Multiobjective Optimal Method for Carbon Dioxide Removal Assembly in Manned Spacecraft
Publication: Journal of Aerospace Engineering
Volume 29, Issue 6
Abstract
Carbon dioxide removal assembly (CDRA) is an essential subsystem in an air revitalization system (ARS) to control concentration in a long-term manned spacecraft cabin. At the same time, it is a main power consumption subsystem. concentration control performance and power consumption are both key factors that need to be considered. To design this subsystem reasonably, some basic processes are analyzed carefully in this paper, such as mass and heat transfer processes in adsorption beds, power consumption for fan and electric heater, and entropy generation in heat transfer process. The relationship between CDRA and other subsystems are also analyzed carefully. Based on these analyses, a multiobjective optimal method is developed in this paper. Its objective functions are specified as cabin concentration level, power consumption, and entropy generation. The optimal parameters are air velocity, absorption bed length, adsorption time (half cycle time), and molecular sieve mass loaded in the absorption bed. An improved genetic algorithm, Nondominated Sorting Genetic Algorithm-II (NSGA-II), is adopted to obtain the final optimal solution set. Furthermore, a CDRA for a space station with three astronauts is taken as an example to show the implementation of the proposed method. Optimal results show that the presented optimal method can obtain the design solution set for the CDRA. The optimal parameter combination is recommended as the final optimal design solution by analyzing the global pareto optimal front of the solution set. This multiobjective optimal method can realize an optimization process for a complex system design by taking a comprehensive consideration of various factors and running performances.
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Acknowledgments
The research is sponsored by the Aviation Science Foundation of China (2014ZC09002).
References
Allison, J. T., and Herber, D. R. (2014). “Multidisciplinary design optimization of dynamic engineering systems.” AIAA J., 52(4), 691–710.
Bekele, E. G., and Nicklow, J. W. (2007). “Multi-objective automatic calibration of SWAT using NSGA-II.” J. Hydrol., 341(3), 165–176.
Chen, J., Tang, Y., Ge, R., An, Q., and Guo, X. (2013). “Reliability design optimization of composite structures based on PSO together with FEA.” Chin. J. Aeronaut., 26(2), 343–349.
Curley, S., Stambaugh, I., Swickrath, M., Anderson, M., and Rotter, H. (2012). “Deep space habitat ECLSS design concept.” 42nd Int. Conf. on Environmental Systems (ICES), AIAA, Reston, VA, 1–16.
Drysdale, A., Ewert, M., and Hanford, A. (1999). “Equivalent system mass studies of missions and concepts.”, SAE International, Warrendale.
Guo, S., Duan, F., Tang, H., Lim, S. C., and Yip, M. S. (2014). “Multi-objective optimization for centrifugal compressor of mini turbojet engine.” Aerosp. Sci. Technol., 39(12), 414–425.
Hager, P., Czupalla, M., and Walter, U. (2010). “A dynamic human water and electrolyte balance model for verification and optimization of life support systems in space flight applications.” Acta Astronautica, 67(9), 1003–1024.
Hu, H. J., et al. (2013). “Development and evaluation of TC-5A and TC-13X molecular sieve in manned spacecraft.” Space Med. Med. Eng., 26(3), 185–189.
Jeyadevi, S., Baskar, S., Babulal, C. K., and Iruthayarajan, M. W. (2011). “Solving multiobjective optimal reactive power dispatch using modified NSGA-II.” Int. J. Electr. Power Energy Syst., 33(2), 219–228.
Jones, H. (2003). “Equivalent mass versus life cycle cost for life support technology selection.” 33rd Int. Conf. on Environmental Systems (ICES), Vancouver, BC, Canada.
Kannan, S., Baskar, S., McCalley, J. D., and Murugan, P. (2009). “Application of NSGA-II algorithm to generation expansion planning.” IEEE Trans. Power Syst., 24(1), 454–461.
Karan, M. E., Jiao, Z. X., and Zhang, H. Q. (2008). “PID controller optimization by GA and its performances on the electro-hydraulic servo control system.” Chin. J. Aeronaut., 21(4), 378–384.
