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MotionSolve User Guide
MotionSolve is a system level, multibody solver that is based on the principles of mechanics.
MotionSolve Optimization Guide
Optimization Output Data
Every optimization run generates a variety of files.

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Overview
MotionSolve^® is an integrated solution to analyze, evaluate, and optimize the performance of multibody systems.
Tutorials
Discover MotionSolve functionality with interactive tutorials.
MotionSolve User Guide
MotionSolve is a system level, multibody solver that is based on the principles of mechanics.
- Introduction to MotionSolve
- Platform Support, Recommended Hardware, and Licensing
- Run MotionSolve
- Model Systems
- Model Simulations
- Visualize Results - Animation and Request Plots
- Couple MotionSolve with Other Software
- Customization Capabilities
- Analysis Tips
- NLFE Bodies Introduction
- User Subroutines in MotionSolve
- msolve API
- MotionSolve Verification Manual
- MotionSolve Optimization Guide
  - Introduction
    The MotionSolve Optimization Guide explains the design sensitivity and optimization capabilities in MotionSolve.
  - Optimization Capabilities in MotionSolve
    Optimization capabilities in MotionSolve include equations of motion for a multibody system, design variables and limits, and analysis support.
  - Application Areas
    Optimization is a vast area that has a many applications in diverse areas such as engineering, economics, business and medicine.
  - Optimization Input Data
    The input data for an optimization is organized in a python parametric model class with methods that operate on the class.
  - Optimization Output Data
    Every optimization run generates a variety of files.
    - summary.log
      The log file for the design optimization run, which contains the overall history of the optimization run.
    - design.log
      This file contains the design variables at each iteration.
    - logfile.log
      logfile.log is generated by the optimizer and records the sequence of events happening underneath, which is useful to troubleshoot optimization crashes.
    - jsonData.py
      Created by the optimizer before the optimization and updated at the end of each iteration.
    - Directories
      Each optimization cost, constraint, or sensitivity evaluation results in a complete simulation.
  - Advanced Topics
    Advanced topics include a scaling optimization problem and tips on how to debug optimization runs.
  - SLA Suspension Example
    This example, referred to as MV3010 in this section, describes the optimization of an SLA suspension and is also available in MotionSolve tutorial topics/solvers/ms/optimization_using_mv_hs_intro_r.html.
  - PID Controller Example
    In this example, we are designing a PID controller whose job is to minimize the effects of a disturbance force on the position, velocity, and acceleration of a block.
  - Glossary
- MotionSolve Environment Variables
- References
MotionSolve Reference Guide
This manual provides a detailed list and usage information regarding command statements, model statements, functions and the Subroutine Interface available in MotionSolve.

Optimization Output Data

Every optimization run generates a variety of files.

The figure below summarizes the output from a typical optimization run.

Figure 1. The output from an optimization of the four bar mechanism

The output from an optimization run is stored in a directory where the simulation was performed. The directory is given a unique name so that it does not conflict with any other existing directory. For the example shown, the directory test-4bar_115807 was created.

Inside this directory, subdirectories and two output files are created.