Electrostatic Actuated Beam Optimization Case Study

Transcription

1 Electrostatic Actuated Beam Optimization Case Study Coupling modefrontier with ANSS

2 SEP :02:33 1 VOLUMES Electrostatic Actuated Beam Model TPE NUM Problem Description: An electrostatic structural analysis is performed to determine the deflection of a silicon beam for a MEMS switch. A clamped beam for an RF MEMS switch device is modeled to compute the center deflection for an applied voltage. Electrostatic clamped beam analysis Forces generated by the electrostatic field will bend the beam towards a ground plane. 2

3 1 VOLUMES TPE NUM U SEP :31:49 FE Geometry & Boundary Definition Boundary Conditions MENTS T N SEP :51:37 Electrostatic clamped beam analysis Surface Interface, Voltage and Ground Potential Locations ctrostatic clamped beam analysis 3

4 Optimization Problem Definition What do we want to improve? Objectives To determine the optimized geometric configuration of the Electrostatic Actuated Beam Model when subjected to a multi objective optimization: Maximize Displacement, Minimize Electric Potential, Minimize Volume Why to Maximize Displacement In order to maximize the performance of the system. Why to Minimize Electric Potential Higher operating voltages exponentially decrease the operating lifetime of the switch. Why to Minimize Volume Minimize the Mass and Material Cost.

5 Multi- Objective Electrostatic Actuated Beam Optimization Problem Definition In modefrontier TM Create workflow in modefrontier Parameter Domain Define the Inputs and their Domains Beam Length mm Set Ansys as an Application Node Beam Width mm Set the Logic flow Set the Outputs Set the Objectives: 1 ELEMENTS Beam Height Voltage mm V SEP 1 16 Maximize Displacement Minimize Electric Potential Minimize Volume Beam Height

6 Multi- Objective Electrostatic Actuated Beam Optimization Problem Definition In modefrontier TM Input variables of the parametric model SOBOL as DOE MOGA-II as Scheduler ANSS Output Variables Multi Objective (functions to be maximized or minimized)

7 Minimize Electric Potential Postprocessing Bubble Plot The Bubble plot shown is a 3D view of the scatter. It compares the design points with respect to different factors (e.g. Displacement, Electric Potential, Volume). All the computed Design configurations are shown in the Bubble plot. Pareto Frontier Maximize Displacement Around 1000 configurations were computed ModeFRONTIER identifies designs that are Pareto (non-dominated) Total CPU time required for the optimization: circa 28 hours

8 Postprocessing Parallel Coordinate Chart The Parallel Chart allows the viewing of all designs simultaneously, with one vertical axis for each variable or output It is most useful for Filtering Designs, especially in cases with multiple, conflicting, objectives Each Jagged Line across the Chart represents one Design Configuration Moving the sliders up or down, hides all designs outside the range, allowing the selection of Designs of interest (RED LINE) The chart represents all the Pareto designs. Optimum Design

9 Postprocessing Parallel Coordinate Chart By sliding the Volume Objective, the designs can be filtered.

10 Postprocessing Parallel Coordinate Chart Sliding the other objectives will further filter designs which doesn t satisfy the criteria.

11 Postprocessing Parallel Coordinate Chart #371 Final Design can be chosen from the parallel co-ordinate chart by further sliding the Max Displacement objective towards the higher end.

12 ANSS Postprocessing Final Design -Displacement Electric Potential 1 NODAL SOLUTION STEP=12 SUB =1 TIME=120 U (AVG) 1 RSS=0 NODAL SOLUTION U DM = STEP=12 SMN = SUB =1 TIME=120 U (AVG) RSS=0 DM = SMN = M M 1 NODAL SOLUTION STEP=12 SUB =1 TIME=120 (AVG) RSS=0 DM = SMN = M MN MN SEP :05:03 1 NODAL SOLUTION STEP=12 SUB =1 SEP 17 TIME= :05:03 VOLT (AVG) RSS=0 DM = SM =108 1 NODAL SOLUTION STEP=12 SUB =1 TIME=120 VOLT (AVG) RSS=0 DM = SM =108 1 NODAL SOLUTION STEP=12 SUB =1 TIME=120 VOLT (AVG) RSS=0 DM = SM =108 MN M MN M SEP :05:03 SEP :10:19 SEP :10:19 MN M MN Electrostatic clamped beam analysis Electrostatic clamped beam analysis Electrostatic clamped beam analysis ectrostatic clamped beam analysis

13 Conclusions In few hours modefrontier tested several configurations, the same task would have taken days for a single operator modefrontier created an automatic procedure: once the parametric model is set, the optimizator will keep iterating it till it finds the best configurations modefrontier finds the optimum solutions (pareto frontier), therefore the need of testing only the best configurations reducing the experimental phase and controlling the spending

14 Conclusions ModeFRONTIER found the optimum design achieving improvement for all the parameter specified except the Electric Potential Objective In this case the Displacement and Volume objectives are improved at the expense of Electric Potential Displacement increase of 14.2% from the initial design Electric potential increase of 1.84% from the initial design Volume reduction of 16.1% from the initial design

15 modefrontier Capabilities Process Integration Design of Experiments Optimization Algorithms Robust Design Response Surface Tool Statistical Analysis Multivariate Analysis MCDM

16 Stay Ahead During Challenging Times To learn more about how Ozen Engineering can help you incorporate simulation into your design and testing processes, please visit us at For more Design Optimization case studies visit: If you would like us to create a demo for your specific case or for any other question, please contact us at: optimization@ozeninc.com