Relevant bibliographies by topics / Adjoint-Based Optimization

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Academic literature on the topic 'Adjoint-Based Optimization'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Adjoint-Based Optimization"

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Qiu, Sheng. "A continuous adjoint-based aeroacoustic shape optimization for multi-mode duct acoustics." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, no. 21 (2017): 3897–914. http://dx.doi.org/10.1177/0954406217743273.

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A multi-mode adjoint-based optimization method is proposed for the noise reduction optimization in multi-mode duct acoustics problems. The objective is to minimize the amplitude of sound from an inlet duct on the wall and integral line while maintaining the aerodynamic performance. The complete detailed derivation of the adjoint equations and their corresponding adjoint boundary conditions are presented firstly based on the multi-mode linear Euler equations. With the solved adjoint variables, the final expression of the cost function gradient with respect to the design variables is formulated.
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Batay, Sagidolla, Bagdaulet Kamalov, Dinmukhamed Zhangaskanov, et al. "Adjoint-Based High-Fidelity Concurrent Aerodynamic Design Optimization of Wind Turbine." Fluids 8, no. 3 (2023): 85. http://dx.doi.org/10.3390/fluids8030085.

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To evaluate novel turbine designs, the wind energy sector extensively depends on computational fluid dynamics (CFD). To use CFD in the design optimization process, where lower-fidelity approaches such as blade element momentum (BEM) are more popular, new tools to increase the accuracy must be developed as the latest wind turbines are larger and the aerodynamics and structural dynamics become more complex. In the present study, a new concurrent aerodynamic shape optimization approach towards multidisciplinary design optimization (MDO) that uses a Reynolds-averaged Navier–Stokes solver in conjun
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Karpouzas, Georgios K., Evangelos M. Papoutsis-Kiachagias, Thomas Schumacher, Villers Eugene de, Kyriakos C. Giannakoglou, and Carsten Othmer. "Adjoint Optimization for Vehicle External Aerodynamics." International Journal of Automotive Engineering 7, no. 1 (2015): 1–7. https://doi.org/10.5281/zenodo.808434.

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Adjoint optimization is an exciting and fast growing field that has many applications in the automotive industry. We focus on the usage of adjoint for the optimization of aerodynami performance. While adjoint methods have come to the attention of mainstream CFD through inclusion in prominent commercial codes, most of the available tools are severely limited, precluding production use in this field. We detail a methodology that is based on the continuous adjoint method and is implemented in an Open Source framework. While more mathematically demanding in terms of its derivation, the continuous
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Nikolova, N. K., R. Safian, E. A. Soliman, M. H. Bakr, and J. W. Bandler. "Accelerated Gradient Based Optimization Using Adjoint Sensitivities." IEEE Transactions on Antennas and Propagation 52, no. 8 (2004): 2147–57. http://dx.doi.org/10.1109/tap.2004.832313.

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Bunting, Gregory, and Timothy F. Walsh. "Adjoint-based, large-scale optimization of metamaterials." Journal of the Acoustical Society of America 146, no. 4 (2019): 2830. http://dx.doi.org/10.1121/1.5136805.

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Wang, Jiahui, Yu Shi, Tyler Hughes, Zhexin Zhao, and Shanhui Fan. "Adjoint-based optimization of active nanophotonic devices." Optics Express 26, no. 3 (2018): 3236. http://dx.doi.org/10.1364/oe.26.003236.

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Nabi, S., P. Grover, and C. P. Caulfield. "Adjoint-based optimization of displacement ventilation flow." Building and Environment 124 (November 2017): 342–56. http://dx.doi.org/10.1016/j.buildenv.2017.07.030.

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Tsiakas, Konstantinos, Xenofon Trompoukis, Varvara Asouti, et al. "Discrete and Continuous Adjoint-Based Aerostructural Wing Shape Optimization of a Business Jet." Fluids 9, no. 4 (2024): 87. http://dx.doi.org/10.3390/fluids9040087.

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This article presents single- and multi-disciplinary shape optimizations of a generic business jet wing at two transonic cruise flow conditions. The studies performed are based on two high-fidelity gradient-based optimization tools, assisted by the adjoint method (following both discrete and continuous approaches). Single discipline and coupled multi-disciplinary sensitivity derivatives computed from the two tools are compared and verified against finite differences. The importance of not making the frozen turbulence assumption in adjoint-based optimization is demonstrated. Then, a number of o
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Hekmat, Mohamad Hamed, and Masoud Mirzaei. "Development of Discrete Adjoint Approach Based on the Lattice Boltzmann Method." Advances in Mechanical Engineering 6 (January 1, 2014): 230854. http://dx.doi.org/10.1155/2014/230854.

