scholarly journals Multiscale representation of simulated time

SIMULATION ◽  
2017 ◽  
Vol 94 (6) ◽  
pp. 519-558 ◽  
Author(s):  
Rhys Goldstein ◽  
Azam Khan ◽  
Olivier Dalle ◽  
Gabriel Wainer

To better support multiscale modeling and simulation, we present a multiscale time representation consisting of data types, data structures, and algorithms that collectively support the recording of past events and scheduling of future events in a discrete event simulation. Our approach addresses the drawbacks of conventional time representations: limited range in the case of 32- or 64-bit fixed-point time values; problematic rounding errors in the case of floating-point numbers; and the lack of a universally acceptable precision level in the case of brute force approaches. The proposed representation provides both extensive range and fine resolution in the timing of events, yet it stores and manipulates the majority of event times as standard 64-bit numbers. When adopted for simulation purposes, the representation allows a domain expert to choose a precision level for his/her model. This time precision is honored by the simulator even when the model is integrated with other models of vastly different time scales. Making use of C++11 programming language features and the Discrete Event System Specification formalism, we implemented a simulator to test the time representation and inform a discussion on its implications for collaborative multiscale modeling efforts.

2014 ◽  
Vol 1 (4) ◽  
pp. 233-242 ◽  
Author(s):  
Moo Hyun Cha ◽  
Duhwan Mun

Abstract A magnetically levitated vehicle (Maglev) system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS) formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.


2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Joong Soon Jang ◽  
Sang C. Park

A mission reliability evaluation methodology for a signal traffic controller is presented in this paper. To develop the new evaluation methodology, this paper combines the Discrete Event System Specification (DEVS) formalism which has been popular in manufacturing area for three reasons: (1) its features compatible with the object-oriented modeling; (2) its rigorous formal definition; and (3) its support for the specifications of discrete event models in a hierarchical and modular manner. By using the DEVS formalism, we construct a simulation model which takes into account not only the characteristics of a traffic signal controller but also the operating environment. Once a model is constructed, it is possible to perform simulation experiments. The proposed methodology computes the mission reliability of a traffic signal controller by using a simulation record, and this information plays a vital role in preparing optimized maintenance policies that maximize availability or minimize life cycle costs.


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