Relevant bibliographies by topics / Structural optimization

Academic literature on the topic 'Structural optimization'

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Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Structural optimization"

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S, Nakkeeran. "Structural Optimization of Automotive Chassis." International Journal of Psychosocial Rehabilitation 23, no. 4 (July 20, 2019): 18–23. http://dx.doi.org/10.37200/ijpr/v23i4/pr190155.

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Yanev, Bojidar. "Structural optimization." Structure and Infrastructure Engineering 7, no. 6 (June 2011): 453–54. http://dx.doi.org/10.1080/15732479.2010.532634.

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SEGUCHI, Yasuyuki. "Structural Optimization." Journal of the Society of Mechanical Engineers 92, no. 847 (1989): 485–91. http://dx.doi.org/10.1299/jsmemag.92.847_485.

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A. Mota Soares, Carlos, Martin P. Bendsoe, Kyung K. Choi, and José Herskovits. "Structural optimization." Computers & Structures 86, no. 13-14 (July 2008): 1385. http://dx.doi.org/10.1016/j.compstruc.2007.05.016.

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Nowak, M. "Improved aeroelastic design through structural optimization." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 2 (October 1, 2012): 237–40. http://dx.doi.org/10.2478/v10175-012-0031-8.

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Abstract. The paper presents the idea of coupled multiphysics computations. It shows the concept and presents some preliminary results of static coupling of structural and fluid flow codes as well as biomimetic structural optimization. The model for the biomimetic optimization procedure was the biological phenomenon of trabecular bone functional adaptation. Thus, the presented structural bio-inspired optimization system is based on the principle of constant strain energy density on the surface of the structure. When the aeroelastic reactions are considered, such approach allows fulfilling the mechanical theorem for the stiffest design, comprising the optimizations of size, shape and topology of the internal structure of the wing.
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Enomoto, Hirohisa, and Shigeru Sakamoto. "Structural Optimization System." Journal of the Acoustical Society of America 129, no. 3 (2011): 1666. http://dx.doi.org/10.1121/1.3573317.

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Liang, Qing Quan. "Structural Design Optimization." Advances in Structural Engineering 10, no. 6 (December 2007): i—ii. http://dx.doi.org/10.1260/136943307783571463.

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Gutkowski, Witold, Jacek Bauer, and Zdzisław Iwanow. "Discrete structural optimization." Computer Methods in Applied Mechanics and Engineering 51, no. 1-3 (September 1985): 71–78. http://dx.doi.org/10.1016/0045-7825(85)90028-3.

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Frangopol, Dan M. "Probabilistic structural optimization." Progress in Structural Engineering and Materials 1, no. 2 (January 1998): 223–30. http://dx.doi.org/10.1002/pse.2260010216.

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Marti, Kurt. "Structural reliability and stochastic structural optimization." Mathematical Methods of Operations Research 46, no. 3 (October 1997): 285–86. http://dx.doi.org/10.1007/bf01194857.

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Dissertations / Theses on the topic "Structural optimization"

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Sibai, Munira. "Optimization of an Unfurlable Space Structure." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99908.