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The purpose of this research is to present a general procedure with low implementation cost to develop the discrete adjoint approach for solving optimization problems based on the LB method. Initially, the macroscopic and microscopic discrete adjoint equations and the cost function gradient vector are derived mathematically, in detail, using the discrete LB equation. Meanwhile, for an elementary case, the analytical evaluation of the macroscopic and microscopic adjoint variables and the cost function gradients are presented. The investigation of the derivation procedure shows that the simplici
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Yang, L., and J. Yang. "Gradient-based aerodynamic shape optimization using a discrete adjoint approach on a graphics processing unit." Journal of Physics: Conference Series 2784, no. 1 (2024): 012008. http://dx.doi.org/10.1088/1742-6596/2784/1/012008.

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Abstract This paper presents a gradient-based aerodynamic shape optimization framework that utilizes a Graphics Processing Unit (GPU) for solving both flow and adjoint equations. It is built based on a GPU-accelerated flow solver that has been developed previously. Hence, the focus of this work is on how to solve the adjoint equations on the GPU and subsequently compute the gradients. The adjoint equations are right-preconditioned by a block Incomplete Lower Upper (ILU) preconditioner and solved by a restarted Generalized Minimum Residual (GMRES) method. The exact residual Jacobian matrix in t
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Dissertations / Theses on the topic "Adjoint-Based Optimization"

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Amoignon, Olivier. "Adjoint-based aerodynamic shape optimization." Licentiate thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86142.

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An adjoint system of the Euler equations of gas dynamics is derived in order to solve aerodynamic shape optimization problems with gradient-based methods. The derivation is based on the fully discrete flow model and involves differentiation and transposition of the system of equations obtained by an unstructured and node-centered finite-volume discretization. Solving the adjoint equations allows an efficient calculation of gradients, also when the subject of optimization is described by hundreds or thousands of design parameters. Such a fine geometry description may cause wavy or otherwise irr
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Chevalier, Mattias. "Adjoint based control and optimization of aerodynamic flows." Licentiate thesis, KTH, Mechanics, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1435.

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Sanchez, Torreguitart Ismael. "Efficient CAD based adjoint optimization of turbomachinery using adaptive shape parameterization." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/667044.

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The present thesis incorporates the CAD model into an adjoint-based optimization loop and uses it for the shape optimization of a 2D transonic turbine blade mid-section (profile). This is demonstrated by performing a single and multipoint optimization of the LS89 turbine, originally designed at the VKI. Substantial aerodynamic improvements are reported for both design point and off-design conditions.The case is deeply analysed from the flow analysis point of view. The present thesis is a step forward in three main aspects. First, the way the CAD model (for turbomachinery applications) is used
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Repke, Sabine [Verfasser]. "Adjoint-Based Optimization Approaches for Stationary Free Surface Flows / Sabine Repke." München : Verlag Dr. Hut, 2011. http://d-nb.info/1018980873/34.

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Müller, Lasse. "Adjoint-Based Optimization of Turbomachinery With Applications to Axial and Radial Turbines." Doctoral thesis, Universite Libre de Bruxelles, 2019. https://dipot.ulb.ac.be/dspace/bitstream/2013/280380/5/contratLM.pdf.

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Numerical optimization methods have made significant progress over the last decades and play an important role in modern industrial design processes. In most cases, gradient-free algorithms are used, which only require the value of the objective function in each optimization step. These methods are robust and can be integrated into a standard design process at low implementation effort. However, in aerodynamic design problems using high-fidelity Computational Fluid Dynamics (CFD), the computational cost is high, especially when a large number of design parameters are used. Gradient-based metho
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Chen, Han Ph D. Massachusetts Institute of Technology. "An adjoint-based optimization method using the solution of gray-box conservation laws." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112409.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 131-138).<br>Many design applications can be formulated as an optimization constrained by conservation laws. Such optimization can be efficiently solved by the adjoint method, which computes the gradient of the objective to the design variables. Traditionally, the adjoint method has not been able to be implemented in "gray-box" conservation law simulations. In gray-box simulations, the analytical and nume
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Prasad, Rachit. "Time Spectral Adjoint Based Design for Flutter and Limit Cycle Oscillation Suppression." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/98574.

