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A Methodology to Model the Statistical Fracture Behavior of Acrylic Glasses for Stochastic Simulation

A statistical modelling method for simulating the fracture behaviour of acrylic glass is presented using the application case of an;

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Discrete Fracture Network Modeling of Hydraulic Stimulation

-mode stimulation. A variety of novel techniques to ensure efficiency and realistic model behavior are implemented, and tested. The simulation;

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Applied Stochastic Hydrogeology

of research that developed considerably over the last 20 years. Applied Stochastic Hydrogeology is a book that allows newcomers to the field an easy;

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Stochastic Optimization with Simulation Based Optimization

simulation is widely applicable. This work extends the traditional response surface methodology into a surrogate model framework to address high;

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Revival: Simulation Methodology for Statisticians, Operations Analysts, and Engineers (1988)

of statistical methods based on graphical techniques and exploratory data is among the highlights of Simulation Methodology for Statisticians, Operations;

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Simulation Methodology for Statisticians, Operations Analysts, and Engineers (1988)

of statistical methods based on graphical techniques and exploratory data is among the highlights of Simulation Methodology for Statisticians, Operations;

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Physical Aspects of Fracture

fracture. It is no longer unrealistic to imagine that a crack initiated through a molecular dynamics description could be propagated at the grain;

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Simulation and Chaotic Behavior of Alpha-stable Stochastic Processes

Presents new computer methods in approximation, simulation, and visualization for a host of alpha-stable stochastic processes.;

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Simulation and Chaotic Behavior of Alpha-stable Stochastic Processes

Presents new computer methods in approximation, simulation, and visualization for a host of alpha-stable stochastic processes.;

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Complex Stochastic Systems

Complex stochastic systems comprises a vast area of research, from modelling specific applications to model fitting, estimation procedures;

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Complex Stochastic Systems

Complex stochastic systems comprises a vast area of research, from modelling specific applications to model fitting, estimation procedures;

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An Introduction to Metallic Glasses and Amorphous Metals

An Introduction to Metallic Glasses and Amorphous Metals gives a background on the physics of materials, describing relevant;

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Simulation and Robust Statistics

methods. In order to facilitate the implementation of simulation experiments, a general software framework for statistical simulation has been;

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Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering

The use of simulation plays a vital part in developing an integrated approach to process design. By helping save time and money before the;

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Process Modelling and Simulation in Chemical, Biochemical and Environmental Engineering

The use of simulation plays a vital part in developing an integrated approach to process design. By helping save time and money before the;

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Foundations and Methods of Stochastic Simulation

language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers;

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Foundations and Methods of Stochastic Simulation

language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers;

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Temperature-dependent Deformation and Fracture Behavior of a Talcum-filled Co-polymer

and fracture behavior of thermoplastic polymers. The model bases on three supporting ambient temperatures, where a thermoplastic polymer has;

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Simulation and Inference for Stochastic Processes with Yuima: A Comprehensive R Framework for Sdes and Other Stochastic Processes

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic;

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Probability

it within a framework for creating models of random phenomena. The author focuses on the synthesis of stochastic models concurrent with the;

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Bayesian Model Selection and Statistical Modeling

, and provides R code for implementation. The author shows how to implement a variety of Bayesian inference using R and sampling methods;

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Modeling and Simulation

aspects of stochastic simulation and statistical reliability. NEW TO THE SECOND EDITION: Chapters on Random Variables Special probability;

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Flowgraph Models For Multistate Time-To-Event Data

A unique introduction to the innovative methodology of statistical flowgraphs This book offers a practical, application--based approach to;

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Mathematical and Statistical Estimation Approaches in Epidemiology

stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions;

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Embedded Discrete Fracture Modeling and Application in Reservoir Simulation

complex fracture geometries can be modelled efficiently and effectively. This volume presents a conventional numerical model to handle;

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Stochastic Simulation Optimization

of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a;

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Analytically Tractable Stochastic Stock Price Models

. In a stock price model with stochastic volatility, the random behavior of the volatility is described by a stochastic process. For instance;

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