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As mentioned in the introduction, FMIGo! is a set of tools for dealing with the FMI standard. The main components are:

Execution backend (fmigo‑*)

The execution backend consists of two sets of binaries: fmigo‑mpi and fmigo‑master/fmigo‑server. fmigo‑mpi is used when communication over MPI is desired, fmigo‑master and fmigo‑server are used when TCP/IP (ZeroMQ) communication is desired.

The backend has the following properties: That one game mac os.

• Written mostly in C++14
• Networked architecture allows connecting simulations that must run on separate physical machines due to licensing constraints
• Ability to solve algebraic loops in initialization mode, if linked with the GNU Scientific Library (see license)
• Various kinematic constraints (shaft, ball joint, lock, hinge etc.), assuming all involved FMUs have the required features
• Ability to compute numerical directional derivatives for FMUs lacking that functionality
• Ability to specify execution order, for Gauss-Seidel stepping. Not strictly allowed in the FMI standard since values must be exchanged at matching communication points, but useful in some cases

Using the execution backend

First off, a word of advice: if you only have a single FMU, you are probably better off using simpler tools such as PyFMI. The primary purpose of FMIGo! is to make it possible to connect two or more FMUs and have such combinations run with reasonable performance without numerically blowing up. With that said we can go on with the rest of this section:

In order for FMIGo! to be of much use, you must pick some method of coupling your simulations. For physical systems FMIGo! provides the SPOOK solver by Claude Lacoursière. Another option is to use the NEPCE method developed by Edo Drenth, which involves adding sinc² filters to FMU outputs and adding stiff springs+dampers to relevant inputs. Some of that work can be automated using our ME→CS FMU wrapper tool. Using special purpose solvers may also be necessary, such as exponential integrators. FMIGo! does not provide this, unless GSL does. On to the example:

You have two FMUs, fmu0.fmu and fmu1.fmu, that you wish to connect with a shaft constraint. By default, shaft constraints are holonomic, meaning the solver will try to keep both angles and angular velocities together. The solver (master) expects to be given references to angle outputs, angular velocity outputs, angular acceleration outputs, and torque inputs. It also expects to be able to request the the partial derivative of angular acceleration wrt torque (mobility aka inverse mass or inverse moment of inertia). Finally, the FMUs must have save/restore functionality (fmi2GetFMUState and friends).

If fmu0.fmu has variables outputs theta1, omega1, alpha1 and tau1, and fmu1.fmu has angle2, angularVelocity2, angularAcceleration2, torque2, then the invocation is:

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The -n option to mpiexec must be the number of FMUs plus one.

Other kinematic constraints are also possible, such as lock constraints, ball constraints and multiway constraints. See the manual for more information about these, and other invocation details.

The output of the backend can be CSV (comma separated values, default), SSV (space separated values) or Matlab .mat files. Column names are 'fmu%i_%s' where %i is the FMU ID (zero-based) and %s is the name of the relevant output variable. Only the variables listed in <Outputs> in modelDescription.xml will end up in the output data. In the above example, some output column names might be fmu0_theta1 and fmu1_angle2.

ssp‑launcher.py

ssp‑launcher.py is used for launching SSPs. It supports enough of the SSP standard for our purposes, plus our extensions listed in tools/ssp/FmiGo.xsd.

Using ssp‑launcher.py

Ensure that the fmigo‑* executables are in your $PATH, and invoke ssp‑launcher.py on your SSP:

Output format is CSV by default.

pygo

pygo consits of some Python classes for abstracting and connecting FMUs (a bit like SSP), and code for converting the output of the backend to HDF5 format. Claude knows more.

wrapper

The wrapper converts ModelExchange FMUs to Co-Simulation FMUs by adding an ODE solver, partial derivatives and optional sinc² filters suitable for NEPCE coupling.