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When designing aircraft wings shapes, it is important to ensure that the flight envelope does not overlap with regions of flutter or Limit Cycle Oscillation (LCO). A quick assessment of these dynamic aeroelastic for various design candidates is key to successful design. Flutter based design requires the sensitivity of flutter parameters to be known with the respect of design parameters. Traditionally, frequency domain based methods have been used to predict flutter characteristics and its sensitivity. However, this approach is only applicable for linear or linearized models and cannot be appli
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Kühl, Niklas [Verfasser]. "Adjoint-based shape optimization constraint by turbulent two-phase Navier-Stokes systems / Niklas Kühl." Hamburg : Universitätsbibliothek der Technischen Universität Hamburg-Harburg, 2021. http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0146294.

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Ghazlane, Imane. "Adjoint-based aerostructural sensitivity analysis for wing design." Phd thesis, Université Nice Sophia Antipolis, 2012. http://tel.archives-ouvertes.fr/tel-00925210.

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Cette thèse a pour cadre le développement de méthodes numériques pour la conception optimale de forme de voilure en aérodynamique compressible. Ce travail a donné lieu au développement et à la validation d'un adjoint discret aéro-structure pour l'analyse de sensibilité par rapport aux paramètres de forme et de structure interne de l 'aile dont dépend la fonction d'intérêt, qu' elle soit aérodynamique ou structurale. Les développements logiciels ont été réalisés dans le code de simulation numérique de mécanique des fluides elsA et font suite aux travaux de Marcelet portant sur l'adjoint aéroéla
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Ghazlane, Imane. "Adjoint-based aerostructural sensitivity analysis for wing design." Phd thesis, Nice, 2012. http://www.theses.fr/2012NICE4110.

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Cette thèse a pour cadre le développement de méthodes numériques pour la conception optimale de forme de voilure en aérodynamique compressible. Ce travail a donné lieu au développement et à la validation d'un adjoint discret aéro-structure pour l'analyse de sensibilité par rapport aux paramètres de forme et de structure interne de l 'aile dont dépend la fonction d'intérêt, qu' elle soit aérodynamique ou structurale. Les développements logiciels ont été réalisés dans le code de simulation numérique de mécanique des fluides elsA et font suite aux travaux de Marcelet portant sur l'adjoint aéroéla
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Books on the topic "Adjoint-Based Optimization"

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ITWM, Kaiserslautern Fraunhofer, and Raphael Hohmann. Continuous Adjoint-Based Shape Optimization for Particle Transport Problems in Fluids. Fraunhofer IRB Verlag, 2020.

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Müller, Lasse. Adjoint-Based Optimization of Turbomachinery with Application to Axial and Radial Turbines. von Karman Institute for Fluid Dynamics, 2019. http://dx.doi.org/10.35294/phdt201903.

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Blauth, Sebastian, and Fraunhofer ITWM. Adjoint-Based Shape Optimization and Optimal Control with Applications to Microchannel Systems. Fraunhofer IRB Verlag, 2021.

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Book chapters on the topic "Adjoint-Based Optimization"

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Damigos, Marios, and Eugene De Villiers. "CAD-Based Parameterization for Adjoint Optimization." In OpenFOAM®. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-60846-4_2.

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Cliff, Eugene M., Matthias Heinkenschloss, and Ajit R. Shenoy. "Adjoint-Based Methods in Aerodynamic Design-Optimization." In Computational Methods for Optimal Design and Control. Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1780-0_6.

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Elssel, Kolja, Kaare Sørensen, and Ögmundur Petersson. "Application of Adjoint Based Optimization on a MALE Platform." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72020-3_8.

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Papoutsis-Kiachagias, Evangelos M., Mehdi Ghavami Nejad, and Kyriakos C. Giannakoglou. "Aerodynamic Shape Optimization Using the Adjoint-Based Truncated Newton Method." In Computational Methods in Applied Sciences. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89988-6_9.

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Zhou, Lin, Xian Chen, Jiangtao Huang, Jun Deng, and Zhenghong Gao. "Adjoint-Based RCS Surface Sensitivity Calculation and Aero/RCS Optimization." In 2023 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2023) Proceedings. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4010-9_133.

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Zahr, Matthew J., and Per-Olof Persson. "Energetically Optimal Flapping Wing Motions via Adjoint-Based Optimization and High-Order Discretizations." In Frontiers in PDE-Constrained Optimization. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8636-1_7.

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Guo, Jingrui, Min Xu, and Yi Li. "Aero-Structural Optimization of a Supersonic Wing Model Using Adjoint-Based Optimization Algorithm." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3305-7_86.

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Li, Ding, and Ralf Hartmann. "Adjoint-Based Error Estimation and Mesh Refinement in an Adjoint-Based Airfoil Shape Optimization of a Transonic Benchmark Problem." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27279-5_47.

