear determinacy of the spreading speed is also given.
Zhang, Zhen; Xia, Changliang; Yan, Yan; Geng, Qiang; Shi, Tingna
2017-08-01
Due to the complicated rotor structure and nonlinear saturation of rotor bridges, it is difficult to build a fast and accurate analytical field calculation model for multilayer interior permanent magnet (IPM) machines. In this paper, a hybrid analytical model suitable for the open-circuit field calculation of multilayer IPM machines is proposed by coupling the magnetic equivalent circuit (MEC) method and the subdomain technique. In the proposed analytical model, the rotor magnetic field is calculated by the MEC method based on the Kirchhoff's law, while the field in the stator slot, slot opening and air-gap is calculated by subdomain technique based on the Maxwell's equation. To solve the whole field distribution of the multilayer IPM machines, the coupled boundary conditions on the rotor surface are deduced for the coupling of the rotor MEC and the analytical field distribution of the stator slot, slot opening and air-gap. The hybrid analytical model can be used to calculate the open-circuit air-gap field distribution, back electromotive force (EMF) and cogging torque of multilayer IPM machines. Compared with finite element analysis (FEA), it has the advantages of faster modeling, less computation source occupying and shorter time consuming, and meanwhile achieves the approximate accuracy. The analytical model is helpful and applicable for the open-circuit field calculation of multilayer IPM machines with any size and pole/slot number combination.
How to get rid of W: a latent variables approach to modelling spatially lagged variables
Folmer, H.; Oud, J.
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
How to get rid of W : a latent variables approach to modelling spatially lagged variables
Folmer, Henk; Oud, Johan
2008-01-01
In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are
Hamzalouh, L.; Ismail, M. T.; Rahman, R. A.
2017-09-01
In this paper, spatial panel models were used and the method for selecting the best model amongst the spatial fixed effects model and the spatial random effects model to estimate the fitting model by using the robust Hausman test for analysis of the exports pattern of the Common Market for Eastern and Southern African (COMESA) countries. And examine the effects of the interactions of the economic statistic of explanatory variables on the exports of the COMESA. Results indicated that the spatial Durbin model with fixed effects specification should be tested and considered in most cases of this study. After that, the direct and indirect effects among COMESA regions were assessed, and the role of indirect spatial effects in estimating exports was empirically demonstrated. Regarding originality and research value, and to the best of the authors’ knowledge, this is the first attempt to examine exports between COMESA and its member countries through spatial panel models using XSMLE, which is a new command for spatial analysis using STATA.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
René Felix Reinhart
2017-02-01
Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-02-08
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-01-01
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697
Spatial stochastic regression modelling of urban land use
Arshad, S H M; Jaafar, J; Abiden, M Z Z; Latif, Z A; Rasam, A R A
2014-01-01
Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable
Spatial modeling for groundwater arsenic levels in North Carolina.
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E
2011-06-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area.
Modeling spatial processes with unknown extremal dependence class
Huser, Raphaël G.
2017-03-17
Many environmental processes exhibit weakening spatial dependence as events become more extreme. Well-known limiting models, such as max-stable or generalized Pareto processes, cannot capture this, which can lead to a preference for models that exhibit a property known as asymptotic independence. However, weakening dependence does not automatically imply asymptotic independence, and whether the process is truly asymptotically (in)dependent is usually far from clear. The distinction is key as it can have a large impact upon extrapolation, i.e., the estimated probabilities of events more extreme than those observed. In this work, we present a single spatial model that is able to capture both dependence classes in a parsimonious manner, and with a smooth transition between the two cases. The model covers a wide range of possibilities from asymptotic independence through to complete dependence, and permits weakening dependence of extremes even under asymptotic dependence. Censored likelihood-based inference for the implied copula is feasible in moderate dimensions due to closed-form margins. The model is applied to oceanographic datasets with ambiguous true limiting dependence structure.
Spatial Modeling for Groundwater Arsenic Levels in North Carolina
Kim, Dohyeong; Miranda, Marie Lynn; Tootoo, Joshua; Bradley, Phil; Gelfand, Alan E.
2013-01-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. PMID:21528844
Spatially balanced topological interaction grants optimal cohesion in flocking models.