Example invocation, converting ME.fmu into CS.fmu in Release mode:

Invoke python wrapper.py --help for full help. The resulting FMUs are subject to the GNU General Public License version 3 (GPLv3).

cgsl

cgsl is used as a convenience library for us, but may be of use for other people. Online drafting software. Check out tools/csgl/demo in the source code for an example.

Developer: Algoryx Simulation AB

Release date: 2012

Interface language: English

Tablet: Is present

Platform: Intel only

Algodoo (/ˌælɡəˈduː/) is a physics-based 2D sandbox freeware from Algoryx Simulation AB (known simply as Algoryx) as the successor to the popular physics application Phun. It was released on September 1, 2009 and is presented as: a learning tool, an open ended computer game, an animation tool, and an engineering tool. The software is functional with: desktop and laptop computers, touch screen tablets, and interactive white board systems such as SMART Boards. The physics engine in Algodoo utilizes the SPOOK linear constraint solver by Claude Lacoursière and a modified version of Smoothed-Particle Hydrodynamics (SPH) computational method. This program has been used by many people including: educators, students, and young kids.

History

In 2008, Emil Ernerfeldt created an interactive 2D physics simulator for his master's thesis project in computer science at Umeå University in Umeå, Sweden. This project was released for public and non-commercial use under the name 'Phun' and gained considerable attention after a clip of Ernerfeldt using the software went viral on YouTube. In May 2008, Ernerfeldt brought the Phun project to Algoryx Simulation AB, a company founded in 2007 by Ernerfeldt's former supervisor at Umeå University, Kenneth Bodin. In 2009, Phun was rereleased under the name 'Algodoo' (a combination of the words algorithm and do). The name change was motivated by the fact that the word 'phun' is used by many sites deemed inappropriate for younger users and the fact that trademarking 'phun' was nearly impossible. In October 2011, Algoryx released two new versions: Algodoo for Education and Algodoo 2.0.0.[citation needed In February 2017, Algodoo for iPad was updated to version 2.1.2 to maintain functionality with iOS 10. Bouncy box (calle englund) mac os. Now, there is a new 3D system called Algoryx Momentum, also made by Emil Ernerfeldt.

The drop down menu (accessed by double clicking or right clicking an object) includes several tools for liquifying, turning into sponges, cloning, and mirroring objects; for generating plots of physics-relevant quantities of the object (such as velocity vs. time or y-position vs. x-position); for selecting objects; for changing the appearance of objects (including the option to toggle the presence of velocity, momentum, and force vectors); for assigning text to an object; for changing the simulated material of the object (including such parameters as density, mass, friction, restitution, and attraction); for assigning and changing an object's velocity; for a list of the information about an object (including the area, mass, moment of inertia, position, velocity, angular velocity, momentum, angular momentum, energy (total), kinetic linear energy, kinetic angular energy, potential energy (gravity), potential energy (attraction), and potential energy (spring)); for assigning objects to various collision layers; for performing 'geometry actions' (such as gluing objects to the background, adding center axles, adding center thrusters, attaching tracers, attaching gears, or transforming the object into a circle); for editing objects via constructive solid geometry (CSG); for assigning keystrokes for controlling the object; and for opening a script menu for that selected object(s).

User-created simulations in Algodoo are referred to as scenes. With the tools listed above, users can create complex scenes. The easily accessible tools in Algodoo allow new users to quickly create simple things like cars or basic machines, while still allowing more experienced users to make more complex constructions like intricate Rube Goldberg machines.

• Operating System: OS X 10.6.8 +
• Processor: Intel Core 2 Duo
• Video card: 256 MB of memory
• RAM: 1 GB
• 56.7 MBfree disk space

Game installation:

1. To install, copy the game from the image to the hard drive.
2. Information for registering the program (you need to do it after launch, through the menu in the upper left corner), take from the file Serials.txt, which is also located on disk.
3. At the first start, you need to wait 1-2 minutes. Do not end the process at this point: the program did not freeze.

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