Simulation Output Data Research Articles

Robust simulation of water atomization

This paper describes a methodology for prediction of powder packing densities which employs a new approach, designated as random sphere construction (RSC), for modelling the shape of irregular particles such as those produced by water atomization of iron. The approach involves modelling an irregular particle as a sphere which incorporates smaller corner spheres located randomly at its surface. The RSC modelling technique has been combined with a previously developed particle packing algorithm (the random build algorithm), to provide a computer simulation of irregular particle packings. Analysis of the simulation output data has allowed relationships to be established between the particle modelling parameters employed by the RSC algorithm, and the density of the simulated packings. One such parameter is η, which is the number of corner spheres per particle. A relationship was established between η (which was found to have a profound influence on packing density), and the fractional density of the packing, fd. Vision system techniques were used to measure the irregularity of the simulated particles, and this was also related to η. These two relationships were then combined to provide a plot of fractional density for a simulated packing against irregularity of the simulated particles. A comparison was made of these simulated packing densities and observed particle packing densities for irregular particles, and a correlation coefficient of 0.96 was obtained. This relatively good correlation indicates that the models developed are able to realistically simulate packing densities for irregular particles. There are a considerable number of potential applications for such a model in powder metallurgy (PM), process control. In combination with on-line particle image analysis, the model could be used to automatically predict powder densities from particle morphology.

Star formation losses due to tidal debris in "hierarchical" galaxy formation

Bottom-up hierarchical formation of dark matter haloes is not as monotonic as implicitly assumed in the Press-Schechter formalism: matter can be ejected into tidal tails, shells or low density `atmospheres'. The implications that the possible truncation of star formation in these tidal `debris' may have for observational galaxy statistics are examined here using the ArFus N-body plus semi-analytical galaxy modelling software. Upper and lower bounds on stellar losses implied by a given set of N-body simulation output data can be investigated by choice of the merging/identity criterion of haloes between successive N-body simulation output times. A median merging/identity criterion is defined and used to deduce an upper estimate of possible star formation and stellar population losses. A largest successor merging/identity criterion is defined to deduce an estimate which minimises stellar losses. In the N-body simulations studied, the debris losses are short range in length and temporary; maximum loss is around 16%. The induced losses for star formation and luminosity functions are strongest (losses of 10%-30%) for low luminosity galaxies and at intermediate redshifts (1 < z < 3). This upper bound on likely losses is smaller than present observational uncertainties. Hence, Press-Schechter based galaxy formation models are approximately valid despite ignoring loss of debris, provided that dwarf galaxy statistics are not under study.

Validation of High-Fidelity Traffic Simulation Models

A multistage validation framework that accounts for the realistic nature of traffic simulation output data is proposed. The framework consists of conceptual validation and operational validation. The operational validation comprises a qualitative approach, which involves static and animated Turing tests, and a quantitative approach, which involves three levels of statistical tests. Particularly in the third-level statistical test, the autocorrelation and nonstationary nature of traffic simulation output data is emphasized, its implications on validation methods are explored, and a univariate nonseasonal autoregressive-integrated-moving-average (ARIMA) modeling approach is proposed. Finally, numerical results for an actual freeway network are presented. The validation results illustrate that the proposed multistage validation procedure can account for the complexity of the validation task and its conclusions.

Analyzing Web-based simulation data

The article deals only with simulation models that have stochastic, or random input. Classical statistical methods for independent observations assume that each observation carries the maximum information, and therefore they compute the smallest confidence interval. Since stationary simulation output data carries less information, the confidence interval resulting from applying classical statistical computations using autocorrelated observations would be too small. This would lead one to conclude the parameter estimate is much more precise than is actually the case. To get around this problem, several methods have been suggested in the output data analysis literature. Two of the most widely accepted methods are: 1) the method of independent replications; and 2) the method of batch means. Both methods try to avoid autocorrelation by breaking the data into "independent" segments. The sample means of these segments are considered i.i.d, and used to calculate confidence intervals. In the first method, several independent runs are executed. In the second method, a long simulation run is executed and divided into several "nearly uncorrelated" batches. The article specifically examines the Java Simulation (JSIM) Web based environment which has evolved to incorporate component based technology. If component based technology succeeds, the long hoped for gains in software development productivity may finally be realized.

