Literatura académica sobre el tema "Multi-objective Design"

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Artículos de revistas sobre el tema "Multi-objective Design"

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Min, Xinyuan, Jaap Sok, Feije de Zwart, and Alfons Oude Lansink. "Multi-stakeholder multi-objective greenhouse design optimization." Agricultural Systems 215 (March 2024): 103855. http://dx.doi.org/10.1016/j.agsy.2024.103855.

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Freier, Lars, and Eric von Lieres. "Robust multi-objective process design." New Biotechnology 33 (July 2016): S27. http://dx.doi.org/10.1016/j.nbt.2016.06.822.

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Sun, Qi, Tinghuan Chen, Siting Liu, Jianli Chen, Hao Yu, and Bei Yu. "Correlated Multi-objective Multi-fidelity Optimization for HLS Directives Design." ACM Transactions on Design Automation of Electronic Systems 27, no. 4 (2022): 1–27. http://dx.doi.org/10.1145/3503540.

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High-level synthesis (HLS) tools have gained great attention in recent years because it emancipates engineers from the complicated and heavy hardware description language writing and facilitates the implementations of modern applications (e.g., deep learning models) on Field-programmable Gate Array (FPGA) , by using high-level languages and HLS directives. However, finding good HLS directives is challenging, due to the time-consuming design processes, the balances among different design objectives, and the diverse fidelities (accuracies of data) of the performance values between the consecutiv
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YAMASHINA, Hajime, Susumu OKUMURA, and Yoshimasa KONDO. "Parameter Design with Multi Objective Characteristics." Journal of the Japan Society for Precision Engineering 58, no. 3 (1992): 516–20. http://dx.doi.org/10.2493/jjspe.58.516.

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Kor, Jean, Xiang Chen, Zhizhong Sun, and Henry Hu. "Casting Design Through Multi-Objective Optimization." IFAC Proceedings Volumes 44, no. 1 (2011): 11642–47. http://dx.doi.org/10.3182/20110828-6-it-1002.01726.

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Joseph, Shaine, Hyung W. Kang, and Uday K. Chakraborty. "Lens design as multi-objective optimisation." International Journal of Automation and Control 5, no. 3 (2011): 189. http://dx.doi.org/10.1504/ijaac.2011.042851.

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Sanchis, J., M. Martinez, and X. Blasco. "Multi-objective engineering design using preferences." Engineering Optimization 40, no. 3 (2008): 253–69. http://dx.doi.org/10.1080/03052150701693057.

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Eckert, Jony Javorski, Fabio Mazzariol Santiciolli, Ludmila C. A. Silva, and Franco Giuseppe Dedini. "Vehicle drivetrain design multi-objective optimization." Mechanism and Machine Theory 156 (February 2021): 104123. http://dx.doi.org/10.1016/j.mechmachtheory.2020.104123.

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Pelinescu, Diana M., and Michael Yu Wang. "Multi-objective optimal fixture layout design." Robotics and Computer-Integrated Manufacturing 18, no. 5-6 (2002): 365–72. http://dx.doi.org/10.1016/s0736-5845(02)00027-3.

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Lim, Dudy, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, and Bu Sung Lee. "Inverse multi-objective robust evolutionary design." Genetic Programming and Evolvable Machines 7, no. 4 (2006): 383–404. http://dx.doi.org/10.1007/s10710-006-9013-7.

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Tesis sobre el tema "Multi-objective Design"

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Kipouros, Timoleon. "Multi-objective aerodynamic design optimisation." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614261.

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Nezhadali, Vaheed. "Multi-objective optimization of Industrial robots." Thesis, Linköpings universitet, Maskinkonstruktion, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-113283.

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Industrial robots are the most widely manufactured and utilized type of robots in industries. Improving the design process of industrial robots would lead to further developments in robotics industries. Consequently, other dependant industries would be benefited. Therefore, there is an effort to make the design process more and more efficient and reliable. The design of industrial robots requires studies in various fields. Engineering softwares are the tools which facilitate and accelerate the robot design processes such as dynamic simulation, structural analysis, optimization, control and so
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Liu, Wei. "A multi-objective approach for RMT design." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27149.

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A reconfigurable manufacturing system (RMS) is designed for rapid adjustment of manufacturing capacity and functionality in response to market changes. An RMS consists of a number of reconfigurable machine tools (RMTs) which can process different jobs by quickly changing processing modules. The potential benefits of an RMS may not be achieved if an RMS is not properly designed. Most of the related studies focus on a few individual technical issues, in particular on modularity or configurability of individual RMTs. Other important concerns such as cost and processing accuracy have not been adeq
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Li, Yinjiang. "Robust multi-objective optimisation in electromagnetic design." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/415498/.

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In electromagnetic design, optimisation often involves evaluating the finite element method (FEM) – repetitive evaluation of the objective function may require hours or days of computation, making the use of standard direct search methods (e.g. genetic algorithm and particle swarm) impractical. Surrogate modelling techniques are helpful tools in these scenarios. Indeed, their applications can be found in many aspects of engineering design in which a computationally expensive model is involved. Kriging, one of the most widely used surrogate modelling techniques, has become an increasingly activ
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Ramadan, Saleem Z. "Bayesian Multi-objective Design of Reliability Testing." Ohio University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1298474937.

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El-Sayed, Jacqueline Johnson. "Multi-objective optimization of manufacturing processes design /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841282.

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Faragalli, Michele. "Multi-objective design optimization of compliant lunar wheels." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=117030.

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The development of the wire-mesh wheel of the Apollo Lunar Roving Vehicle was realized through a time consuming trial and error design process, primarily driven by manufacturability and physical testing. Recent wheel development, motivated by renewed interest in lunar surface exploration, utilizes more sophisticated numerical simulation tools. However, many researchers still employ trial and error or parametric approaches to designing the wheels. This thesis proposes a systematic approach to the design optimization of compliant lunar wheels. The problem is decomposed into system and component
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Skinner, Benjamin Adam. "Multi-objective evolutionary optimisation of submarine propulsion design." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611230.

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Brown, Nathan C. (Nathan Collin). "Early building design using multi-objective data approaches." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123573.

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Thesis: Ph. D. in Architecture: Building Technology, Massachusetts Institute of Technology, Department of Architecture, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 201-219).<br>During the design process in architecture, building performance and human experience are increasingly understood through computation. Within this context, this dissertation considers how data science and interactive optimization techniques can be combined to make simulation a more effective component of a natural early design process. It focuses on conceptual design, since
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Paik, Sangwook. "Multi-objective optimal design of steel trusses in unstructured design domains." Thesis, Texas A&M University, 2005. http://hdl.handle.net/1969.1/3124.

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Researchers have applied genetic algorithms (GAs) and other heuristic optimization methods to perform truss optimization in recent years. Although a substantial amount of research has been performed on the optimization of truss member sizes, nodal coordinates, and member connections, research that seeks to simultaneously optimize the topology, geometry, and member sizes of trusses is still uncommon. In addition, most of the previous research is focused on the problem domains that are limited to a structured domain, which is defined by a fixed number of nodes, members, load locations, and load
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Libros sobre el tema "Multi-objective Design"

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Liu, Aying. A multi-objective and multi-design evaluation procedure for environmental protection forestry. University of Portsmouth, Department of Economics, 1997.

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Wang, Lihui, Amos H. C. Ng, and Kalyanmoy Deb, eds. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-652-8.

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Silvano, Cristina, William Fornaciari, and Eugenio Villar, eds. Multi-objective Design Space Exploration of Multiprocessor SoC Architectures. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8837-9.

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C, Ng Amos H., Deb Kalyanmoy, and SpringerLink (Online service), eds. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. Springer-Verlag London Limited, 2011.

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United States. National Aeronautics and Space Administration., ed. Multi-objective decision-making under uncertainty: Fuzzy logic methods. National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. Multi-objective decision-making under uncertainty: Fuzzy logic methods. National Aeronautics and Space Administration, 1994.

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S, Rao S. Applications of fuzzy theories to multi-objective system optimization. National Aeronautics and Space Administration, Ames Research Center, 1991.

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Center, Lewis Research, and United States. National Aeronautics and Space Administration., eds. Multi objective controller design for linear systems via optimal interpolation. Ohio State University, 1996.

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Center, Lewis Research, and United States. National Aeronautics and Space Administration., eds. Multi objective controller design for linear systems via optimal interpolation. Ohio State University, 1996.

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Sun, Xiaodong, Kaikai Diao, Gang Lei, and Jianguo Zhu. Multi-objective Design Optimization of Switched Reluctance Motor Drive Systems. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-96-0672-6.

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Capítulos de libros sobre el tema "Multi-objective Design"

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Han, Xu, and Jie Liu. "Micro Multi-objective Genetic Algorithm." In Numerical Simulation-based Design. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-10-3090-1_9.

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Chen, Yi, and Yun Li. "Extra‐Numerical Multi‐Objective optimization." In Computational Intelligence Assisted Design. CRC Press, 2018. http://dx.doi.org/10.1201/9781315153179-8.

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Sun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Control Design." In Cell Mapping Methods. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_10.

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Sun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Structure Design." In Cell Mapping Methods. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_11.

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Sun, Jian-Qiao, Fu-Rui Xiong, Oliver Schütze, and Carlos Hernández. "Multi-objective Optimal Airfoil Design." In Cell Mapping Methods. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0457-6_12.

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Han, Xu, and Jie Liu. "Introduction to Multi-objective Optimization Design." In Numerical Simulation-based Design. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-10-3090-1_8.

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Parmee, Ian C. "Multi-objective Satisfaction and Optimisation." In Evolutionary and Adaptive Computing in Engineering Design. Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0273-1_10.

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Jerin Leno, I., S. Saravana Sankar, and S. G. Ponnambalam. "Multi Objective Integrated Layout Design Problem." In Swarm, Evolutionary, and Memetic Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35380-2_59.

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D’Errico, Fabrizio. "Multi-Objective Optimization in Engineering Design." In SpringerBriefs in Materials. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13030-9_2.

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M’laouhi, Ibrahim, Najeh Ben Guedria, and Hichem Smaoui. "Multi-objective Discrete Rotor Design Optimization." In Condition Monitoring of Machinery in Non-Stationary Operations. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_20.

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Actas de conferencias sobre el tema "Multi-objective Design"

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Govindan, Srinivasan, Srikrishnan Venkataraman, Beomseok Choi, and Amit Kumar. "Multi-objective Optimization of FIVR Control Loop." In 2024 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS). IEEE, 2024. https://doi.org/10.1109/edaps64431.2024.10988456.

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Liu, Yiwei, Yiping Liu, Jiahao Yang, Xinyi Zhang, Li Wang, and Xiangxiang Zeng. "Multi-Objective Molecular Design in Constrained Latent Space." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651509.

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Jian, Huang, and Wang Yihan. "Asset Optimization Scheme Design with Multi-Objective Optimization." In 2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS). IEEE, 2024. http://dx.doi.org/10.1109/iciteics61368.2024.10625611.

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Zangl, H., and G. Steiner. "Optimal design of multi-objective multi-sensor systems." In Proceedings of the 2005 IEEE International Workshop on Advanced Methods for Uncertainty Estimation in Measurement. IEEE, 2005. http://dx.doi.org/10.1109/amuem.2005.1594616.

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Yuan-Chang Chang, Li-Wei Kuo, and Jenq-Lang Wu. "Reliable multi-objective decentralized controller design." In 2010 International Conference on System Science and Engineering (ICSSE). IEEE, 2010. http://dx.doi.org/10.1109/icsse.2010.5551749.

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Wang, Wei, Xin-long Chang, You-hong Zhang, and Chun-wen Wang. "Composite Laminated Multi-Objective Optimization Design." In 2020 International Conference on Artificial Intelligence and Electromechanical Automation (AIEA). IEEE, 2020. http://dx.doi.org/10.1109/aiea51086.2020.00134.

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Keough, Ian, and David Benjamin. "Multi-objective optimization in architectural design." In the 2010 Spring Simulation Multiconference. ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878736.

