Showing papers on "Verification and validation of computer simulation models published in 1987"

An overview of verification and validation of simulation models

Abstract: We give a general introduction to verification and validation of simulation models, define the various validation techniques, and present a recommended model validation procedure in this overview paper.

Techniques for ascertaining the validity of large-scale production simulation models

Abstract: Statistical method, and in particular, simulation is the most widely used operations research modelling approach now employed by industry and government. Validation of a simulation model is the procedure designed to determine whether the model is an accurate representation of the portion of reality under consideration. It is a process distinct from model building or debugging (although interrelated). In this work, strategies and practical numerical techniques for validating large-scale production simulation models (or any other large system) are detailed. An evolution of the central concepts of large-scale model validation is represented first. The distinction between model user's risk and model builder's risk is highlighted as an important development which alters the problem into a consideration of the basis a decision-maker should use in determining whether to rely on the outputs of such models. Two quantitative techniques which are applications of the Turing test and of mathematical programming are de...

Validation of simulation models using decision theory

Abstract: To determine the necessary resources for sufficient validation of a simulation model is an extremely difficult and subjective task There are two potential trouble spots for individuals validating the project First, they may overvalidate a model and conse quently waste resources Second, they may insufficiently validate a model; consequently, the results of the model may be in error In this paper, the validation process is divided into two separate phases Within each phase, techniques using decision theory con cepts are presented to aid in the validation process

How accurate are the predictions of complex air movement models

Abstract: The validation of computer predictions of physical processes is still a topic of concern, particularly in relation to dynamic thermal simulation modelling. However, far more complex computer programs are now being introduced into the building services industry. These new programs solve the conservation equations of momentum, energy and mass to simulate air movement in and around buildings. The validation task is potentially more difficult than that encountered to date. This paper discusses some of the problems associated with the application and validation of these codes and suggests how a user can ensure that the physical processes are being modelled realistically.

Simulation model testing

Abstract: THe cost of repairing an error in a simulation program increases with the length of time that the error remains in the system. Simulation model testing, an analog to and extension of software testing, is proposed as an attempt to aggressively seek errors latent in a simulation model/program. Goals of and a preliminary set of techniques for simulation model testing are presented, as are the results of an initial investigation of its utility.

Large system simulation using Ada

Abstract: This paper describes the significant positive impact that the Ada® programming language can have on the development and application of simulation models. The Ada language has specific features which are shown to be ideally suited for implementing the unique requirements of discrete-event simulation, including such simulation functions as list processing, dynamic memory management, and event calendar management. Experiences and conclusions are described based upon the development of a general purpose discrete-event simulation package. The central issues of discrete-event simulation are addressed by describing the implementation of key simulation requirements in the package and indicating how Ada language capabilities drove the design of these features. Examples of design alternatives of general interest to both simulation modelers and Ada developers are presented. In addition, issues related to very large simulation models such as long model running times and verification of complex models are specifically addressed.

Space station data management system: A common GSE test interface for systems testing and verification

Abstract: This paper examines the fundamental problems and goals associated with test, verification, and flight-certification of man-rated distributed data systems. First, a summary of the characteristics of modern computer systems that affect the testing process is provided. Then, verification requirements are expressed in terms of an overall test philosophy for distributed computer systems. This test philosophy stems from previous experience that was gained with centralized systems (Apollo and the Space Shuttle), and deals directly with the new problems that verification of distributed systems may present. Finally, a description of potential hardware and software tools to help solve these problems is provided.