Browsing by Subject "Structural optimization"

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    Cellular Helmet Liner Design through Bio-inspired Structures and Topology Optimization of Compliant Mechanism Lattices
    (SAE International, 2018-12-28) Najmon, Joel; DeHart, Jacob; Wood, Zebulun; Tovar, Andres; Department of Mechanical Engineering, School of Engineering and Technology
    The continuous development of sport technologies constantly demands advancements in protective headgear to reduce the risk of head injuries. This article introduces new cellular helmet liner designs through two approaches. The first approach is the study of energy-absorbing biological materials. The second approach is the study of lattices comprised of force-diverting compliant mechanisms. On the one hand, bio-inspired liners are generated through the study of biological, hierarchical materials. An emphasis is given on structures in nature that serve similar concussion-reducing functions as a helmet liner. Inspiration is drawn from organic and skeletal structures. On the other hand, compliant mechanism lattice (CML)-based liners use topology optimization to synthesize rubber cellular unit cells with effective positive and negative Poisson's ratios. Three lattices are designed using different cellular unit cell arrangements, namely, all positive, all negative, and alternating effective Poisson's ratios. The proposed cellular (bio-inspired and CML-based) liners are embedded between two polycarbonate shells, thereby, replacing the traditional expanded polypropylene foam liner used in standard sport helmets. The cellular liners are analyzed through a series of 2D extruded ballistic impact simulations to determine the best performing liner topology and its corresponding rubber hardness. The cellular design with the best performance is compared against an expanded polypropylene foam liner in a 3D simulation to appraise its protection capabilities and verify that the 2D extruded design simulations scale to an effective 3D design.
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    Design optimization of heterogeneous microstructured materials
    (2014) Emami, Anahita; Tovar, Andrés; Zhu, Likun; Wasfy, Tamer; Chen, Jie
    Our ability to engineer materials is limited by our capacity to tailor the material’s microstructure morphology and predict resulting properties. The insufficient knowledge on microstructure-property relationship is due to complexity and randomness in all materials at different scales. The objective of this research is to establish a design optimization methodology for microstructured materials. The material design problem is stated as finding the optimum microstructure to maximize the desired performance satisfying material processing constrains. This problem has been solved in this thesis by means of numerical techniques through four main steps: microstructure characterization, model reconstruction, property evaluation, and optimization. Two methods of microstructure characterizations have been investigated along with the advantages and disadvantages of each method. The first microstructure characterization method is a statistical method which utilizes correlation functions to extract the microstructural information. Algorithms for calculating these correlations functions have been developed and optimized based on their computational cost using MATLAB software. The second microstructure characterization method is physical characterization which works based on evaluation of physical features in microstructured domain. These features have been measured by means of MATLAB codes. Three model reconstruction techniques are proposed based on these characterization methods and employed to generate material models for further evaluation. The first reconstructing algorithm uses statistical functions to reconstruct the statistical equivalent model through simulating annealing optimization method. The second algorithm uses cellular automaton concepts to simulate the grain growth utilizing physical descriptors, and the third one generates elliptical inclusions in a material matrix using physical characteristic of microstructure. The finite element method is used to analysis the mechanical behavior of material models. Several material samples with different microstructural characteristics have been generated to model the micro-scale design domain of AZ31 magnesium alloy and magnesium matrix composite with silicon carbide fibers. Then, surrogate models have been created based on these samples to approximate the entire design domain and demonstrate the sensitivity of the desired mechanical property to two independent microstructural features. Finally, the optimum microstructure characteristics of material samples for fracture strength maximization have been obtained.
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    Structural Optimization of Thin Walled Tubular Structure for Crashworthiness
    (2014) Shinde, Satyajeet Suresh; Tovar, Andrés; Anwar, Sohel; Wasfy, Tamer
    Crashworthiness design is gaining more importance in the automotive industry due to high competition and tight safety norms. Further there is a need for light weight structures in the automotive design. Structural optimization in last two decades have been widely explored to improve existing designs or conceive new designs with better crashworthiness and reduced mass. Although many gradient based and heuristic methods for topology and topometry based crashworthiness design are available these days, most of them result in stiff structures that are suitable only for a set of vehicle components in which maximizing the energy absorption or minimizing the intrusion is the main concern. However, there are some other components in a vehicle structure that should have characteristics of both stiffness and flexibility. Moreover, the load paths within the structure and potential buckle modes also play an important role in efficient functioning of such components. For example, the front bumper, side frame rails, steering column, and occupant protection devices like the knee bolster should all exhibit controlled deformation and collapse behavior. This investigation introduces a methodology to design dynamically crushed thin-walled tubular structures for crashworthiness applications. Due to their low cost, high energy absorption efficiency, and capacity to withstand long strokes, thin-walled tubular structures are extensively used in the automotive industry. Tubular structures subjected to impact loading may undergo three modes of deformation: progressive crushing/buckling, dynamic plastic buckling, and global bending or Euler-type buckling. Of these, progressive buckling is the most desirable mode of collapse because it leads to a desirable deformation characteristic, low peak reaction force, and higher energy absorption efficiency. Progressive buckling is generally observed under pure axial loading; however, during an actual crash event, tubular structures are often subjected to oblique impact loads in which Euler-type buckling is the dominating mode of deformation. This undesired behavior severely reduces the energy absorption capability of the tubular structure. The design methodology presented in this paper relies on the ability of a compliant mechanism to transfer displacement and/or force from an input to desired output port locations. The suitable output port locations are utilized to enforce desired buckle zones, mitigating the natural Euler-type buckling effect. The problem addressed in this investigation is to find the thickness distribution of a thin-walled structure and the output port locations that maximizes the energy absorption while maintaining the peak reaction force at a prescribed limit. The underlying design for thickness distribution follows a uniform mutual potential energy density under a dynamic impact event. Nonlinear explicit finite element code LS-DYNA is used to simulate tubular structures under crash loading. Biologically inspired hybrid cellular automaton (HCA) method is used to drive the design process. Results are demonstrated on long straight and S-rail tubes subject to oblique loading, achieving progressive crushing in most cases.