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- Path: sparky!uunet!caen!uflorida!simulation
- From: simulation@uflorida.cis.ufl.edu (Moderator: Paul Fishwick)
- Newsgroups: comp.simulation
- Subject: SIMULATION DIGEST V30 N6
- Message-ID: <37955@uflorida.cis.ufl.edu>
- Date: 17 Dec 92 21:20:46 GMT
- Sender: fishwick@uflorida.cis.ufl.edu
- Reply-To: simulation@uflorida.cis.ufl.edu
- Lines: 1071
- Approved: fishwick@uflorida.cis.ufl.edu
-
- Volume: 30, Issue: 6, Thu Dec 17 16:19:53 EST 1992
-
- +----------------+
- | TODAY'S TOPICS |
- +----------------+
-
-
- [NEW QUESTIONS]
- Books on Simulation
- Hierarchical Decomposition
- Introductory Books
- Synchronization in Distributed Systems
- VHDL vs. Verilog
- Boat Simulator
- ModSim Compiler
- [SOFTWARE]
- Simulating the US Budget
- LOOPN: Object Oriented Petri Net Simulator
- [CALL FOR PAPERS/PARTICIPATION]
- Annual Simulation Symposium
- Summer Computer Simulation Conference (SCSC '93)
- [DEPARTMENTS]
- Simulation in the Service of Society
-
- * Moderator: Paul Fishwick, Univ. of Florida
- * Send topical mail to: simulation@bikini.cis.ufl.edu OR
- post to comp.simulation via USENET
- * Archives available via FTP to bikini.cis.ufl.edu (128.227.224.1).
- Login as 'anonymous', use your e-mail address as the password, change
- directory to pub/simdigest. Do 'binary' before any file transfers.
- * Simulation Tools available by doing above and changing the
- directory to pub/simdigest/tools.
-
-
-
-
- -----------------------------------------------------------------------------
-
-
- Subject: [NEW QUESTIONS]
-
-
- ------------------------------
-
-
- Date: Wed, 9 Dec 1992 20:06:19 GMT
- From: news@ns1.nodak.edu (News login)
- To: comp-simulation@uunet.UU.NET
- Content-Length: 1409
- X-Lines: 32
-
-
- Newsgroups: comp.simulation
- Path: plains.NoDak.edu!bhati
- From: bhati@plains.NoDak.edu (Amit Bhati)
- Subject: req., suggestions on text books in Simulation
- Sender: usenet@ns1.nodak.edu (News login)
- Date: Wed, 9 Dec 1992 20:06:18 GMT
- Nntp-Posting-Host: plains.nodak.edu
- Organization: North Dakota Higher Education Computing Network
-
- Hi folks, I am a starting Grad. student in CS and want to learn the theory,
- programming (for my present work it will be in C/C++) and all the Statistics
- necessary in basic Computer based Simulation. However, I am fairly ignorent
- of the area and would like people to suggest a good, comprehensive book(s)
- to read on introductory to intermediate stuff in Simuation. You may suggest
- advanced stuff, that I could use later too.
- If it may help, my work shall be in investigating Scheduling strategies
- for multi-processor systems.
- I do not read this news-group regularly, so replies by e-mail shall be
- greatly appreciated. Many thanks in advance.
-
- Cheers,
- Amit
- --
-
- =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
- |Amit Bhati |bhati@plains.NoDak.edu| "All that is there in the|
- |Computer Science Dept.,|!uunet!plains!bhati | middle of the road is a |
- |IACC Building, NDSU, |Ph: (701) 232-6754 | dumb, yellow line and a |
- |Fargo, ND 58105. | | dead skunk." |
-
-
-
- ------------------------------
-
- Date: Fri, 11 Dec 92 17:08 GMT
- From: Evan Gamblin <0001847804@mcimail.com>
- To: "simulation@uflorida" <simulation@bikini.cis.ufl.edu>
- Subject: Hierarchical.decomposition software
- Content-Length: 1210
- X-Lines: 32
-
- In the early 1960's the architect Christopher Alexander used graphical
- decomposition as a means of understanding and solving complex community
- planning problems having hundreds of potentially conflicting variables.
-
-
- To do this, Alexander and an associate at MIT Marvin Manheim, wrote
- several programs for the IBM machine at their disposal. Does anyone know
- whether these (or progeny) have been ported to the Mac or IBM-PC, and where
- I'd find them? (I have newsgroup and mail/mail server access only).
-
- Otherwise, what tools can you recommend for this task?
-
- The programs Alexander wrote were HIDEC2: a computer program for the
- hierarchical decomposition of a set with an associated graph (MIT Civil
- Engineering Sys Lab Publication no. 160, 1962) and HIDECS3: Four computer
- programs for the hierarchical decomposition of systems which have an
- associated linear graph (MIT Civil Engineering Sys Lab research report
- no R63-27, 1963).
