Going to bat for the environment

Dr. Sadegh Mazloomi

How are artificial intelligence, climate change, and baseball connected? More than you might think.

Ash is the most popular wood species for making bats, prized for its flexibility, which players believe gives more “whip”; its grain provides a larger sweet spot and lightness combined with toughness and durability.

But a green monster—and not the one at Fenway—is threatening the species used to produce bats like Rawlings and the iconic Louisville Slugger.

Emerald ash borers—a wood-boring beetle native to East Asia—have killed tens of millions of trees across North America. This destructive, invasive insect, first detected in Michigan and Ontario in 2002, has spread to over 30 states and five provinces. Warmer winters and less extreme cold have meant that more beetles survive in North American climates, leading to faster and increased reproduction and further spread. This threat is compounded in Europe by ash dieback, a fungus devastating native species in the UK and across the continent.

In recent years, other species like maple have risen in popularity for the manufacture of bats. However, these bats may also be impacted by climate change. Maple, for example, is threatened by the invasive Asian longhorned beetle.

So, how do you climate-proof the baseball bat?

Together with Dr. Phil Evans, professor and BC Leadership Chair at UBC’s Faculty of Forestry’s Department of Wood Science, I have been researching how the geometry of the baseball bat can be optimized for other, more common, or sustainably produced species to achieve similar performance.

Using a combination of ANSYS for computer modelling and MATLAB for evolutionary optimization techniques—and applying design specifications defined by MLB’s Official Baseball Rules—we were able to improve the bat’s performance by altering its shape.

Previous research on wooden baseball bats has shown that nodal points (points on the bat that do not vibrate) and centre of percussion influence performance. We deconstructed this by converging the nodal points and the centre of percussion to reveal new designs. Specifically, by minimizing the vibration and maximizing the rebound energy when the bat makes contact with a ball, a batter would be able to transfer the full power of their swing.

Interestingly, the resulting baseball bat design based on physics and machine learning resembles the best professional-grade bats available, which have been refined over nearly 150 years of trial and error and incremental innovation.

Our modelling approach could be used to optimize the baseball bat design for a stronger, more shock-resistant wood species, such as hickory, to improve performance. And it can be used for other wooden ball-and-bat sports. We used a similar modeling approach to optimize the cricket bat’s performance, and this research could be applied to sports such as hurling or table tennis.

Our research also revealed some new design features, which could further improve performance. Most notably, shifting the mass of the baseball bat closer to the sweet spot and making a slight reduction in mass at the very end of the bat. This approach can potentially be extended by adding additional criteria, for example, vibrational energy loss. Further research is needed to see if new designs would emerge from these approaches, which requires extra computational power.

Given the importance of the bat in baseball and other bat and ball sports, our research addresses supply as it pertains to climate change could result in great commercial potential. Now that would be a home run.

This article is reprinted from Branchlines with permission. You can find the original article here.

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