Camperi, Marcelo; Cavagna, Andrea; Giardina, Irene; Parisi, Giorgio; Silvestri, Edmondo
2012-12-06
Models of self-propelled particles (SPPs) are an indispensable tool to investigate collective animal behaviour. Originally, SPP models were proposed with metric interactions, where each individual coordinates with neighbours within a fixed metric radius. However, recent experiments on bird flocks indicate that interactions are topological: each individual interacts with a fixed number of neighbours, irrespective of their distance. It has been argued that topological interactions are more robust than metric ones against external perturbations, a significant evolutionary advantage for systems under constant predatory pressure. Here, we test this hypothesis by comparing the stability of metric versus topological SPP models in three dimensions. We show that topological models are more stable than metric ones. We also show that a significantly better stability is achieved when neighbours are selected according to a spatially balanced topological rule, namely when interacting neighbours are evenly distributed in angle around the focal individual. Finally, we find that the minimal number of interacting neighbours needed to achieve fully stable cohesion in a spatially balanced model is compatible with the value observed in field experiments on starling flocks.
Spatial modeling for groundwater arsenic levels in North Carolina
Kim, D.; Miranda, M.L.; Tootoo, J.; Bradley, P.; Gelfand, A.E.
2011-01-01
To examine environmental and geologic determinants of arsenic in groundwater, detailed geologic data were integrated with well water arsenic concentration data and well construction data for 471 private wells in Orange County, NC, via a geographic information system. For the statistical analysis, the geologic units were simplified into four generalized categories based on rock type and interpreted mode of deposition/emplacement. The geologic transitions from rocks of a primary pyroclastic origin to rocks of volcaniclastic sedimentary origin were designated as polylines. The data were fitted to a left-censored regression model to identify key determinants of arsenic levels in groundwater. A Bayesian spatial random effects model was then developed to capture any spatial patterns in groundwater arsenic residuals into model estimation. Statistical model results indicate (1) wells close to a transition zone or fault are more likely to contain detectible arsenic; (2) welded tuffs and hydrothermal quartz bodies are associated with relatively higher groundwater arsenic concentrations and even higher for those proximal to a pluton; and (3) wells of greater depth are more likely to contain elevated arsenic. This modeling effort informs policy intervention by creating three-dimensional maps of predicted arsenic levels in groundwater for any location and depth in the area. ?? 2011 American Chemical Society.
Analytical modeling for heat transfer in sheared flows of nanofluids
Ferrari, C.; Kaoui, B.; L'vov, V.S.; Procaccia, I.; Rudenko, O.; Thije Boonkkamp, ten J.H.M.; Toschi, F.
2012-01-01
We developed a model for the enhancement of the heat flux by spherical and elongated nanoparticles in sheared laminar flows of nanofluids. Besides the heat flux carried by the nanoparticles, the model accounts for the contribution of their rotation to the heat flux inside and outside the particles.
Health promotion in context – a reflective-analytical model
Liveng, Anne; Andersen, Heidi Lene; Lehn-Christiansen, Sine
2018-01-01
model,” which is presented in this article. The model provides a framework for the analysis of health-promotion initiatives, employing eight perspectives each intertwined with the others. It is based on the assumption that health and health inequities are contextual and that the theoretically inspired...
Energy demand analytics using coupled technological and economic models
Impacts of a range of policy scenarios on end-use energy demand are examined using a coupling of MARKAL, an energy system model with extensive supply and end-use technological detail, with Inforum LIFT, a large-scale model of the us. economy with inter-industry, government, and c...
Spatial Durbin model analysis macroeconomic loss due to natural disasters
Kusrini, D. E.; Mukhtasor
2015-03-01
Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.
Spatial and spatio-temporal bayesian models with R - INLA
Blangiardo, Marta
2015-01-01
Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr
Hu, Tengfei; Mao, Jingqiao; Pan, Shunqi; Dai, Lingquan; Zhang, Peipei; Xu, Diandian; Dai, Huichao
2018-07-01
Reservoir operations significantly alter the hydrological regime of the downstream river and river-connected lake, which has far-reaching impacts on the lake ecosystem. To facilitate the management of lakes connected to regulated rivers, the following information must be provided: (1) the response of lake water levels to reservoir operation schedules in the near future and (2) the importance of different rivers in terms of affecting the water levels in different lake regions of interest. We develop an integrated modeling and analytical methodology for the water level management of such lakes. The data-driven method is used to model the lake level as it has the potential of producing quick and accurate predictions. A new genetic algorithm-based synchronized search is proposed to optimize input variable time lags and data-driven model parameters simultaneously. The methodology also involves the orthogonal design and range analysis for extracting the influence of an individual river from that of all the rivers. The integrated methodology is applied to the second largest freshwater lake in China, the Dongting Lake. The results show that: (1) the antecedent lake levels are of crucial importance for the current lake level prediction; (2) the selected river discharge time lags reflect the spatial heterogeneity of the rivers' impacts on lake level changes; (3) the predicted lake levels are in very good agreement with the observed data (RMSE ≤ 0.091 m; R2 ≥ 0.9986). This study demonstrates the practical potential of the integrated methodology, which can provide both the lake level responses to future dam releases and the relative contributions of different rivers to lake level changes.
