Topic
Modeling and simulation
About: Modeling and simulation is a research topic. Over the lifetime, 10273 publications have been published within this topic receiving 111550 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, the authors present models for 5-axis milling process geometry, cutting force and stability, and apply the models in selection of important parameters for the selection of part quality and productivity.
134 citations
07 Dec 2003
TL;DR: In this paper, the authors propose a framework for integration of modeling, simulation, and visualization tools for emergency response, which will significantly improve the nation's capability in the emergency response area.
Abstract: A number of modeling and simulation tools have been developed and more are being developed for emergency response applications. The available simulation tools are meant mostly for standalone use. Addressing an emergency incident requires addressing multiple interdependent aspects of the situation. The simulation tools addressing different aspects of an emergency situation need to be integrated to provide the whole picture to planners, trainers, and responders. A framework is required to ensure that modeling and simulation tools can be systematically integrated together to address the overall response. This paper proposes a framework for integration of modeling, simulation, and visualization tools for emergency response. The development and implementation of the proposed framework will significantly improve the nation's capability in the emergency response area.
134 citations
Book•
14 Jul 2014
TL;DR: This book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods, and demonstrates the rigorous representation of the models and theoretical properties of the methods.
Abstract: Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects Models:
Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time.
Easy-to-Use Techniques and Tools for Real-World Data Modeling:
The book first shows how the framework allows model representation for different data types, including continuous, categorical, count, and time-to-event data. This leads to the use of generic methods, such as the stochastic approximation of the EM algorithm (SAEM), for modeling these diverse data types. The book also covers other essential methods, including Markov chain Monte Carlo (MCMC) and importance sampling techniques. The author uses publicly available software tools to illustrate modeling tasks. Methods are implemented in Monolix, and models are visually explored using Mlxplore and simulated using Simulx.
Careful Balance of Mathematical Representation and Practical Implementation:
This book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. Statisticians and mathematicians will appreciate the rigorous representation of the models and theoretical properties of the methods while modelers will welcome the practical capabilities of the tools. The book is also useful for training and teaching in any field where population modeling occurs.
134 citations
TL;DR: The Galerkin h-p method as discussed by the authors is based on a generalized finite-element scheme with self-adaptive grid-and order construction and is connected to a time discretization of Rothe's type.
132 citations
TL;DR: The results of this study indicate hybrid simulation and digital twin as the primary simulation-based approaches in the context of Industry 4.0 and a cross-analysis of concepts and evaluation of models’ development suggest that simulation can capture the design principles of Industry 5.0.
130 citations