Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings

Name: Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings
Author: Abbasi, Ahmad, Firoozi, Behnam, Şendur, Polat, Heidari, A. A., Tiwari, R.

İsim	Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings
Yazar	Abbasi, Ahmad, Firoozi, Behnam, Şendur, Polat, Heidari, A. A., Tiwari, R.
Basım Tarihi:	2022-12
Basım Yeri	- Springer
Konu	Constrained optimization, Fatigue life, Harris hawks optimization, Optimization, Swarm-intelligence algorithms, Tapered roller bearing
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0177-0667
Kayıt Numarası	40c68f28-3f70-460b-91ff-161d7ac6b66e
Lokasyon	Mechanical Engineering
Tarih	2022-12
Notlar	Ozyegin University
Örnek Metin	Bearing is one of the most fundamental components of rotary machinery, and its fatigue life is a crucial factor in designing. The design optimization of tapered roller bearing (TRB) is a complex design problem because various arrays of designing parameters and functional requirements should be fulfilled. Since there are many design variables and nonlinear constraints, presenting an optimal design of TRBs poses some challenges for metaheuristic algorithms. The Harris hawks optimization (HHO) algorithm is a robust nature-inspired method with unique exploitation and exploration phases due to its time-varying structure. However, this metaheuristic algorithm may still converge to local optima for more challenging problems such as the design of TRBs. Therefore, this study aims to improve the accuracy and efficiency of the shortcomings of this algorithm. The performance of the proposed algorithm is first evaluated for the TRB optimization problem. The TRB optimization design has nine design variables and 26 constraints because of geometrical dimensions and strength conditions. The productivity of the proposed method is compared with diverse metaheuristic algorithms in the literature. The results demonstrate the significant development of dynamic load capacity in comparison to the standard value. Furthermore, the enhanced version of the HHO algorithm presented in this study is benchmarked with various well-known engineering problems. For supplementary materials regarding algorithms in this research, readers can refer to https://aliasgharheidari.com.
DOI	10.1007/s00366-021-01442-3
Cilt	38

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Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings

Yazar Abbasi, Ahmad, Firoozi, Behnam, Şendur, Polat, Heidari, A. A., Tiwari, R.

Basım Tarihi 2022-12

Basım Yeri - Springer

Konu Constrained optimization, Fatigue life, Harris hawks optimization, Optimization, Swarm-intelligence algorithms, Tapered roller bearing

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0177-0667

Kayıt Numarası 40c68f28-3f70-460b-91ff-161d7ac6b66e

Lokasyon Mechanical Engineering

Tarih 2022-12

Notlar Ozyegin University

Örnek Metin Bearing is one of the most fundamental components of rotary machinery, and its fatigue life is a crucial factor in designing. The design optimization of tapered roller bearing (TRB) is a complex design problem because various arrays of designing parameters and functional requirements should be fulfilled. Since there are many design variables and nonlinear constraints, presenting an optimal design of TRBs poses some challenges for metaheuristic algorithms. The Harris hawks optimization (HHO) algorithm is a robust nature-inspired method with unique exploitation and exploration phases due to its time-varying structure. However, this metaheuristic algorithm may still converge to local optima for more challenging problems such as the design of TRBs. Therefore, this study aims to improve the accuracy and efficiency of the shortcomings of this algorithm. The performance of the proposed algorithm is first evaluated for the TRB optimization problem. The TRB optimization design has nine design variables and 26 constraints because of geometrical dimensions and strength conditions. The productivity of the proposed method is compared with diverse metaheuristic algorithms in the literature. The results demonstrate the significant development of dynamic load capacity in comparison to the standard value. Furthermore, the enhanced version of the HHO algorithm presented in this study is benchmarked with various well-known engineering problems. For supplementary materials regarding algorithms in this research, readers can refer to https://aliasgharheidari.com.

DOI 10.1007/s00366-021-01442-3

Cilt 38