How to cite this paper
Meibody, M., Naseh, H & Ommi, F. (2019). A kriging based multi objective gray wolf optimization for hydrazine catalyst bed.Engineering Solid Mechanics, 7(3), 179-192.
Refrences
Adami, A., Mortazavi, M., Nosratollahi, M., Taheri, M., & Sajadi, J. (2015a). Multidisciplinary design optimization and analysis of hydrazine monopropellant propulsion system. International Journal of Aerospace Engineering, 2015.
Adami, A., Mortazavi, M., & Nosratollahi, M. (2015b). Multidisciplinary design optimization of hydrogen peroxide monopropellant propulsion system using GA and SQP. International Journal of Computer Applications, 113(9).
Amrousse, R., Brahmi, R., Batonneau, Y., & Kappenstein, C. (2011). Thermal and catalytic decomposition of H2O2–ionic liquid monopropellant mixtures on monolith-based catalysts. Paper presented at the Proc. of 46th Joint Propulsion Conference and Exhibit.
Bechikh, S., & Coello, C. A. C. (2018). Advances in Evolutionary Multi-objective Optimization. In: Elsevier.
Bezerra, M. A., Santelli, R. E., Oliveira, E. P., Villar, L. S., & Escaleira, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta, 76(5), 965-977.
Branke, J. (2012). Evolutionary optimization in dynamic environments (Vol. 3): Springer Science & Business Media.
Branke, J., Deb, K., Dierolf, H., & Osswald, M. (2004). Finding knees in multi-objective optimization. Paper presented at the PPSN.
Chen, J., Li, G., Zhang, T., Wang, M., & Yu, Y. (2016). Experimental investigation of the catalytic decomposition and combustion characteristics of a non-toxic ammonium dinitramide (ADN)-based monopropellant thruster. Acta Astronautica, 129, 367-373.
Chen, X., Zhang, T., Ying, P., Zheng, M., Wu, W., Xia, L., . . . Li, C. (2002). A novel catalyst for hydrazine decomposition: molybdenum carbide supported on γ-Al 2 O 3. Chemical Communications, 3, 288-289.
Coello, C. A. C., Lamont, G. B., & Van Veldhuizen, D. A. (2007). Evolutionary algorithms for solving multi-objective problems (Vol. 5): Springer.
Coello, C. C. (2006). Evolutionary multi-objective optimization: a historical view of the field. IEEE Computational Intelligence Magazine, 1(1), 28-36.
Deb, K. (2012). Advances in evolutionary multi-objective optimization. Paper presented at the International Symposium on Search Based Software Engineering.
Eisenhower, B., O’Neill, Z., Narayanan, S., Fonoberov, V. A., & Mezić, I. (2012). A methodology for meta-model based optimization in building energy models. Energy and Buildings, 47, 292-301.
Eppinger, S. D., & Browning, T. R. (2012). Design structure matrix methods and applications: MIT press.
Fazeley, H. R., Taei, H., Naseh, H., & Mirshams, M. (2016). A multi-objective, multidisciplinary design optimization methodology for the conceptual design of a spacecraft bi-propellant propulsion system. Structural and Multidisciplinary Optimization, 53(1), 145-160. doi:10.1007/s00158-015-1304-2
Hwang, C. H., Lee, S. N., Baek, S. W., Han, C. Y., Kim, S. K., & Yu, M. J. (2012). Effects of catalyst bed failure on thermochemical phenomena for a hydrazine monopropellant thruster using Ir/Al2O3 catalysts. Industrial & Engineering Chemistry Research, 51(15), 5382-5393.
Jia, G., & Taflanidis, A. A. (2013). Kriging metamodeling for approximation of high-dimensional wave and surge responses in real-time storm/hurricane risk assessment. Computer Methods in Applied Mechanics and Engineering, 261, 24-38.
Jung, H., Kim, J. H., & Kim, J. S. (2013). An Approach to the Optimization of Catalyst-bed L/D Configuration in 70 N-class Hydrazine Thruster. Journal of the Korean Society of Propulsion Engineers, 17(6), 30-37.
Krejci, D., Woschnak, A., Scharlemann, C., & Ponweiser, K. (2011). Hydrogen peroxide decomposition for micro propulsion: Simulation and experimental verification. AIAA paper, 5855, 2011.
Kwon, H., & Choi, S. (2015). A trended Kriging model with R2 indicator and application to design optimization. Aerospace Science and Technology, 43, 111-125.
Larson, W. J., Henry, G. N., & Humble, R. W. (1995). Space propulsion analysis and design: McGraw-Hill.
Lohner, K., Scherson, Y., Lariviere, B., Cantwell, B., & Kenny, T. (2008). Nitrous Oxide Monopropellant Gas Generator Development. Paper presented at the 3rd Spacecraft Propulsion Joint Subcommittee Meeting, JANNAF.
