國立虎尾科技大學 |

AI Optimization of Phononic Crystal Bandgaps.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	AI Optimization of Phononic Crystal Bandgaps./
作者:	Handlovsky, Trent.
面頁冊數:	1 online resource (52 pages)
附註:	Source: Masters Abstracts International, Volume: 85-05.
Contained By:	Masters Abstracts International85-05.
標題:	Aerospace engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9798380845748

AI Optimization of Phononic Crystal Bandgaps.
Handlovsky, Trent.

AI Optimization of Phononic Crystal Bandgaps. - 1 online resource (52 pages)

Source: Masters Abstracts International, Volume: 85-05.

Thesis (M.S.)--Rutgers The State University of New Jersey, School of Graduate Studies, 2023.

Includes bibliographical references

Phononic crystals are artificial materials comprised of periodic structures that can manipulate propagating mechanical waves. They have potential applications in various fields such as acoustic wave control, thermal management, energy harvesting, and sensing. Bandgaps are frequency ranges where wave propagation is prohibited and are a crucial parameter that affects the functionality of phononic crystals. However, the optimization of phononic crystal bandgaps is a challenging task due to the complex relationships between the geometric and material parameters of the structure. However, understanding complex relationships is where the field of Machine Learning (ML) excels.We present an approach for analyzing the input dimensions of a phononic crystal simulation to create and tune an Artificial Intelligence (AI)-based model that can predict the starting frequency and width of the bandgaps. This produces a neural network model that is capable of rapid forecasting without the heavy computational demands of a simulation. The resultant framework, also when used more generally, provides an efficient and effective method for studying or applying phenomena with complex governing equations that are difficult to solve analytically, and are typically addressed through numerical methods.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380845748Subjects--Topical Terms:

686400
Aerospace engineering.
Subjects--Index Terms:

Artificial IntelligenceIndex Terms--Genre/Form:

554714
Electronic books.

AI Optimization of Phononic Crystal Bandgaps.
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520 $a Phononic crystals are artificial materials comprised of periodic structures that can manipulate propagating mechanical waves. They have potential applications in various fields such as acoustic wave control, thermal management, energy harvesting, and sensing. Bandgaps are frequency ranges where wave propagation is prohibited and are a crucial parameter that affects the functionality of phononic crystals. However, the optimization of phononic crystal bandgaps is a challenging task due to the complex relationships between the geometric and material parameters of the structure. However, understanding complex relationships is where the field of Machine Learning (ML) excels.We present an approach for analyzing the input dimensions of a phononic crystal simulation to create and tune an Artificial Intelligence (AI)-based model that can predict the starting frequency and width of the bandgaps. This produces a neural network model that is capable of rapid forecasting without the heavy computational demands of a simulation. The resultant framework, also when used more generally, provides an efficient and effective method for studying or applying phenomena with complex governing equations that are difficult to solve analytically, and are typically addressed through numerical methods.
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