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- All Subjects: Aerospace Engineering
- Genre: Masters Thesis
Description
This study focuses on implementing probabilistic nature of material properties (Kevlar® 49) to the existing deterministic finite element analysis (FEA) of fabric based engine containment system through Monte Carlo simulations (MCS) and implementation of probabilistic analysis in engineering designs through Reliability Based Design Optimization (RBDO). First, the emphasis is on experimental data analysis focusing on probabilistic distribution models which characterize the randomness associated with the experimental data. The material properties of Kevlar® 49 are modeled using experimental data analysis and implemented along with an existing spiral modeling scheme (SMS) and user defined constitutive model (UMAT) for fabric based engine containment simulations in LS-DYNA. MCS of the model are performed to observe the failure pattern and exit velocities of the models. Then the solutions are compared with NASA experimental tests and deterministic results. MCS with probabilistic material data give a good prospective on results rather than a single deterministic simulation results. The next part of research is to implement the probabilistic material properties in engineering designs. The main aim of structural design is to obtain optimal solutions. In any case, in a deterministic optimization problem even though the structures are cost effective, it becomes highly unreliable if the uncertainty that may be associated with the system (material properties, loading etc.) is not represented or considered in the solution process. Reliable and optimal solution can be obtained by performing reliability optimization along with the deterministic optimization, which is RBDO. In RBDO problem formulation, in addition to structural performance constraints, reliability constraints are also considered. This part of research starts with introduction to reliability analysis such as first order reliability analysis, second order reliability analysis followed by simulation technique that are performed to obtain probability of failure and reliability of structures. Next, decoupled RBDO procedure is proposed with a new reliability analysis formulation with sensitivity analysis, which is performed to remove the highly reliable constraints in the RBDO, thereby reducing the computational time and function evaluations. Followed by implementation of the reliability analysis concepts and RBDO in finite element 2D truss problems and a planar beam problem are presented and discussed.
ContributorsDeivanayagam, Arumugam (Author) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2012
Description
Composites are replacing conventional materials in aerospace applications due to their light weight, non-corrosiveness, and high specific strength. This thesis aims to characterize the input data for IM7-8552 unidirectional composite to support MAT213, an orthotropic elasto-plastic damage material model and MAT_186, a mixed mode cohesive zone model used to model delamination. MAT_213 in conjunction with MAT_186 can be used to predict the behavior of composite under crush and impact loads including delamination. MAT_213 requires twelve sets of stress-strain curves, direction-dependent material constants, and flow rule coefficients as input. All the necessary inputs are obtained through the post-processing of a total of twelve distinct quasi-static and room temperature (QS-RT) experiments. MAT_186 is driven by a set of Mode I and Mode II fracture parameters and traction separation laws, a constitutive law that derives the relationship between stresses and relative displacements at integration points of cohesive elements. Obtaining cohesive law parameters experimentally is a tedious process as it requires close monitoring of the crack length during the test, which is a difficult task to achieve with accuracy even after using sophisticated equipment such as Digital Image Correlation (DIC). In this thesis, a numerical inverse analysis method to precisely predict these parameters by using finite element analysis with cohesive zone modeling and response surface methodology (RSM) is proposed. Three steps comprise RSM. The process in Step 1 involves calculating the root mean square error between the finite element and experimental load-displacement curves to produce the response surface. In step 2, the response surface is fitted with a second-order polynomial using the Levenberg-Marquardt algorithm. In step 3, an optimization problem is solved by minimizing the fitted function to find the optimum cohesive zone parameters. Finally, the obtained input for MAT_213 and MAT_186 material models is validated by performing a quasi-isotropic tension test simulation.
ContributorsRaihan, Mohammed (Author) / Rajan, Subramaniam (Thesis advisor) / Neithalath, Narayanan (Committee member) / Hoover, Christian (Committee member) / Yellavajjala, Ravi (Committee member) / Arizona State University (Publisher)
Created2023