Trial and Error: an Outdated Approach

In the past, only trial-and-error approach was used in the design process. Given a problem, it was solved directly, without knowing the indirect consequences onto other aspects. A solution was achieved only after several iterations which were impossible to quantify previously. The time-to-market needs becoming more strict, this approach is effective no more. Since the origins and alongside the design path, the Customer must think about system in its entirety. The must is to consider every single component not only as a single entity, but also as a player which interacts with other components mutually. The System Modeling concept is born.

The System Modeling Approach

DOFWARE has a deep and certified expertise concerning modeling of systems involving several different physical aspects. Dymola is the reference platform, based on Modelica standard language. Within this framework, the typical approach to the System Modeling could be subdivided into the following steps:

  1. System analysis in its entirety;
  2. Identification and isolation of every single component which can be modeled virtually by means of ordinary differential equations, algebraic relations and/or appropriate algorithms;
  3. Appropriate model construction for every single component: either by exploiting what Dymola/Modelica libraries already offer or by implementing from scratch mathematical algorithms with Modelica language;
  4. Virtual system assembly: single component models are made communicate by the simple drag&drop technique; the multi-physical nature of the Dymola solver enables components belonging to different domains to interact without any problem.


  • pre-design: high-level models implementation for analyzing and for comparing preliminary configurations during feasibility studies;
  • design: collaborative platform creation where engineering domains interact, each by inserting its pertaining models and by recovering constraints coming from other domains;
  • on-design calibration: once a real prototype has been built, an experimental campaign is performed which allows the calibration of the virtual system model and the evaluation of the margins of error;
  • off-design evaluation: by exploiting the calibrated model, the system is made work in critical operating conditions (e.g. dictated by regulations) and possible malfunctionings are highlighted;
  • control logics validation: the calibrated model allows the validation of control algorithms, even implemented in different environments;

optimization: by means of appropriate mathematical strategies (ranging from gradient-based to evolutionary algorithms), the design variable optimal parameters are identified which minimize the objective functions chosen by designers. By exploiting the computational lightness of system models, DoE (Design of Experiments) activities can be performed beforehand for identifying the most influencing parameters. DOFWARE uses several tools to this aim, beloging both to the commercial (Dymola®, Isight®, Matlab®) and to the open-source (Scilab, Dakota, Octave, Python™, OpenModelica) worlds;

  • MiL-HiL: by means of hard real-time techniques, the developed models are made communicate among themselves in order to certify the cohesion to the theoretic models. The same check is then performed by building a co-simulation system between the plant and the real hardware;
  • virtual realities: mathematical models are put inside immersive 3D graphical engines in order to reproduce the behavior of the real world. The main applications pertain to the implementation of technical personnel training tools and of monitoring systems of hostile places.