| <p>Previously, we have tried to straighten the sides of the best-evolved curved antenna in <a href="http://radiorm.physics.ohio-state.edu/elog/GENETIS/229">elog 229</a>. However, there were potential issues with how closely this line resembled the curve of the antenna.</p>
<p>So, I attempted to create another straightened sides antenna using a linear regression model to find the best fitting line for the curve to create an antenna.</p>
<p>I made a Python notebook to separate the equations for each curve into 1000 discrete points. Then I ran a linear regression model to fit a curve of the points 1 - n, and a second curve of the n - 1000 points, looping from n = 2 to n = 999.</p>
<p>These results are from the combined output with the least squared error compared to the original.</p>
<p>Pictured is a plot showing the two sides of the curved bicone in red and blue, with the best fitting lines for each in black as well as a model in XF.</p>
<p> </p>
<p>Results:</p>
<p>The antenna has a fitness score of 3.80627 with an error of 0.0759725.</p>
<p>This is much lower than the 5.71 of the curved antenna and 5.11 of the other attempt at straightening.</p>
<p>For the next attempt, we could consider constraining the endpoints to be the same as the original antenna to conserve the radius, and/or adding an extra line to fit the curve.</p>
<p>I've also attached a picture of what my notebook found for fitting 3 lines to the curve (not modeled or tested).</p>
<p> </p>
<p>Professor Chen recommended using 3 sides and constraining the outer radii of the cones to match the original curved design.</p>
<p> </p>
<p>Path to linear regression notebook: /users/PAS1960/dylanwells1629/developing/notebook.ipynb</p>
<p>Path to XF project: /users/PAS1960/dylanwells1629/straightened.xf</p> |