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Efficient Reliability Analysis and Reliability-Based Design Optimization of Mechanical Systems by Using Latin Hypercube Sampling

Yıl 2018, Cilt: 5 Sayı: 1, 31 - 36, 26.03.2018

Öz

Considering uncertainty in
engineering design is computationally more expensive than solving traditional
deterministic problems. This challenge force researches to search for more
efficient methods. For that purpose, in this work, the superiority of the LHS
over MCS in the process of reliability analysis and RBDO of a mechanical system
is investigated. Accordingly, the reliability analysis and RBDO process with
both LHS and MCS is implemented separately on the tension-compression spring
design problem. According to these results, in both reliability analysis and
RBDO process, LHS was more stable in convergence compared to MCS. Moreover, LHS
can be considered to be more efficient than MCS in RBDO of the spring problem. 

Kaynakça

  • 1. Börklü, H.R., Helvacılar, E. and Özdemir, V., "Conceptual Design of a New Buoy", Gazi University Journal of Science PART A: Engineering and Innovation 4(4): 125-143, (2017).
  • 2. Çırak, B., "Mathematically Modeling and Optimization by Artificial Neural Network of Surface Roughness in CNC Milling – A Case Study", World Wide Journal of Multidisciplinary Research and Development, 3(8): 299-307, (2017).
  • 3. Mayda, M., "An Efficient Simulation-Based Search Method for Reliability-Based Robust Design Optimization of Mechanical Components", MECHANIKA, 23(05): 696-702, (2017).
  • 4. Choi, S.-K., Grandhi, R.V. and Canfield, R.A., Reliability-based Structural Design: Springer-Verlag London, (2007).
  • 5. Mayda, M. and Choi, S.-K., "A reliability-based design framework for early stages of design process", Journal of the Brazilian Society of Mechanical Sciences and Engineering, 39(6): 2105-2120, (2017).
  • 6. He, S., Prempain, E. and Wu, Q.H., "An improved particle swarm optimizer for mechanical design optimization problems", Engineering Optimization, 36(5): 585-605, (2004).
  • 7. Rao, R.V. and Savsani, V.J., Mechanical Design Optimization Using Advanced Optimization Techniques: Springer Publishing Company, Incorporated, 240, (2014).
  • 8. Arora, J.S., Chapter 13 - More on Numerical Methods for Constrained Optimum Design, in Introduction to Optimum Design (Third Edition). 2012, Academic Press: Boston. p. 533-573.
Yıl 2018, Cilt: 5 Sayı: 1, 31 - 36, 26.03.2018

Öz

Kaynakça

  • 1. Börklü, H.R., Helvacılar, E. and Özdemir, V., "Conceptual Design of a New Buoy", Gazi University Journal of Science PART A: Engineering and Innovation 4(4): 125-143, (2017).
  • 2. Çırak, B., "Mathematically Modeling and Optimization by Artificial Neural Network of Surface Roughness in CNC Milling – A Case Study", World Wide Journal of Multidisciplinary Research and Development, 3(8): 299-307, (2017).
  • 3. Mayda, M., "An Efficient Simulation-Based Search Method for Reliability-Based Robust Design Optimization of Mechanical Components", MECHANIKA, 23(05): 696-702, (2017).
  • 4. Choi, S.-K., Grandhi, R.V. and Canfield, R.A., Reliability-based Structural Design: Springer-Verlag London, (2007).
  • 5. Mayda, M. and Choi, S.-K., "A reliability-based design framework for early stages of design process", Journal of the Brazilian Society of Mechanical Sciences and Engineering, 39(6): 2105-2120, (2017).
  • 6. He, S., Prempain, E. and Wu, Q.H., "An improved particle swarm optimizer for mechanical design optimization problems", Engineering Optimization, 36(5): 585-605, (2004).
  • 7. Rao, R.V. and Savsani, V.J., Mechanical Design Optimization Using Advanced Optimization Techniques: Springer Publishing Company, Incorporated, 240, (2014).
  • 8. Arora, J.S., Chapter 13 - More on Numerical Methods for Constrained Optimum Design, in Introduction to Optimum Design (Third Edition). 2012, Academic Press: Boston. p. 533-573.
Toplam 8 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makine Mühendisliği
Yazarlar

Murat Mayda

Yayımlanma Tarihi 26 Mart 2018
Gönderilme Tarihi 10 Şubat 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 5 Sayı: 1

Kaynak Göster

APA Mayda, M. (2018). Efficient Reliability Analysis and Reliability-Based Design Optimization of Mechanical Systems by Using Latin Hypercube Sampling. Gazi University Journal of Science Part A: Engineering and Innovation, 5(1), 31-36.