Automating parallel simulation using parallel time streams

This paper describes a package for parallel steady-state stochastic simulation that was designed to overcome problems caused by long simulation times experienced in our ongoing research in performance evaluation of high-speed and integrated-services communication networks, while maintaining basic statistical rigors of proper analysis of simulation output data. The package, named AKAROA, accepts ordinary (nonparallel) simulation programs, and alll further stages of stochastic simulation should be transparent for users. The package employs a new method of sequential estimation for the Multiple-Replications-in-Parallel scenario. All basic functions, including the transformation of originally nonparallel simulators into ones suitable for parallel execution, control of the precision of estimates, and stopping of parallel simulation processes when the required precision of the overall steady-state estimates is achieved, are automated. The package can be used on multiprocessor systems and/or heterogeneous computer networks, involving an arbitrary number of processors. The design issues, architecture, and implementation of AKAROA, as well as the results of its preliminary performance studies are presented

Modeling and control of a continuous crystallization process Part 1. Linear and non-linear modeling

Single-input–single-output (SISO) and multi-input–single-output (MISO) models of a cooling crystallization process are developed using time series and neural network approaches. The process description is simulated using first principles including the population balance to describe the crystal size distribution. The process model is identified from the input–output data of the process simulation using either a linear ARX model or a non-linear model constructed using a recurrent or a feedforward neural network.

Comparison of Speed-Acceleration Profiles from Field Data with NETSIM Output for Modal Air Quality Analysis of Signalized Intersections

New vehicle modal emissions rate models will assess emissions as a function of specific operating mode or engine load surrogates. These new models require that vehicle activity be input by fraction of time spent in different operating modes. However, the ability to realistically model onroad modal vehicle activity currently limits the implementation of these models. Few data on how vehicles operate in a real-world setting exist. Simulation models offer attractive advantages for modal modeling. They are readily available and generally can be used with both simple and detailed data input. Simulation models were developed to model the impacts of signal timing, incidents, or design features on traffic flow and perform well for these applications. However, simulation models, such as CORSIM, use theoretical profiles of vehicle acceleration and speed relationships that have not been validated in the field. To determine the feasibility of using simulation models to predict on-road speedacceleration profiles and to identify potential problems in their use as such, a study intersection was modeled in NETSIM, and the simulation output was compared with data collected from field studies of signalized intersections. Analyses of the simulation output and field data indicate that NETSIM does not adequately simulate instantaneous modal vehicle activity. NETSIM intersection activity shows higher fractions of hard accelerations [≥ 9.7+ km/h/s (6 mph/s)] than are demonstrated by field data for the study intersection. For midblock, the results indicate that field data demonstrate a much greater distribution of speeds and accelerations than the distribution modeled by NETSIM.

Coverage of confidence intervals in sequential steady-state simulation

Stochastic discrete-event simulation has become one of the most-used tools for performance evaluation in science and engineering. But no innovation can replace the responsibility of simulators for obtaining credible results from their simulation experiments. In this paper we address the problem of the statistical correctness of simulation output data analysis, in the context of sequential steady-state stochastic simulation, conducted for studying long run behavior of stable systems. Such simulations are stopped as soon as the relative precision of estimates, defined as the relative half-width of confidence intervals at a specified confidence level, reaches the required level. We formulate basic rules for the proper experimental analysis of the coverage of steady-state interval estimators. Our main argument is that such an analysis should be done sequentially. The numerical results of our coverage analysis of the method of non-overlapping batch means and spectral analysis are presented, and compared with those obtained by the traditional, non-sequential approach. Two scenarios for stochastic simulation are considered: traditional sequential simulation on a single processor, and fast concurrent simulation based on multiple replications in parallel (MRIP), with multiple processors cooperating in the production of output data.

Computer simulation of morphology and packing behaviour of irregular particles, for predicting apparent powder densities

This paper describes a methodology for prediction of powder packing densities which employs a new approach, designated as random sphere construction (RSC), for modelling the shape of irregular particles such as those produced by water atomization of iron. The approach involves modelling an irregular particle as a sphere which incorporates smaller corner spheres located randomly at its surface. The RSC modelling technique has been combined with a previously developed particle packing algorithm (the random build algorithm), to provide a computer simulation of irregular particle packings. Analysis of the simulation output data has allowed relationships to be established between the particle modelling parameters employed by the RSC algorithm, and the density of the simulated packings. One such parameter is η, which is the number of corner spheres per particle. A relationship was established between η (which was found to have a profound influence on packing density), and the fractional density of the packing, fd. Vision system techniques were used to measure the irregularity of the simulated particles, and this was also related to η. These two relationships were then combined to provide a plot of fractional density for a simulated packing against irregularity of the simulated particles. A comparison was made of these simulated packing densities and observed particle packing densities for irregular particles, and a correlation coefficient of 0.96 was obtained. This relatively good correlation indicates that the models developed are able to realistically simulate packing densities for irregular particles. There are a considerable number of potential applications for such a model in powder metallurgy (PM), process control. In combination with on-line particle image analysis, the model could be used to automatically predict powder densities from particle morphology.

