Pinar Acar

Utilization of a Linear Solver for Multiscale Design and Optimization of Microstructures

Microstructures have a significant effect on the performance of critical components in numerous aerospace metallic material applications. Examples include panels in airframes that are exposed to high temperatures and sensors used for vibration tuning. This paper addresses the techniques to optimize the microstructure design for polycrystalline metals. The microstructure is quantified with the orientation distribution function that determines the volume densities of crystals that make up the polycrystal microstructure. The orientation distribution function of polycrystalline alloys (e.g., hexagonal close-packed titanium) is represented in a discrete form, and the volume-averaged properties are computed through the orientation distribution function. The optimization is performed using the space of all possible volume-averaged macroproperties (stiffness and thermal expansion). A direct linear solver is employed to find the optimal orientation distribution functions. The direct solver is capable of finding ex...

Linear Solution Scheme for Microstructure Design with Process Constraints

This paper addresses a two-step linear solution scheme to find an optimum metallic microstructure satisfying performance needs and manufacturability constraints. The microstructure is quantified using the orientation distribution function, which determines the volume densities of crystals that make up the polycrystal microstructure. The orientation distribution function of polycrystalline alloys is represented in a discrete form using finite elements, and the volume-averaged properties are computed. The first step of the solution approach identifies the orientation distribution functions that lead to the set of optimal engineering properties using linear programming. This step leads to multiple solutions, of which only a few can be manufactured using traditional processing routes such as rolling and forging. In the second step, textures from a given process are represented in a space of reduced basis coefficients called the process plane. This step involves generation of orthogonal basis functions for rep...

Stochastic Design Optimization of Microstructures with Utilization of a Linear Solver

Microstructure design can have a substantial effect on the performance of critical components in numerous aerospace applications. However, the stochastic nature of metallic microstructures leads to deviations in material properties from the design point, and it alters the performance of these critical components. In this work, an inverse stochastic design approach is introduced such that the material is optimized while accounting for the inherent variations in the microstructure. The highlight is an analytical uncertainty quantification model via a Gaussian distribution to model propagation of microstructural uncertainties to the properties. A metallic microstructure is represented using a finite element discretized form of the orientation distribution function. A stochastic optimization approach is proposed that employs the analytical model for uncertainty quantification, to maximize the yield strength of Galfenol microstructure in a compliant beam when constrained by uncertainties in the designed natura...

Utilization of a linear solver for multiscale design and optimization of microstructures in an airframe panel buckling problem

Microstructures have a significant effect on the performance of critical components in numerous aerospace metallic material applications. Examples include panels in airframes that are exposed to high temperatures and sensors used for vibration tuning. This paper addresses the techniques to optimize the microstructure design for polycrystalline metals. The microstructure is quantified with the orientation distribution function (ODF) that determines the volume densities of crystals that make up the polycrystal microstructure. The ODF of polycrystalline alloys (e.g. HCP Titanium) is represented in a discrete form and the volume averaged properties are computed through the ODF. The optimization is performed using the space of all possible volume averaged macro properties (stiffness and thermal expansion). A direct linear solver is employed to find the optimal ODFs. The direct solver is capable of finding exact solutions even for multiple or infinite solution problems. It is firstly applied to the optimization of the panel buckling problem. The objective of the buckling optimization problem is to find the best microstructure design that maximizes the critical buckling temperature. The optimum solution computed with this approach is found to be same as the optimum solution of a global approach that utilizes a genetic algorithm. The linear solver methodology is extended to plastic properties and applied to explore design of a Galfenol beam microstructure for vibration tuning with a yielding objective. We show that the design approach can lead us to multiple optimum solutions.

Steady and Unsteady Aeroelastic Computations of HIRENASD Wing for Low and High Reynolds Numbers

We perform static and dynamic aeroelastic analyses of the HIRENASD wing based on NASA’s reference data delivered for two test cases with dierent ight conditions. The tests have been conducted in cryogenic medium to investigate steady and unsteady aeroelastic responses in transonic regime for low and high Reynolds numbers. For computational studies, the latest structural model of NASA is used. First, a free vibration analysis is performed in Nastran. Then, the modal solution is imported from the nite element solver to ZEUS, where the aerodynamic model and uid structure interaction parameters are constructed. Steady and unsteady aeroelastic results are examined for the specied stations along the wing span, and interpolated for chordwise direction so as to match them with the wind tunnel test points. The designated output parameters such as steady aerodynamic lift, moment and drag coecients, and steady and unsteady pressure distributions along the chordwise direction are compared to the experimental results.

