Dynamic simulation has been used in the process industry during decades for several important applications over the process plant lifecycle. Recent trends on plant digitalization have resulted on the development of Simulation-based Digital Twins (SBDT) of process plants. In a SBDT, a dynamic first-principles simulation model is used to capture the process plant dynamics. In this application, the first-principles model (FPM) of the plant is run in parallel with the process while dynamic model parameter estimation methods adjust the model results by comparing process measurements with model results to continuously drive the simulated state to the current plant state. As a result, the underlying FPM of the SBDT is continuously synchronized with the operational plant. SBDTs can provide non-measured information of the process and they can be used to obtain high-fidelity predictions that are based on the current state of the process. They can also be utilized to develop operator training simulators, trouble-shooting and fault diagnoses systems. Furthermore, they can be applied for offline and online optimization of the plant. SBDTs are a holistic application for operation support of process plants. However, development of their underlying FPM remains laborious and expensive. Although re-utilization of existing models, developed for plant engineering, could reduce implementation effort and time of SBDTs, these models are still created manually. Moreover, integration of SBDTs with the ICT architecture of the plant could leverage on existing industrial operability standard to seamlessly interface different simulation methods and other SBDT system components with the plant. In this thesis, these implementation shortcomings are tackled by utilizing a combination of implementation methods proposed in this work. First, laborious FPMs development is addressed by applying an AMG method based on deriving 3D plant model information for automatically generating the FPM of the SBDT. Furthermore, laborious integration between the simulation system and the process plant is addressed by utilizing a method for implementing a lifecycle-wide tracking simulation architecture. The main results of the thesis show that the model generated using the proposed AMG approach can be successfully applied for implementing SBDTs after its integration into the physical plant. Furthermore, the proposed simulation architecture leverages on the application of industrial interoperability standards for reducing the effort required for configuring the communication between different architecture components and for enabling systematic information exchange between the architecture components and methods.
|Translated title of the contribution||Simulation-based Digital Twins of Industrial Process Plants: A Semi-Automatic Implementation Approach|
- , Supervisor
- , Advisor
- , Advisor
|Publication status||Published - 2019|
|MoE publication type||G5 Doctoral dissertation (article)|
- digital twin, dynamic simulation, engineering automation, industrial process simulation