Quantitative stochastic simulation of telecommunication networks in DESC+ +

DESC+ + (Discrete Event Simulation package using C+ +) has been developed as an object-oriented tool for quantitative simulation studies of communication protocols and architectures of telecommunication networks. The main issue of such performance studies is to secure proper statistical accuracy of the final simulation results. In DESC+ + this problem has been solved by automating analysis of simulation output data, aimed at stopping simulation when the estimates reach the required level of precision. The package consists of various object classes. While some of them are responsible for on-line output data analysis, others allow simulation programs of telecommunication networks to be easily developed by re-using existing (sub)models. We discuss main design and implementational issues of DESC+ +, and illustrate them by an example.

Visualization of Reservoir Simulation Data With an Immersive Virtual Reality System

Summary This paper discusses an investigation into the use of an immersive virtual reality (VR) system to visualize reservoir simulation output data. The hardware and software configurations of the test-immersive VR system are described and compared to a nonimmersive VR system and to an existing workstation screen-based visualization system. The structure of 3D reservoir simulation data and the actions to be performed on the data within the VR system are discussed. The subjective results of the investigation are then presented, followed by a discussion of possible future work.

Validating models of complex, stochastic, biological systems

The highly variable nature of many biological entities, particularly those occurring in natural ecosystems, makes the validation of models and simulations extremely important. Valuable tools such as simulations should not be discounted simply because of a lack of cookbook validation procedures. This paper considers the process of validation as it relates to complex biological systems, and examines some methods to compare the inherently multivariate values required to characterise biological entities. A model of Pinus radiata root system morphology is used as a case study. It is concluded that, while time consuming, development of system-specific objective indices may often be the most useful way to compare simulation output and field data when complex biological entities are modelled.

THE USE OF A DISCRETE-EVENT SIMULATION MODEL WITH ERLANG PROBABILITY DISTRIBUTIONS IN THE ESTIMATION OF EARTHMOVING PRODUCTION

Abstract Earthmoving operations are a major part of many civil engineering works and as such they present an ideal opportunity for improved estimation forecasts and efficiency. This paper presents a computer simulation model which is based on the assumption that an earthmoving cycle can be broken down into its component parts which can be represented by Erlang probability distributions. Such a distribution can be generated on a computer and incorporated into a discrete-event simulation program. The development of the model and of a program to carry out simulation runs is described. The importance of model validity is discussed; results from a simulation cannot be relied upon if the model does not actually agree with the real system. The results of a validation exercise are shown which compares system output data (obtained from actual contracts in the UK) and model output data. Simulation output data is also shown in a graphical form which is intended to ease the use of the model on a site basis.

Comparison of NETSIM, NETFLO I, and NETFLO II Traffic Simulation Models for Fixed-Time Signal Control

This paper documents a comparative analysis of the NETSIM, NETFLO I, and NETFLO II traffic simulation models when simulating traffic networks with fixed-time signal control. The objective was to find out whether the results of simulating the same traffic network with the three models were compatible. The three models employ different approaches to simulate traffic flow on urban street networks. Four different scenarios with varying network configurations and intersection geometries were simulated for three volume levels. The average speed and delay measures of effectiveness generated by the three models were compared for each scenario. Analysis of variance techniques were used for statistical analyses of the simulation output data. The execution speeds of the models were also compared. The quickness of simulation will be very important in the ITS applications, real-time traffic adaptive systems, and so forth. The results of this study indicated that the estimated measures of effectiveness from the three m...

