Samir Nayfeh [CV here] has been part of the small engineering firm Equilibria since 2008. Prior to that, he served as an Assistant and then Associate Professor of Mechanical Engineering at MIT.
We often want to incorporate a finite-element solve into a larger program for design automation or optimization. The example below includes a Python function that runs an APDL script and then checks the output file for errors.
In a previous post, we built a quick model for eddy currents in a plate stationary in a time-varying magnetic field. Here we examine the induced currents and damping force that result from motion of the plate relative to the magnetic field.
In electric machines, there are two common causes of eddy currents: (1) time-varying currents in coils, and (2) motion of conductors relative to sources of magnetic field. In this post, we show how to estimate the current density arising from a time-varying magnetic field passing through a plate.
This post shows how to set exact view orientation, zoom, pan, and lighting in CFD post. This is especially useful for making consistent figures for reports or presentations.
This picture below is a stream-ribbon visualization of a swirling flow, viewed using the built in “Isometric View (Z up).” The view is centered too low and the lighting angle is not favorable.
There is a neat correspondence between the mathematical concept of a constraint and the practice of exact-constraint or kinematic machine design. This leads to some really useful insight for people designing machines with dynamics in mind. The PDF below is the extended abstract for a paper that Justin presented in Austin last week at the ASPE annual meeting.
Thin layers of adhesive, plastic, or rubber are often employed in precision machines for joining, shimming, and sealing. These layers are often the most compliant and most dimensionally unstable elements of an assembly, so it is important to understand their behavior.
Microslip in rolling motion is often very complicated, but the net effect can sometimes be estimated pretty easily based on strain and the resulting changes in velocity.
The power spectral density (PSD) is one of the primary ways we characterize random or broadband signals. In many cases, a PSD is read from a signal analyzer and used qualitatively to describe the frequency content of a signal. But to do anything quantitative with a PSD, we need to understand its units. Continue reading Units of Power Spectral Density→
Paraview is a very powerful tool for post-processing and displaying data, especially from FE or CFD simulations. But because it typically acts on the mesh without the underlying geometry, it doesn’t inherently know about the edges of parts or volumes. In this post, I run through the steps to detect the edges and draw them as a wireframe.