Multibody System Dynamics - Science topic

Dear Rajesh Kolkundi

It would be better if u could attach the geometry of your problem with boundaries you had applied on walls.

Hi Subhash,

You are looking for an object tracker / feature matcher. Here below a few tools I remember of:

1) https://physlets.org/tracker/ -> it's manual, quick and dirty for analysing a small quantity of data.

2) https://opencv.org/ -> start writing some code, requires some learning curve but scales better with large amount of data ( see https://docs.opencv.org/trunk/dc/dc3/tutorial_py_matcher.html , https://stackoverflow.com/questions/42938149/opencv-feature-matching-multiple-objects, https://docs.opencv.org/trunk/dc/dc3/tutorial_py_matcher.html, and https://www.pyimagesearch.com/2018/07/23/simple-object-tracking-with-opencv/). If you start analysing frame by frame, at some point you will need to move a probabilistic model overlay ( http://www.cs.toronto.edu/~urtasun/courses/teaching.html).

3) http://www.mousemotorlab.org/deeplabcut -> this tool seems promising enough, but computationally heavy.

Keep it simple if you can.

Best,

Andrea

You might be interested in

The educational version of SAMS/2000 can be downloaded from John Wiley & Sons, Inc.

https://www.wiley.com/en-us/Computational+Dynamics%2C+3rd+Edition-p-9780470686867

yes i do it several times, so you can see my researches

Valuable submission by Dr. Amjad Albayati and Dr. Victor Nazimko.

I agree with your statement.  All the tools and programs are expensive so I have used a combination of many evaluations on children to come to conclusions.  Here is a couple of guides we have used to train resident on:

Dear Shinaj,

of course I would say that reading the recommended literature above is inevitable, however I think that it is possible to break down the answer on few core considerations after which you may find through the specific case you have.

1) Principal component  (PCA) vs. factor (axis) analysis (FA). When you want to reduce the data-set (lots of items) to few variables (e.g. summed factor scores for participants that cover the data best), then you choose principal component analysis. In other words, the goal is describing the participants data in the least possible numbers of variables. These then would be the sum scores of the items which belong to the components (at least if it makes apparent sense putting the found items together, and be carefull, explaining all variance also means that this includes binning 'item specific' variance and systematic (factor explained) variance together, which inflates the overall amount of explained variance. Example: You measure response time for each item in a questionnaire and PCA will find a component, which explains the 'longer' reading time, which is due to the length of the given questions the participants read. This will not happen that easily in FA which seeks to separate the item specific variance and the 'meaningful' covariance between items). Hence, when you believe that there is a fine-grained factor structure behind the data, and this is the only thing you want to know, then choose an axis analysis, which is more sensitive to this (usually simply termed factor analysis).

2) Rotation.First, rotation means that you optimize the solution by rotating the (hypothetical) factors in the space of observations such that as much as variance can be explained by the factors, and to further differentiate the factor loadings on the items. When you perform PCA, rotation is futile, because the analysis by definition searches for othogonal components that explain most of the variance (highest factor loadings). Hence, rotation will only give you (nearly) the same results. When using FA rotation makes sense, because FA searches for the structure in the first place, but not maximum variance explanation. After conducting a rotation, which again optimizes factor loadings, you can more easily see which item belongs to each factor. The basic choice further is between orthogonal and oblique rotation, e.g. varimax rotation, which assumes that factors are independent (orthogonal), and promax rotation, which assumes that factors are dependent (oblique/correlated). Last one is to be preferred in EFA, because it is exploratory..., and when the factors are in fact indepented, the promax will give the same solution as the varimax.

There are more points, but I hope this helps priming the indepth reading into the complex topic :)

Best, René

Yes, that sounds interesting.

Hello, I develop the opensource software openmeca : https://gitlab.com/damien.andre/openmeca available for Windows, Mac OsX and Linux. OpenMeca is a standalone program designed for educational mechanics. OpenMeca does not support cosimulation. Its usage is very easy but it does not gives realistic drawing of system because openmeca uses symbols instead of real parts with complex geometries.    Some examples are available on youtube.

Thank you very much.

However, I was hoping for (some) more simple and graphical presentation (3D) using any simulation software!

In my view, "Introduction to System Dynamics Modeling" written by George P. Richardson, Alexander L.Pugh III, is a quite easy and helpful reference for teaching the system dynamics methodology in graduate level courses. The book is firstly useful for practical managers and analysts, but on the other hand it is highly recommended as a basic introduction to system dynamics while it will also go over some non-technical examples of computer implementation of this methodology. 

Bifurcations have specific normal forms. In that sense, you do not traditionally find bifurcations using the normal form, you find the normal form of the bifurcation (close to the singularity.) From here you can find the specifics of the bifurcation, but everything rests on knowing the eigenvalues of the system linearized about a certain equilibrium.

It depends on how you want the rigid body to move. 

If you interpolate the yaw-pitch-roll angles, the interpolated orientation trajectory can be counter-intuitive.  The trajecotry also depends on the frame in which you describe the orientation of the rigid body. You can also express the end orientation with respect to the start orientation using yaw-pitch-roll angles and interpolate these. This is sometimes called three-axis interpolation. 

The orientation trajectory can also be interpolated along one rotation axis, with a constant rotational velocity.   This is sometimes a one-axis interpolation or a SLERP, this can be computed geometrically or using quaternions.  This motion is what most people find most intuitive. 

However, these motions only correspond to the natural motion of rigid bodies with specific inertia properties.  If you'll need a motion corresponding to a free floating rigid body, you'll need the Euler equations for the dynamics of rigid bodies.

also you can utilize this plugin in matlab:

which there's the code sources and guides here:

hi mr mostafa

prismatic or revolute joint?

i tried different times (about 1 month) to model the wheels in SimMechanic, ADAMS and working model softwares. but i couldn't model it. after consultation with some of my friends in other univ, i concluded that we don't know a good software to model the wheel behavior on terrain. 

thank you for your helping 

I guess that you mean the "Modal Neutral File"?

Actually this is a binary file format used by MSC Adams that contains the data of a flexible body. It can contain information like the invariants of the inertia matrix, the mode shapes and frequencies of the modal base derived from fixed boundary eigenmodes and constaint modes (through orthonormalization, Craig-Bampton modal synthesis) and the position of the chosen interface nodes and maybe other nodes (for graphical representation).

This data is obtained from a linear FE analysis (eigenmode analysis, substructuring) and the major commercially available FE-solvers can write this file ready for import in Adams.

The 'reduced' modal representation of the deformable body contains much less degrees of freedom than the original nodal representation as tze higher frequency modes are usually truncated.

To 'transfer' a transient analysis, you might have to build an analog model to the FE-model in MBS-software and apply the same time dependent loads at the same interface nodes. If you get similar results will mostly depend on a proper choice of the modal basis.

Prismatic joints have only translation dofs, but screw joints provide both translation as well as rotation together. For a 3D-rigid body, screw motion is the shortest way to get to another point.

You could use prismatic joint to get the same behavior of screw joint by breaking down the rotation part to infinitely small translations.