Makled, A., & Belal, H. (2009). Modeling of hydrazine decomposition for monopropellant thrusters. Paper presented at the 13th International Conference on Aerospace Sciences & Aviation Technology.
Mao-Guo, G., Li-Cheng, J., Dong-Dong, Y., & Wen-Ping, M. (2009). Evolutionary multi-objective optimization algorithms.
Martin, J., & Simpson, T. (2002). Use of adaptive metamodeling for design optimization. Paper presented at the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46-61.
Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. d. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Mokarram, V., & Banan, M. R. (2018). A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables. Structural and Multidisciplinary Optimization, 57(2), 509-533.
Most, T., & Will, J. (2008). Metamodel of Optimal Prognosis-an automatic approach for variable reduction and optimal metamodel selection. Proc. Weimarer Optimierungs-und Stochastiktage, 5, 20-21.
Pasini, A., Torre, L., Romeo, L., Cervone, A., & d'Agostino, L. (2011). Performance Characterization of pellet catalytic beds for hydrogen peroxide monopropellant rockets. Journal of Propulsion and Power, 27(2), 428-436.
Rath, M., Schimtz, H., & Steenborg, M. (1996). Development of a 400 N hydrazine thruster for ESA’s atmospheric re-entry demonstrator. Paper presented at the Proceedings of the 32nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference.
Rhee, M. S., Zakrzwski, C. M., & Thomas, M. A. (2000). Highlights of Nanosatellite Propulsion Development Program at NASA-Goddard Space Flight Center.
Raza, W., & Kim, K.-Y. (2008). Shape optimization of wire-wrapped fuel assembly using Kriging metamodeling technique. Nuclear Engineering and Design, 238(6), 1332-1341.
Schmuland, D., Masse, R., & Sota, C. (2011). Hydrazine propulsion module for CubeSats.
Simpson, T. W., Poplinski, J., Koch, P. N., & Allen, J. K. (2001). Metamodels for computer-based engineering design: survey and recommendations. Engineering with Computers, 17(2), 129-150.
Sutton, G. P., & Biblarz, O. (2010). Rocket propulsion elements: John Wiley & Sons.
Venturelli, G., & Benini, E. (2016). Kriging-assisted design optimization of S-shape supersonic compressor cascades. Aerospace Science and Technology, 58, 275-297.
Wang, G. G. (2003). Adaptive response surface method using inherited latin hypercube design points. Journal of Mechanical Design, 125(2), 210-220.
Whitehead, J. C. (1998). Hydrogen Peroxide Propulsion for Smaller Satellites. Paper presented at the 12th Annual AIAA/USU Conference on Small Satellites.
Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE transactions on evolutionary computation, 1(1), 67-82.
Yondo, R., Andrés, E., & Valero, E. (2017). A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses. Progress in Aerospace Sciences.
Adami, A., Mortazavi, M., & Nosratollahi, M. (2015b). Multidisciplinary design optimization of hydrogen peroxide monopropellant propulsion system using GA and SQP. International Journal of Computer Applications, 113(9).
Amrousse, R., Brahmi, R., Batonneau, Y., & Kappenstein, C. (2011). Thermal and catalytic decomposition of H2O2–ionic liquid monopropellant mixtures on monolith-based catalysts. Paper presented at the Proc. of 46th Joint Propulsion Conference and Exhibit.
Bechikh, S., & Coello, C. A. C. (2018). Advances in Evolutionary Multi-objective Optimization. In: Elsevier.
Bezerra, M. A., Santelli, R. E., Oliveira, E. P., Villar, L. S., & Escaleira, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta, 76(5), 965-977.
Branke, J. (2012). Evolutionary optimization in dynamic environments (Vol. 3): Springer Science & Business Media.
Branke, J., Deb, K., Dierolf, H., & Osswald, M. (2004). Finding knees in multi-objective optimization. Paper presented at the PPSN.
Chen, J., Li, G., Zhang, T., Wang, M., & Yu, Y. (2016). Experimental investigation of the catalytic decomposition and combustion characteristics of a non-toxic ammonium dinitramide (ADN)-based monopropellant thruster. Acta Astronautica, 129, 367-373.
Chen, X., Zhang, T., Ying, P., Zheng, M., Wu, W., Xia, L., . . . Li, C. (2002). A novel catalyst for hydrazine decomposition: molybdenum carbide supported on γ-Al 2 O 3. Chemical Communications, 3, 288-289.
Coello, C. A. C., Lamont, G. B., & Van Veldhuizen, D. A. (2007). Evolutionary algorithms for solving multi-objective problems (Vol. 5): Springer.
Coello, C. C. (2006). Evolutionary multi-objective optimization: a historical view of the field. IEEE Computational Intelligence Magazine, 1(1), 28-36.
Deb, K. (2012). Advances in evolutionary multi-objective optimization. Paper presented at the International Symposium on Search Based Software Engineering.
Eisenhower, B., O’Neill, Z., Narayanan, S., Fonoberov, V. A., & Mezić, I. (2012). A methodology for meta-model based optimization in building energy models. Energy and Buildings, 47, 292-301.