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Deployable structures serve a large number of space missions. They are vital since spacecraft are launched by placing them inside launch vehicle payload fairings of limited volume. Traditional spacecraft design often involves large components. These components could have power, communication, or optics applications and include booms, masts, antennas, and solar arrays. Different stowing methods are used in order to reduce the overall size of a spacecraft. Some examples of stowing methods include simple articulating, more complex origami inspired folding, telescoping, and rolling or wrapping. Wrapping of a flexible component could reduce the weight by eliminating joints and other components needed to enable some of the other mechanisms. It also is one of the most effective methods at reducing the compaction volume of the stowed deployable. In this study, a generic unfurlable structure is optimized for maximum natural frequency at its fully deployed configuration and minimal strain energy in its stowed configuration. The optimized stowed structure is then deployed in simulation. The structure consists of a rectangular panel that tightly wraps around a central cylindrical hub for release in space. It is desired to minimize elastic energy in the fully wrapped panel and hinge to ensure minimum reaction load into the spacecraft as it deploys in space, since that elastic energy stored at the stowed position transforms into kinetic energy when the panel is released and induces a moment in the connected spacecraft. It is also desired to maximize the fundamental frequency of the released panel as a surrogate for the panel having sufficient stiffness. Deployment dynamic analysis of the finite element model was run to ensure satisfactory optimization formulation and results.
Master of Science
Spacecraft, or artificial satellites, do not fly from earth to space on their own. They are launched into their orbits by placing them inside launch vehicles, also known as carrier rockets. Some parts or components of spacecraft are large and cannot fit in their designated space inside launch vehicles without being stowed into smaller volumes first. Examples of large components on spacecraft include solar arrays, which provide power to the spacecraft, and antennas, which are used on satellite for communication purposes. Many methods have been developed to stow such large components. Many of these methods involve folding about joints or hinges, whether it is done in a simple manner or by more complex designs. Moreover, components that are flexible enough could be rolled or wrapped before they are placed in launch vehicles. This method reduces the mass which the launch vehicle needs to carry, since added mass of joints is eliminated. Low mass is always desirable in space applications. Furthermore, wrapping is very effective at minimizing the volume of a component. These structures store energy inside them as they are wrapped due to the stiffness of their materials. This behavior is identical to that observed in a deformed spring. When the structures are released in space, that energy is released, and thus, they deploy and try to return to their original form. This is due to inertia, where the stored strain energy turns into kinetic energy as the structure deploys. The physical analysis of these structures, which enables their design, is complex and requires computational solutions and numerical modeling. The best design for a given problem can be found through numerical optimization. Numerical optimization uses mathematical approximations and computer programming to give the values of design parameters that would result in the best design based on specified criterion and goals. In this thesis, numerical optimization was conducted for a simple unfurlable structure. The structure consists of a thin rectangular panel that wraps tightly around a central cylinder. The cylinder and panel are connected with a hinge that is a rotational spring with some stiffness. The optimization was solved to obtain the best values for the stiffness of the hinge, the thickness of the panel, which is allowed to vary along its length, and the stiffness or elasticity of the panel's material. The goals or objective of the optimization was to ensure that the deployed panel meets stiffness requirement specified for similar space components. Those requirements are set to make certain that the spacecraft can be controlled from earth even with its large component deployed. Additionally, the second goal of the optimization was to guarantee that the unfurling panel does not have very high energy stored while it's wrapped, so that it would not cause large motion the connected spacecraft in the zero gravity environments of space. A computer simulation was run with the resulting hinge stiffness and panel elasticity and thickness values with the cylinder and four panels connected to a structure representing a spacecraft. The simulation results and deployment animation were assessed to confirm that desired results were achieved.
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Denli, Huseyin. "Structural-acoustic optimization of composite sandwich structures." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 168 p, 2007. http://proquest.umi.com/pqdlink?did=1251904511&Fmt=7&clientId=79356&RQT=309&VName=PQD.

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Peters, David W. "Design of diffractive optical elements through low-dimensional optimization." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/54614.

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The simulation of diffractive optical structures allows for the efficient testing of a large number of structures without having to actually fabricate these devices. Various forms of analysis of these structures have been done through computer programs in the past. However, programs that can actually design a structure to perform a given task are very limited in scope. Optimization of a structure can be a task that is very processor time intensive, particularly if the optimization space has many dimensions. This thesis describes the creation of a computer program that is able to find an optimal structure while maintaining a low-dimensional search space, thus greatly reducing the processor time required to find the solution. The program can design the optimal structure for a wide variety of planar optical devices that conform to the weakly-guiding approximation with an efficient code that incorporates the low-dimensional search space concept. This work is the first use of an electromagnetic field solver inside of an optimization loop for the design of an optimized diffractive-optic structure.
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Panayirci, Huseyin Murat. "Structural Optimization Using Ansys." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/2/12607075/index.pdf.

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This study describes the process of performing structural optimization using ANSYS. In the first part, the general concepts in optimization and optimization algorithms for different type of optimization problems are covered. Also finite element method is introduced briefly in this part. In the second part, important definitions in structural optimization are mentioned. Then the optimization methods available in ANSYS are explained with their theories. Necessary steps to perform optimization with ANSYS are described at the end of this part. In the next part, sample problems found from scientific papers are solved using ANSYS and the results are compared. At the end of the study, the results obtained from the example problems are discussed whether they came out as expected or not. Also conclusions are made about solving optimization problems and performing structural optimization with ANSYS.
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Schmidt, Martin-Pierre. "Computational generation and optimization of mechanical structures On structural topology optimization using graded porosity control Structural topology optimization with smoothly varying fiber orientations." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMIR01.

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Cette thèse étudie et développe des méthodes de modélisation mathématique, analyse et optimisation numérique appliquées à la génération d’objets 3D. Les approches proposées sont utilisées pour la génération de structures lattices et de structure continue par optimisation topologique
This thesis studies and develops methods for mathematical modeling, numerical analysis and optimization applied to the generation of 3D objects. The proposed approaches are used to generate lattice structures and continuum structures with topology optimization
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Mahfouz, S. Y. "Design optimization of structural steelwork." Thesis, University of Bradford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.534650.

