Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
On the use of model-driven engineering principles for the management of simulation experiments
Date
2019-04-03
Author
Dayibas, Orcun
Oğuztüzün, Mehmet Halit S.
Yilmaz, Levent
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
192
views
0
downloads
Cite This
Simulation experiments are an essential part of computational science and engineering. The use of simulation models is widely adopted by practitioners from diverse areas of applied sciences. Nevertheless, simulations are rarely replicated due to reuse and maintenance challenges related to models and data. In this respect, we propose that crucial and labor intensive parts of simulation experiments could be supported by model transformations. This work focuses on model-driven engineering practices to enable replicable and reusable simulation experiments. These practices are used to devote researchers' time to analyze the system under investigation rather than dealing with low level details to create a working environment. The results of our framework development work are presented.
Subject Keywords
Modelling and Simulation
,
Software
URI
https://hdl.handle.net/11511/47293
Journal
JOURNAL OF SIMULATION
DOI
https://doi.org/10.1080/17477778.2017.1418638
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Modeling cultures of the embedded software industry: feedback from the field
Akdur, Deniz; Say, Bilge; Demirörs, Onur (Springer Science and Business Media LLC, 2020-06-01)
Engineering of modern embedded systems requires complex technical, managerial and operational processes. To cope with the complexity, modeling is a commonly used approach in the embedded software industry. The modeling approaches in embedded software vary since the characteristics of modeling such as purpose, medium type and life cycle phase differ among systems and industrial sectors. The objective of this paper is to detail the use of a characterization model MAPforES ("Modeling Approach Patterns for Embe...
Towards interoperable and composable trajectory simulations: an ontology-based approach
Durak, U.; Oğuztüzün, Mehmet Halit S.; Algin, C. Koksal; Ozdikis, O. (Informa UK Limited, 2011-08-01)
Trajectory simulation is a software module that computes the flight path and flight parameters of munitions. It is used throughout the engineering process, including simulations for studying the design trade-offs, to mission simulations for defended area analysis. In this wide application domain, reuse has always been one of the challenges of the trajectory simulation community. We apply an ontology-based simulation development methodology to fulfil the functional requirements of a trajectory simulation whi...
Numerical simulation of solidification kinetics in A356/SiCp composites for assessment of as-cast particle distribution
CETIN, Arda; Kalkanlı, Ali (Elsevier BV, 2009-06-01)
The present work is aimed at studying the effect of solidification rate on reinforcement clustering in particle reinforced metal matrix composites (PMMCs) through numerical simulations and experimental studies. A macrotransport-solidification kinetics (MTSK) model was used to simulate the solidification kinetics of the PMMCs. The experimental validation of the numerical model was achieved through the Newtonian and Fourier thermal analysis methods. Results reveal that the MTSK model can be successfully used ...
Non-autonomous equations with unpredictable solutions
Akhmet, Marat (Elsevier BV, 2018-06-01)
To make research of chaos more amenable to investigating differential and discrete equations, we introduce the concepts of an unpredictable function and sequence. The topology of uniform convergence on compact sets is applied to define unpredictable functions [1,2]. The unpredictable sequence is defined as a specific unpredictable function on the set of integers. The definitions are convenient to be verified as solutions of differential and discrete equations. The topology is metrizable and easy for applica...
Modelling and predicting binding affinity of PCP-like compounds using machine learning methods
Erdaş, Özlem; Alpaslan, Ferda Nur; Department of Computer Engineering (2007)
Machine learning methods have been promising tools in science and engineering fields. The use of these methods in chemistry and drug design has advanced after 1990s. In this study, molecular electrostatic potential (MEP) surfaces of PCP-like compounds are modelled and visualized in order to extract features which will be used in predicting binding affinity. In modelling, Cartesian coordinates of MEP surface points are mapped onto a spherical self-organizing map. Resulting maps are visualized by using values...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Dayibas, M. H. S. Oğuztüzün, and L. Yilmaz, “On the use of model-driven engineering principles for the management of simulation experiments,”
JOURNAL OF SIMULATION
, pp. 83–95, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47293.