Dergiler / Gazi University Journal of Science Part A: Engineering and Innovation / 2018 / Cilt: 5 - Sayı: 1

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

Sayfa
31–36
Yayın Tarihi
2018-03-26
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Moreover, LHS can be considered to be more efficient than MCS in RBDO of the spring problem.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Considering uncertainty in engineering design is computationally more expensive than solving traditional deterministic problems.
📊
Temel Bulgular & Veri:Accordingly, the reliability analysis and RBDO process with both LHS and MCS is implemented separately on the tension-compression spring design problem.
💡
Sonuç & Katkı:Moreover, LHS can be considered to be more efficient than MCS in RBDO of the spring problem.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Reliability analysis · Design optimization · Uncertainty

Abstract

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.

🔖

Bu Makaleye Atıf Yap

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, Cilt: 5 - Sayı: 1, 31–36. https://ajindex.com/articles/667262

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (8)

  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.