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Sanchez Torreguitart, Ismael, Tom Verstraete, and Lasse Mueller. "CAD and Adjoint Based Multipoint Optimization of an Axial Turbine Profile." In Computational Methods in Applied Sciences. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89890-2_3.

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Jakubek, Daria, and Claus Wagner. "Adjoint-Based, CAD-Free Aerodynamic Shape Optimization of High-Speed Trains." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27279-5_36.

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Conference papers on the topic "Adjoint-Based Optimization"

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Mani, Karthik, Dimitri Mavriplis, Asitav Mishra, and Jay Sitaraman. "Time-depedent Adjoint-based Aerodynamic Shape Optimization Applied to Helicopter Rotors." In Vertical Flight Society 70th Annual Forum & Technology Display. The Vertical Flight Society, 2014. http://dx.doi.org/10.4050/f-0070-2014-9443.

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A formulation for sensitivity analysis of fully coupled time-dependent aeroelastic problems is given in this paper. Both forward sensitivity and adjoint sensitivity formulations are derived that correspond to analogues of the non-linear aeroelastic analysis problem. Both sensitivity analysis formulations make use of the same iterative disciplinary solution techniques used for analysis, and make use of an analogous coupling strategy. The information passed between fluid and structural solvers is dimensionally equivalent in all cases, enabling the use of the same data structures for analysis, fo
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Fabiano, Enrico, and Dimitri Mavriplis. "Adjoint-based Aeroacoustic Design-Optimization of Flexible Rotors in Forward Flight." In Vertical Flight Society 72nd Annual Forum & Technology Display. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11384.

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This paper presents the development and application of a time-dependent adjoint-based method for aeroacoustic design optimization of flexible helicopter rotors in forward flight. The rotor noise signature at a farfield observer is computed with the hybrid aeroacoustic approach in which a near-body coupled computational fluid dynamics/ computational structural dynamics solver provides flow and geometry data to an FW-H acoustic module that propagates the acoustic waves to a farfield observer. Forward and adjoint sensitivity formulations are derived that correspond to analogues of the multidiscip
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Vlemmix, Stijn, Gerard J. P. Joosten, Roald Brouwer, and Jan-Dirk Jansen. "Adjoint-Based Well Trajectory Optimization." In EUROPEC/EAGE Conference and Exhibition. Society of Petroleum Engineers, 2009. http://dx.doi.org/10.2118/121891-ms.

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Bisson, Francois, and Sivakumaran Nadarajah. "Adjoint-Based Aerodynamic Optimization Framework." In 52nd Aerospace Sciences Meeting. American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-0412.

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Crean, Jared, Kinshuk Panda, and Jason E. Hicken. "Adjoint-based Local Reanalysis of Nonlinear PDEs." In 2018 Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3110.

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Wei, Mingjun, and Jonathan Freund. "Noise Control Using Adjoint-based Optimization." In 8th AIAA/CEAS Aeroacoustics Conference & Exhibit. American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-2524.

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Van Doren, Jorn, Sippe G. Douma, L. Bart M. Wassing, J. F. B. M. Kraaijevanger, and Albert Hendrik De Zwart. "Adjoint-based Optimization of Polymer Flooding." In SPE Enhanced Oil Recovery Conference. Society of Petroleum Engineers, 2011. http://dx.doi.org/10.2118/144024-ms.

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Yamaleev, Nail, Boris Diskin, and Eric Nielsen. "Adjoint-Based Methodology for Time-Dependent Optimization." In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-5857.

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Luers, Mathias, Max Sagebaum, Sebastian Mann, Jan Backhaus, David Grossmann, and Nicolas R. Gauger. "Adjoint-based Volumetric Shape Optimization of Turbine Blades." In 2018 Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-3638.

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Yang, Jinguang, Xiuquan Huang, and Hu Wu. "Multi-Row Inverse Method Based on the Adjoint Optimization." In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/gt2011-46130.

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The conventional inverse method possesses several disadvantages: experience-dependence, inconvenience for multi-row application and lots of human intervention. This hinders it from becoming a routine design tool. In the present paper, those mentioned shortcomings are conquered by combining the inverse method with a multi-row adjoint method, which could give an automatic and optimized design in a multi-row enviroment. The principles of the inverse method and adjoint method are first introduced. Then a derivation for the adjoint equation based on the Euler inverse method is conducted, and the co
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Reports on the topic "Adjoint-Based Optimization"

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Bewley, Thomas R. Adjoint-Based Optimization and Control of Complex Dynamics in Fluid Systems. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada441360.

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Gu, Grace, Judith Alice Brown, and Joseph E. Bishop. Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1375571.

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