Development and use of a computer simulation model for the evaluation of design and control alternatives for intersections of minor roads with multi-lane rural highways: model application. Interim report.

Federal Highway Administration, Washington, D.C.

Development and use of a computer simulation model for the evaluation of design and control alternatives for intersections of minor roads with multi-lane rural highways: selection of the simulation model. Interim report.

Federal Highway Administration, Washington, D.C.

NETGRAF: a computer graphics aid to the operation and interpretation of NETSIM, a traffic simulation model. Part 1: overview and experimental results. Final report.

Transportation Department, Office of University Research, Washington, D.C.

NETGRAF: a computer graphics aid to the operation and interpretation of NETSIM, a traffic simulation model. Part 3: programmer's guide.

Transportation Department, Office of University Research, Washington, D.C.

Prediction of wave refraction and shoaling using two numerical models /

"August 1981."

Hydrologic simulation on solid waste disposal sites (HSSWDS) /

"SW-868"--Cover.

Reducing errors in simulated satellite views of clouds from large-scale models

Thesis (Ph.D.)--University of Washington, 2016-06

Testing Independence in High Dimensions & Identifiability of Graphical Models

Thesis (Ph.D.)--University of Washington, 2016-06

Molecular dynamics simulation of organic-inorganic nanocomposites: Layering behavior and interlayer structure of organoclays

Isothermal-isobaric (NPT) molecular dynamics simulation has been performed to investigate the layering behavior and structure of nanoconfined quaternary alkylammoniums in organoclays. This work is focused on systems consisting of two clay layers and a number of alkylammoniums, and involves the use of modified Dreiding force field. The simulated basal spacings of organoclays agree satisfactorily with the experimental results in the literature. The atomic density profiles in the direction normal to the clay surface indicate that the alkyl chains within the interlayer space of montmorillonite exhibit an obvious layering behavior. The headgroups of long alkyl chains are distributed within two layers close to the clay surface, whereas the distributions of methyl and methylene groups are strongly dependent on the alkyl chain length and clay layer charge. Monolayer, bilayer, and pseudo-trilayer structures are found in organoclays modified with single long alkyl chains, which are identical to the structural models based on the measured basal spacings. A pseudo-quadrilayer structure, for the first time to our knowledge, is also identified in organoclays with double long alkyl chains. In the mixture structure of paraffin-type and multilayer, alkyl chains do not lie flat within a single layer but interlace, and also jump to the next layer in pseudo-trilayer as well as next nearest layer in pseudo-quadrilayer.

Simulation modelling applied to runoff modelling using mapscript

Dynamic spatial analysis addresses computational aspects of space–time processing. This paper describes the development of a spatial analysis tool and modelling framework that together offer a solution for simulating landscape processes. A better approach to integrating landscape spatial analysis with Geographical Information Systems is advocated in this paper. Enhancements include special spatial operators and map algebra language constructs to handle dispersal and advective flows over landscape surfaces. These functional components to landscape modelling are developed in a modular way and are linked together in a modelling framework that performs dynamic simulation. The concepts and modelling framework are demonstrated using a hydrological modelling example. The approach provides a modelling environment for scientists and land resource managers to write and to visualize spatial process models with ease.

The transform likelihood ratio method for rare event simulation with heavy tails

We present a novel method, called the transform likelihood ratio (TLR) method, for estimation of rare event probabilities with heavy-tailed distributions. Via a simple transformation ( change of variables) technique the TLR method reduces the original rare event probability estimation with heavy tail distributions to an equivalent one with light tail distributions. Once this transformation has been established we estimate the rare event probability via importance sampling, using the classical exponential change of measure or the standard likelihood ratio change of measure. In the latter case the importance sampling distribution is chosen from the same parametric family as the transformed distribution. We estimate the optimal parameter vector of the importance sampling distribution using the cross-entropy method. We prove the polynomial complexity of the TLR method for certain heavy-tailed models and demonstrate numerically its high efficiency for various heavy-tailed models previously thought to be intractable. We also show that the TLR method can be viewed as a universal tool in the sense that not only it provides a unified view for heavy-tailed simulation but also can be efficiently used in simulation with light-tailed distributions. We present extensive simulation results which support the efficiency of the TLR method.

Two empirical hydrocyclone models revisited

There has been an abundance of literature on the modelling of hydrocyclones over the past 30 years. However, in the comminution area at least, the more popular commercially available packages (e.g. JKSimMet, Limn, MODSIM) use the models developed by Nageswararao and Plitt in the 1970s, either as published at that time, or with minor modification. With the benefit of 30 years of hindsight, this paper discusses the assumptions and approximations used in developing these models. Differences in model structure and the choice of dependent and independent variables are also considered. Redundancies are highlighted and an assessment made of the general applicability of each of the models, their limitations and the sources of error in their model predictions. This paper provides the latest version of the Nageswararao model based on the above analysis, in a form that can readily be implemented in any suitable programming language, or within a spreadsheet. The Plitt model is also presented in similar form. (C) 2004 Elsevier Ltd. All rights reserved.

Large-eddy simulation of heat transfer downstream of a backward-facing step

Large-eddy simulation is used to predict heat transfer in the separated and reattached flow regions downstream of a backward-facing step. Simulations were carried out at a Reynolds number of 28 000 (based on the step height and the upstream centreline velocity) with a channel expansion ratio of 1.25. The Prandtl number was 0.71. Two subgrid-scale models were tested, namely the dynamic eddy-viscosity, eddy-diffusivity model and the dynamic mixed model. Both models showed good overall agreement with available experimental data. The simulations indicated that the peak in heat-transfer coefficient occurs slightly upstream of the mean reattachment location, in agreement with experimental data. The results of these simulations have been analysed to discover the mechanisms that cause this phenomenon. The peak in heat-transfer coefficient shows a direct correlation with the peak in wall shear-stress fluctuations. It is conjectured that the peak in these fluctuations is caused by an impingement mechanism, in which large eddies, originating in the shear layer, impact the wall just upstream of the mean reattachment location. These eddies cause a 'downwash', which increases the local heat-transfer coefficient by bringing cold fluid from above the shear layer towards the wall.

Forecasting with serially correlated regression models

In this article we investigate the asymptotic and finite-sample properties of predictors of regression models with autocorrelated errors. We prove new theorems associated with the predictive efficiency of generalized least squares (GLS) and incorrectly structured GLS predictors. We also establish the form associated with their predictive mean squared errors as well as the magnitude of these errors relative to each other and to those generated from the ordinary least squares (OLS) predictor. A large simulation study is used to evaluate the finite-sample performance of forecasts generated from models using different corrections for the serial correlation.

The specification of vector autoregressive moving average models

In this paper we propose a new identification method based on the residual white noise autoregressive criterion (Pukkila et al. , 1990) to select the order of VARMA structures. Results from extensive simulation experiments based on different model structures with varying number of observations and number of component series are used to demonstrate the performance of this new procedure. We also use economic and business data to compare the model structures selected by this order selection method with those identified in other published studies.