Modeling and simulation of large-scale Systems: a systematic comparison of modeling paradigms

@article{Schweiger2020ModelingAS,
  title={Modeling and simulation of large-scale Systems: a systematic comparison of modeling paradigms},
  author={Gerald Schweiger and Henrik Nilsson and Josef Schoeggl and Wolfgang Birk and Alfred Posch},
  journal={ArXiv},
  year={2020},
  volume={abs/1909.00484}
}
View PDF on arXiv
18 Citations
Background Citations
2
Methods Citations
1
Results Citations
1

Figures and Tables from this paper

18 Citations

Ship-course modeling and control using the SIMSCAPE physical modeling environment
TLDR
The ship-course control system model here developed represents an interesting benchmark in the field of engineering systems to get insight on the physical modeling approach under SIMSCAPE or even under MODELICA, despite its specificity to marine systems.
Experiences from City-Scale Simulation of Thermal Grids
TLDR
The experiences from developing and working with a city-scale simulator of a district heating grid located in Lulea, Sweden and lessons learned are presented along with future research directions, corresponding to identified gaps and challenges.
Coupling physical and machine learning models: case study of a single-family house
TLDR
A physical model of a building’s heating system implemented in Modelica is cosimulated with a machine learning models of a stratified hot water tank implemented in Python, exported as Functional Mock-up Unit using UniFMU.
Enabling large-scale dynamic simulations and reducing model complexity of district heating and cooling systems by aggregation
ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling
TLDR
ModelingToolkit is described, a symbolic equationbased modeling system which allows for composable transformations to generate stable, efficient, and parallelized model implementations and how composable model transformations can be combined with automated data-driven surrogate generation techniques, allowing machine learning methods to generate accelerated approximate models within an acausal modeling framework.
District Heating Systems: An Analysis of Strengths, Weaknesses, Opportunities, and Threats of the 4GDH
TLDR
The ability of 4GDH to serve as a label bundling and stimulating considerations with respect to the further development of district heating systems and the increased value creation within the national economy through the inclusion of local, renewable energy sources were weighted with the highest relative importance.
Active consumer participation in smart energy systems
Decarbonization of Industrial Energy Systems: A Case Study of Printed Circuit Board manufacturing
TLDR
This paper presents the modelling work towards the creation of a Digital Energy Twin of the energy supply system of a printed boarding circuit manufacturing by means of a classical use case, system design optimization.
Connected Components in Undirected Set-Based Graphs. Applications in Object-Oriented Model Manipulation
TLDR
This work introduces a novel algorithm for finding the connected components of a graph where the vertices and edges are grouped into sets defining a Set--Based Graph, which has the remarkable property of achieving constant computational costs with the number of vertice and edges.
Machine learning approach for higher-order interactions detection to ecological communities management
...
...

References

SHOWING 1-10 OF 47 REFERENCES
An Empirical Survey on Co-simulation: Promising Standards, Challenges and Research Needs
Functional Hybrid Modeling
TLDR
The goal is to combine the strengths of functional programming and non-causal modeling to create a powerful, strongly typed fully declarative modeling language that provides modeling and simulation capabilities beyond the current state of the art.
Solving large-scale Modelica models: new approaches and experimental results using OpenModelica
TLDR
Recently implemented sparse solver techniques in OpenModelica are described in order to efficiently compile and simulate large-scale Modelica models.
Automated Simulation of Modelica Models with QSS Methods : The Discontinuous Case
This study describes the current implementation of an interface that automatically translates a discontinuous model described using the Modelica language into the Discrete Event System Specification…
Type-Based Structural Analysis for Modular Systems of Equations
TLDR
This paper investigates a novel approach to a type system for modular systems of equations; i.e., equation systems constructed by composition of individual equation system fragments that reflects which variables occur in which equations.
An Approach to Parallel Simulation of Ordinary Differential Equations
TLDR
This paper investigates methods to partition and simulate differential equation-based models of cyber-physical systems using multiple threads on multi-core CPUs that can share data across threads to avoid simulation performance degradation due to cache conflicts.
Determining over- and under-constrained systems of equations using structural constraint delta
TLDR
This paper describes a novel technique to determine over- and under-constrained systems of equations in models, based on a concept called structural constraint delta, which makes use of static type checking and consists of a type inference algorithm.
District energy systems: Modelling paradigms and general-purpose tools
The OpenModelica Integrated Modeling, Simulation, and Optimization Environment
  • P. FritzsonA. Pop P. Östlund
  • Computer Science
    Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA
  • 2019
TLDR
An up-to-date brief description of the capabilities of the OpenModelica system, and the main vision behind its development are given.
MODELICA VERSUS TRNSYS – A COMPARISON BETWEEN AN EQUATION-BASED AND A PROCEDURAL MODELING LANGUAGE FOR BUILDING ENERGY SIMULATION
TLDR
The computation time of the Modelica model was three to four times longer than TRNSYS, but it is believed that dismissing equation-based modeling languages as computation- ally inefficient is a premature conclusion.
...
...