Comparison of NETSIM, NETFLO I, and NETFLO II Traffic Simulation Models for Fixed-Time Signal Control

This paper documents a comparative analysis of the NETSIM, NETFLO I, and NETFLO II traffic simulation models when simulating traffic networks with fixed-time signal control. The objective was to find out whether the results of simulating the same traffic network with the three models were compatible. The three models employ different approaches to simulate traffic flow on urban street networks. Four different scenarios with varying network configurations and intersection geometries were simulated for three volume levels. The average speed and delay measures of effectiveness generated by the three models were compared for each scenario. Analysis of variance techniques were used for statistical analyses of the simulation output data. The execution speeds of the models were also compared. The quickness of simulation will be very important in the ITS applications, real-time traffic adaptive systems, and so forth. The results of this study indicated that the estimated measures of effectiveness from the three models were statistically significantly different at each level of comparison. The speed values generated by NETSIM were found to be the lowest; NETFLO II values were highest. NETFLO I values in all cases were between NETFLO II and NETSIM values. In most cases, NETFLO I values were closer to NETFLO II than to NETSIM values. Identical results were obtained from the analysis of delay values, with NETSIM delay estimates always being highest and NETFLO II values lowest. The program execution time for NETSIM and NETFLO I increased significantly as the volume level increased, whereas it practically did not change for NETFLO II. The execution times for NETSIM were found to be about 20 to 45 times higher than for NETFLO II. Even NETFLO I was found to be about 5 to 10 times faster than NETSIM.

Analyzing Simulation Output Using the Bootstrap Method

There are many situations in which parametric statistical techniques are less than ideal for evaluating a simulated system. For most simulation output, one must rely heavily on the central limit theorein in order to apply parametric statistical techniques. The bootstrap statistic is a nonparametric sample-resample technique that makes no distributional assumptions and may be used for estimation and hypothesis testing. The authors propose the bootstrap as a valuable tool for the analysis of simulation output data since it can be used in situations in which either the distribution is not known or normal approximations are inappropriate. Furthermore, since bootstrapping is itself a simulation technique it is inherently satisfying as a tool for the analysis of simulation output data. Illustrations are presented.

Perturbation method for sinusoidally excited FDTD analysis

A method for perturbing a sinusoidally excited FDTD simulation is introduced. In this scheme, desired simulation output data is read after the first steady state is reached. Simulated structure is altered slightly as the simulation runs, and thus a perturbation is created into the steady state. A new steady state emerges faster than the initial one and computational efficiency is gained. The new steady state can be perturbed again with similar efficiency. The method is applicable for fast optimization of various microwave applications in FDTD analysis.

Initial transient detection in simulations using the second-order cumulant spectrum

Procedures for detecting an initial transient in simulation output data are developed. The tests use the second-order cumulant spectrum which differs from the power spectrum in that the stationarity constraint is not required for the former. The second-order cumulant spectrum can be interpreted as the nonstationary power spectrum and is an orthogonal decomposition of the variance of a nonstationary process. The null hypothesis is that the simulation output data series is a covariance stationary process. Equivalently, all estimates of the second-order cumulant spectrum in the region which excludes the estimates of the power spectrum will have an expected value of zero. The test procedures are designed to detect initialization bias in the estimation of the mean and the variance. These procedures can be extended to detect bias in the moments of cumulants of ordern, wheren>2. Results are presented from the application of the test to simulated processes with superimposed mean and variance transients and anM/M/1 queue example.

Evaluating alternative system configurations using simulation: A nonparametric approach

The real utility of simulation lies in comparing different alternatives that might represent competing system designs. Conventional statistical techniques are not directly applicable to the analysis of simulation output data in the evaluation of competing alternatives since the usual assumptions of normality and common variance are difficult to justify in simulation experiments. This paper revisits a known nonparametric test whose application has recently become feasible due to considerable increases in computing power:randomization tests assess the significance of the observed value of the test statistic by evaluating different permutations of the data. The procedure only requires invariance of the data under all permutations.

Finite‐Element Modeling of Storm Water Runoff Using GRASS GIS

Abstract: This paper presents methodologies used in the model r.water.fea for simulating storm water runoff using the finite‐element method and a raster geographic information system (GIS). The internally integrated model r.water.fea simulates storm water runoff by interfacing the raster data structure with the finite‐element solution of the kinematic wave equations. The integrated system offers many advantages because the GIS and simulation model exchange input and output data internally. Distributed simulation of the spatially and temporally variable hydrologic process is possible with r.water.fea. Storm water runoff simulated with r.water.fea compares favorably with analytic solutions for a simple domain. An example simulation of a catchment demonstrates the capabilities of r.water.fea.