Uncertainty Quantification of Microstructural Properties due to Experimental Variations

Electron backscatter diffraction scans are an important experimental input for microstructure generation and homogenization. Multiple electron backscatter diffraction scans can be used to sample th...

Fiber Path Optimization of Symmetric Laminates with Cutouts for Thermal Buckling

Automated fiber placement technology has pushed for the need to explore nonconventional fiber paths in laminated composites. This paper investigates optimal spatially varying fiber paths in a symmetric linear orthotropic laminate, which could increase the critical buckling temperature under uniform applied thermal loads. The key idea here is to achieve gains in buckling performance yet focus on manufacturability of the obtained optimal fiber path. The subject of this study is a four-layer symmetric orthotropic laminated plate, with a central circular cutout that is clamped on all the edges. A novel finite element algorithm is proposed, which imposes a condition on the definition of discrete fiber angles within each element. The main objectives of the proposed finite element approach are to maintain continuity of the fiber paths and to use a computationally efficient model by reducing the number of optimization variables.

Fiber Path Optimization of a Symmetric Laminate with a Cutout for Thermal Buckling, Using a Novel Finite Element Algorithm

Automated fiber placement (AFP) technology has pushed for the need to explore nonconventional fiber paths in laminated composites. This paper investigates optimal spatially varying fiber paths in a symmetric linear orthotropic laminate which could increase the critical buckling temperature under uniform applied thermal loads. The key idea here is to achieve gains in buckling performance, yet focus on manufacturability of the obtained optimal fiber path. The subject of this study is a four layer symmetric orthotropic laminated plate, with a central circular cutout that is clamped on all the edges. A novel Finite Element algorithm is proposed which imposes a condition on the definition of discrete fiber angles within each element. The main objectives of the proposed finite element approach are to maintain continuity of the fiber paths, and to use a computationally efficient model by reducing the number of optimization variables.

Reliability Based Design Optimization of a CubeSat De-Orbiting Mechanism

We optimize de-orbiting mechanism of a 3-Unit satellite structure to enable a reliable and efficient orbit decay process through enhancement of aerodynamic drag with a probabilistic design approach. The system consists of spiral springs as energy producing mechanisms needed for deployment and thin membranes needed as aero-brake structures. A multi-objective optimization problem is formulated to maximize both aerodynamic drag force and also moment produced by spiral springs for a carefree and fast orbit decay. Mass of membranes and stresses acting on spiral springs are subjected to constraints for lightweight and durability. An in-house code is developed to evaluate the deterministic optimization criteria in terms of the optimization variables which are attributes of thin membranes and spiral springs. In space environment, atmospheric density is highly affected by solar radiation and also the system components are strictly related to manufacturing quality, so uncertainties in design parameters are incoorperated into optimization and a reliability based design optimization of the de-orbiting mechanism is performed. Dimensions of membrane structures, outside diameter of spiral springs and atmospheric density are considered to be uncertain parameters. These uncertainties are propagated by Monte Carlo Simulation method which is integrated into reliability evaluation loop in the optimization framework. Finally, de-orbiting duration values of pareto optimal designs are computed using Satellite Tool Kit where it is shown that the selected optimum design is expected to satisfy the specified maximum life-time criterion.

REDUCED ORDER MODELLING OF HIGH-FIDELITY COMPUTATIONAL FLUID-STRUCTURE INTERACTION ANALYSIS FOR AEROELASTIC SYSTEMS

We investigate model reduction techniques through computational aeroelastic analyses of the HIRENASD and ST wings. The aim of the present work is to construct accurate and computationally efficient reduced order models for high-fidelity aeroelastic computations. Firstly, the aeroelastic analyses of the specified wings are performed by high-fidelity structural and aerodynamic models to substantiate the fluid-structure interaction. Concerning high amount of computational time required to perform such high-fidelity fluid-structure interaction analyses, the model orders are reduced by introducing relevant reduction techniques such as Polynomial Chaos Expansion and Proper Orthogonal Decomposition. The final aeroelastic analyses performed on these reduced models agree well with the initial high-fidelity computational analyses.