-
- Appreciate any assistance you can p
- rovide,
-
- Evan Gamblin
-
- The Halifax Group
- Ottawa, Ont Canada
-
- E-mail: 0001847804@mcimail.com
-
-
-
- ------------------------------
-
- Date: Sun, 13 Dec 1992 22:29:37 GMT
- From: news@ns1.NoDak.edu (News login)
- To: comp-simulation@uunet.UU.NET
-
- Hi folks, I am a starting Grad. student in CS and want to learn the theory,
- programming (for my present work it will be in C/C++) and all the Statistics
- necessary in basic Computer based Simulation. However, I am fairly ignorent
- of the area and would like people to suggest a good, comprehensive book(s)
- to read on introductory to intermediate stuff in Simuation. Specially a book
- that will cover the required Statistics very well will be highly appreciated.
- You may suggest advanced stuff, that I could use later too.
- If it may help, my work shall be in investigating Scheduling strategies
- for multi-processor systems.
- I do not read this news-group regularly, so replies by e-mail shall be
- greatly appreciated. Many thanks in advance.
-
- Cheers,
- Amit
- --
-
- =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
- |Amit Bhati |bhati@plains.NoDak.edu| "All that is there in the|
- |Computer Science Dept.,|!uunet!plains!bhati | middle of the road is a |
- |IACC Building, NDSU, |Ph: (701) 232-6754 | dumb, yellow line and a |
- |Fargo, ND 58105. | | dead skunk." |
-
-
-
- ------------------------------
-
- To: comp-simulation@ucsd.edu
- Path: delilah!johansen
- From: johansen@delilah.ccsf.caltech.edu (Jonathan Johansen)
- Newsgroups: comp.simulation,comp.parallel,comp.realtime,sci.engr.control
- Subject: Synch of Distributed Clocks
- Date: 13 Dec 1992 22:34:31 GMT
- Organization: California Institute of Technology, Pasadena
- Distribution: world
- Nntp-Posting-Host: delilah.ccsf.caltech.edu
-
-
- I'm developing a distributed simulation which employs two kinds
- of processes. I'll refer to these processes as the sensor and
- tracker processes. The sensor processes simulate noisy
- measurements of a physical phenomena. As a sensor generates each
- discrete data set, it broadcasts the data to each each of the
- tracker processes over a workstation LAN. The communication is
- is supported via UNIX sockets. After receiving data blocks
- from all sensors, the trackers try to fuse this multiple sensor
- data into a noise free estimate of the physical phenomena's state.
-
- I would like to have the sensors broadcast information based
- upon a realtime clock. That is, each time a sensor process
- sends a data messsage, it would time-stamp the message with
- the local "wall clock" time of its computing node. This method
- is in contrast to a system which uses a simulated clock's time
- stamp; i.e., a loop of the sort:
- sim_time = 0.0;
- while (!end_simulation) {
- generate_sensor_data();
- send_data_2_trackers();
- sim_time = sim_time + dt;
- }
- I want to use a simulation time based upon the UNIX gettimeofday()
- function. The problem is that in a distributed environment, the
- "wall clock" time of the multiple sensor processes may be slightly
- different. It's important that the tracker nodes receive data
- blocks which are stamped with a time that accurately reflects
- when the data was generated. Is anybody aware of work that has
- been done on synchronizing the "wall clocks" of distributed
- computing nodes? For example, synchronizing the clocks of multiple
- workstations on an Ethernet LAN. Preferably to at least a
- 10 millisecond accuracy. Please respond with email, and I will
- summarize with a posting. Thanks.
-
- Jonathan Johansen
- Engineering Physics Division
- Argonne National Laboratory
- johansen@delco.ep.anl.gov
-
-
-
- ------------------------------
-
- To: comp-simulation@ames.arc.nasa.gov
- Path: juts!oran
- From: oran@spg.amdahl.com (Oran Davis)
- Newsgroups: comp.lang.vhdl,comp.lang.verilog,comp.simulation
- Subject: VHDL vs Verilog the eternal question, collecting input.
- Date: 15 Dec 92 18:19:24 GMT
- References: <1992Dec15.004358.22535@EE.Stanford.EDU>
- Organization: Amdahl Corp., Sunnyvale CA
-
-
- Hi Netters,
-
- We are users of both Verilog and VHDL under synopsys
- all of us have our favorite system
- that we will not give up. I am collecting a list of pros and cons to
- summarize the strengths and weaknesses of these two contenders.
-
- Any ideas input of strong feeling are welcomed. Please keep in mind that
- the project I am targeting for is VERY large with MANY people involved.
-
- Thanks for any input,
-
- >- Oran
-
-
-
- ------------------------------
-
- To: comp-simulation@uunet.UU.NET
- From: jhsegal@wiscon.weizmann.ac.il (Livian)
- Newsgroups: comp.simulation
- Subject: Boat Simulator
- Date: 15 Dec 92 11:41:47 GMT
- Sender: news@wisipc.weizmann.ac.il
- Organization: Weizmann Institute of Science, Computation Center
-
-
- I don't know how many people read this newsgroup out there,but if anyone
- reads,I would like to receive a recomandation of a war ship/boat/vessel.
- Thank you very much.
- ___
- (o o)
- ------------------------------ooO-(_)-Ooo------------------------------------
- __ __ __ ___ __ _ ___ __
- | | \ / | \ \ | VM/CMS:
- | | \ / | _ \ \ | JHSEGALL @ Weizmann.weizmann.ac.il
- |___ | / | _ \ | \ | UNIX:
- | | / | / \ | | JHSEGAL @ Wiscon.weizmann.ac.il
-
-
-
- ------------------------------
-
- Date: Wed, 16 Dec 92 23:58:48 -0600
- From: David A Dreyer <etcdad@iitmax.iit.edu>
- To: comp-simulation@rutgers.edu
-
- Hi all....
-
- I'm looking for a ModSim compiler, preferably for the
- PC, although any machine or environment will do.
-
- Does anybody know of one in ftp-land or shareware land? Any
- info on the subject is mucho appreciated.
-
- Thanks,
-
- Dave
-
-
-
-
- ------------------------------
-
-
- Subject: [SOFTWARE]
-
-
- ------------------------------
-
-
- Date: Sat, 12 Dec 92 05:49:37 -0600
- From: gmk@pegasos.ccsr.uiuc.edu (Gottfried Mayer-Kress)
- To: mcleod@sdsc.edu
- Subject: Budget Balancer ?
-
- I read about a very nifty simulation program that should allow
- you to test different strategies to balance the US budget. It is
- called "Budget Balancer" and distributed by Banner Blue
- Software.
-
-
- ---
- Gottfried Mayer-Kress
- Center for Complex Systems Research, Department of Physics
- 3025 Beckman Institute, 405 N Mathews, Urbana, Il 61801
- gmk@pegasos.ccsr.uiuc.edu (NeXT-Mail)
- gmk@goshawk.lanl.gov, gmk@santafe.edu
-
- (217)-244-5877 (voice/fax modem),x8371(fax), x1994 (msg)
-
-
-
- ------------------------------
-
- Newsgroups: comp.simulation
- Path: probitas!charles
- From: charles@probitas.cs.utas.edu.au (Charles Lakos)
- Subject: LOOPN - Language for Object-Oriented Petri Nets
- Sender: news@newsroom.utas.edu.au
- Organization: University of Tasmania, Australia.
- Date: Tue, 15 Dec 1992 05:22:20 GMT
- Apparently-To: simulation@bikini.cis.ufl.edu
-
-
- I wish to announce the availability of a compiler, simulator and associated
- source control for an object-oriented petri net language called LOOPN.
-
- In LOOPN, a petri net is an extension of coloured timed petri nets. The
- extension means firstly that token types are classes. In other words, they
- consist of both data fields and functions, they can be declared by
- inheriting from other token types, and they can be used polymorphically.
- The object-oriented extensions also mean that module or subnet types are
- classes. In other words, the declaration of a subnet encapsulates
- constants, types, places, transitions, access functions and parameters.
- These module types may be declared by inheriting from other modules and can
- be used polymorphically.
-
- LOOPN has been developed over a period of about 5 years at the University of
- Tasmania, where it has been used in teaching computer simulation and the
- modelling of network protocols.
-
- Further details on the syntax of LOOPN, its application and the conditions
- under which it is distributed are available in the distribution.
-
- The LOOPN compiler, simulator and associated documentation is available by
- anonymous ftp from
- ftp.utas.edu.au (131.217.10.1)
- as
- departments/computer_science/loopn.tar.Z
-
- --
- --
- Charles Lakos. C.A.Lakos@cs.utas.edu.au
- Computer Science Department, charles@probitas.cs.utas.edu.au
- University of Tasmania, Phone: +61 02 20 2959
- Sandy Bay, TAS, Australia. Fax: +61 02 20 2913
-
-
-
- ------------------------------
-
-
- Subject: [CALL FOR PAPERS/PARTICIPATION]
-
-
- ------------------------------
-
-
- Date: Thu, 10 Dec 92 17:18:11 EST
- From: jam@pollux.cs.uga.edu (John Miller)
- To: simulation@bikini.cis.ufl.edu
- Content-Length: 11145
- X-Lines: 300
-
- 26TH ANNUAL SIMULATION SYMPOSIUM
-
- in conjunction with the
- 1993 Simulation MultiConference
-
- March 29 - April 1, 1993 * Washington D.C.
-
- This year's Simulation Symposium will be presenting 37 state-of-the-art
- papers from industry, government, and academia. These 37 papers were
- selected from 50 full paper submissions which were fully refereed by a
- 25 member Program Committee. Papers will be presented in the following
- topical areas: Parallel Simulation, Neural Networks, AI & Simulation,
- Object-Oriented Simulation, Simulation Languages & Environments,
- Simulation of Parallel Processors, and Simulation of Circuits, Networks,
- Distributed Systems and Databases.
-
- The Annual Simulation Symposium is the oldest continuously operating
- conference/symposium dedicated to simulation. The Symposium features
- the Ira M. Kay Memorial Best Paper Award of $500. Also, authors of
- top papers will be encouraged to submit a follow-on paper to the
- International Journal in Computer Simulation.
-
- The Symposium is sponsored by the Society for Computer Simulation (SCS)
- in cooperation with the IEEE Computer Society and ACM/SIGSIM.