Analytical modeling for heat transfer in sheared flows of nanofluids.
Ferrari, Claudio; Kaoui, Badr; L'vov, Victor S; Procaccia, Itamar; Rudenko, Oleksii; ten Thije Boonkkamp, J H M; Toschi, Federico
2012-07-01
We developed a model for the enhancement of the heat flux by spherical and elongated nanoparticles in sheared laminar flows of nanofluids. Besides the heat flux carried by the nanoparticles, the model accounts for the contribution of their rotation to the heat flux inside and outside the particles. The rotation of the nanoparticles has a twofold effect: it induces a fluid advection around the particle and it strongly influences the statistical distribution of particle orientations. These dynamical effects, which were not included in existing thermal models, are responsible for changing the thermal properties of flowing fluids as compared to quiescent fluids. The proposed model is strongly supported by extensive numerical simulations, demonstrating a potential increase of the heat flux far beyond the Maxwell-Garnett limit for the spherical nanoparticles. The road ahead, which should lead toward robust predictive models of heat flux enhancement, is discussed.
An analytical gate tunneling current model for MOSFETs
Kazerouni, Iman Abaspur, E-mail: imanabaspur@gmail.com; Hosseini, Seyed Ebrahim [Sabzevar Tarbiat Moallem University, Electrical and Computer Department (Iran, Islamic Republic of)
2012-03-15
Gate tunneling current of MOSFETs is an important factor in modeling ultra small devices. In this paper, gate tunneling in present-generation MOSFETs is studied. In the proposed model, we calculate the electron wave function at the semiconductor-oxide interface and inversion charge by treating the inversion layer as a potential well, including some simplifying assumptions. Then we compute the gate tunneling current using the calculated wave function. The proposed model results have an excellent agreement with experimental results in the literature.
Analytical modeling of nuclear power station operator reliability
Sabri, Z.A.; Husseiny, A.A.
1979-01-01
The operator-plant interface is a critical component of power stations which requires the formulation of mathematical models to be applied in plant reliability analysis. The human model introduced here is based on cybernetic interactions and allows for use of available data from psychological experiments, hot and cold training and normal operation. The operator model is identified and integrated in the control and protection systems. The availability and reliability are given for different segments of the operator task and for specific periods of the operator life: namely, training, operation and vigilance or near retirement periods. The results can be easily and directly incorporated in system reliability analysis. (author)
Cake filtration modeling: Analytical cake filtration model and filter medium characterization
Koch, Michael
2008-05-15
Cake filtration is a unit operation to separate solids from fluids in industrial processes. The build up of a filter cake is usually accompanied with a decrease in overall permeability over the filter leading to an increased pressure drop over the filter. For an incompressible filter cake that builds up on a homogeneous filter cloth, a linear pressure drop profile over time is expected for a constant fluid volume flow. However, experiments show curved pressure drop profiles, which are also attributed to inhomogeneities of the filter (filter medium and/or residual filter cake). In this work, a mathematical filter model is developed to describe the relationship between time and overall permeability. The model considers a filter with an inhomogeneous permeability and accounts for fluid mechanics by a one-dimensional formulation of Darcy's law and for the cake build up by solid continuity. The model can be solved analytically in the time domain. The analytic solution allows for the unambiguous inversion of the model to determine the inhomogeneous permeability from the time resolved overall permeability, e.g. pressure drop measurements. An error estimation of the method is provided by rewriting the model as convolution transformation. This method is applied to simulated and experimental pressure drop data of gas filters with textile filter cloths and various situations with non-uniform flow situations in practical problems are explored. A routine is developed to generate characteristic filter cycles from semi-continuous filter plant operation. The model is modified to investigate the impact of non-uniform dust concentrations. (author). 34 refs., 40 figs., 1 tab
Bosu, S.; Robinson, D.; Saha, A.
2017-12-01
Tectonic models developed from the Himalayan thrust belt constitute three models- critical taper, channel flow and wedge extrusion. Their differences are manifested in predicted minimum shortening, deformation propagation style and tectonic architecture across the thrust belt. Recent studies from isolated synformal klippen composed of Greater and Tethyan Himalayan rock within the Himalayan thrust belt disagree over the tectonic history, especially in the Almora-Dadeldhura klippe, which is the largest klippe in the thrust belt. These recent studies are limited to one transect each, and two or fewer types of analytical data to justify their models. Due to the limited spatial coverage, these studies often reflect a narrow perspective in their tectonic models; thus, combining the data from these studies provides a holistic view of the regional tectonic history. This study compiled the available data across the 350 km wide Almora-Dadeldhura klippe, using petrology, stratigraphy, metamorphic history, microstructure, U-Pb ages of intrusive granite, monazite and muscovite ages of the shear zones, and exhumation ages from apatite fission track, along with original field observations, microstructure and microtexture data from 5 different transects in northwest India and far western Nepal. The review of the compiled data suggests that the Himalayan thrust belt in northwest India and far western Nepal is a forward propagating thrust system, and that the analytical data support the critical taper model.
