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- All Subjects: Optimization
Description
Buildings consume a large portion of the world's energy, but with the integration of phase change materials (PCMs) in building elements this energy cost can be greatly reduced. The addition of PCMs into building elements, however, becomes a challenge to model and analyze how the material actually affects the energy flow and temperatures in the system. This research work presents a comprehensive computer program used to model and analyze PCM embedded wall systems. The use of the finite element method (FEM) provides the tool to analyze the energy flow of these systems. Finite element analysis (FEA) can model the transient analysis of a typical climate cycle along with nonlinear problems, which the addition of PCM causes. The use of phase change materials is also a costly material expense. The initial expense of using PCMs can be compensated by the reduction in energy costs it can provide. Optimization is the tool used to determine the optimal point between adding PCM into a wall and the amount of energy savings that layer will provide. The integration of these two tools into a computer program allows for models to be efficiently created, analyzed and optimized. The program was then used to understand the benefits between two different wall models, a wall with a single layer of PCM or a wall with two different PCM layers. The effect of the PCMs on the inside wall temperature along with the energy flow across the wall are computed. The numerical results show that a multi-layer PCM wall was more energy efficient and cost effective than the single PCM layer wall. A structural analysis was then performed on the optimized designs using ABAQUS v. 6.10 to ensure the structural integrity of the wall was not affected by adding PCM layer(s).
ContributorsStockwell, Amie (Author) / Rajan, Subramaniam D. (Thesis advisor) / Neithalath, Narayanan (Thesis advisor) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Laminated composite materials are used in aerospace, civil and mechanical structural systems due to their superior material properties compared to the constituent materials as well as in comparison to traditional materials such as metals. Laminate structures are composed of multiple orthotropic material layers bonded together to form a single performing part. As such, the layup design of the material largely influences the structural performance. Optimization techniques such as the Genetic Algorithm (GA), Differential Evolution (DE), the Method of Feasible Directions (MFD), and others can be used to determine the optimal laminate composite material layup. In this thesis, sizing, shape and topology design optimization of laminated composites is carried out. Sizing optimization, such as the layer thickness, topology optimization, such as the layer orientation and material and the number of layers present, and shape optimization of the overall composite part contribute to the design optimization process of laminates. An optimization host program written in C++ has been developed to implement the optimization methodology of both population based and numerical gradient based methods. The performance of the composite structural system is evaluated through explicit finite element analysis of shell elements carried out using LS-DYNA. Results from numerical examples demonstrate that optimization design processes can significantly improve composite part performance through implementation of optimum material layup and part shape.
ContributorsMika, Krista (Author) / Rajan, Subramaniam D. (Thesis advisor) / Neithalath, Narayanan (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2014
Description
The focus of this dissertation is first on understanding the difficulties involved in constructing reduced order models of structures that exhibit a strong nonlinearity/strongly nonlinear events such as snap-through, buckling (local or global), mode switching, symmetry breaking. Next, based on this understanding, it is desired to modify/extend the current Nonlinear Reduced Order Modeling (NLROM) methodology, basis selection and/or identification methodology, to obtain reliable reduced order models of these structures. Focusing on these goals, the work carried out addressed more specifically the following issues:
i) optimization of the basis to capture at best the response in the smallest number of modes,
ii) improved identification of the reduced order model stiffness coefficients,
iii) detection of strongly nonlinear events using NLROM.
For the first issue, an approach was proposed to rotate a limited number of linear modes to become more dominant in the response of the structure. This step was achieved through a proper orthogonal decomposition of the projection on these linear modes of a series of representative nonlinear displacements. This rotation does not expand the modal space but renders that part of the basis more efficient, the identification of stiffness coefficients more reliable, and the selection of dual modes more compact. In fact, a separate approach was also proposed for an independent optimization of the duals. Regarding the second issue, two tuning approaches of the stiffness coefficients were proposed to improve the identification of a limited set of critical coefficients based on independent response data of the structure. Both approaches led to a significant improvement of the static prediction for the clamped-clamped curved beam model. Extensive validations of the NLROMs based on the above novel approaches was carried out by comparisons with full finite element response data. The third issue, the detection of nonlinear events, was finally addressed by building connections between the eigenvalues of the finite element software (Nastran here) and NLROM tangent stiffness matrices and the occurrence of the ‘events’ which is further extended to the assessment of the accuracy with which the NLROM captures the full finite element behavior after the event has occurred.
i) optimization of the basis to capture at best the response in the smallest number of modes,
ii) improved identification of the reduced order model stiffness coefficients,
iii) detection of strongly nonlinear events using NLROM.
For the first issue, an approach was proposed to rotate a limited number of linear modes to become more dominant in the response of the structure. This step was achieved through a proper orthogonal decomposition of the projection on these linear modes of a series of representative nonlinear displacements. This rotation does not expand the modal space but renders that part of the basis more efficient, the identification of stiffness coefficients more reliable, and the selection of dual modes more compact. In fact, a separate approach was also proposed for an independent optimization of the duals. Regarding the second issue, two tuning approaches of the stiffness coefficients were proposed to improve the identification of a limited set of critical coefficients based on independent response data of the structure. Both approaches led to a significant improvement of the static prediction for the clamped-clamped curved beam model. Extensive validations of the NLROMs based on the above novel approaches was carried out by comparisons with full finite element response data. The third issue, the detection of nonlinear events, was finally addressed by building connections between the eigenvalues of the finite element software (Nastran here) and NLROM tangent stiffness matrices and the occurrence of the ‘events’ which is further extended to the assessment of the accuracy with which the NLROM captures the full finite element behavior after the event has occurred.
ContributorsLin, Jinshan (Author) / Mignolet, Marc (Thesis advisor) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Spottswood, Stephen (Committee member) / Rajan, Subramaniam D. (Committee member) / Arizona State University (Publisher)
Created2020