Mostrar el registro sencillo del documento

dc.rights.licenseAtribución-NoComercial 4.0 Internacional
dc.contributor.advisorGalvis Arrieta, Juan Carlos
dc.contributor.advisorNorato Escobar, Julian Andrés
dc.contributor.authorOrtegón Villacorte, Andrés Felipe
dc.date.accessioned2023-11-30T19:08:55Z
dc.date.available2023-11-30T19:08:55Z
dc.date.issued2023-10-03
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/85030
dc.descriptionilustraciones, diagramas
dc.description.abstractEste trabajo de investigación estudia las técnicas de optimización topológica aplicadas al problema clásico del calor y al problema de la elasticidad. El estudio destaca varios aspectos clave encontrados durante el proceso de búsqueda de soluciones para problemas específicos, incluida la influencia de las condiciones iniciales y los parámetros del optimizador. Además, el documento explora enfoques novedosos y variaciones de métodos fundamentales encaminados a lograr soluciones finales mejoradas para cada problema. Estas adaptaciones abarcan ajustes del funcional minimizado, la representación del espacio de densidad y la aplicación de métodos de regularización. (Texto tomado de la fuente)
dc.description.abstractThis work studies topological optimization techniques applied to the classical heat problem and the elasticity problem. The study highlights various key aspects encountered during the solution search process for specific problems, including the influence of initial conditions and optimizer parameters. Moreover, the paper explores novel approaches and variations of fundamental methods aimed at achieving improved final solutions for each problem. These adaptations encompass adjustments to the minimized functional, the representation of density space, and the application of regularization methods.
dc.format.extentxiii, 83 páginas
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherUniversidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject.ddc510 - Matemáticas::518 - Análisis numérico
dc.titleOn numerical solutions of topology optimization problems
dc.typeTrabajo de grado - Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programBogotá - Ciencias - Maestría en Ciencias - Matemática Aplicada
dc.description.degreelevelMaestría
dc.description.degreenameMagíster en Ciencias - Matemática Aplicada
dc.description.researchareaOptimización Estructural
dc.description.researchareaAnálisis Numérico
dc.identifier.instnameUniversidad Nacional de Colombia
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourlhttps://repositorio.unal.edu.co/
dc.publisher.facultyFacultad de Ciencias
dc.publisher.placeBogotá, Colombia
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotá
dc.relation.referencesAndreassen, E., Clausen, A., Schevenels, M., Lazarov, B. S., and Sigmund, O. (2010). Efficient topology optimization in matlab using 88 lines of code. Structural and Multidisciplinary Optimization, 43:1–16.
dc.relation.referencesBarrón-Romero, C. and Gómez, S. (1991). The exponential tunneling method. Reporte de Investigacion IIMAS, 1:1–23.
dc.relation.referencesBeghini, L. L., Beghini, A., Katz, N., Baker, W. F., and Paulino, G. H. (2014). Connecting architecture and engineering through structural topology optimization. Engineering Structures, 59:716–726
dc.relation.referencesBell, B., Norato, J., and Tortorelli, D. (2012). A Geometry Projection Method for Continuum-Based Topology Optimization of Structures.
dc.relation.referencesBendsøe, M. and Sigmund, O. (1999). Material interpolation schemes in topology optimization. Archive of Applied Mechanics, 69:635–654.
dc.relation.referencesBendsøe, M. and Sigmund, O. (2004). Topology Optimization. Chapter 1, pages 1–68. Springer, first edition.
dc.relation.referencesCavazzuti, M., Baldini, A., Bertocchi, E., Costi, D., Torricelli, E., and Moruzzi, P. (2011). High performance automotive chassis design: A topology optimization based approach. Structural and Multidisciplinary Optimization, 44:45–56.
dc.relation.referencesDeaton, J. D. and Grandhi, R. V. (2014). A survey of structural and multidisciplinary continuum topology optimization: post 2000. Structural and Multidisciplinary Optimization, 49:1615–1488.
dc.relation.referencesDonofrio, M. (2016). Topology optimization and advanced manufacturing as a means for the design of sustainable building components. Procedia Engineering, 145:638–645.
dc.relation.referencesGelfand, I. and Fomin, S. (2012). Calculus of Variations. Dover Books on Mathematics. Dover Publications.
dc.relation.referencesGockenbach, M. (2006). Understanding and Implementing the Finite Element Method. Other Titles in Applied Mathematics. Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104).
dc.relation.referencesGómez, S. and Levy, A. (1970). The tunnelling method for solving the constrained global optimization problem with several non-connected feasible regions, volume 909, pages 34–47.
dc.relation.referencesJohnson, C. (2012). Numerical Solution of Partial Differential Equations by the Finite Element Method. Dover Books on Mathematics Series. Dover Publications, Incorporated.
dc.relation.referencesKreyszig, E. (2007). Introductory Functional Analysis with Applications. Wiley classics library. Wiley India Pvt. Limited.
dc.relation.referencesMarheineke, N. (2020). Lecture notes: Numerics for differential equations. Trier University.
dc.relation.referencesMatsimbi, M., Nziu, P., Masu, L. M., and Maringa, M. (2021). Topology optimization of automotive body structures: A review.
dc.relation.referencesNorato, J., Bell, B., and Tortorelli, D. (2015). A geometry projection method for continuum-based topology optimization with discrete elements. Computer Methods in Applied Mechanics and Engineering, 293:306–327.