Family Environment and Cognitive Development: Twelve Analytic Models
Walberg, Herbert J.; Marjoribanks, Kevin
1976-01-01
The review indicates that refined measures of the family environment and the use of complex statistical models increase the understanding of the relationships between socioeconomic status, sibling variables, family environment, and cognitive development. (RC)
Kerst, Stijn; Shyrokau, Barys; Holweg, Edward
2018-05-01
This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.
Advanced Video Activity Analytics (AVAA): Human Performance Model Report
2017-12-01
effectively. The goal of the modeling effort is to provide an understanding of the current state of the system with respect to the impact on human ...representation of the human ‒ machine system. Third, task network modeling is relatively easy to use and understand . Lastly, it is more cost effective and can...and communication issues. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 2006;48(2):2396–2400. Reid GB, Colle HA
Human performance modeling for system of systems analytics :soldier fatigue.
Lawton, Craig R.; Campbell, James E.; Miller, Dwight Peter
2005-10-01
The military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives as can be seen in the Department of Defense's (DoD) Defense Modeling and Simulation Office's (DMSO) Master Plan (DoD 5000.59-P 1995). To this goal, the military is currently spending millions of dollars on programs devoted to HPM in various military contexts. Examples include the Human Performance Modeling Integration (HPMI) program within the Air Force Research Laboratory, which focuses on integrating HPMs with constructive models of systems (e.g. cockpit simulations) and the Navy's Human Performance Center (HPC) established in September 2003. Nearly all of these initiatives focus on the interface between humans and a single system. This is insufficient in the era of highly complex network centric SoS. This report presents research and development in the area of HPM in a system-of-systems (SoS). Specifically, this report addresses modeling soldier fatigue and the potential impacts soldier fatigue can have on SoS performance.
The role of analytical models: Issues and frontiers
Blair, P.
1991-03-01
A number of modeling attempts to analyze the implications of increasing competition in the electric power industry appeared in the early 1970s and occasionally throughout the early 1980s. Most of these of these analyses, however, considered only modest mechanisms to facilitate increased bulk power transactions between utility systems. More fundamental changes in market structure, such as the existence of independent power producers or wheeling transactions between customers and utility producers, were not considered. More recently in the course of the policy debate over increasing competition, a number of models have been used to analyze altemative scenarios of industry structure and regulation. In this Energy Modeling Forum (EMF) exercise, we attempted to challenge existing modeling frameworks beyond their original design capabilities. We tried to interpret altemative scenarios or other means of increasing competition in the electric power industry in the terms of existing modeling frameworks, to gain perspective using such models on how the different market players would interact, and to predict how electricity prices and other indicators of industry behavior might evolve under the altemative scenarios.
The role of analytical models: Issues and frontiers
Blair, P.
1991-03-01
A number of modeling attempts to analyze the implications of increasing competition in the electric power industry appeared in the early 1970s and occasionally throughout the early 1980s. Most of these of these analyses, however, considered only modest mechanisms to facilitate increased bulk power transactions between utility systems. More fundamental changes in market structure, such as the existence of independent power producers or wheeling transactions between customers and utility producers, were not considered. More recently in the course of the policy debate over increasing competition, a number of models have been used to analyze altemative scenarios of industry structure and regulation. In this Energy Modeling Forum (EMF) exercise, we attempted to challenge existing modeling frameworks beyond their original design capabilities. We tried to interpret altemative scenarios or other means of increasing competition in the electric power industry in the terms of existing modeling frameworks, to gain perspective using such models on how the different market players would interact, and to predict how electricity prices and other indicators of industry behavior might evolve under the altemative scenarios
Analytical models approximating individual processes: a validation method.
Favier, C; Degallier, N; Menkès, C E
2010-12-01
Upscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. The validity of such approximations is generally tested only on a limited range of parameter sets. A more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. This method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. As a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models. Copyright © 2010 Elsevier Inc. All rights reserved.
Whittington, Jesse; Sawaya, Michael A
2015-01-01
Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071) for females, 0.844 (0.703-0.975) for males, and 0.882 (0.779-0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024) for females, 0.825 (0.700-0.948) for males, and 0.863 (0.771-0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth