CSP approach and interval computation for the coupling between static and dynamic requirements in the preliminary design of a compression spring
Keywords:
design, interval computation, constraint satisfaction problem, compression spring, suspension system, requirementsAbstract
In this study, a new design approach based on an interval computation method and the constraint satisfaction problem technique (CSP approach) was discussed. It has been applied in the design of a compression spring, implemented in the vehicle suspension system. A design process is proposed and compared with what is done in conventional design. IT allows making static and dynamic sizing in one step. In fact, with the CSP, static and dynamic requirements can be coupled in the same step of sizing. In the CSP all requirements imposed can be integrated from the beginning. So it avoids falling on the loop “design-simulate-back to the initial step in case of failure”. In this study, the design parameters values of the compression spring generated by the CSP verify all requirements and the resulting simulation of the system behaviour respects all constraints required. The results obtained in this study affirmed that the suggested method is valid and potentially useful to the size dynamic system and can be applied easily and effectively.
Downloads
References
Choné, J. (2007). Automotive suspension springs steel. Engineer Technical, BM5440.
Colton, J. S., & Ouellette, M. P. (1994). A form verification system for the conceptual design of
complex mechanical systems. Engineering with Computers, 10, 33–44.
Deb, K., & Goyal, M. (1998). A flexible optimization procedure for mechanical component design
based on genetic adaptive search. Journal of Mechanical Design, ASME, 120, 162–164.
Del Llano-Vizcaya, L., Rubio-Gonzalez, C., Mesmacque, G., & Banderas-Hernandez, A. (2007).
Stress relief effect on fatigue and relaxation of compression springs. Materials & Design, 28,
–1134.
DIN 2088, DIN 2089–1, DIN 2089–2, Burggrafenstrate 6, postfach 11 07, 10787 Berlin, Germany.
Duchemin, M. (1985). Metal springs – constraints traction or compression. Engineer Technical,
B5431.Edmunds, R., Feldman, J. A., Hicks, B. J., & Mullineux, G. (2011). Constraint-based modelling and
optimization to support the design of complex multi-domain engineering problems. Engineering
with Computers, 27, 319–336.
Eldon, H. (2002). Global optimization using interval analysis: The one-dimensional case. Journal
of Optimization Theory and Application, 29, 331–344.
Granvilliers, L., Monfroy, E., & Benhamou, F. (2001). Symbolic-interval cooperation in
constraint programming. ISSAC ‘01 Proceedings of the 2001 International Symposium on
Symbolic and Algebraic Computation. New York: NY. pp. 150–166.
Hwang, H. Y., Jung, K. J., Kang, I. M., Kim, M. S., Park, S. I., & Kim, J. H. (2006). Multidisciplinary
aircraft design and evaluation software integrating CAD, analysis, database, and
optimization. Advances in Engineering Software, 37, 312–326.
IBM: http://www01.ibm.com/software/websphere/products/optimization/academic-initiative
Kulkani, S. V., & Balasubrahmanyam, K. (1979). Optimal design of open coiled helical springs.
Journal of the Institution of Engineers (India), 60, 7–14.
Meyer, Y., & Yvars, P. A. (2012). Optimization of a passive structure for active vibration
isolation: An interval-computation-and constraint-propagation-based approach. Engineering
Optimization, 44, 1463–1489. doi:10.1080/0305215X. 2011.652102.
Montanari, U. (1974). Networks of constraints: Fundamental properties and application to picture
processing. Information Science, 7, 95–132.
Moore, R. E. (1966). Interval Matrices. In R.E. Moore, R. Baker Kearfott, & M.J. Cloud (Eds.),
Introduction to Interval Analysis (pp. 85–103). Englewood Cliffs, NJ: Prentice Hall.
Paredes, M. (2000). Development of tools to support the optimal design of elastic connections by
spring (doctoral thesis) INSA, Toulouse.
Paredes, M. (2009). Methodology to build an assistance tool dedicated to preliminary design:
Application to compression springs. International Journal on Interactive Design and
Manufacturing (IJIDeM), 3, 265–272.
Paredes, M., Sartor, M., & Daidie, A. (2005). Advanced assistance tool for optimal compression
spring design. Engineering with Computers, 21, 140–150.
Philipp, G. (2009). Component-oriented decomposition for multidisciplinary design optimization
in building design. Advanced Engineering Informatics, 23, 12–31.
Song, C. Y., Lee, J., & Choung, J. (2011). Reliability-based design optimization of an FPSO riser
support using moving least squares response surface meta-models. Ocean Engineering, 38,
–318.
Spaes, J. (1989). The helical springs, applications and calculations. Paris: Nathan communication.
Suciu, C. V., Buma, S. (2009) On the structural simplification, compact and light design of a
vehicle suspension, achieved by using a colloidal cylinder with a dual function of absorber
and compression-spring. Proceedings of the FISITA 2012 World Automotive Congress, Kyushu,
Japan, Electrical Engineering, 198, pp. 21–32.
Teorey, T. J., Yang, D., & Fry, J. P. (1986). A logical design methodology for relational databases
using the extended entity relationship model. ACM Computing Surveys, 18, 197–222.
Yokota, T., Taguchi, T., Gen, M. (1997) A solution method for optimal weight design problem of
herical spring using genetic algorithms. Computing Industrial Engineering, 33, 71–76.
Yvars, P. A., Lafon, P., & Zimmer, L. (2009). Optimization of mechanical system: Contribution of
constraint satisfaction method. Proceedings of the IEEE International Conference of Computers
and industrial engineering, CIE’39, Troyes. pp. 1379–1384.