-
- The 26th Annual Simulation Symposium will be held at the
-
- Key Bridge Marriott
- 1401 Lee Highway
- Arlington, Virginia 22209
- phone: (703) 524-6400
- fax: (703) 243-3280
-
- The hotel is just across the bridge from Georgetown in Washington D.C.
- It is only two blocks from the Metro (subway) and downtown Washington
- is just minutes away. For additional information please contact the
- Symposium President/General Chair:
-
- John A. Miller
- Computer Science Department
- 415 Graduate Studies
- University of Georgia
- Athens, GA 30602
- phone: (706) 542-3440
- email: jam@pollux.cs.uga.edu
-
- For information on next year's Symposium (the 27th) please contact
- Patrick W. Dowd; email: dowd@eng.buffalo.edu.
-
- ________________________________ cut _________________________________
- 0 1 2 3 4 5 6 7
- 1234567890123456789012345678901234567890123456789012345678901234567890
- ______________________________________________________________________
-
-
- Preliminary Program
-
- 26th Annual Simulation Symposium
-
-
- General Chair: John A. Miller, University of Georgia
- Program Chair: Philip A. Wilsey, University of Cincinnati
-
-
- SESSION 1: Parallel and Distributed Simulation
- Monday, March 29, 10:30-12:00 a.m.
- Chair: George W. Zobrist
-
- Evaluation of Three Approaches to Parallel Logic Simulation
- on a Distributed Memory Multiprocessor
- by Peter Luksch, Technical University of Munich, Germany
-
- Reducing Rollback Overhead in Time-Warp Based Distributed
- Simulation with Optimized Incremental State Saving
- by Herbert Bauer and Christian Sporrer,
- Technical University of Munich, Germany
-
- Performance Measures for Several Optimizations to a
- Distributed Digital System Simulator
- by Avinash C. Palaniswamy, Sandeep Aji, Philip A. Wilsey,
- University of Cincinnati
-
- WarpLog: Time Warped Logical Objects
- by Krys J. Kochut and John A. Miller, University of Georgia
-
-
- SESSION 2: Parallel Architectures I
- Monday, March 29, 1:30-3:00 p.m.
- Chair: Enrique V. Kortright
-
- The CacheMire Testbench -- A Flexible and Effective Approach
- for Simulation of Multiprocessors
- by Mats Brorsson, Fredrik Dahlgren, Hakan Nilsson and
- Per Stenstrom, Lund University, Sweden
-
- Implementation and Simulation of Acquisition Consistency
- for Cache-Based Multiprocessors
- by Yung-Syau Chen, University of Southern California
-
- Multilevel Simulation of Distributed-Memory Program Traces
- by Jean-Pierre Prost and Shlomo Kipnis,
- IBM T.J. Watson Research Center
-
- Latency Hiding Strategies for Pre-Allocation Based
- Media Access Protocols for WDM Photonic Networks
- by Krishna M. Sivalingam and Patrick W. Dowd,
- State University of New York at Buffalo
-
-
- SESSION 3: Parallel Architectures II
- Monday, March 29, 3:30-5:00 p.m.
- Chair: Herbert Bauer
-
- Throughput Analysis of Multiple-Bus Multiprocessor Systems
- with Simultaneous Possession of Common Resources
- by Ibrahim Onyuksel, Northern Illinois University
-
- Performance Evaluations of Adaptive Wormhole Routing
- with Three Different Selection Functions
- by Ziqiang Liu and Handong Wu,
- Royal Institute of Technology, Sweden
-
- Interaction of Cache Coherency and Media Access Protocols in
- the Optically Interconnected Distributed Memory Environment
- by John Chu, Kwan AuYeung and Patrick W. Dowd,
- State University of New York at Buffalo
-
- A Parallel Algorithm for Dynamics Simulation of Multibody Chains --
- Implementation on a Transputer System
- by Burke Pond and Inna Sharf, University of Victoria, Canada
-
-
- SESSION 4: Networks and Distributed Systems
- Tuesday, March 30, 8:30-10:00 a.m.
- Chair: Yi-Bing (Jason) Lin
-
- The Limited Benefits of Load Sharing in Multicomputer Systems
- by Sayed A. Banawan, University of Houston
-
- Design and Analysis of a Network Level Channel Abstraction
- to Support Real-Time Communications
- by Taieb Znati and Brian Field, University of Pittsburgh
-
- The Simulation of Coadaptive Decision-Making
- by Alexander Glockner, Bowie State University
-
- Maximizing the Benefit of Load Information
- by Margaret Schaar, Louisiana Tech University
-
-
- SESSION 5: Distributed Systems and Databases
- Tuesday, March 30, 10:30-12:00 a.m.
- Chair: Krys J. Kochut
-
- A Database Simulation Environment and Its Use for Evaluation
- of Replication Control Algorithms
- by Sang H. Son and Spiros Kouloumbis, University of Virginia
-
- Simulating the Global Directory Service with OPNET
- by Alex Andrianopoulos and David Chadwick,
- University of Salford, United Kingdom
-
- The Use of VHDL as the Database for the Complete Electronic
- Hardware Design Cycle
- by William A. Hanna, McDonnell Douglas Electronics
-
- Simulation of Optimized Distributed Query Schedules on a
- Hypercube Network
- by S. Popovich, M. Alam and S. Bandyopadhyay,
- University of Windsor, Canada
-
-
- SESSION 6: Object-Oriented Simulation: Tools and Languages
- Tuesday, March 30, 1:30-3:00 p.m.
