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Multiobjective optimization including design robustness objectives for the embodiment design of a two-stage flash evaporator

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Abstract

During the early phases of design processes, designers have to take the best decisions in order to converge quickly toward the most preferred design solution. More precisely, in a preliminary design context, the phase of embodiment design consists in determining the best values for the main dimensioning parameters of the system to improve its performances. In general, these performances must satisfy functional or technical requirements related to design objectives. The balancing act between the satisfaction of constraints and objectives can be treat as a multiobjective optimization problem. Although designers often face to a qualitative evaluation of design solutions, difficulty arises from his ability to express preferences and expectations throughout the objective function of the multiobjective optimization problem. Illustrated through the preliminary design of a two stage flash evaporator, the purpose of this article aims to develop a methodology to formulate both constraints and preferences into the optimization model. Thus design solutions are evaluated with a single global indicator of confidence. Flash evaporators are thermal systems which are mainly used for flash cooling and juice concentration applications. The design of such a system has to respect specific constraints related to these areas of applications and should meet multiple design objectives. Several goal-oriented design solutions are discussed, in particular when low design sensitivity is expected.

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References

  1. Roy R., Hinduja S., Teti R.: Recent advances in engineering design optimization: challenges and future trends. CIRP Ann. Manuf. Technol. 57(2), 697–715 (2008)

    Article  Google Scholar 

  2. Park C., Joh C.Y., Kim Y.S.: Multidisciplinary design optimization of a structurally nonlinear aircraft wing via parametric modeling. Int. J. Precis. Eng. Manuf. 10(2), 87–96 (2009)

    Article  Google Scholar 

  3. Wang X.D. et al.: Multi-objective optimization of turbomachinery using improved NSGA-II and approximation model. Comput. Methods Appl. Mech. Eng. 200(9–12), 883–895 (2011)

    Article  MATH  Google Scholar 

  4. Stadler W.: Fundamentals of Multicriteria Optimization, pp. 1–25. Multicriteria Optimization in Engineering and in the Sciences Plenum Press, New York (1988)

    Google Scholar 

  5. Messac A. et al.: Aggregate objective functions and Pareto Frontiers: required relationships and practical implications. Optim. Eng. 1(2), 171–188 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chen W. et al.: A procedure for robust design: minimizing variations caused by noise factors and control factors. ASME J. Mech. Des. 118, 478–485 (1996)

    Article  Google Scholar 

  7. Samson, S., et al.: Reliable design optimization under aleatory and epistemic uncertainties. In: ASME 2009 International Design Engineering Technical Conferences & 35th Design Automation Conference, San Diego, USA (2009)

  8. Beyer H.G., Sendhoff B.: Robust optimization—a comprehensive survey. Comput. Methods Appl. Mech. Eng. 196(33–34), 3190–3218 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  9. Arvidsson M., Gremyr I., Johansson P.: Use and knowledge of robust design methodology: a survey of Swedish industry. J. Eng. Des. 14(2), 129 (2003)

    Article  Google Scholar 

  10. Gremyr I., Arvidsson M., Johansson P.: Robust Design Methodology: Status in the Swedish Manufacturing Industry. Qual. Reliab. Eng. Int. 19(4), 285–293 (2003)

    Article  Google Scholar 

  11. HoKon Tiat V., Sebastian P., Quirante T.: Multiobjective optimization of the design of two-stage flash evaporators: Part 1: Process modeling. Int J Thermal Sci. 49(12), 2453–2458 (2010)

    Article  Google Scholar 

  12. Sebastian P. et al.: Multiobjective optimization of the design of two-stage flash evaporators: Part 2: Multiobjective optimization. Int. J. Thermal Sci. 49(12), 2459–2466 (2010)

    Article  Google Scholar 

  13. Cadiot, D., Sebastian, P., Callede, D., Nadeau, J.P.: System for cooling a heated juice by partial low-pressure evaporation, Patent WO02096530 (2002)

  14. Bouchama A., Sebastian P., Nadeau J.-P.: Flash evaporation: modelling and constraint formulation. Chem. Eng. Res. Des. 81(9), 1250–1258 (2003)

    Article  Google Scholar 

  15. Ho Kon Tiat V., Sebastian P., Nadeau J.-P.: Multicriteria-oriented preliminary design of a flash evaporation process for cooling in the wine-making process. J. Food Eng. 85(4), 491–508 (2008)

    Article  Google Scholar 

  16. Taguchi G.: Introduction to quality engineering: designing quality into products and processes. Quality Resources, Northbrook (1986)

    Google Scholar 

  17. Harrington E.: The desirability function. Ind. Qual. Control 21(10), 494–498 (1965)

    Google Scholar 

  18. Fischer, X.: Stratégie de conduite du calcul pour l’aide à la décision en conception mécanique intégrée—application aux appareils à pression. Thèse de docteur en mécanique (2000)

  19. Derringer G., Suich R.: Simultaneous optimization of several response variables. J. Qual. Technol. 12(4), 214–219 (1980)

    Google Scholar 

  20. Scott, M., Antonsson, E.K.: Aggregation functions for engineering design trade-offs. In: 9th International Conference On Design Theory And Methodology, vol. 2, pp. 389–396 (1995)

  21. Saaty, Thomas L.: Relative measurement and its generalization in decision making: why pairwise comparisons are central in mathematics for the measurement of intangible factors—the analytic hierarchy/network process. In: RACSAM Review of the Royal Spanish Academy of Sciences 102, no. 2, Mathematics, pp. 251–318 (2008)

  22. Koza J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection, 1st edn. The MIT Press, Cambridge (1992)

    MATH  Google Scholar 

Download references

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Authors and Affiliations

  1. Université de Bordeaux, I2M, UMR CNRS 5295, Esplanade des Arts et Métiers, 33405, Talence Cedex, France

    T. Quirante, Y. Ledoux & P. Sebastian

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  1. T. Quirante
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  2. Y. Ledoux
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  3. P. Sebastian
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Correspondence to T. Quirante.

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Quirante, T., Ledoux, Y. & Sebastian, P. Multiobjective optimization including design robustness objectives for the embodiment design of a two-stage flash evaporator. Int J Interact Des Manuf 6, 29–39 (2012). https://doi.org/10.1007/s12008-011-0134-8

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  • DOI: https://doi.org/10.1007/s12008-011-0134-8

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