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  1. Home
  2. Research
  3. Multi-Scale Multi-Rate Simulation (MS²)

Multi-Scale Multi-Rate Simulation (MS²)

How can simulations help us with the development of complex systems?

Digitization undoubtedly brings many advantages – but it also presents us with new challenges. Combined simulations at various levels, from the overall system to the component, are used to provide answers to what-if questions including many variables that influence each other. This type of question is, for example, common in the transportation sector. What happens if driving on public traffic routes suddenly costs money? Or what happens to traffic if downtown areas are closed to cars? How do assistive systems influence traffic flows? Co-simulations run through varying scenarios and evaluate them to facilitate improved system understanding. They are an important tool for the ensuring of system characteristics.

Such simulation systems are also helpful in the energy sector, where the so-called "energy revolution" is resulting new structures and requirements. Our energy is increasingly being provided by small, decentralized producers who are replacing large power plants as key energy suppliers. What was formerly an information-poor energy supply system is becoming a de-centralized, highly complex system, within the scope of which information is exchanged dynamically. The establishment and integration of the ICT infrastructure needed for this purpose requires the use of development methods that both meet requirements regarding the complexity and dynamics of the future energy supply system and are also faster and cheaper than conventional field tests.

This is made possible by complex simulation systems that run multiple simulations simultaneously at different levels. These co-simulations are used to carry out virtual analysis of the interaction between a larger number of  components and architectures within one dynamic overall system.

Multiple simulators that each observe the corresponding differing details of degree and highly diverse systems are linked together. A self-driving car is already a highly complex microsystem that becomes even more complex when competing interests and goals on the macro-level of the roadway system meet and must be weighed against each other. In such cases simulations must be carried out on multiple levels to identify how traffic flow can be optimized in such a way that objectives which, in some cases, are opposed can cooperate with each other. Individual interests such as faster transportation from A to B must be balanced against general rules and goals such as safety, environmental protection, and traffic flow. Parallel to this, systems should be designed in such a way that individual personal freedoms are preserved to the greatest extent possible.

Complex co-simulation models can signifi cantly shorten the product development process and identify problematic issues relating to the interaction of many functions and components at an early stage. The Multi-Scale Multi-Rate Simulation competence cluster carries out virtual testing of prototypes; optimizes and validates design processes; and examines model creation for descriptive research. Over and above this, co-simulation itself is a research focus.

  • Applied Artificial Intelligence (AAI)
  • Architecture Frameworks (AF)
  • Cyber-Resilient Architectures and Security (CRAS)
  • Embedded System Design (ESD)
  • Human Machine Cooperation (HMC)
  • Multi-Scale Multi-Rate Simulation (MS²)
  • Sustainability
  • Safety Relevant Cyber Physical Systems (SRCPS)

Chairman of the Competence Cluster

Axel Hahn
Axel Hahn

Persons

F

Martin Fränzle

E-Mail: Martin.Fraenzle(at)uni-oldenburg.de, Phone: +49 441 9722-500, Room: D122

H

Axel Hahn

E-Mail: axel.hahn(at)offis.de

L

Prof. Dr. rer. nat. Sebastian Lehnhoff

E-Mail: sebastian.lehnhoff(at)offis.de, Phone: +49 441 9722-240, Room: O50

Projects

2020

Int2Grids

Integration von intelligenten Quartiersnetzen in Verbundnetze

Duration: 2020 - 2023

ENSURE Phase 2

Neue EnergieNetzStruktURen für die Energiewende (Phase 2)

Duration: 2020 - 2023

2019

ZLE

Zukunftslabor Digitalisierung Energie

Duration: 2019 - 2025

Publications

2021

Introduction to SmartKai

Sebastian Feuerstack; SICK Sensors Oceans Conference; August / 2021

BIB
SmartKai: LIDAR Based Real-Time Detection and Tracking of Moving Objects in Maritime Environments

Aparna Nagarajan, Jan Mentjes, Sebastian Feuerstack, Axel Hahn; SmartKai: LIDAR Based Real-Time Detection and Tracking of Moving Objects in Maritime Environments; 2021

BIB

2019

Distributed multi-objective scheduling of power consumption for smart buildings

Marvin Nebel-Wenner,Christian Reinhold,Farina Wille,Astrid Nieße,Michael Sonnenschein; Energy Informatics; September / 2019

PDF DOI BIB
Virtual power plant architecture using OpenADR 2.0b for dynamic charging of automated guided vehicles

Mitja Kolenc and Norman Ihle and Christoph Gutschi and Peter Nemček and Thomas Breitkreuz and Karlheinz Gödderz and Nermin Suljanović and Matej Zajc; International Journal of Electrical Power & Energy Systems; 2019

DOI BIB

2018

Behavior Tree Based Knowledge Reasoning For Intelligent Vessels In Maritime Traffic Simulations

Volker Gollücke and Daniel Lange and Axel Hahn and Sören Schweigert; European Conference on Modelling and Simulation, ECMS 2018, Wilhelmshaven, Germany, May 22-25, 2018, Proceedings; 2018

DOI BIB
Behavior Tree Based Knowledge Reasoning For Intelligent Vessels In Maritime Traffic Simulations

Volker Gollücke and Sören Schweigert and Daniel Lange and Axel Hahn; European Conference on Modelling and Simulation, ECMS 2018, Wilhelmshaven, Germany, May 22-25, 2018, Proceedings; 2018

DOI BIB
Co-simulation Set-up for Testing Controller Interactions in Distribution Networks

Jorge Velasquez, Felipe Castro, Davood Babazadeh, Sebastian Lehnhoff, Thomas Kumm, Daniel Heuberger, Riccardo Treydel, Tim Lueken, Steffen Garske, Lutz Hofmann; July / 2018

URL DOI BIB
Konzept eines modellgestützten telemedizinisch-supervidierten Trainings am Beispiel von KHK-Patienten

Frerk Müller-von Aschwege; Januar / 2018

BIB

2017

Automatic SDF-based Code Generation from Simulink Models for Embedded Software Development

Maher Fakih and Sebastian Warsitz; HIP3ES 2017 ; 1 / 2017

URL BIB
Cyber-Physical Energy Systems Modeling, Test Specification, and Co-Simulation Based Testing

A. A. van der Meer, P. Palensky, K. Heussen, D. E. Morales Bondy, O. Gehrke, C. Steinbrink,M. Blank, S. Lehnhoff, E. Widl, C. Moyo, T. I. Strasser, V. H. Nguyen, N. Akroud, M. H. Syed,A. Emhemed, S. Rohjans, R. BrandlA. M. Khavari; 2017 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems; August / 2017

BIB
EN: Alle Publikationen aus dem Competence Cluster Multi-Scale Multi-Rate Simulation (MS²)
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