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Rojas, José David, and Victor M. Alfaro. "Multi-objective design of industrial controllers." In 2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC). IEEE, 2017. http://dx.doi.org/10.1109/ccac.2017.8320344.

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Kor, Jean, Xiang Chen, Zhizhong Sun, and Henry Hu. "Casting Design through Multi-objective Optimization." In 2009 Second International Conference on Future Information Technology and Management Engineering (FITME). IEEE, 2009. http://dx.doi.org/10.1109/fitme.2009.156.

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Poian, M., S. Poles, F. Bernasconi, E. Leroux, W. Steffe, and M. Zolesi. "Multi-objective optimization for antenna design." In 2008 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS). IEEE, 2008. http://dx.doi.org/10.1109/comcas.2008.4562817.

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Informes sobre el tema "Multi-objective Design"

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Kuprowicz, Nicholas J. The Integrated Multi-Objective Multi-Disciplinary Jet Engine Design Optimization Program. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada372032.

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Fernandez, Ruben, Hernando Lugo, and Georfe Dulikravich. Aerodynamic Shape Multi-Objective Optimization for SAE Aero Design Competition Aircraft. Florida International University, 2021. http://dx.doi.org/10.25148/mmeurs.009778.

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The SAE Regular Class Aero Design Competition requires students to design a radio-controlled aircraft with limits to the aircraft power consumption, take-off distance, and wingspan, while maximizing the amount of payload it can carry. As a result, the aircraft should be designed subject to these simultaneous and contradicting objectives: 1) minimize the aerodynamic drag force, 2) minimize the aerodynamic pitching moment, and 3) maximize the aerodynamic lift force. In this study, we optimized the geometric design variables of a biplane configuration using 3D aerodynamic analysis using the ANSYS
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Wenren, Yonghu, Joon Lim, Luke Allen, Robert Haehnel, and Ian Dettwiler. Helicopter rotor blade planform optimization using parametric design and multi-objective genetic algorithm. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46261.

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In this paper, an automated framework is presented to perform helicopter rotor blade planform optimization. This framework contains three elements, Dakota, ParBlade, and RCAS. These elements are integrated into an environment control tool, Galaxy Simulation Builder, which is used to carry out the optimization. The main objective of this work is to conduct rotor performance design optimizations for forward flight and hover. The blade design variables manipulated by ParBlade are twist, sweep, and anhedral. The multi-objective genetic algorithm method is used in this study to search for the optim
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Dulikravich, George S., Igor N. Egorov, Vinod K. Sikka, and G. Muralidharan. Alloys-by-Design Strategies Using Stochastic Multi-Objective Optimization: Initial Formulation and Results. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada416083.

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Bau, Domenico. Recovery Act: Multi-Objective Optimization Approaches for the Design of Carbon Geological Sequestration Systems. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1097612.

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Barlow, Gregory J. Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles Using Multi-Objective Genetic Programming. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada460111.

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Kobayashi, Marcelo H. (HBCU) Development and Application of a Biologically Inspired Methodology for the Optimized, Multi-Disciplinary and Multi-Objective Design of Air Vehicles. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada584389.

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Choi, Yong-Joon, Mohammad M Mostafa Abdo, Yong-Joon Choi, et al. Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2006453.

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Choi, Yong-Joon, Junyung Kim, Mohammad M Mostafa Abdo, et al. Pressurized-Water Reactor Core Design Demonstration with Genetic Algorithm Based Multi-Objective Plant Fuel Reload Optimization Platform. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2006437.

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Allen, Luke, Joon Lim, Robert Haehnel, and Ian Dettwiller. Helicopter rotor blade multiple-section optimization with performance. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41031.

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This paper presents advancements in a surrogate-based, rotor blade design optimization framework for improved helicopter performance. The framework builds on previous successes by allowing multiple airfoil sections to designed simultaneously to minimize required rotor power in multiple flight conditions. Rotor power in hover and forward flight, at advance ratio 𝜇 = 0.3, are used as objective functions in a multi-objective genetic algorithm. The framework is constructed using Galaxy Simulation Builder with optimization provided through integration with Dakota. Three independent airfoil sections
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