Browsing by Subject "crashworthiness"

Now showing 1 - 5 of 5
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    Bio-Inspired Design of Lightweight and Protective Structures
    (SAE, 2016-04) Mehta, Prasad S.; Solis Ocampo, Jennifer; Tovar, Andres; Chaudhari, Prathamesh; Mechanical and Energy Engineering, School of Engineering and Technology
    Biologically inspired designs have become evident and proved to be innovative and efficacious throughout the history. This paper introduces a bio-inspired design of protective structures that is lightweight and provides outstanding crashworthiness indicators. In the proposed approach, the protective function of the vehicle structure is matched to the protective capabilities of natural structures such as the fruit peel (e.g., pomelo), abdominal armors (e.g., mantis shrimp), bones (e.g., ribcage and woodpecker skull), as well as other natural protective structures with analogous protective functions include skin and cartilage as well as hooves, antlers, and horns, which are tough, resilient, lightweight, and functionally adapted to withstand repetitive high-energy impact loads. This paper illustrates a methodology to integrate designs inspired by nature, Topology optimization, and conventional modeling tools. Two designs are explained to support this methodology: Helmet design inspired by human bone cellular structure (trabecular structure) and vehicle body inspired by a water droplet, ribcage, and human bone. In the helmet design, a finite part of is optimized using topology optimization to generate the porous structure. In the vehicle body design, a water droplet framework, the bio-inspired simulation-based design algorithm used in this work generates innovative layouts. At the vehicle scale, the generated spaceframe has a structure similar to the one of a long bone. In essence, the aerodynamic water droplet shape is protected by the specialized ribcage. At the component scale, each spaceframe tubular component is filled with a functionally graded cellular structure. This internal cellular structure reminds the one of a bone. The spaceframe is attainable with few parts of greater complexity. Such complex, lightweight, multiscale structural layout can be manufactured using 3D printing technologies.
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    Cluster-Based Optimization of Cellular Materials and Structures for Crashworthiness
    (ASME, 2018-09) Liu, Kai; Detwiler, Duane; Tovar, Andres; Mechanical and Energy Engineering, School of Engineering and Technology
    The objective of this work is to establish a cluster-based optimization method for the optimal design of cellular materials and structures for crashworthiness, which involves the use of nonlinear, dynamic finite element models. The proposed method uses a cluster-based structural optimization approach consisting of four steps: conceptual design generation, clustering, metamodel-based global optimization, and cellular material design. The conceptual design is generated using structural optimization methods. K-means clustering is applied to the conceptual design to reduce the dimensional of the design space as well as define the internal architectures of the multimaterial structure. With reduced dimension space, global optimization aims to improve the crashworthiness of the structure can be performed efficiently. The cellular material design incorporates two homogenization methods, namely, energy-based homogenization for linear and nonlinear elastic material models and mean-field homogenization for (fully) nonlinear material models. The proposed methodology is demonstrated using three designs for crashworthiness that include linear, geometrically nonlinear, and nonlinear models.
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    Metamodel-Based Global Optimization of Vehicle Structures for Crashworthiness Supported by Clustering Methods
    (Springer, 2018) Liu, Kai; Detwiler, Duane; Tovar, Andres; Mechanical Engineering, School of Engineering and Technology
    This work introduces a metamodel-based global optimization method for crashworthiness with the ability to synthesize continuum structures with an optimal distribution of material phases or gauges. The proposed optimization method makes use of fully nonlinear, dynamic crash simulations and consists of three main elements: (1) the generation of a conceptual design from the structures crash response, (2) the optimal clustering of the conceptual design to define the location of the material phases or gauges, (3) the metamodel-based global optimization, which aims to find the optimal settings for each cluster. The conceptual design can be generated from extracting finite element analysis information or by using structural optimization. The conceptual design is then clustered using clustering analysis to reduce the dimension of the design space. The global optimization problem aims to find the optimal material distribution on the reduced design space using metamodels. The metamodels are built using sampling and cross-validation, and sequentially updated using an expected improvement function until convergence. The proposed methodology is demonstrated using examples from multi-objective crashworthiness design examples.
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    Optimal Design of Cellular Material Systems for Crashworthiness
    (SAE, 2016-04) Liu, Kai; Xu, ZongYing; Detwiler, Duane; Tovar, Andres; Mechanical and Energy Engineering, School of Engineering and Technology
    This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework. In comparison to traditional structures that made of a single cellular phase, the results demonstrate the improved performance when multiple cellular phases are used.
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    Optimal Design of Nonlinear Multimaterial Structures for Crashworthiness Using Cluster Analysis
    (ASME, 2017-08) Liu, Kai; Detwiler, Duane; Tovar, Andres; Mechanical Engineering, School of Engineering and Technology
    This study presents an efficient multimaterial design optimization algorithm that is suitable for nonlinear structures. The proposed algorithm consists of three steps: conceptual design generation, clustering, and metamodel-based global optimization. The conceptual design is generated using a structural optimization algorithm for linear models or a heuristic design algorithm for nonlinear models. Then, the conceptual design is clustered into a predefined number of clusters (materials) using a machine learning algorithm. Finally, the global optimization problem aims to find the optimal material parameters of the clustered design using metamodels. The metamodels are built using sampling and cross-validation and sequentially updated using an expected improvement function until convergence. The proposed methodology is demonstrated using examples from multiple physics and compared with traditional multimaterial topology optimization (MTOP) method. The proposed approach is applied to a nonlinear, multi-objective design problems for crashworthiness.