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Hassani, B. "Homogenization and topological structural optimization." Thesis, Swansea University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493797.

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Clune, Rory P. (Rory Patrick). "Algorithm selection in structural optimization." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82832.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 153-162).
Structural optimization is largely unused as a practical design tool, despite an extensive academic literature which demonstrates its potential to dramatically improve design processes and outcomes. Many factors inhibit optimization's application. Among them is the requirement for engineers-who generally lack the requisite expertise-to choose an optimization algorithm for a given problem. A suitable choice of algorithm improves the resulting design and reduces computational cost, yet the field of optimization does little to guide engineers in selecting from an overwhelming number of options. The goal of this dissertation is to aid, and ultimately to automate, algorithm selection, thus enhancing optimization's applicability in real-world design. The initial chapters examine the extent of the problem by reviewing relevant literature and by performing a short, empirical study of algorithm performance variation. We then specify hundreds of bridge design problems by methodically varying problem characteristics, and solve each of them with eight commonly-used nonlinear optimization algorithms. The resulting, extensive data set is used to address the algorithm selection problem. The results are first interpreted from an engineering perspective to ensure their validity as solutions to realistic problems. Algorithm performance trends are then analyzed, showing that no single algorithm outperforms the others on every problem. Those that achieve the best solutions are often computationally expensive, and those that converge quickly often arrive at poor solutions. Some problem features, such as the numbers of design variables and constraints, the structural type, and the nature of the objective function, correlate with algorithm performance. This knowledge and the generated data set are then used to develop techniques for automatic selection of optimization algorithms, based on a range supervised learning methods. Compared to a set of current, manual selection strategies, these techniques select the best algorithm almost twice as often, lead to better-quality solutions and reduced computational cost, and-on a randomly-chosen set of mass minimization problems-reduce average material use by 9.4%. The dissertation concludes by outlining future research on algorithm selection, on integrating these techniques in design software, and on adapting structural optimization to the realities of design. Keywords: Algorithm selection, structural optimization, structural design, machine learning
by Rory Clune.
Ph.D.
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Debenham, Shaun T. (Shaun Todd) 1973. "Optimization of outrigger structural systems." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/80923.

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Tayar, Memduh Ali. "Design approaches to structural optimization." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/78067.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1986.
MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.
Includes bibliographical references (leaves 84-86).
The objective of this thesis is to develop design approaches to structural optimization. In the example of three-dimensional grid structures, widely known as 'space frames', possible configurations are explored which maximize the load-bearing capacity of the system in relation to its weight. The study has been organized in two chapters: The first chapter starts with a brief review of structural concepts. Along with Gothic as a historical example to optimization, modem analytical methods to optimal structural design are presented which include Maxwell's Lemma, Michell's Fields and Ultimate Strength Analysis. In the second part of the thesis the design solutions are presented. The emphasis lies on a deployable space frame which is based on bar-joist like elements.
by Memduh Ali Tayar.
M.S.
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Books on the topic "Structural optimization"

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MacBain, Keith M., and William R. Spillers. Structural Optimization. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-95865-1.

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Save, M., W. Prager, and W. H. Warner, eds. Structural Optimization. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4615-7921-2.

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Rozvany, G. I. N., and B. L. Karihaloo, eds. Structural Optimization. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1.

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Kirsch, Uri. Structural Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84845-2.

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MacBain, Keith M. Structural Optimization. Boston, MA: Springer-Verlag US, 2009.

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M, Save, Prager William 1903-1980, Sacchi G, and Warner William H. 1929-, eds. Structural optimization. New York: Plenum Press, 1985.

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Gutkowski, Witold, and Jacek Bauer, eds. Discrete Structural Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85095-0.

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Gutkowski, W., ed. Discrete Structural Optimization. Vienna: Springer Vienna, 1997. http://dx.doi.org/10.1007/978-3-7091-2754-4.

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Xie, Y. M., and G. P. Steven. Evolutionary Structural Optimization. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0985-3.

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Xie, Y. M. Evolutionary Structural Optimization. London: Springer London, 1997.

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Book chapters on the topic "Structural optimization"

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Kirsch, Uri. "Optimization Methods." In Structural Optimization, 57–124. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84845-2_2.

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Spillers, William R., and Keith M. MacBain. "Multicriteria Optimization." In Structural Optimization, 175–78. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-95865-1_8.

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Kirsch, Uri. "Problem Statement." In Structural Optimization, 1–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84845-2_1.

