Browsing by Subject "Global optimization"

Now showing 1 - 3 of 3
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    Bifurcated Topological Optimization for IVIM
    (Frontiers Media, 2021-12-15) Fadnavis, Shreyas; Endres, Stefan; Wen, Qiuting; Wu, Yu-Chien; Cheng, Hu; Koudoro, Serge; Rane, Swati; Rokem, Ariel; Garyfallidis, Eleftherios; Radiology and Imaging Sciences, School of Medicine
    In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM) for diffusion and perfusion estimation by characterizing the objective function using simplicial homology tools. We provide a robust solution via topological optimization of this model so that the estimates are more reliable and accurate. Estimating the tissue microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem. Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model we perform the optimization using simplicial homology based global optimization to better understand the topology of objective function surface. We theoretically show how the proposed methodology can recover the model parameters more accurately and consistently by casting it in a reduced subspace given by VarPro. Additionally we demonstrate that the IVIM model parameters cannot be accurately reconstructed using conventional numerical optimization methods due to the presence of infinite solutions in subspaces. The proposed method helps uncover multiple global minima by analyzing the local geometry of the model enabling the generation of reliable estimates of model parameters.
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    Predictive Optimal Control of Mild Hybrid Trucks
    (MDPI, 2022) Pramanik, Sourav; Anwar, Sohel; Mechanical and Energy Engineering, Purdue School of Engineering and Technology
    Numerous per- and polyfluoroalkyl substances (PFASs) occur in consumer food packaging due to intentional and unintentional addition, despite increasing concern about their health and environmental hazards. We present a substance flow analysis framework to assess the flows of PFASs contained in plant fiber-based and plastic food packaging to the waste stream and environment. Each year between 2018 and 2020, an estimated 9000 (range 1100–25 000) and 940 (range 120–2600) tonnes per year of polymeric PFASs were used in 2% of food packaging in the U.S. and Canada, respectively. At least 11 tonnes per year of non-polymeric PFASs also moved through the food packaging life cycle. Approximately 6100 (range 690–13 000) and 700 (range 70–1600) tonnes per year of these PFASs were landfilled or entered composting facilities in the U.S. and Canada, respectively, with the potential to contaminate the environment. The results suggest that minimal food packaging contains intentionally added PFASs which, nonetheless, has the potential to contaminate the entire waste stream. Further, this indicates that PFASs are not needed for most food packaging. These results serve as a benchmark to judge the effectiveness of future industry and government initiatives to limit PFAS use in food packaging.
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    Surrogate-based global optimization of composite material parts under dynamic loading
    (2017-08) Valladares Guerra, Homero Santiago; Tovar, Andres; Jones, Alan; Anwar, Sohel
    The design optimization of laminated composite structures is of relevance in automobile, naval, aerospace, construction and energy industry. While several optimization methods have been applied in the design of laminated composites, the majority of those methods are only applicable to linear or simplified nonlinear models that are unable to capture multi-body contact. Furthermore, approaches that consider composite failure still remain scarce. This work presents an optimization approach based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design process towards a global optimum. Kriging metamodel is used in the optimization algorithm. This metamodel enables the definition of an expected improvement function that is maximized at each iteration in order to locate new designs to update the metamodel and find optimal designs. This work uses explicit finite element analysis to study the crash behavior of composite parts that is available in the commercial code LS-DYNA. The optimization algorithm is implemented in MATLAB. Single and multi-objective optimization problems are solved in this work. The design variables considered in the optimization include the orientation of the plies as well as the size of zones that control the collapse of the composite parts. For the ease of manufacturing, the fiber orientation is defined as a discrete variable. Objective functions such as penetration, maximum displacement and maximum acceleration are defined in the optimization problems. Constraints are included in the optimization problem to guarantee the feasibility of the solutions provided by the optimization algorithm. The results of this study show that despite the brittle behavior of composite parts, they can be optimized to resist and absorb impact. In the case of single objective problems, the algorithm is able to find the global solution. When working with multi-objective problems, an enhanced Pareto is provided by the algorithm.