- Chair: Avinash Palaniswamy
-
- CEDES - A C++ Engine for Discrete Event Simulation
- by Jhyfang Hu, Tulane University
-
- A C++ Environment for Modeling Communication Systems
- by Wlodek Dobosiewicz and Pawel Gburzynski,
- University of Alberta, Canada
-
- COPS: A Computer Operations Performance Simulation System
- by Dennis Mok, Dan Daly, Joe Geigel, Krishna Kant,
- Yi-Bing (Jason) Lin and Victor Mak, Bellcore
-
- Simulation of the Object Flow Model: A Conceptual Modeling
- Language for Object-Driven Applications
- by Jyotsna Naranswamy, Lois Delcambre and Lissa Pollacia,
- University of Southwestern Louisiana
-
-
- SESSION 7: Object-Oriented Simulation: Environments
- Tuesday, March 30, 3:30-5:00 p.m.
- Chair: Patrick W. Dowd
-
- An Integrated Modeling Environment for Object-Oriented Simulation
- of Ecological Models
- by Luca Del Furia and Andrea Rizzoli, Politecnico di Milano, Italy
-
- A Multi-Domain Tool for Building Object-Oriented Animation
- Environments of Simulation Results
- by M. Gourgand, D. Hill and P. Kellert,
- Universite Blaise Pascal - Clermont-Ferrand II, France
-
- Towards an Object-Oriented Simulation Environment for
- Manufacturing Systems Analysis
- by Michel Fabre and Daniel Leblanc,
- Ecole Polytechnique de Montreal, Canada
-
-
- SESSION 8: Object-Oriented Simulation: Applications
- Wednesday, March 31, 8:30-10:00 a.m.
- Chair: Lissa Pollacia
-
- Object-Oriented Simulation of Capability Based Architectures
- by Stephen R. Daily and Mansur H. Samadzadeh,
- Oklahoma State University
-
- Building Hierarchical Symbolic Models and Large Scale Simulations
- Using the General Simulation System
- by William C. Cave and Naeem Malik,
- PSI Simulation Systems Corporation
-
- Object-Oriented Simulation for Air Traffic Control Training
- by Andrew J. Kornecki, Embry-Riddle Aeronautical University
-
-
- SESSION 9: Scheduling Algorithms and Operating Systems
- Wednesday, March 31, 10:30-12:00 a.m.
- Chair: Margaret Schaar
-
- Computational Schemes for Efficient Simulation of Service
- Disciplines
- by Janche Sang, Ke-Hsiung Chung and Vernon Rego, Purdue University
-
- Effects of Nonsymmetric Release Times on Rate Monotonic Scheduling
- by Randall G. Karl, T. Leo Lo and Daniel C. St.Clair,
- University of Missouri-Rolla
-
- A Practical Approach to Using Simulation to Analyze the Effects
- of a Non-Poisson Stream on Traffic in a Switch
- by Steven C. Adamson, Steven P. Gordon and Donald G. Otterbein,
- Booz, Allen & Hamilton, Inc.
-
- Dynamic Performance Profiles of Simulation Calendars
- by Ke-Hsiung Chung, Janche Sang and Vernon Rego, Purdue University
-
-
- SESSION 10: AI & Simulation
- Wednesday, March 31, 1:30-3:00 p.m.
- Chair: Mansur H. Samadzadeh
-
- Development of Intelligent Scheduling Aids Using Simulation and
- Neural Networks
- by Yuehwern Yih, Luis C. Rabelo, Albert T. Jones and
- George M. Witzgall, Purdue University
-
- Using the PARLOG Parallel Programming Language for the Performance
- Analysis of Concurrent Systems
- by Vincenza Carchiolo and Maurizio Papale,
- Istituto di Informatica e Telecomunicazioni, Italy
-
- A Stochastic Simulation Model of Family Income
- by Thomas Wong and David Tepper,
- Baruch College, City University of New York
-
-
- SESSION 11: 26th Annual Simulation Symposium Business Meeting
- Wednesday, March 31, 3:30-5:00 p.m.
-
- ______________________________________________________________________
- 0 1 2 3 4 5 6 7
- 1234567890123456789012345678901234567890123456789012345678901234567890
- ________________________________ cut _________________________________
-
-
-
-
- ------------------------------
-
- From: tttron@escher.lerc.nasa.gov (William Krauss)
- Subject: Call for Papers...
- Sender: news@eagle.lerc.nasa.gov
- Nntp-Posting-Host: escher.lerc.nasa.gov
- Organization: NASA Lewis Research Center [Cleveland, Ohio]
- Date: Wed, 16 Dec 1992 20:22:45 GMT
- Apparently-To: comp-simulation@cis.ohio-state.edu
-
-
-
-
- Call For Papers
-
- Summer Computer Simulation Conference (SCSC `93)
- Boston, Massachusetts
- July 19-21, 1993
-
- (Sponsored by The Society for Computer Simulation)
-
-
-
- Computer Graphics Techniques for Simulations
-
- "SCSC `93 will feature presentations of innovative work, state-of-the-art
- technology reviews, panel discussions, tutorials, and trade exhibits designed
- to provide comprehensive coverage of this rapidly evolving field. Major
- themes will be emerging and enabling technologies, simulation methodologies
- and practices, industrial applications, validation and verification techniques,
- and the cost benefits of rapid prototyping."
