SIMULATION: Transactions of The Society for Modeling and Simulation International

doi: 10.1177/003754977302000101pmid: N/A

Golden, D.G.; Schoeffler, J.D.

doi: 10.1177/003754977302000103pmid: N/A

GSL is a FORTRAN-oriented language which combines the activity and process concepts of a discrete simula tion language with continuous simulation concepts, thereby permitting the simulation of systems which call for combining continuous and discrete simula tion techniques. The basic structural component of GSL is the simulation block, which corresponds either to an activity of a discrete system or a dynamic re gion of a continuous system. Both discrete and con tinuous simulation blocks may have multiple process instances which may be controlled dynamically at run- time. The result is a combined language which re tains the features of both continuous and discrete simulation languages and moreover takes advantage of the desirable features of each to supplement the other. GSL syntax is described by examples which illustrate the application of the language in a typical combined simulation problem and permit the evaluation of the various features of the language.

Morehouse, N.F.; Carter, J.C.; Bryant, L.T.

doi: 10.1177/003754977302000104pmid: N/A

This paper describes the simulation of a nuclear re actor system using the neutron diffusion equations coupled to the thermodynamic and mechanical equations. In this coupling, representation of the diffusion equation presents considerable difficulty when large power excursions are being simulated. This difficul ty arises from the diverse response times (from 10-8to 10-1second) of the coupled equations of the system. In this paper a transformation of the dif fusion equations is developed which permits coupling them to mechanical and thermodynamic equations of much slower response times, thus eliminating the difficulties previously encountered in simulating these coupled sets of equations.In the transformation, time is the continuous vari able and energy and space are made discrete. The reactor core is divided into concentric cylindrical regions and the energy is divided into bands. The transformtion involves using natural logarithm of the neutron flux in the center region as a refer ence and determining the change in the ratio of the natural logarithm of the neutron fluxes in the other regions to that in the center region as a result of a regional variation in neutron produc tion. The transformation permits a simulation to cover many decades of continuous change in neutron flux. It also gives directly the deviation from the steady-state neutron flux distribution.

Shampine, L.F.

doi: 10.1177/003754977302000105pmid: N/A

Ricci, F.J.

doi: 10.1177/003754977302000107pmid: N/A

This paper presents a tutorial analysis of a hybrid computer model of a missile reentering the atmosphere. An important aspect of the paper is that an example of how to go about analyzing the suitability of a hybrid computer configuration for a particular large- scale simulation is presented from an overall systems point of view. Equations describing a missile (six- degrees of freedom) reentering the atmosphere are given, as is a hybrid computer configuration for solving them. This configuration is then analyzed to establish its suitability for simulation.

Hodgetts, Richard M.; Braskamp, Larry

doi: 10.1177/003754977302000108pmid: N/A

Two of the most interesting and challenging questions posed by performance in general management simula tions are: (1) why are some participants successful while others are not, and (2) are there some common characteristics that can be identified through stan dard psychological tests which differentiate success ful and unsuccessful performance? We attempted to answer these questions by testing two classes of seniors in the College of Business at the University of Nebraska-Lincoln. All were scheduled to play the University of Nebraska game TOP MANAGEMENT SIMULATION (TMS).1This is a general management simulation which requires each team to operate its own company by selling industrial machinery in a finished and in an unfinished goods market. All companies start with identical assets, produce the same product and sell in the same market. The game is of medium complexity requiring ten decisions per period of play in the areas of plant capacity, production, advertising, research and development, pricing, salesmen, distri bution centers, and the financing of operations.

Mawson, J. Bruce

doi: 10.1177/003754977302000109pmid: N/A

McLeod, John

doi: 10.1177/003754977302000110pmid: N/A