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The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

This work introduces a new Advanced Layered Composite (ALC) design that redirects impact load through the action of a lattice of 3D printed micro-compliant mechanisms. The first layer directly comes in contact with the impacting body and its function is to prevent an intrusion of the impacting body and uniformly distribute the impact forces over a large area. This layer can be made from fiber woven composites imbibed in the polymer matrix or from metals. The third layer is to serve a purpose of establishing contact between the protective structure and body to be protected. It can be a cushioning material or a hard metal depending on the application. The second layer is a compliant buffer zone (CBZ) which is sandwiched between two other layers and it is responsible for the dampening of most of the impact energy.

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.

In regions at war, the increasing use of improvised explosive devices (IEDs) is the main threat against military vehicles. Large cabin”s penetrations and high gross accelerations are primary threats against the occupants” survivability. The occupants” survivability under an IED event largely depends on the design of the vehicle armor. Under a blast load, a vehicle armor should maintain its structural integrity while providing low cabin penetrations and low gross accelerations. This investigation employs Bayesian global optimization (BGO) and non-uniform rational B-splines (NURBS) to design sandwich composite armors that simultaneously mitigate the cabin”s penetrations and the reaction force at the armor”s supports. The armors are made of four layers: steel, carbon fiber reinforced polymer (CFRP), aluminum honeycomb, and CFRP.