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--- start [2025/05/07 11:06] – [Acknowledgements] bp
+++ start [2025/11/22 13:38] (current) – bp
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 {{ :wiki:images:mupif-logo.png?100|}}
 {{keywords> Open Simulation Platform, Digital twin, Interoperability, Modelling, Simulations, Workflows}}
-====== MuPIF ======
+====== MuPIF - Empowering Complex Multiphysics Simulations with Open-Source, Modular Integration and Digital Twin Technology ======
-MuPIF is an open-source, modular, and object-oriented simulation platform designed to create complex, distributed, multiphysics simulation workflows and execute them on distributed resources. It integrates existing simulation tools to handle various scales and processing chains.
-**Key features of MuPIF include:**
+MuPIF is an open-source, modular, and object-oriented simulation platform designed to create complex, distributed, multiphysics simulation workflows with integrated Digital Twin technology.
+**Key MuPIF features**
   * Distributed Design: Allows execution of simulation scenarios involving remote applications and data.
-  * Data Management System (DMS): Builds digital twin representations of physical systems, enhancing predictive simulations.
+  * Data Management System (DMS): Builds digital twin representations of physical systems, enhancing predictive simulations. Provides full traceability.
   * Interoperability: Standardizes application and data component interfaces, enabling seamless integration of different simulation models and data types.
   * Graphical Workflow Editor: Facilitates low-code workflow development and makes implementation more accessible.
@@ Line 15: / Line 16: @@
   * Open Source: Available under LGPL Open source license
-MuPIF utilizes an object-oriented approach, with abstract classes defining standardized interfaces introduced to represent simulation models and data types.
+Read more [[about|about MuPIF and its design]].
-This concept allows to manipulate and steer all models using generic interface. It will also allow to abstract from a particular internal data representation of a data type, including storage and location.
-In turn, the models working with the data obtain required information from data objects using services, rather than obtaining them by interpreting raw data (which yields the data format dependence). One can think of abstract classes as representing data as “data bricks” with standardized connectors able to be used in their appropriate place in workflows to represent abstract data containers.
-MuPIF achieves interoperability with standardization of application and data component interfaces and it is not reliant on standardized data structures or protocols. Any existing data representation or simulation model can be plugged in and used transparently, provided the corresponding data interface is implemented.
-{{ :wiki:images:mupif-distributed-v2-cropped.png?nolink&400|}}
-Even though the platform can be used locally on a single computer orchestrating installed applications, the real strength of the MuPIF platform is its distributed design, allowing to execute simulation scenarios involving remote applications and data. MuPIF provides a transparent distributed object system, which takes care of the network communication between the objects when they are distributed over different machines on the network.
-The simulation workflows are implemented as Python scripts built on top of MuPIF. The graphical workflow editor is available to make the workflow implementation more accessible and convenient.
-MuPIF comes with a Data Management System (DMS) called MuPIFDB. The DMS is used to track integrated simulation workflows, their executions including execution inputs and outputs. It also provides a generic Digital Twin model, which is based on Entity Data Model (EDM). The EDM identifies the individual entities, their attributes and relations between them. The EDM is defined using JSON schema, and the DMS structure is generated from this schema. The EDM allows to map entity attributes to simulation workflow inputs (determining the initial conditions) and simulation workflow outputs can be mapped to newly cloned entities representing updated configuration(s). The EDM can be regarded as hypergraph, where nodes represent entity states and edges representing processes.
+{{ :wiki:videos:mupif_introduction.mp4| MuPIF Introduction}}
 ====== Documentation & Resources ======
+  * <wrap hi>New</wrap> [[tutorials|MuPIF platform video tutorials]]
   * The Musicode project MuPIF training video recording is available on YouTube: [[https://youtu.be/oaN78pB8vxw | Musicode MuPIF training]].
   * The mupif/jupyter-demos repository on GitHub contains
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      * [[http://musicode.eu|H2020 MuSICODE project: An experimentally-validated multi-scale materials, process and device modeling & design platform enabling non-expert access to open innovation in the organic and large area electronics industry]], Grant agreement no. 953187, 2021-2024.
     * DeeMa project (Deep-Learning and Optimisation Enabled Material Microstructure Design), funded by Technology Agency of the Czech Republic, grant agreement no. TH75020002.
+    * INODIN project (Innovative methods for materials diagnostics and monitoring of engineering infrastructure to improve its durability and service life), funded by MŠMT, grant agreement CZ.02.01.01/00/23_020/0008487.