-
- One very important enabling technology for simulation is computer graphics
- (visualization techniques, animation, etc.). Visual feedback of simulated
- systems can provide rapid, intuitive, and meaningful insight to researchers
- and engineers especially during prototype phases.
-
- Simulation and computer graphics methods have recently become "married" into
- a "single" integrated technology. The field of virtual environments, an ideal
- example of this relationship, relies heavily upon the recent advancements
- in both of the respective disciplines.
-
- I am organizing a session within the Simulation Methodologies Group and
- am searching for speakers who are interested in presenting work in the
- aforementioned areas.
-
- Abstracts of approximately 500 words should be submitted by anyone
- interested.
-
- Please contact me via e-mail, US mail, or phone.
-
-
-
- --
- >>>> W.D. Krauss Sverdrup Technology, Inc. <<<<
- >>>> NASA Lewis Research Center MS 142-5 Cleveland, OH 44135 USA <<<<
- >>>> william@lerc.nasa.gov (216) 433-8991 <<<<
-
-
-
- ------------------------------
-
-
- Subject: [DEPARTMENTS]
-
-
- ------------------------------
-
-
- Date: Wed, 16 Dec 92 11:04:15 GMT
- From: mcleod@Sdsc.Edu
- Subject: E-S3-1-11-Part One
-
- The following sample issue of our electronic magazine, "E-S3",
- covering selected topics about computer modeling and simulation,
- is sent to you with the compliments of the publisher of the
- technical journal SIMULATION, the Society for Computer
- Simulation, and John and Suzette McLeod, the Editors of
- Simulation in the Service of Society (S3), a special section of
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- E-S3 Vol. 1, No. 11, Part One
-
- based on the November 1992 issue of
- "Simulation in the Service of Society"
- John McLeod, Technical Editor Suzette McLeod, Managing Editor
- 8484 La Jolla Shores Dr., La Jolla, CA 92037.
- E-mail: mcleod@sdsc.bitnet
- *
- S3 is a special section of
- SIMULATION
- the monthly journal of the
- SOCIETY for COMPUTER SIMULATION
- P.O.Box 17900, San Diego, CA 92177-7900
- Phone: (619) 277-3888 FAX: (619) 277-3930
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- [Copyright Notice: E-S3 is the electronically delivered version of
- "Simulation in the Service of Society" which is a special section of
- SIMULATION, a monthly technical journal of the Society for Computer
- Simulation International. It may be reproduced only for personal use
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- the original source of publication: SIMULATION 59:5, November 1992.
- All rights reserved, (c) 1992, Simulation Councils, Inc.]
- ----------------------------------------------------------------------
-
- A Simple, Globally Aggregated, Stochastic-Simulation Model
-
- In an attempt to enlist the participation of recognized
- contributors to the solution of the problems of our environment,
- your Ed. invited Paul Ehrlich to join us in a session on the
- environment at one of our conferences. He politely declined,
- pleading being "snowed" (a situation which most of us can
- understand), but he sent us a copy of a paper that he co-authored
- that certainly has, in our opinion, some thoughts worth passing
- on.
-
- Because "Simulation in the Service of Society" is not a technical
- publication we will skip the seven 16-column tables of output
- data and their detailed discussion, and bring you only what we
- consider extremely pertinent (i.e., life- and death-related)
- excerpts.
- * *
-
- An Exploratory Model of the Impact of Rapid Climate Change
- on the World Food Situation*
-
- Gretchen C. Daily and Paul R. Ehrlich
- Department of Biological Sciences
- Stanford University
- Stanford, California
-
- *Published in Proceedings of the Royal Society London, vol. 241, 1990.
-
- The Model
-
- The model simulates the effect of stochastic perturbations in
- food production (due to climate change) on population size. In
- yearly increments, the model calculates human population size,
- number of hunger-related deaths, and the production, consumption
- and storage of grain under different climatic scenarios.
- Parameters that may vary in each run of the model include the
- initial population size, the initial level of grain production
- and grain stores, the rate of change in population size and grain
- production, whether climate change has a net favourable or
- unfavourable impact on global agricultural production, the
- frequency and magnitude of changes in global harvest because of
- changed weather patterns, the projection time, and the desired
- number of simulations. The climate scenarios are described in
- terms of two parameters: the frequency and the magnitude of
- changes in global grain production caused by changing weather
- patterns. All of the parameters in the model represent
- aggregates for the world as a whole.
-
- Global aggregation of the model is a serious limitation.
- Geographic variation in weather tends to make gluts or shortfalls
- of grain regional events whose consequences can, at least in
- theory, be compensated by trade. When the highly aggregated
- "Limits to Growth" model (Meadows et al. 1972) was re-run at
- regional levels (Mesarovic and Pestel 1974) it was found to have
- overestimated global disaster but underpredicted regional
- disasters. However, because of the uncertainties of modelling
- climate (especially at regional levels), the changing patterns of
- international grain trade, and the functioning of futures
- markets, disaggregating our model did not seem a wise course.
