References
- Bachmayer, R., Leonard, N.E., Graver, J., Fiorelli, E., Bhatta, P., Paley, D., 2004. Underwater gliders: recent developments and future applications. Proc. IEEE Int. Symp. Underw. Technol. 195-200.
- Chandra, S., 2013. Design and analysis of experiments. Technometrics 30 (2), 308.
- Farin, G., 2002. North-Holland, Amsterdam. Handbook of Computer Aided Geometric Design, 18(8), pp. 771-795.
- Graver, J. Grady, 2005. Underwater gliders :dynamics, control and design. J. Fluids Eng. 127 (3), 523-528. https://doi.org/10.1115/1.1899169
- Hussain, N.A.A., Arshad, M.R., Mohd-Mokhtar, R., 2011. Underwater glider modelling and analysis for net buoyancy, depth and pitch angle control. Ocean Eng. 38 (16), 1782-1791. https://doi.org/10.1016/j.oceaneng.2011.09.001
- Jenkins, S.A., Humphreys, D.E., Sherman, J., Osse, J., Jones, C., Leonard, N., Graver, J., Bachmayer, R., Clem, T., Carroll, P. Underwater Glider System Study, Scripps Institution of Oceanography.
- Jeong, S., Murayama, M., Yamamoto, K., 2005. Efficient optimization design method using kriging model. J. Aircr. 42 (2), 413-420. https://doi.org/10.2514/1.6386
- Jones, D.R., Schonlau, M., Welch, W.J., 1998. Efficient global optimization of expensive black-box functions. J. Glob. Optim. 13 (4), 455-492. https://doi.org/10.1023/A:1008306431147
- Kay, M., Beckman, R.J., Conover, W.J., 1979. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code in wsc '05: proceedings of the 37th conference on winter simulation. Technometrics 21 (1), 239-245.
- Lee, J., 2007. A novel three-phase trajectory informed search methodology for global optimization. J. Glob. Optim. 38 (38), 61-77. https://doi.org/10.1007/s10898-006-9083-3
- Leonard, N.E., Graver, J.G., 2001. Model-based feedback control of autonomous underwater gliders. IEEE J. Ocean. Eng. 26 (4), 633-645. https://doi.org/10.1109/48.972106
- Ma, Z., Zhang, H., Zhang, N., Ma, D.-M., 2006. Study on energy and hydrodynamic performance of the underwater glider. J. Ship Mech. 10 (3), 53-60.
- Martin, J.D., Simpson, T.W., 2005. Use of kriging models to approximate deterministic computer models. AIAA J. 43 (4), 853-863. https://doi.org/10.2514/1.8650
- ONR, 2006. Liberdade Xray Advanced Underwater Glider. URL. http://www.onr.navy.mil/media/extra/factsheets/advancedunderwaterglider.pdf.
- Sun, C., Song, B., Wang, P., 2015. Parametric geometric model and shape optimization of an underwater glider with blended-wing-body. Int. J. Nav. Archit. Ocean Eng. 7 (6), 995-1006. https://doi.org/10.1515/ijnaoe-2015-0069
- Yu, J., Zhang, F., Zhang, A., Jin, W., Tian, Y., 2013. Motion parameter optimization and sensor scheduling for the sea-wing underwater glider. Ocean. Eng. IEEE J. 38 (2), 243-254. https://doi.org/10.1109/JOE.2012.2227551
Cited by
- Layout Optimization of Two Autonomous Underwater Vehicles for Drag Reduction with a Combined CFD and Neural Network Method vol.2017, pp.None, 2017, https://doi.org/10.1155/2017/5769794
- Hydrofoil optimization of underwater glider using Free-Form Deformation and surrogate-based optimization vol.10, pp.6, 2017, https://doi.org/10.1016/j.ijnaoe.2017.12.005
- Design and Optimization of a Blended-Wing-Body Underwater Glider vol.491, pp.None, 2019, https://doi.org/10.1088/1757-899x/491/1/012001
- Performance study of a simplified shape optimization strategy for blended-wing-body underwater gliders vol.12, pp.None, 2020, https://doi.org/10.1016/j.ijnaoe.2020.05.002
- Shape optimisation of blended-wing-body underwater gliders based on free-form deformation vol.15, pp.3, 2017, https://doi.org/10.1080/17445302.2019.1611989
- A Double-Stage Surrogate-Based Shape Optimization Strategy for Blended-Wing-Body Underwater Gliders vol.34, pp.3, 2017, https://doi.org/10.1007/s13344-020-0036-2
- Shape optimization for blended-wing-body underwater glider using an advanced multi-surrogate-based high-dimensional model representation method vol.52, pp.12, 2020, https://doi.org/10.1080/0305215x.2019.1694674
- An Efficient Surrogate-Based Optimization Method for BWBUG Based on Multifidelity Model and Geometric Constraint Gradients vol.2021, pp.None, 2017, https://doi.org/10.1155/2021/6939863
- Design and optimization of a bio-inspired hull shape for AUV by surrogate model technology vol.15, pp.1, 2017, https://doi.org/10.1080/19942060.2021.1940287
- Energy consumption prediction method based on LSSVM-PSO model for autonomous underwater gliders vol.230, pp.None, 2017, https://doi.org/10.1016/j.oceaneng.2021.108982
- Shape Optimization for A Conventional Underwater Glider to Decrease Average Periodic Resistance vol.35, pp.5, 2021, https://doi.org/10.1007/s13344-021-0064-6
- Energy Consumption Modeling for Underwater Gliders Considering Ocean Currents and Seawater Density Variation vol.9, pp.11, 2017, https://doi.org/10.3390/jmse9111164