From: vbl@mace.cc.purdue.edu (Randall Julian)
Subject: N-Body Simulations
Keywords: simulation, multiparticle
Organization: Purdue University
Distribution: na
Date: Thu, 3 Sep 1992 02:39:10 GMT


I haven't read this group much but the last two digests (v28n9 and 10)
had a question about N-body simulations.  I am working on a model of
an ion trap which tracks the trajectory of 16K ions.  It has been 
ported to the Connection Machine C*, but currently ions do not interact.

To add ion-ion interaction seems like an N-body problem.  Are there
standard references on this ?  So far this has been a big electrostatics
problem with a bit of numerical integration mixed in, so I haven't 
though much about N-body work.  However a Thinking Machines consultant
suggested that 16K particles is now considered on the low end for
some.  I would be interested in hearing from anyone with experience
in this area.

Randy Julian, Dept. of Chemistry, Purdue University
vbl@mace.cc.purdue.edu
(317)494-6898



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Subject: [REGARDING PAST QUESTIONS]


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Date: Tue, 1 Sep 92 15:09:56 MDT
From: randy@tigercat.den.mmc.com (Randy Stafford)
To: simulation@bikini.cis.ufl.edu
Subject: Re: SIMULATION DIGEST V29 N1

In regard to the question about the company that produces QASE:

Advanced System Technologies, Inc.
12200 E. Briarwood Ave., Suite 260
Englewood, CO 80112
(303) 790-4242

 -- 
|===========================================================================|
| from:  Randy Stafford               |  Martin Marietta Astronautics Group |
| mail:  randy@tigercat.den.mmc.com   |  Denver, Colorado                   |
| voice: (303) 977-1069               |  The foregoing opinions are mine    |
| fax:   (303) 977-2326               |  and not necessarily my employer's. |
|---------------------------------------------------------------------------|
| Words dissemble, words be quick, words resemble walking sticks.           |
| Plant them and they will grow; watch them waver so.                       |
| I'll always be a word man - better than a bird man.        --Jim Morrison |
|===========================================================================|



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Subject: [PUBLICATIONS]


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Date: Thu, 3 Sep 1992 11:25 +0100
From: "Jack Kleijnen, Tilburg, Netherlands" <KLEIJNEN@KUB.NL>
Subject: abstract "Two-stage versus sequential..."
To: simulation@cis.ufl.edu
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Verification and validation of simulation models

Jack P.C. Kleijnen
Department of Information Systems and Auditing, Katholieke
Universiteit Brabant (Tilburg University), P.O. Box 90153,
5000 LE Tilburg, Netherlands.

This paper surveys many issues in the verification and valida-
tion of models, especially simulation models in operations
research. For verification it discusses (a) checking of inter-
mediate simulation outputs through tracing and statistical
testing per module, (b) comparing final simulation outputs
with analytical results, using statistical tests, (c) animati-
on, and (d) general good programming practice. For validation
it discusses (a) obtaining real-world data for trace driven
simulation, which may be scarce or abundant, (b) some simple
tests for comparing simulated and real data, such as graphi-
cal, Schruben-Turing, and t tests and, (c) a new statistical
procedure, based on regression analysis, for testing whether
simulated and real responses are positively correlated, (d)
sensitivity and risk analyses, (e) system dynamics type of
simulation, (f) relationships between simulation and other
types of models, including white and black box models, (g)
Documentation and credibility assessment. Finally 37 referen-
ces are given for further study.

Keywords: simulation, statistics, time series, philosophy,
practice.



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Date: Thu, 3 Sep 1992 11:24 +0100
From: "Jack Kleijnen, Tilburg, Netherlands" <KLEIJNEN@KUB.NL>
Subject: new book info
To: simulation@cis.ufl.edu
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New Book Information

"Simulation: A Statistical Perspective" by

Jack P. Kleijnen and Willem v. Groenendaal, Tilburg University, The Netherlands

This text is aimed at those readers who wish to acquire a basic knowledge of 
simulation. The authors combine simulation theory and statistical theory with 
practical applications to show how certain problems in the areas of management 
science, operations research, economics, business administration and mathemati-
cal statistics can be analysed by means of simulation. By explaining how to 
analyse simulation results, it also shows how to arrive at more general 
conclusions when using simulation. The efficient design of simulation experim-
ents is also discussed.

The book includes examples and definitions of simulation, an introduction to 
Forrester's Industrial Dynamics or System Dynamics and the evaluation of 
pseudorandom number generation. It also discusses the application of simulation
in mathematical statistics and operational research, with particular reference 
to inventory and queuing systems. Experiments using statistical designs are
analysed through ANOVA, and information on the verification and validation of 
models is supplied.

CONTENTS:
 -           Introduction
 -           Random Numbers
 -           Sampling from Non-Uniform Distributions
 -           Economic and Corporate Models
 -           Operations Research Models
 -           Simulation Software
 -           Statistical Applications
 -           Regression Metamodels
 -           Experimental Design
 -           Tactical Aspects
 -           Verification and Validation
 -           Epilogue
 -           Solution to Exercises
 -           Author Index
 -           Subject Index

            0471 93055 5 (paperback) 280pp Augustus 1992
16.50/$35.10


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ORDER FORM

Please send me ____ copy(ies) of: You may telephone our Customer
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KLEIJNEN & VAN GROENENDAAL/SIMULATION (paperback) (ouside UK)

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Date: Thu, 3 Sep 1992 11:26 +0100
From: "Jack Kleijnen, Tilburg, Netherlands" <KLEIJNEN@KUB.NL>
Subject: abstract "Verification and validation..."
To: simulation@cis.ufl.edu
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The follwing paper may be requested from the author: TWO-STAGE VERSUS
SEQUENTIAL SAMPLE-SIZE DETERMINATION IN REGRESSION ANALYSIS OF
SIMULATION EXPERIMENTS

by JACK P.C. KLEIJNEN and WILLEM VAN GROENENDAAL

                 Katholieke Universiteit Brabant (Tilburg University)
                          School of Management and Economics
                    Department of Information Systems and Auditing
                             5000 LE Tilburg, Netherlands

In practice, simulation models usually have responses with variances
that vary with the inputs, that is, the variances are not constant.
Then the number of observations (also called simulation runs or
replications) per combination of simulation inputs can be selected
such that the variances of the average simulation responses become
(approximately) equal; in other words, combinations with high
variability are replicated more often. These average responses can be
analyzed through a regression metamodel. To estimate the regression
parameters (or simulation input effects), Weighted Least Squares (WLS)
can be applied. WLS becomes identical to Ordinary Least Squares (OLS)
applied to the average simulation responses. Because the response
variances are unknown, they are estimated by repeating the simulation
runs with different random numbers. The estimated response variances
yield the number of runs required to obtain approximately equal
variances per average simulation response. Two rules for selecting the
required number of simulation runs are presented, namely a two-stage
and a sequential rule. The rules are first formalized and analyzed,
and then evaluated through a Monte Carlo experiment. Both procedures
turn out to yield confidence intervals for the estimated regression
parameters that have acceptable coverage probabilities. The sequential
rule demands more complicated computations to select the number of
simulation runs, but this rule saves runs.

(Key Words: EXPERIMENTAL DESIGN; METAMODEL; PILOT SAMPLE; STEIN
ESTIMATOR; ITERATIVE PROCEDURE; STOPPING RULE)




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Subject: [CALL FOR PAPERS/PARTICIPATION]


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Newsgroups: comp.simulation