Design Optimization of Sandwich Composite Armors for Blast Mitigation Using Bayesian Optimization with Single and Multi-Fidelity Data

2020 ◽  
Author(s):  
Homero Valladares ◽  
Andres Tovar
Keyword(s):  
Design Optimization ◽  
Bayesian Optimization ◽  
Sandwich Composite ◽  
Blast Mitigation

A Simple and Effective Methodology to Perform Multi-Objective Bayesian Optimization: An Application in the Design of Sandwich Composite Armors for Blast Mitigation

2020 ◽  
Author(s):  
Homero Valladares ◽  
Andres Tovar
Keyword(s):  
Finite Element ◽  
Surrogate Model ◽  
Test Problem ◽  
Pareto Front ◽  
Computational Cost ◽  
Bayesian Optimization ◽  
Sandwich Composite ◽  
Blast Mitigation ◽  
Multi Objective ◽  
Probabilistic Information

Abstract Bayesian optimization is a versatile numerical method to solve global optimization problems of high complexity at a reduced computational cost. The efficiency of Bayesian optimization relies on two key elements: a surrogate model and an acquisition function. The surrogate model is generated on a Gaussian process statistical framework and provides probabilistic information of the prediction. The acquisition function, which guides the optimization, uses the surrogate probabilistic information to balance the exploration and the exploitation of the design space. In the case of multi-objective problems, current implementations use acquisition functions such as the multi-objective expected improvement (MEI). The evaluation of MEI requires a surrogate model for each objective function. In order to expand the Pareto front, such implementations perform a multi-variate integral over an intricate hypervolume, which require high computational cost. The objective of this work is to introduce an efficient multi-objective Bayesian optimization method that avoids the need for multi-variate integration. The proposed approach employs the working principle of multi-objective traditional methods, e.g., weighted sum and min-max methods, which transform the multi-objective problem into a single-objective problem through a functional mapping of the objective functions. Since only one surrogate is trained, this approach has a low computational cost. The effectiveness of the proposed approach is demonstrated with the solution of four problems: (1) an unconstrained version of the Binh and Korn test problem (convex Pareto front), (2) the Fonseca and Fleming test problem (non-convex Pareto front), (3) a three-objective test problem and (4) the design optimization of a sandwich composite armor for blast mitigation. The optimization algorithm is implemented in MATLAB and the finite element simulations are performed in the explicit, nonlinear finite element analysis code LS-DYNA. The results are comparable (or superior) to the results of the MEI acquisition function.

Design optimization of hopper cars employing functionally graded honeycomb sandwich panels

2021 ◽  
pp. 095440972110496
Author(s):  
Ayman Al-Sukhon ◽  
Mostafa SA ElSayed
Keyword(s):  
Design Optimization ◽  
Sandwich Panels ◽  
Design Procedure ◽  
Functionally Graded ◽  
Sandwich Composite ◽  
Wall Structure ◽  
Concentrate Mass ◽  
Cross Sectional ◽  
Baseline Design ◽  
Honeycomb Sandwich

In this paper, a novel multiscale and multi-stage structural design optimization procedure is developed for the weight minimization of hopper cars. The procedure is tested under various loading conditions according to guidelines established by regulatory bodies, as well as a novel load case that considers fluid-structure interaction by means of explicit finite elements employing Smoothed Particle Hydrodynamics. The first stage in the design procedure involves topology optimization whereby optimal beam locations are determined within the design space of the hopper car wall structure. This is followed by cross-sectional sizing of the frame to concentrate mass in critical regions of the hopper car. In the second stage, hexagonal honeycomb sandwich panels are considered in lower load regions, and are optimized by means of Multiscale Design Optimization (MSDO). The MSDO drew upon the Kreisselmeier–Steinhausser equations to calculate a penalized cost function for the mass and compliance of a hopper car Finite Element Model (FEM) at the mesoscale. For each iteration in the MSDO, the FEM was updated with homogenized sandwich composite properties according to four design variables of interest at the microscale. A cost penalty is summed with the base cost by comparing results of the FEM with the imposed constraints. Efficacy of the novel design methodology is compared according to a baseline design employing conventional materials. By invoking the proposed methodology in a case study, it is demonstrated that a mass savings as high as 16.36% can be yielded for a single hopper car, which translates into a reduction in greenhouse gas emissions of 13.09% per car based on available literature.

Use of aluminum foam core sandwich structures to improve the blast-mitigation performance of light tactical vehicle side-vent-channel solution

2016 ◽  
Vol 232 (12) ◽  
pp. 993-1011
Author(s):  
M Grujicic ◽  
R Yavari ◽  
JS Snipes ◽  
S Ramaswami
Keyword(s):  
Design Optimization ◽  
Aluminum Foam ◽  
Sandwich Structures ◽  
Optimization Methods ◽  
Gaseous Detonation ◽  
Rocket Engines ◽  
Foam Core ◽  
Blast Mitigation ◽  
Detonation Products ◽  
Tactical Vehicle

In our recent work, a side-vent-channel blast-mitigation concept/solution for light tactical vehicles was proposed. As a part of this solution, side-vent channels are attached to the V-shaped vehicle underbody, in order to promote venting of the soil ejecta and gaseous detonation products and, in turn, generate a downward thrust on the targeted light tactical vehicle. As a consequence, the blast loads resulting from a shallow-buried mine detonated underneath a light tactical vehicle are mitigated, improving the probability for vehicle survival. The concept was motivated by the principles of operation of the so-called “pulse detonation” rocket engines. To quantify the utility and blast-mitigation capacity of this concept, use was made of several computational and design optimization methods and tools in our prior work. It was found that the capacity of the proposed blast-mitigation solution is relatively small, but still noteworthy. The present work focuses on further improvements in the blast-mitigation capacity of the side-vent-channel solution. Specifically, the benefits offered by substitution of the all-steel side-vent channels with side-vent channels made of sandwich structures (consisting of steel face-sheets and aluminum foam core) for all-steel side-vent channels are explored. The results obtained clearly demonstrated that this substitution can improve the blast-mitigation efficiency of the side-vent-channel solution. In addition, through the use of a design optimization analysis, it was established that this improvement can be further increased through proper grading of the aluminum foam density profile through the sandwich structure core.

PAM-4 based PCIe 6.0 Channel Design Optimization Method using Bayesian Optimization

2021 ◽  
Author(s):  
Jihun Kim ◽  
Hyunwook Park ◽  
Minsu Kim ◽  
Seongguk Kim ◽  
Seonguk Choi ◽  
...  
Keyword(s):  
Design Optimization ◽  
Optimization Method ◽  
Bayesian Optimization ◽  
Channel Design

Blast Mitigation in a Sandwich Composite Using Graded Core and Polyurea Interlayer

2011 ◽  
Vol 52 (2) ◽  
pp. 119-133 ◽  
Author(s):  
N. Gardner ◽  
E. Wang ◽  
P. Kumar ◽  
A. Shukla
Keyword(s):  
Sandwich Composite ◽  
Blast Mitigation
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