Numerical methods for analysis of mechanical systems with uncertain parameters

• Autorzy: Vasko M. , Saga M. , Vasko A.
• Języki publikacji: EN

Abstrakty

EN

The paper presents new and improved numerical methods designed for analysis of mechanical systems with uncertain parameters. Uncertain parameters in mechanical systems are described using possibility theory. The main representatives of this theory are fuzzy and interval numbers. Algorithms using interval and fuzzy numbers are incorporated into the analysis. The possibilities and efficiency of suggested methods and algorithms are tested by programs created in the environment of the software package MATLAB.

Słowa kluczowe

EN

possibility theory; uncertain parameters; interval numbers; fuzzy numbers; numerical methods; MATLAB

PL

teoria możliwości; niepewne parametry; liczby rozmyte; metody numeryczne; MATLAB

• Wydawca: Oficyna Wydawnicza Stowarzyszenia Menedżerów Jakości i Produkcji
• Czasopismo: Production Engineering Archives
• Rocznik: 2016
• Tom: Vol. 11, No. 2
• Strony: 18--21
• Opis fizyczny: Bibliogr. 14 poz., rys.

Twórcy

autor

Vasko M.

• University of Žilina, Faculty of Mechanical Engineering, Department of Applied Mechanics, Univerzitná 8215/1, 010 26 Žilina, Slovakia, phone: [phone]

autor

Saga M.

• University of Žilina, Faculty of Mechanical Engineering, Department of Applied Mechanics, Univerzitná 8215/1, 010 26 Žilina, Slovakia, phone: [phone]

autor

Vasko A.

• University of Žilina, Faculty of Mechanical Engineering, Department of Materials Engineering, Univerzitná 8215/1, 010 26 Žilina, Slovakia, phone: [phone]

Bibliografia

• 1. Dekýš V., Sapietová A., Kocúr R. 2006. On the Reliability Estimation of the Conveyer Mechanism Using the Monte Carlo Method. “Machine Dynamics Problems“, Vol. 30, No. 3, p. 58–64.
• 2. Hanss M. 2000. A Nearly Strict Fuzzy Arithmetic for Solving Problems with Uncertainties. 19th Int. Conf. NAFIPS ’2000, Atlanta, USA, p. 439–443.
• 3. HARGREAVES G.I. 2002. Interval Analysis in MATLAB. “Numerical Analysis Report”, 416.
• 4. Hurtalová L., Tillová E., Chalupová M., Belan J. 2015. Morphology of intermetallic phases in Al-Si cast alloys and their fracture behaviour. „Prod. Engineer. Archives”, Vol. 6, No. 1, p. 2-5.
• 5. Jagusiak-Kocik M. 2014. Ensuring continuous improvement processes through standardization in the automotive company. „Production Engineering Archives”, Vol. 2, No. 1, p. 12-15.
• 6. Kaufman A., Gupta M. 1991. Introduction to Fuzzy Arithmetic. Van Nostrand Reinhold, 384 p.
• 7. Moore R. E. 1979. Methods and Applications of Interval Analysis. Philadelphia, 200 p.
• 8. Neumaier A. 1990. Interval Methods for Systems of Equations. Cambridge. 272 p.
• 9. Sága M., Vaško M. 2009. Solution of Mechanical Systems with Uncertainty Parameters using IFEA. “Communications”, Vol. 11/2, p. 19–27.
• 10. Trško L., Bokůvka O., Nový F., Lago J. 2016. Quality and fatigue characteristics relation. „Production Engineering Archives”, Vol. 10, No. 1, p. 9-12.
• 11. Ulewicz R., Nový F., Mazur M., Szataniak P. 2014. Fatigue properties of the HSLA steel in high and ultra-high cycle region. „Production Engineering Archives”, Vol. 4, No. 3, p. 18-21.
• 12. Vaško M. 2007. Application of Genetic Algorithms for Solving of Mechanical Systems with Un-certain Parameters. PhD. thesis. (in Slovak).
• 13. Zadeh L. A. 1965. Fuzzy sets. “Information and Control”, Vol. 8, p. 338–353.
• 14. Zhang H. 2005. Nondeterministic Linear Static Finite Element Analysis: An Interval Approach. Georgia Institute of Technology, 177 p.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.