Open Ontology-Based Integration Platform for Modeling and Simulation in Engineering

Abstract

The benefits of the use of modeling and simulation in engineering are acknowledged widely. It has proven its advantages e.g., in virtual prototyping i.e., simulation aided design and testing as well as in training and R&D. It is recognized to be a tool for modern decision making. However, there are still reasons that slow down the wider utilization of modeling and simulation in companies. Modeling and simulation tools are separate and are not an integrated part of the other engineering information management in the company networks. They do not integrate well enough into the used CAD, PLM/PDM and control systems. The co-use of the simulation tools themselves is poor and the whole modeling process is considered often to be too laborious. In this article we introduce an integration solution for modeling and simulation based on the semantic data modeling approach. Semantic data modeling and ontology mapping techniques have been used in database system integration, but the novelty of this work is in utilizing these techniques in the domain of modeling and simulation. The benefits and drawbacks of the chosen approach are discussed. Furthermore, we describe real industrial project cases where this new approach has been applied.

Automatic Generation of Dynamic Simulation Models Based on Standard Engineering Data

“…Conditions too costly or dangerous to test with traditional testing methods can be tested. In industry, despite recognised benefits of utilising simulation, it is commonly exploited only at certain times when needed and usually very late in the engineering workflow (Karhela et al, 2012). Corrective actions are more expensive and cause more disturbances to project schedules compared to if errors would have been discovered and corrected in an earlier phase (Oppelt et al, 2015b;Barth et al, 2013).…”

“…This also applies to offered interfaces available in software. This restricts software interoperability and thereby both resource intensive and error-prone manual information transfer is taking place in the engineering workflow (Karhela et al, 2012;Estevez et al, 2012). However, an emerging trend of utilising standard data models and formats is emerging (Estevez et al, 2012), enabling engineering software interoperability.…”

“…Simulation is not utilised to its full capability due to its laborious modelling requirement, partly as a result of noninteroperable engineering software (Karhela et al, 2012;Oppelt et al, 2014). Modelling effort can be significantly reduced by automating simulation model generation based on available design data (Karhela et al, 2012). In practise this means that simulation software must be made interoperable with plant engineering software.…”

Requirement verification in simulation-based automation testing

“…Steam is injected to maintain the temperature of 220 • C. In addition to these injections, sulphuric acid concentration of 40-50 g/L is maintained inside the autoclave by injecting it to the first compartment to keep the solution acidic enough for metals to dissolve. Simplified flow diagram of the autoclave is illustrated in Fig 2. The process and its automation were modelled using a tool called Apros, which is built using software implementation platform called Simantics [14].…”

Simulating Cyber-Physical Energy Systems: Challenges, Tools and Methods

“…Generic open-source co-simulation frameworks with a focus on energy systems are Simantics [40] and Mosaik [41]. They both provide extensive functionalities for formal model description and couplings to other simulation engines.…”