- Instead, we attempted to capture some of the complexities of
- regional variations in our parameterization of mortality relative
- to global grain stocks.
-
- The manipulations of the input parameters were shown in a flow
- diagram of the model (Figure 1 of the published paper). The
- initial values of input parameters for population and
- agricultural production were selected from recent but not extreme
- years.
-
- In the following, delta N is the annual rate of natural increase
- of the population size, and delta G is the annual growth in grain
- production. The initial population size and growth rate were set
- at 5.000 billion and 1.7% per year, respectively, figures that
- roughly reflect conditions in 1986, the year of peak grain
- harvest to date. Population size may be sharply reduced by grain
- shortages (which cause rapid increases in deaths by starvation).
- These periods of population decrease are assumed to be
- instantaneous. Following such periods, the constant rate of
- increase is applied to the new lower population size. The
- feedback between low or empty grain stocks and population is
- described below.
-
- For most scenarios, initial production was set at 1.65 billion
- metric tons (T) grain, roughly the amount that was consumed in
- 1986. The underlying rate of change in grain production (the
- "trend") also remains constant. For reference, the average value
- of the trend was 2.6% per year from 1969 to 1979, and 1.4% per
- year from 1980 to 1988 (Food and Agriculture Organization 1970-
- 89).
-
- Results
-
- The output of the model under a variety of scenarios was
- displayed in Tables 1-7 and summarized in Figure 2 [not
- reproduced here].
-
- Discussion
-
- The complexity of the systems that interface in this model,
- including population, agriculture, and climate, not to mention
- economics, trade, government policy and international
- relations, make it impossible to quantify accurately the interactions
- between them. Nonetheless, the results of our relatively simple
- model have heuristic and perhaps some predictive value. They
- offer insight [emphasis JM] to the vulnerabilities of our
- agricultural system and growing population, and provide a measure
- of the relative importance of key factors in the population-food-
- climate interaction.
-
- (a) Limitations of the model
-
- The model has several important limitations. First, it accounts
- for regional heterogeneity only by including deaths caused by
- maldistribution. This is a crude approximation because
- inequitable distribution of food (and wealth in general) and
- extreme heterogeneity in population density, in agricultural
- productivity (over space and time), in climate regimes, and in the
- variability of weather patterns, are key factors in generating
- regional famine. For example, at least since 1966, the world has
- never experienced a global grain deficit (by our standard of 0.33
- T per person per year) yet hunger has afflicted local and
- regional populations repeatedly throughout this period.
-
- Secondly, the model does not include mechanisms whereby
- compensation for imminent food shortages could be made. Such
- mechanisms include (1) spurring research and development of new
- technology and crop strains to increase yields; (2) intensifying
- crop production with increased inputs of water, fertilizer and
- pesticides; (3) bringing set-aside and other marginal land in the
- USA and elsewhere into production; (4) consuming more crops
- directly (as opposed to feeding livestock); (5) reducing herds by
- temporarily consuming more livestock (which represent a large
- food reserve); (6) reducing wastage between farm and stomach; and
- (7) development and implementation of emergency relief measures
- to minimize and contain the effects of local crop failures.
-
- How likely are such ameliorating factors to make major impacts?
- The potential effectiveness of mechanism (1) is debatable;
- although no bright technological prospects lie on the immediate
- horizon, there is evidence in support of the hypothesis that
- crises stimulate innovation. Mechanisms (2) and (3) are likely
- to provide only short-term relief, and to be detrimental in the
- longer term; these traditional methods of expanding agricultural
- production are very resource-intensive, generally not
- sustainable, and rapidly approaching physical constraints.
- Mechanisms (4)-(7) are critical steps towards buffering over-
- large populations from the most devastating effects of
- insufficient production. All of these mechanisms may operate to
- reduce the number of deaths predicted by the model, but none
- represents a long-term solution to the problem of delta N
- outstripping delta G.
-
- Thirdly, the model implicitly assumes that the underlying 'trend`
- (rate of change) in grain production will remain constant even in
- the face of the social and economic turmoils sure to result from
- massive crop failures, severe famine. loss of habitable land in
- coastal areas and other impacts of unfavourable climate change.
- Furthermore, maintaining a growth rate in agricultural output of
- 1.7% per year embodies a series of optimistic assumptions of
- success in the development and implementations of better
- agricultural practices and technologies. In addition, the
- effects of climate change are assumed to be constant, when really
- they may intensify. These assumptions would all have the effect
- of under-estimating the number of deaths that may result from the
- impacts of deleterious climate change.
-
- Fourthly, the number of deaths produced by the model under
- different scenarios depends to a large degree on the factor used
- to convert grain deficits to deaths. Currently, three people are
- supported on average by each tonne* of grain produced per year.