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Kirsch, Uri. "Approximation Concepts." In Structural Optimization, 125–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84845-2_3.

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Kirsch, Uri. "Design Procedures." In Structural Optimization, 179–291. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84845-2_4.

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Anderson, Melvin S. "Practical Design of Shear and Compression Loaded Stiffened Panels." In Structural Optimization, 1–8. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_1.

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de Boer, R. "Optimization of Vibrating Thin-Walled Structures." In Structural Optimization, 69–76. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_10.

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Ellyin, Fernand. "Shape Optimization of Intersecting Pressure Vessels." In Structural Optimization, 77–84. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_11.

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Eschenauer, H. A., and P. U. Post. "Optimization Procedure S A P 0 P Applied to Optimal Layouts of Complex Structures." In Structural Optimization, 85–92. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_12.

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Esping, B., and D. Holm. "Structural Shape Optimization Using OASIS." In Structural Optimization, 93–100. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_13.

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Conference papers on the topic "Structural optimization"

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SOBIESZCZANSKI-SOBIESKI, J., B. JAMES, and M. RILEY. "Structural optimization by generalized, multilevel optimization." In 26th Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1985. http://dx.doi.org/10.2514/6.1985-697.

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BENNETT, J., and R. LUST. "Conservative methods for structural optimization." In 30th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1219.

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VANDERPLAATS, G., H. MIURA, H. CAI, and S. HANSEN. "Structural optimization using synthetic functions." In 30th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1222.

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GRANDHI, R., and V. VENKAYYA. "Structural optimization with frequency constraints." In 28th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-787.

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THANEDAR, PRAMOD, and SRINIVAS KODIYALAM. "Structural optimization using probabilistic constraints." In 32nd Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-922.

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HAFTKA, R., and R. GRANDHI. "Structural shape optimization - A survey." In 26th Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1985. http://dx.doi.org/10.2514/6.1985-772.

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BES, CH, and J. LOCATELLI. "Structural optimization at Aerospatiale Aircraft." In 33rd Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-2371.

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Mogami, Katsuya, Shinji Nishiwaki, Kazuhiro Izui, Masataka Yoshimura, and Tsuyoshi Nomura. "Structural Optimization for the Design of Band-Gap Structures Using Discrete Structural Elements." In 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7010.

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Yu, Xiaoye, and Tianjian Ji. "Searching Efficient Structural Forms: Evolutionary Structural Optimization Vs Structural Concepts." In The Seventh International Structural Engineering and Construction Conference. Singapore: Research Publishing Services, 2013. http://dx.doi.org/10.3850/978-981-07-5354-2_st-163-487.

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Choi, Kwong-Kit, Chung-Hsiang Lin, Kok-Ming Leung, and Theodor Tamir. "QWIP structural optimization." In International Symposium on Optical Science and Technology, edited by Randolph E. Longshore and Sivalingam Sivananthan. SPIE, 2002. http://dx.doi.org/10.1117/12.453827.

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Reports on the topic "Structural optimization"

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Lenee-Bluhm, Pukha. Structural Optimization Final Technical Report. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1737349.

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Flynn, Eric B. Design Optimization of Structural Health Monitoring Systems. Office of Scientific and Technical Information (OSTI), March 2014. http://dx.doi.org/10.2172/1122908.

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Park, Gyung-Jin. Structural Optimization Using the Equivalent Load Concept. Fort Belvoir, VA: Defense Technical Information Center, November 2005. http://dx.doi.org/10.21236/ada451871.

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Voon, B. K., and M. A. Austin. Structural Optimization in a Distributed Computing Environment. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada454846.

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Moon, Young I. Geodesic Wing Structural Optimization and Dynamic Analysis. Fort Belvoir, VA: Defense Technical Information Center, August 1996. http://dx.doi.org/10.21236/ada361169.

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Striz, Alfred G. Influence of Structural and Aerodynamic Modeling on Flutter Analysis and Structural Optimization. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada248487.

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Aksay, I. A. Structural Hierarchy in Materials: Processing and Property Optimization. Fort Belvoir, VA: Defense Technical Information Center, June 1995. http://dx.doi.org/10.21236/ada371474.

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Kohn, Robert V. Optimization of Structural Topology in the High-Porosity Regime. Fort Belvoir, VA: Defense Technical Information Center, July 2004. http://dx.doi.org/10.21236/ada425439.

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Johnson, E. H., and D. J. Neill. Automated Structural Optimization System (ASTROS). Volume 3. Applications Manual. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/adb130470.

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Plemmons, Robert J. Fast Algorithms for Structural Optimization, Least Squares and Related Computations. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada205047.

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