How to Setup Batch Runs in Adams Using Adams Insight

Basic Requirements

Several methods exist with which batches of simulations can be setup and run in Adams, from very basic to highly advanced, from simple batches to automated optimisations.

Basic requirements:

1. At least one design variable must exist in the model with a standard (default) value as well as its range of values, e.g.:

2. The design variable must be referenced (used) somewhere in the model, like the examples below:
3. A measure (or objective function) must exist in the model, e.g.:
In the above example of a horizontal double pendulum that will fall under gravity, the X-location, where the two links join, is determined by the value of the design variable.

Method 1: Quick and simple (only one objective & one or more design variables):

1. Create a study using the Design Evaluation Tools option.
2. Select the measure (result) to study.
3. Set which value of the measure (last, min, max, avg., RMS or STDEV) to study.

4. Set the type of study:
4.1. If Design Study, set which design variable to change and how many simulations to run. The design variable value will be changed from its set minimum to maximum in that many steps (levels).
4.2. If Design of Experiments, more design variables can be selected, and how the range of values should be calculated.
PS: If the design variable changes a location, the Preview option can be used to see the layout changes in the model for the various parameter values.
4.3. If optimisation, more design variables can be selected, and whether to minimise or maximise the studied measure value (last, min, max, avg., RMS or STDEV).
NB: Unlike the design study and design of experiments, the optimisation changes the design variable(s) to drive the result value (last, min, max, avg., RMS or STDEV) to a minimum or maximum.
5. Start the study:
The batch of models will now run, applying the changes to the design variable(s).
Tip: The batch of runs will complete much faster if the Update Display option is off:
By default, the default or last simulation settings used (from an earlier analysis) are used:
6. Once finished, the goal (objective) value will be shown in a graph for each iteration, and the list of results vs. design variable(s) values can be shown:

Method 2: More advanced - Adams Insight

If more advanced settings are required, creating an Adams Insight Experiment provides more control over the input distribution, linking variables and optimisation methods.

  1. Create an objective and reference a previously created measure or request, or define a function or macro:
2. Create an Adams Insight experiment:
3. A new window opens:
4. Expand the Factors and Responses. The available design variables, point coordinates and objectives in the model are now listed:
5. You now need to select (promote) the variables and objectives, from those created, to use in this study:
6. Random distributions of the Design Variable values, for stochastic and/or designs of experiments, can now be set:
7. For the objective(s), the optimisation target can be set:
8. Save the experiment setup:
9. The design specification can further be set in terms of how the input variable values should be spread and how many runs are requested:
10. Using the provided input, the next step is to show the chosen/calculated input values for the design variable(s):
11. If this range and distribution of input values are as required, the batch of analyses can be started:
12. Adams View will open and show the results:
13. A table of the requested result values can be found in the workspace details of the experiment:
14. The results are also available in the post processor but limited to the included design variable and objective values:
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