-
- *Metric ton, 2352 pounds
-
- However, 1 T grain per year delivered to the mouth can provide
- four adults with 'adequate` diets and five adults with
- 'subsistence` diets. The brunt of any deficits is likely to be
- borne by the world's poorest people; in response to the same
- decrease in supply, the poor reduce their grain consumption more
- than ten times as much as the wealthy, who simply forego luxury
- items. At one extreme, a few tonnes deficit in a rich country
- would probably not cause any deaths, whereas at the other, a one-
- tonne deficit in a poor country might cause the deaths of four
- subsistence-diet adults and two children. Considering these
- various factors and uncertainties, we feel an estimate of two
- deaths per tonne deficit is conservative.
-
- Finally, a few comments relative to our validation of the model
- must be made. It is very difficult to quantify the actual number
- of people that have starved to death over the past two decades.
- Aside from poor censusing in famine-stricken areas, malnutrition
- compromises the immune system, and the immediate cause of death
- of severely malnourished people is thus usually reported as
- disease. The rough estimate of 200 million deaths is
- considerably higher than the average of 100 (+ 30) million deaths
- per simulation produced in our test scenario that approximtes
- conditions over those decades. The numbers of deaths produced by
- the distributional aspects of the model are therefore probably
- conservative.
-
- Conclusions
-
- Four general conclusions can be drawn from the model regarding
- the number of people at risk of starvation and the importance of
- the relation between delta N and delta G to both the creation of
- deficits and the relative impact of unfavourable climatic
- conditions.
-
- First, the model suggests that several hundreds of millions to a
- billion or so people could die of hunger in future decades.
- Examinations of the pattern of deaths within runs suggest that
- such numbers of people are not likely to die in a single large
- famine. Those additional deaths would not, however, be primarily
- 'distributional`, as have been those of the past two decades.
- Instead, the vast majority of them could be due to absolute
- global shortage.
-
- The second primary conclusion from the model is that seemingly
- small (on the order of 0.3%) differences in the annual rates of
- growth in population and agricultural production can have a large
- impact on global food security. This is an important point
- because land degradation (in the form of soil erosion,
- waterlogging and salinization of irrigated land, and decline in
- soil fertility), scarcity of fresh water in many parts of the
- world, and the increasing cost of fertilizer and pesticide
- inputs, threaten to constrain growth in grain production.
-
- The model highlights the effectiveness of declines in population
- growth toward minimizing the impact of deleterious global climate
- change and providing food for everyone. Initiation of the socio-
- economic changes required to reduce birth rates is critical to
- bringing the human population to a size compatible even with the
- short-term carrying capacity of Earth.
-
- Thirdly, the model produced the interesting result that climate
- change contributes proportionally much less to food deficits when
- population growth outpaces growth in agricultural production
- than when growth in each is equal.
-
- Though the results under scenarios leading to high mortality may
- appear roughly the same (hundreds of millions of deaths) the
- distribution of deficits between rich and poor nations may be
- quite different. If the main cause of deficits is that growth
- in population size exceeds 'trend` growth in grain production,
- then the swelling populations in the Third World will be most
- directly affected.
-
- Finally, it is conceivable that CO2 fertilization and concomitant
- reduced transpiration will enhance global agricultural
- productivity. In our view, however, the potential benefits of
- CO2 fertilization are likely to be outweighed by the negative
- impact of changing temperature belts, reduced water
- availability in major grain-growing regions, possible
- unfavourable changes in crop-pest relations, and social and
- economic disruptions.
-
- As to be expected, when production keeps pace with population
- growth, relatively few deaths occur (and those as a result of
- maldistribution). However, if population growth outpaces
- production by 0.8% per year or so, then even very favourable
- climatic scenarios (e.g. with 5 or 10% increases in production
- every three-five years), do not prevent the deaths of over 800
- million people on average over a 20-year period.
-
- The model highlights the delicate balance between the nutritional
- needs of a rapidly growing human population and the ability of
- Earth to sustain the food production required to meet those
- needs. The odds that climate change will produce a net benefit
- to global agriculture seem small. But even if the odds of
- favourable and deleterious impact were even, the model suggests
- trying to slow the climatic change, since if delta N = delta G,
- many more lives would be lost if the changes were harmful than
- would be saved if they were beneficial, especially as the
- climatic impact (probability of event times magnitude of change)
- increases.
-
- Analysis of the model further suggests that humanity may face a
- situation unprecedented in the modern era: absolute global food
- shortage. The political, economic and social consequences of
- such a situation in a "global village" are difficult to imagine.
- That possibility presents itself at a time when conventional
- methods of expanding food production may be reaching physical and
- economic limits.
-
- For the immediate future, global food security could be increased
- by minimizing the amount of food wasted between harvest and
- consumption, by strengthening the agricultural sectors of poor
- nations, and by improving the equity of food distribution.
- Long-term food security can ultimately be achieved only by
- initiating the socio-economic changes necessary to bring about
- reduced birth rates. In addition, the model reinforces the
- prudence of striving to reduce the emission of greenhouse gases
- into the atmosphere (which in turn is strongly driven by
- population growth). It also supports the view that providing
- everyone with adequate diets will remain a tremendous challenge
- even without the threat of global climatic change.
-
- * * *
-
-
-
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-
-
- END OF SIMULATION DIGEST
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-
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