Digital Twin applications using the SIMULTAN data model and Python

Abstract

Python is an open, general-purpose programming language that is used in many tools, libraries and APIs for Building Performance Simulations (BPS). Advantages of Python in the context of digital twins are the simple and powerful capabilities to generate input files, automate processes, import libraries in many languages and a large number of useful modules. However, in order to use BPS tools and libraries with real time data, a comprehensive data model is required in which all necessary data such as geometry, system engineering, databases, sensors, or simulation parameters for the different BPS are defined. Python in combination with SIMULTAN as a suitable open Building Information Modelling (BIM) data model allows an effective use of these tools and libraries to perform and automate analyses. This paper presents a Python module that integrates the SIMULTAN model in Python and enables almost seamless integration with minor adaptations to existing tools or modules. The import is achieved using simple text-based templates for the data types and their mapping in the data model. The data model, the definition of the data types and the use of this module is demonstrated by calculating the trend of the CO2 concentration in a zone of a digital twin using real time data.

Development of Plugins for seamless Integration of the SIMULTAN Meta Data Model with IDA-ICE and RFEM 6

“…[1] A proof of concept for solving this problem with the SIMULTAN Meta Data Model (MDM) for the evolution of a virtual building from design through construction into operation has been shown in [1,2] and [3]. While an example of the seamless integration of specialised tools developed by domain experts has been given in [4], the coupling of proprietary software in the design phase is yet to be explored.…”

“…Figure1. Core SIMULTAN classes as described in[2] and used by[4]. Components serve as hierarchical containers which contain Parameters and other Components.…”