How to Enable Complex Simulations: The Power of Multiphysics & Digital Thread Seminar

Using Digital Thread to Demonstrate Load Prediction in Finite Element Analysis Workshop

Author: Michael C. Sevier and Timothy Hunter - Milwaukee School of Engineering

Abstract

The goal of most undergraduate courses in finite element analysis (FEA) is to prepare students to adequately use FEA to achieve meaningful results in basic static structural scenarios. This is typically done using a combination of background theory and practical application via commercial software such as Ansys Workbench. While many students may become somewhat proficient at running FEA analyses, it becomes clear during their Capstone Design Project that many struggle to use FEA meaningfully. One such struggle includes the ability to create boundary conditions that accurately reflect the physical environment an object is expected to exist in. This paper describes how a workshop and follow-up demonstration is used to address student misconceptions in load prediction.

The workshop portion asks the student to predict the loading for a pogo stick’s footpad based on the how the pogo stick may be used in practice. Many students incorrectly assume the static weight of the rider as the load. Better students may relate the potential energy at the height of the jump to the strain energy during max compression to determine an equivalent max static load. Nearly every student assumes the load to be evenly distributed across the footpad.

In a separate workshop period, Wolfstar Technologies is brought in to demonstrate their True-Load software using a pogo-stick instrumented with strain gauges and a data acquisition unit. The students are allowed to test the pogo-stick themselves and subsequently view the load bearing results of their tests. The True-Load software is then used to generate FEA transient boundary conditions that reflect the tests recently performed by the students. The FEA results from the test-derived boundary conditions are then compared with the results generated from initial student assumptions. Students are subsequently asked to reflect on why they believe the results are different and what they should consider in future analyses.

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