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Mechanical behavior of mycelium-based particulate composites

We study the mechanical behavior of mycelium composites reinforced with biodegradable agro-waste particles. In the composite, the mycelium acts as a supportive matrix which binds reinforcing particles within its filamentous network structure. The compressive behavior of mycelium composites is investigated using an integrated experimental and computational approach.

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Mechanics of Mushroom as a material

We recently characterized a unique material developed from root structure (Mycelium) of mushroom. Mycelium has a filamentous network structure with mechanics largely controlled by filament elasticity and branching, and network density. We report the morphological and mechanical characterization of mycelium. The monotonic mechanical behavior of the mycelium is non-linear both in tension and compression.

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Poisson Contraction and Fiber Kinematics in Tissue: Insight from Collagen Network Simulations

Connective tissue mechanics is highly non-linear, exhibits a strong Poisson effect and is associated with significant collagen fiber re-arrangement. Although the general features of the stress-strain behavior in tension and compression and under uniaxial, biaxial and shear loading have been discussed extensively, especially from the macroscopic perspective, the Poisson effect and the kinematics of filaments have received less attention. In general, the relationship between the microscopic fiber network mechanics and the macroscopic experimental observations remains poorly defined.

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Microstructure modeling of random composites with cylindrical inclusions having high volume fraction and broad aspect ratio distribution

We proposed a computational methodology for generating microstructure models of random composites with cylindrical or sphero-cylindrical inclusions having high volume fraction and broad aspect ratio distribution. The proposed methodology couples the random sequential adsorption (RSA) algorithm and dynamic finite element (FE) simulations. It uses RSA to generate sparse inclusion assemblies of low volume fraction and subsequently utilizes dynamic FE simulation for inclusion packing to achieve high volume fractions.

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Simulation-based numerical optimization of arc welding process for reduced distortion in welded structures

This paper presents an effective numerical approach for welding process
parameter optimization to minimize weld-induced distortion in
structures. A numerical optimization framework based on coupled Genetic
Algorithm (GA) and Finite Element Analysis (FEA) is developed and
implemented for a low and a high fidelity model. Classical weakly
coupled thermo-mechanical analysis with thermo-elasto-plastic
assumptions is carried out for distortion prediction of numerical
models. The search for optimum process parameters is executed by direct
integration of numerical models and GA-based optimization technique. The
developed framework automatically inserts the process parameters into
the simulation models, executes the FE-based welding simulations and

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