CITE THIS NOTEBOOK: Wolfram R&D LIVE: Latest features in System Modeler by Jan Brugard. Wolfram Community MAR 1 2023.

When Can I Use System Modeler?

Dynamic models in a wide variety of domains and combinations thereof

Example—Heat Transfer

What’s New?

New in System Modeler

New in Blogs

New in Libraries

Energy • SaaS • Aircraft

Model of an Electric Grid

Very simplified version of Sweden’s electric grid

Background

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  • Power sources:
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  • Nuclear (Forsmark)
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  • Hydro (Harsprånget)
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  • Wind (Mönsterås)
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  • Consumers:
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  • Luleå
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  • Sundsvall
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  • Stockholm
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  • Malmö
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  • Dispatcher:
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  • Manages power distribution among power sources

    • The Model

    Air Conditioning: Effect of Building Orientation

    Collect data

    Dataset obtained from A. Tsanas and A. Xifara, “Accurate Quantitative Estimation of Energy Performance of Residential Buildings Using Statistical Machine Learning Tools,” Energy and Buildings, 49, pp. 560-567, 2012.

    Preprocess data

    Covert the dataset into a form suitable for training a neural net.
    Add suitable names to headers:
    Helper function to check for missing data:
    Check if the dataset has missing data:
    There are rows with empty elements. They need to be removed before feeding it to the neural net.
    Remove unused columns and rows, and filter out any missing data:
    Obtain numeric values:
    Labelled data:

    Train a Neural Net

    The data is split for training and validation. A neural net consisting of multiple layers is created, and all its learnable parameters are initialized.
    Split data for training and validation:
    Create and initialize a neural net:
    Train for 2 minutes:

    Create a SystemModel

    The trained neural net is converted to an input-output block that can be connected to other models.
    Extract trained net:
    Create a SystemModel from the trained net:

    Connect to the Building Model

    The model is then attached to a single-room building model that consists of walls, roofs and an air conditioner. The connected model can be fed with external temperature data, and its energy performance can be tested.

    Energy • SaaS • Aircraft

    Introduction—Business Simulations

    Why?

    How?

    Example—Growth Strategy of a SaaS Company

    Model

    Simulation results

    Automatically create dashboards

    Energy • SaaS • Aircraft

    Introduction

    With the Aircraft library you can model:
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  • The aerodynamic forces locally on each surface of the aircraft
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  • The forces and torques due to the aircraft's mass properties
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  • Consequently, the aircraft’s motion through air can be modeled and simulated as a 6DOF flight mechanics model
    • When to use
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  • Enables quick testing of the aircraft design for any flight trajectory with high fidelity
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  • Early testing can be done in one single tool which derives aircraft properties from the properties that are available at the conceptual design stage

    • Example—Tow and Glide

    What about the Simulator?

    Sneak Peak—Rotating Machinery

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  • Compatible with Modelica Multibody library.
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  • Includes gears, masses, shafts, supports and rolling bearings.
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  • Easily parametrize 100s of bearings from SKF, NSK, KOYO, etc

    • Example—Bearing

    Simulate system with a defect on the outer ring.
    Plot the default plot (roller force for a specific roller)
    Plot the forces for 6 different rollers

    Example—Planetary Gear