dc.relation.referencesOrme, M., Gschweitl, M., Ferrari, M., Madera, I., and Mouriaux, F. (2017). Designing for additive manufacturing: Lightweighting through topology optimization enables lunar spacecraft. Journal of Mechanical Design, 139.
dc.relation.referencesOrtegón-Villacorte, A. (2021). Pygpto. Github repository.
dc.relation.referencesOrtegón-Villacorte, A. (2023). Topopt experiments. Github repository.
dc.relation.referencesPapadopoulos, I. P. A., Farrell, P. E., and Surowiec, T. M. (2021). Computing multiple solutions of topology optimization problems. SIAM Journal on Scientific Computing, 43(3):A1555–A1582.
dc.relation.referencesPaulino, G. H. and Le, C. H. (2009). A modified q4/q4 element for topology optimization. Structural and Multidisciplinary Optimization, 37:255–264.
dc.relation.referencesRahmatalla, S. and Swan, C. (2004). A q4/q4 continuum structural optimization implementation. Structural and Multidisciplinary Optimization, 27:130–135.
dc.relation.referencesRozvany, G. (2009). Rozvany, g.i.n.: A critical review of established methods of structural topology optimization. structural and multidisciplinary optimization 37, 217-237. Structural and Multidisciplinary Optimization, 37:217–237.
dc.relation.referencesRozvany, G. I. N. (1998). Exact analytical solutions for some popular benchmark problems in topology optimization. Structural optimization, 15(1):42–48.
dc.relation.referencesSigmund, O. (2022). On benchmarking and good scientific practise in topology optimization. Structural and Multidisciplinary Optimization, 65.
dc.relation.referencesSigmund, O. and Maute, K. (2013). Topology optimization approaches. Structural and Multidisciplinary Optimization, 48:1031 –1055.
dc.relation.referencesSigmund, O. and Petersson, J. (1998). Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima. Structural Optimization, 16:68–75.
dc.relation.referencesSmith, H. and Norato, J. (2020). A matlab code for topology optimization using the geometry projection method. Structural and Multidisciplinary Optimization, pages 1162 –1166.
dc.relation.referencesSmith, H. and Norato, J. (2022). Topology optimization of structures made of fiber-reinforced plates. Structural and Multidisciplinary Optimization, 65:58.
dc.relation.referencesStolpe, M. and Svanberg, K. (2001). On the trajectories of penalization methods for topology optimization. Structural and Multidisciplinary Optimization, 21:128–139.
dc.relation.referencesSvanberg, K. (1987). The method of moving asymptotes—a new method for structural optimization. International Journal for Numerical Methods in Engineering, 24(2):359–373.
dc.relation.referencesSvanberg, K. (1998). The method of moving asymptotes - modelling aspects and solution scheme.
dc.relation.referencesTarek, M. and Huang, Y. (2022). Simplifying deflation for non-convex optimization with applications in bayesian inference and topology optimization.
dc.relation.referencesvan Dijk, N. P., Langelaar, M., and van Keulen, F. (2010). Critical study of design parameterization in topology optimization ; the influence of design parameterization on local minima.
dc.relation.referencesWatada, R. and Oshaki, M. (2009). Continuation approach for investigation of the non-uniqueness of optimal topology for minimum compliance. 8th World Congress of Structural and Multidisciplinary Optimization.
dc.relation.referencesWein, F., Dunning, P. D., and Norato, J. A. (2020). A review on feature-mapping methods for structural optimization. Structural and Multidisciplinary Optimization, 62:1597–1638.
dc.relation.referencesWein, F. and Stingl, M. (2018). A combined parametric shape optimization and ersatz material approach. Structural and Multidisciplinary Optimization, 57.
dc.relation.referencesYan, S., Wang, F., and Sigmund, O. (2018). On the non-optimality of tree structures for heat conduction. International Journal of Heat and Mass Transfer, 122:660–680.
dc.relation.referencesZhang, S. and Norato, J. (2018). Finding better local optima in topology optimization via tunneling. page V02BT03A014.
dc.relation.referencesZhu, J.-H., Zhang, W.-H., and Xia, L. (2016). Topology optimization in aircraft and aerospace structures design. Archives of Computational Methods in Engineering, 23:595–622.
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.lembDinámica topológica
dc.subject.lembTopological Dynamic
dc.subject.lembSistemas dinámicos diferenciales
dc.subject.lembDifferentiable dynamical systems
dc.subject.lembAnálisis numérico
dc.subject.lembNumerical analysis
dc.subject.proposalTopology Optimization
dc.subject.proposalPartial Diferential Equations
dc.subject.proposalOptimización Topológica
dc.subject.proposalEcuaciones Diferenciales Parciales
dc.subject.proposalFinite Elements
dc.subject.proposalElementos Finitos
dc.subject.proposalNumerical Analysis
dc.subject.proposalAnálisis Numérico
dc.subject.proposalRegularization
dc.subject.proposalRegularización
dc.subject.proposalStructural Optimization
dc.subject.proposalOptimización Estructural
dc.title.translatedSobre soluciones numéricas a problemas de optimización topológica
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2
dcterms.audience.professionaldevelopmentInvestigadores


Archivos en el documento

Thumbnail

Este documento aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del documento

Atribución-NoComercial 4.0 InternacionalEsta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.Este documento ha sido depositado por parte de el(los) autor(es) bajo la siguiente constancia de depósito