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About 10,000 papers for “simulation experiments”

Simulation experiments.

Yaai Dang (558235), Wei Ren (267391), Bo Tao (558236) et al. · Figshare · 2015

<p>Notes: Climate-LCLUC means the combination effects of climate and LCLUC. Others include the effects of atmospheric CO<sub>2</sub>, ozone pollution (AOT 40 index), nitrogen deposition, nitrogen fertilizer application, etc. All means the simulation experiment which includes all above environmental factors.</p>

Cited by 0Open access

Simulation Experiments

Didier Cossin, Felipe Aparicio · Advances in computational management science · 2001

Cited by 2

SIMULATION EXPERIMENTS

Along A Bus, Lane The, Movement Along et al. · 2013

Delays at bus stops and signals have a negative impact on bus speeds, even if priorities are provided in the form of bus lanes or busways. On the other hand, the

Cited by 0

10 Simulation, and simulation experiments

Michael D. Heine · 2013

The term 'simulation ' is variously defined: 'Some simulations seem to be searches for structure, for important variables, for hypotheses. Others are tests of hypotheses. Still others trace the implications of a theory or simply enumerate the consequences of

Cited by 0

Experiments vs. simulation.

Yangjin Kim (191134), Soyeon Roh (191139), Sean Lawler (191146) et al. · Figshare · 2015

<p>Effect of glucose deprivation on miR-451 expression levels. In <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028293#pone.0028293-Godlewski1" target="_blank">[2]</a>, miR-451 level was reduced by 21% for different cell lines (U251, LN229) after cells are cultured for 24 hr in normal (+, glucose or reduced glucose (−, glucose 0.3 g/l). Simulation results (red) are in good agreement with experimental results (blue; U251 cell line) from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028293#pone.0028293-Godlewski1" target="_blank">[2]</a>. Y-axis in the figure is the relative miR-451 concentration for high (glucose+; dimensionless value in simulation) and low (glucose−, glucose−, in simulation) level of glucose in the medium.</p>

Cited by 0Open access

Designing simulation experiments

W. David Kelton · 1999

This tutorial introduces some of the ideas, issues, challenges, solutions, and opportunities in deciding how to experiment with a simulation model to learn about its behavior. Careful planning, or designing, of simulation experiments is generally a great help, saving time and effort by providing efficient ways to estimate the effects of changes in the model's inputs on its outputs. Traditional experimental design methods are discussed in the context of simulation experiments, as are the broader questions pertaining to planning computer-simulation experiments.

Cited by 66

Designing simulation experiments

Russell R. Barton · 2013 Winter Simulations Conference (WSC) · 2013

Much effort goes into building and validating simulation models. Similar care is necessary in the use of the model to support decision making. Good simulation experiment design is important to get useful and valid insights for specific management questions. This introductory tutorial gives an overview of experiment design techniques for justifying and planning a series of simulation runs to uncover the impact of system design parameters on simulation output performance. Graphical methods are emphasized.

Cited by 17

Perceptron Simulation Experiments

Frank F. Rosenblatt · Proceedings of the IRE · 1960

An experimental simulation program, which has been in progress at the Cornell Aeronautical Laboratory since 1957, is described. This program uses the IBM 704 computer to simulate perceptual learning, recognition, and spontaneous classification of visual stimuli in the perceptron, a theoretical brain model which has been described elsewhere. The paper includes a brief review of the organization of simple perceptrons, and theoretically predicted performance curves are compared with those obtained from the simulation programs, in several types of experiments, designed to study "forced" and "spontaneous" learning of pattern discriminations.

Cited by 192

Categorized simulation experiments.

Kai Budde (11238237), Jacob Smith (1844773), Pia Wilsdorf (11238240) et al. · Figshare · 2021

<p>We present the results of the categorization of the simulation experiments found in the 19 simulation studies using our categories.</p> <p>(CSV)</p>

Cited by 0Open access

Designing Simulation Experiments

2011

Much effort goes into building and validating simulation models.Similar care is necessary in the use of the model to support decision making.Good simulation experiment design is important to get useful and valid insights for specific management questions.This introductory tutorial gives an overview of experiment design techniques for justifying and planning a series of simulation runs to uncover the impact of system design parameters on simulation output performance.Graphical methods are emphasized.

Cited by 0

Designing simulation experiments

R.R. Barton · Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304) · 2002

Simulation models are useful for examining the performance of alternative system configurations and/or alternative operating procedures for a system. The article provides some techniques for planning a set of simulation model runs, in order to gain insight on system behavior. There is an emphasis on graphical methods.

Cited by 7

Setups of simulation experiments.

Daria Stepanova (9955498), Helen M. Byrne (224868), Philip K. Maini (108832) et al. · Figshare · 2021

<p>For each setup of numerical simulation we specify the lattice dimensions, and ; the set of indices corresponding to the vascular plexus, ; the initial cell nuclei positions, ; the initial polarisation direction, <i>s</i><sub><i>init</i></sub>; the initial ECM and BM concentrations, <i>c</i><sub><i>init</i></sub> and <i>m</i><sub><i>init</i></sub>, respectively; the VEGF distribution over the lattice, <i>V</i>; and cell line used in simulations.</p> <p>(PDF)</p>

Cited by 0Open access

titan simulation laboratory experiments

Jérémy Bourgalais · Figshare · 2019

we performed low-pressure EUV photochemical laboratory experiments. The APSIS reactor was filled with a N2/CH4 (90/10\%) gas mixture relevant to the upper atmosphere of Titan. The cell was irradiated by using a EUV photon source at 73.6 nm which has been difficult to produce in the laboratory for previous studies. The photoproducts (both neutral and ionic species) were monitored in situ with a quadrupole mass spectrometer.

Cited by 0Open access

Web-Based Simulation Experiments

Ycesan, Enver, Chen, Chun Hung, Lee, Insup · NCSU Libraries Repository (North Carolina State University Libraries) · 1998

The use of the World Wide Web and Java-based mobile code provides new opportunities for distributed simulation. First, the infrastructure provided by the Internet eliminates the need for multiprocessor hardware, making it feasible to distribute simulation models over different hardware platforms through the Internet. Second, "Internet-aware" mobile Java code makes the applications fully portable and reusable. These enabling technologies are already exploited for distributed simulation modeling. This paper reports on the preliminary results of an on-going effort to construct a parallel discrete event simulation support system to distribute simulation experiments over the Internet with a view on simulation optimization. A research prototype for ranking and selection problems is described. The overall project goals are discussed.

Cited by 0Open access

SIMULATION AND EXPERIMENTS BY

Richard James Otten · 2012

Ever since the invention of air conditioning and refrigeration in the late nineteenth century, there has been tremendous interest in increasing system efficiency to reduce the impact these systems have on global energy consumption. Efficiency improvements have been accomplished through component design, refrigerant design, and most recently control system design. The emergence of the electronic expansion valve and variable speed drives has made immense impacts on the ability to regulate system parameters, resulting in important strides towards efficiency improvement. This research presents tools and methodologies for model development and controller design for air conditioning and refrigeration systems. In this thesis, control-oriented nonlinear dynamic models are developed and validated with test data collected from a fully instrumented experimental system. These models enable the design of advanced control configurations which supplement the performance of the commonly used proportional-integral-derivative (PID) controller. Evaporator superheat is a key parameter considered in this research since precise control optimizes evaporator efficiency while protecting the system from component damage. The controllers developed in this thesis ultimately provide better transient and steady state

Cited by 0