INSTAR, a discrete event model for simulating zooplankton population dynamics

Hydrobiologia ◽  
1982 ◽  
Vol 95 (1) ◽  
pp. 275-285 ◽  
Author(s):  
P. Hogeweg ◽  
A. F. Richter
Keyword(s):  
Population Dynamics ◽  
Discrete Event ◽  
Zooplankton Population ◽  
Event Model ◽  
Discrete Event Model

Rescheduling subway trains by a discrete event model considering service balance performance

2016 ◽  
Vol 40 (2) ◽  
pp. 1446-1466 ◽  
Author(s):  
Xiaoming Xu ◽  
Keping Li ◽  
Lixing Yang
Keyword(s):  
Discrete Event ◽  
Balance Performance ◽  
Event Model ◽  
Discrete Event Model

scholarly journals A discrete event model of clinical trial enrollment at eli lilly and company

2007 ◽  
Author(s):  
Bernard M. McGarvey ◽  
Nancy J. Dynes ◽  
Burch C. Lin ◽  
Wesley H. Anderson ◽  
James P. Kremidas ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Discrete Event ◽  
Event Model ◽  
Clinical Trial Enrollment ◽  
Discrete Event Model

Arena-Based Modeling of the Maintenance Operation for a Wind Farm

2013 ◽  
Vol 401-403 ◽  
pp. 2205-2208 ◽  
Author(s):  
Huai Zhong Li ◽  
Tong Jing ◽  
Hong Zhang
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Discrete Event ◽  
Onshore Wind ◽  
Electric System ◽  
System A ◽  
Factors Influencing ◽  
Event Model ◽  
Main Factors ◽  
Discrete Event Model

Wind energy has become a leading developing direction in electric power. The high cost associated with turbine maintenance is a key challenging issue in wind farm operation as wind turbines are hard-to access for inspection and repair. Analysis of an onshore wind farm is carried out in this paper in terms of the operation, failure, and maintenance. Failures are categorized into three classes according to the downtime. It is found that the pitch, gearbox and generator have the most amount of downtime, while the most number of failures is from the pitch and electric system. A discrete-event model is developed by using Arena to simulate the operation, failure occurrence, and maintenance of the wind turbines, with an aim to determine the main factors influencing maintenance costs and the availability of the turbines in the wind farm.

scholarly journals Validation of a Stochastic Discrete Event Model Predicting Virus Concentration on Nurse Hands

Risk Analysis ◽  
2019 ◽  
Vol 39 (8) ◽  
pp. 1812-1824 ◽  
Author(s):  
Amanda M. Wilson ◽  
Kelly A. Reynolds ◽  
Marc P. Verhougstraete ◽  
Robert A. Canales
Keyword(s):  
Discrete Event ◽  
Virus Concentration ◽  
Event Model ◽  
Discrete Event Model

scholarly journals Approaches to Modeling the Gas-Turbine Maintenance Process

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Tai-Tuck Yu ◽  
James P. Scanlan ◽  
Richard M. Crowder ◽  
Gary B. Wills
Keyword(s):  
Decision Making ◽  
Gas Turbine ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Modeling ◽  
Human Decision ◽  
Event Model ◽  
Discrete Event Model

Discrete-event modeling has long been used for logistics and scheduling problems, while multi-agent modeling closely matches human decision-making process. In this paper, a metric-based comparison between the traditional discrete-event and the emerging agent-based modeling approaches is reported. The case study involved the implementation of two functionally identical models based on a realistic, nontrivial, civil aircraft gas turbine global repair operation. The size, structural complexity, and coupling metrics from the two models were used to gauge the benefits and drawbacks of each modeling paradigm. The agent-based model was significantly better than the discrete-event model in terms of execution times, scalability, understandability, modifiability, and structural flexibility. In contrast, and importantly in an engineering context, the discrete-event model guaranteed predictable and repeatable results and was comparatively easy to test because of its single-threaded operation. However, neither modeling approach on its own possesses all these characteristics nor can each handle the wide range of resolutions and scales frequently encountered in problems exemplified by the case study scenario. It is recognized that agent-based modeling can emulate high-level human decision-making and communication closely while discrete-event modeling provides a good fit for low-level sequential processes such as those found in manufacturing and logistics.

scholarly journals AGN variability time scales and the discrete-event model

2005 ◽  
Vol 443 (2) ◽  
pp. 451-463 ◽  
Author(s):  
P. Favre ◽  
T. J.-L. Courvoisier ◽  
S. Paltani
Keyword(s):  
Time Scales ◽  
Discrete Event ◽  
Event Model ◽  
Discrete Event Model
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