Uncertainty Quantification (UQ) studies allow us to determine whether a model is fit for a particular purpose, as well as the operational domain in which it can be used. Standardising the UQ analysis setup and result summary enables the iterative composition of UQ information, which is a crucial step in evaluating model credibility. In this paper, we present an initial attempt to specify UQ information as a cross-layer standard for Modelica-, FMI-, and SSP-based workflows subject to two essential restrictions: (a) uncertainties can only be described in terms of parameters, and (b) analysis is limited to forward uncertainty propagation and sensitivity analysis of nonlinear models. More analysis features are planned for the future. The approach is illustrated using both a simple example and an industrial use case.

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The Modelica language (Modelica.org) makes it easy to build large, complex models by allowing the instantiation of reusable component models. Modelica tools typically expand arrays of variables, equations and components and perform symbolic transformations on the scalar elements. This reduces the efficiency of the translation process and makes it difficult to change array dimensions after translation.

Scalarization can be avoided by imposing certain restrictions on the way models are written. This paper describes such restrictions, and the algorithms needed to be applied during the translation. As a result, arrays are resizable after translation and also during simulation. Several examples demonstrate the approach with the Web App Modiator. As a side effect, it is also shown how to provide meaningful diagnostics for erroneous models.

The Modelica language (www.modelica.org) has become a de facto standard for systems modeling and many tools exist. This paper describes certain modern enhancements and a static web app implementation called Modiator (Modelica Instant Simulator). It allows an improved immediate first-time user experience since the web app is available in seconds and simulations can be done directly in the browser. State of the art numerical solvers from the Sundials suite have been compiled into WebAssembly. The Modelica model is translated into Javascript code using techniques such as sorting, tearing, index reduction, state selection, etc. A subset of Modelica is supported with some extensions, for example, support for self-modifying models. This paper also presents the Fluid1D and Model3D libraries.