Eppinger, S. D., & Browning, T. R. (2012). Design structure matrix methods and applications: MIT press.
Fazeley, H. R., Taei, H., Naseh, H., & Mirshams, M. (2016). A multi-objective, multidisciplinary design optimization methodology for the conceptual design of a spacecraft bi-propellant propulsion system. Structural and Multidisciplinary Optimization, 53(1), 145-160. doi:10.1007/s00158-015-1304-2
Hwang, C. H., Lee, S. N., Baek, S. W., Han, C. Y., Kim, S. K., & Yu, M. J. (2012). Effects of catalyst bed failure on thermochemical phenomena for a hydrazine monopropellant thruster using Ir/Al2O3 catalysts. Industrial & Engineering Chemistry Research, 51(15), 5382-5393.
Jia, G., & Taflanidis, A. A. (2013). Kriging metamodeling for approximation of high-dimensional wave and surge responses in real-time storm/hurricane risk assessment. Computer Methods in Applied Mechanics and Engineering, 261, 24-38.
Jung, H., Kim, J. H., & Kim, J. S. (2013). An Approach to the Optimization of Catalyst-bed L/D Configuration in 70 N-class Hydrazine Thruster. Journal of the Korean Society of Propulsion Engineers, 17(6), 30-37.
Krejci, D., Woschnak, A., Scharlemann, C., & Ponweiser, K. (2011). Hydrogen peroxide decomposition for micro propulsion: Simulation and experimental verification. AIAA paper, 5855, 2011.
Kwon, H., & Choi, S. (2015). A trended Kriging model with R2 indicator and application to design optimization. Aerospace Science and Technology, 43, 111-125.
Larson, W. J., Henry, G. N., & Humble, R. W. (1995). Space propulsion analysis and design: McGraw-Hill.
Lohner, K., Scherson, Y., Lariviere, B., Cantwell, B., & Kenny, T. (2008). Nitrous Oxide Monopropellant Gas Generator Development. Paper presented at the 3rd Spacecraft Propulsion Joint Subcommittee Meeting, JANNAF.
Makled, A., & Belal, H. (2009). Modeling of hydrazine decomposition for monopropellant thrusters. Paper presented at the 13th International Conference on Aerospace Sciences & Aviation Technology.
Mao-Guo, G., Li-Cheng, J., Dong-Dong, Y., & Wen-Ping, M. (2009). Evolutionary multi-objective optimization algorithms.
Martin, J., & Simpson, T. (2002). Use of adaptive metamodeling for design optimization. Paper presented at the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46-61.
Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. d. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Mokarram, V., & Banan, M. R. (2018). A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables. Structural and Multidisciplinary Optimization, 57(2), 509-533.
Most, T., & Will, J. (2008). Metamodel of Optimal Prognosis-an automatic approach for variable reduction and optimal metamodel selection. Proc. Weimarer Optimierungs-und Stochastiktage, 5, 20-21.
Pasini, A., Torre, L., Romeo, L., Cervone, A., & d'Agostino, L. (2011). Performance Characterization of pellet catalytic beds for hydrogen peroxide monopropellant rockets. Journal of Propulsion and Power, 27(2), 428-436.
Rath, M., Schimtz, H., & Steenborg, M. (1996). Development of a 400 N hydrazine thruster for ESA’s atmospheric re-entry demonstrator. Paper presented at the Proceedings of the 32nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference.
Rhee, M. S., Zakrzwski, C. M., & Thomas, M. A. (2000). Highlights of Nanosatellite Propulsion Development Program at NASA-Goddard Space Flight Center.
Raza, W., & Kim, K.-Y. (2008). Shape optimization of wire-wrapped fuel assembly using Kriging metamodeling technique. Nuclear Engineering and Design, 238(6), 1332-1341.
Schmuland, D., Masse, R., & Sota, C. (2011). Hydrazine propulsion module for CubeSats.
Simpson, T. W., Poplinski, J., Koch, P. N., & Allen, J. K. (2001). Metamodels for computer-based engineering design: survey and recommendations. Engineering with Computers, 17(2), 129-150.
Sutton, G. P., & Biblarz, O. (2010). Rocket propulsion elements: John Wiley & Sons.
Venturelli, G., & Benini, E. (2016). Kriging-assisted design optimization of S-shape supersonic compressor cascades. Aerospace Science and Technology, 58, 275-297.
Wang, G. G. (2003). Adaptive response surface method using inherited latin hypercube design points. Journal of Mechanical Design, 125(2), 210-220.
Whitehead, J. C. (1998). Hydrogen Peroxide Propulsion for Smaller Satellites. Paper presented at the 12th Annual AIAA/USU Conference on Small Satellites.
Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE transactions on evolutionary computation, 1(1), 67-82.
Yondo, R., Andrés, E., & Valero, E. (2017). A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses. Progress in Aerospace Sciences.