Kohlhase, A. O., Porth, N., and Doyé, J. (2010). “Operational engineering of the COLUMBUS thermal and environmental control system: Achievements, optimizations.” Space Ops 2010 Conf., American Institute of Aeronautics and Astronautics (AIAA), Reston, VA, 2010–2907.
Lian, Y., Oyama, A., and Liou, M. S. (2010). “Progress in design optimization using evolutionary algorithms for aerodynamic problems.” Progr. Aerosp. Sci., 46(5), 199–223.
Liu, J. Q. (2007). Separation process and simulation, Tinghua University Press, Beijing.
MATLAB [Computer software]. MathWorks, Natick, MA.
Maul, W. A., Kopasakis, G., Santi, L. M., Sowers, T. S., and Chicatelli, A. (2008). “Sensor selection and optimization for health assessment of aerospace systems.” J. Aerosp. Comput. Inf. Commun., 5(1), 16–34.
Modefrontier [Computer software]. ESTECO, Trieste, Italy.
Mohamadinejad, H. (1999). “The adsorption of on 5A zeolite and silica gel in a packed column in one and two-dimensional flows.” Ph.D. thesis, Univ. of Alabama in Huntsville, AL.
Nicholson, A., Slojkowski, S., Long, A., Beckman, M., and Lamb, R. (2010). “NASA GSFC lunar reconnaissance orbiter (LRO) orbit estimation and prediction.” SpaceOps 2010 Conf., American Institute of Aeronautics and Astronautics (AIAA), Reston, VA, 2010–2328.
Perry, J. L., Carrasquillo, R. L., and Harris, D. W. (2006). “Atmosphere revitalization technology development for crewed space exploration.” 44th AIAA Aerospace Sciences Meeting and Exhibit, American Institute of Aeronautics and Astronautics (AIAA), Reston, VA, 2006–2140.
Rezaei, F., and Webley, P. (2009). “Optimum structured adsorbents for gas separation processes.” Chem. Eng. Sci., 64(24), 5182–5191.
Shafeeyan, M. S., Daud, W. M., and Shamiri, A. (2014). “A review of mathematical modeling of fixed-bed columns for carbon dioxide adsorption.” Chem. Eng. Res. Des., 92(5), 961–988.
Stambaugh, I., et al. (2013). “Environmental controls and life support system (ECLSS) design for a multi-mission space exploration vehicle (MMSEV).” Proc., 2013 Int. Conf. of Environmental Systems (ICES), AIAA, Reston, VA.
Tito, D. A., et al. (2013). “Feasibility analysis for a manned Mars free-return mission in 2018.” IEEE Aerosp. Conf., IEEE, Manhattan Beach, CA, 1–18.
Trélat, E. (2012). “Optimal control and applications to aerospace: Some results and challenges.” J. Optim. Theory Appl., 154(3), 713–758.
Welty, J. R., Wicks, C. E., Rorrer, G., and Wilson, R. E. (2009). Fundamentals of momentum, heat, and mass transfer, Wiley, West Sussex, U.K.
Xiong, D. X., Li, Z. X., and Guo, Z. Y. (1997). “Analysis on effectiveness and entropy generation in heat exchangers.” J. Eng. Thermophys., 18(1), 91–94.
Yang, R. T. (2003). Adsorbents: Fundamentals and applications, Wiley, West Sussex, U.K.
Yang, Y. M., and Wu, Z. Q. (2013). “RMS design concept and key technology analysis of the space Station’s ELCSS.” Manned Spaceflight, 19(4), 38–44.
Yao, W., Chen, X., Luo, W., Tooren, M., and Guo, J. (2011). “Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles.” Progr. Aerosp. Sci., 47(6), 450–479.
Zhukov, A., and Czupalla, M. (2014). “The virtual habitat—Optimization of life support systems.” 44th Int. Conf. on Environ. Systems, Institute for Computational Engineering and Sciences (ICES), Austin, TX.
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Published In
Journal of Aerospace Engineering
Volume 29 • Issue 6 • November 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Jan 22, 2016
Accepted: Apr 7, 2016
Published online: Jun 27, 2016
Published in print: Nov 1, 2016
Discussion open until: Nov 27, 2016
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