Output Data Organization – Part 2
As stated in Part 1 of the series of blog posts on output data organization, it is helpful to create collections of variables at the experiment level of a simulation which serve as output data repositories. Part 2 of this series on output data organization will outline one way...
Modifications introduced in Modelica 3.4
The Modelica Association released the Modelica Language Specification version 3.4 on 15 May 2017. This blog entry summarises the major changes to the language specification with the aim of helping users to be aware of the changes. These changes have been supported in Dymola since Dymola 2018. Main Changes The...
New Features in Dymola 2019
Dymola 2019 is now out and there are many new features that have been added to this new release. More information on these can be found in the official Dymola 2019 Release Notes. DAE mode for more efficient simulation of large models Improved initial guesses for equations in the...
Dymola Basics: 9. Modelica Language – Variables
This blog post is a continuation from a previous post on the Modelica Language. This blog post goes into a little more detail regarding variable definition and syntax in equations and algorithms. The Class Restriction of a class can restrict the ability to use certain elements and methods, also described...
How to Debug an Engine Model
This blog post describes a procedure to debug a crank-angle resolved engine model (CAREM) in Dymola. It helps narrow down to the cause of the problem in case the engine runs but does not produce the expected results. A CAREM is a multi-domain (mechanics, fluids, thermal, electrical) model so...
Case study: Using Dymola to automate testing and post processing by writing a function
Background – Why does steering feel matter? Creating a realistic feel to the steering of a vehicle model is very important for DiL simulations, due to the role torque feedback through the steering wheel plays in how the driver interprets the dynamic response of the vehicle. A vehicle with...
Profiling
Dymola provides a means to measure where the CPU time is being spent in the model code execution. This feature is known as profiling. Profiling is described in Section 5.7.5 of the Dymola User Manual Volume 1. This blog article supplies further information. Profiling is implemented by inserting timers...
FMI Blockset for Cloud Simulation
The FMI Blockset for Cloud allows co-simulation FMUs to be simulated in the cloud using a REST API. By deploying this as an Amazon Lambda Function we can build powerful and flexible simulation applications that provide a browser based user interface. The goal is to provide a simulation platform...
Multiple object swapping in one go
This blog post follows on from a previous one, Speed up creating your system models, that writes about tips for speeding up model development and editing within the diagram layer. Simple but effective changes in the way we work with models can yield much faster model architecture alterations and...
Vehicle Setup using VeSyMA Motorsports
A key feature of the VeSyMA Motorsports library is the adjustments in the suspensions models which allows vehicle setup. These replicate the physical adjustments available on a race car, such as shims, preload adjusters and variable mounting positions. With 20+ adjustments available in a suspension model, a setup experiment...