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- Suresh, Shyam, 1990-
(författare)
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Developments of Topology Optimization Methods for Additive Manufacturing involving High-cycle Fatigue
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Additive manufacturing (AM) is a versatile manufacturing process which is gaining popularity in the automotive and aerospace industries. Through AM one can manufacture complex structures and combined with topology optimization (TO) a powerful design tool that provides great freedom in geometric form emerges. The goal of the research presented in this thesis is to develop new TO methods that consider specific properties related to AM for metals. In particular, anisotropy, non-homogeneity in the form of surface effects, and constraints on high-cycle fatigue (HCF) damage are treated. In the first paper of the thesis, an HCF constraint is introduced into a TO problem where the total structural mass is minimized. The HCF model is based on a continuous-time approach in contrast to more conventional cycle-counting approaches. It is based on the concept of a moving endurance surface, and a system of ordinary differential equations is used to predict the fatigue damage at every point in the design domain. The model is capable of handling arbitrary load histories, including most non-proportional loads. Gradient-based optimization is utilized, and the fatigue sensitivities are determined by the adjoint method. In the subsequent papers, several extensions are made to the original HCFconstrained TO problem: The HCF model is extended so that it is applicable not only to isotropic materials but also to transversely isotropic materials. The anisotropic properties are manifested in the constitutive elastic response and in the fatigue properties. Acceleration of fatigue and sensitivity analyses by extrapolation is introduced, making the treatment of an unlimited number of load cycles possible. Simultaneous optimization of build orientation and topology, considering stress- and HCF constraints, is performed. For better prediction of fatigue, especially for non-proportional loads, the original continuous-time HCF model is modified using a quadratic polynomial endurance function. In the final paper, a new TO method, taking surface layer effects into account, is introduced. This essentially models the impaired mechanical properties observed in as-built AM components compared to components having polished surfaces. Numerical test problems as well as application-like problems are solved in all papers to exemplify the applicability of the developed TO methodology.
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| 2. |
- Gade, Jan-Lucas, 1988-
(författare)
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Mechanical Properties of Arteries : Identification and Application
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this Licentiate of Engineering thesis, a method is proposed that identifies the mechanical properties of arteries in vivo. The mechanical properties of an artery are linked to the development of cardiovascular diseases. The possibility to identify the mechanical properties of an artery inside the human body could, thus, facilitate disease diagnostization, treatment and monitoring.Supplied with information obtainable in the clinic, typically limited to time- resolved pressure-radius measurement pairs, the proposed in vivo parameter identi- fication method calculates six representative parameters by solving a minimization problem. The artery is treated as a homogeneous, incompressible, residual stress- free, thin-walled tube consisting of an elastin dominated matrix with embedded collagen fibers referred to as the constitutive membrane model. To validate the in vivo parameter identification method, in silico arteries in the form of finite element models are created using published data for the human abdominal aorta. With these in silico arteries which serve as mock experiments with pre-defined material parameters and boundary conditions, in vivo-like pressure-radius data sets are generated. The mechanical properties of the in silico arteries are then determined using the proposed parameter identification method. By comparing the identified and the pre-defined parameters, the identification method is quantitatively validated. The parameters for the radius of the stress-free state and the material constant associated with elastin show high agreement in case of healthy arteries. Larger differences are obtained for the material constants associated with collagen, and the largest discrepancy occurs for the in situ axial prestretch. For arteries with a pathologically small elastin content, incorrect parameters are identified but the presence of a diseased artery is revealed by the parameter identification method.Furthermore, the identified parameters are used in the constitutive membrane model to predict the stress state of the artery in question. The stress state is thereby decomposed into an isotropic and an anisotropic component which are primarily associated with the elastin dominated matrix and the collagen fibers, respectively. In order to assess the accuracy of the predicted stress, it is compared to the known stress state of the in silico arteries. The comparison of the predicted and the in silico decomposed stress states show a close agreement for arteries exhibiting a low transmural stress gradient. With increasing transmural stress gradient the agreement deteriorates.The proposed in vivo parameter identification method is capable of identifying adequate parameters and predicting the decomposed stress state reasonably well for healthy human abdominal aortas from in vivo-like data.
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