Improving Numerical Modeling Accuracy for Fiber Orientation and Mechanical Properties of Injection Molded Glass Fiber Reinforced Thermoplastics.

Local fiber alignment in fiber-reinforced thermoplastics is governed by complex flows during the molding process. As fiber-induced material anisotropy leads to non-homogeneous effective mechanical properties, accurate prediction of the final orientation state is critical for integrated structural simulations of these composites. In this work, a data-driven inverse modeling approach is proposed to improve the physics-based structural simulation of short glass fiber reinforced thermoplastics. The approach is divided into two steps: (1) optimization of the fiber orientation distribution (FOD) predicted by the Reduce Strain Closure (RSC) model, and (2) identification of the composite's mechanical properties used in the Ramberg-Osgood (RO) multiscale structural model. In both steps, the identification of the model's parameters was carried out using a Genetic Algorithm. Artificial Neural Networks were used as a machine learning-based surrogate model to approximate the simulation results locally and reduce the computational time. X-ray micro-computed tomography and tensile tests were used to acquire the FOD and mechanical data, respectively. The optimized parameters were then used to simulate a tensile test for a specimen injection molded in a dumbbell-shaped cavity selected as a case study for validation. The FOD prediction error was reduced by 51% using the RSC optimized coefficients if compared with the default coefficients of the RSC model. The proposed data-driven approach, which calculates both the RSC coefficients and the RO parameters by inverse modeling from experimental data, allowed improvement in the prediction accuracy by 43% for the elastic modulus and 59% for the tensile strength, compared with the non-optimized analysis.

Pore-Scale Transport and Two-Phase Fluid Structures in Fibrous Porous Layers: Application to Fuel Cells and Beyond.

We present pore-scale simulations of two-phase flows in a reconstructed fibrous porous layer. The three-dimensional microstructure of the material, a fuel cell gas diffusion layer, is acquired via X-ray computed tomography and used as input for lattice Boltzmann simulations. We perform a quantitative analysis of the multiphase pore-scale dynamics, and we identify the dominant fluid structures governing mass transport. The results show the existence of three different regimes of transport: a fast inertial dynamics at short times, characterised by a compact uniform front, a viscous-capillary regime at intermediate times, where liquid is transported along a gradually increasing number of preferential flow paths of the size of one-two pores, and a third regime at longer times, where liquid, after having reached the outlet, is exclusively flowing along such flow paths and the two-phase fluid structures are stabilised. We observe that the fibrous layer presents significant variations in its microscopic morphology, which have an important effect on the pore invasion dynamics, and counteract the stabilising viscous force. Liquid transport is indeed affected by the presence of microstructure-induced capillary pressures acting adversely to the flow, leading to capillary fingering transport mechanism and unstable front displacement, even in the absence of hydrophobic treatments of the porous material. We propose a macroscopic model based on an effective contact angle that mimics the effects of the such a dynamic capillary pressure. Finally, we underline the significance of the results for the optimal design of face masks in an effort to mitigate the current COVID-19 pandemic.

Assessment of Gradient-Based Algorithm for Surface Determination in Multi-Material Gap Measurements by X ray Computed Tomography.

X-ray computed tomography is one of the most promising measurement techniques for the dimensional evaluation of industrial components. However, the inherent complexity of this technology also involves important challenges. One of them is to develop surface determination algorithms capable of providing measurement results with better accuracy in any situation-for example, for single and multi-material parts, inner and outer geometries, with and without image artefacts, etc.-and reducing user influence. The surface determination is particularly complex in the case of multi-material parts, especially when they are separated by small air gaps. In previous works, two gradient-based algorithms were presented, that showed less measurement variability throughout the whole part, and reduced the computational cost and operator influence compared to threshold-based algorithms. This work focuses on the evaluation of the performance of these algorithms when used in a scenario so complex that parts of it are made of one or more materials (metal-metal and polymer-metal) with gaps inside. For this purpose, a set of multi-material reference standards is used. The presented gradient-based algorithms show measurement errors comparable to commercial threshold-based algorithms, but with the capability of obtaining accurate measurements in smaller gaps, apart from reducing the user influence on the measurement process.

Conformation and mechanics of the polymeric cuff of artificial urinary sphincter.

The surgical treatment of urinary incontinence is often performed by adopting an Artificial Urinary Sphincter (AUS). AUS cuff represents a fundamental component of the device, providing the mechanical action addressed to urethral occlusion, which can be investigated by computational approach. In this work, AUS cuff is studied with reference to both materials and structure, to develop a finite element model. Materials behavior is investigated using physicochemical and mechanical characterization, leading to the formulation of a constitutive model. Materials analysis shows that AUS cuff is composed by a silicone blister joined with a PET fiber-reinforced layer. A nonlinear mechanical behavior is found, with a higher stiffness in the outer layer due to fiber-reinforcement. The cuff conformation is acquired by Computer Tomography (CT) both in deflated and inflated conditions, for an accurate definition of the geometrical characteristics. Based on these data, the numerical model of AUS cuff is defined. CT images of the inflated cuff are compared with results of numerical analysis of the inflation process, for model validation. A relative error below 2.5% was found. This study is the first step for the comprehension of AUS mechanical behavior and allows the development of computational tools for the analysis of lumen occlusion process. The proposed approach could be adapted to further fluid-filled cuffs of artificial sphincters.

Quantification of Wear and Deformation in Different Configurations of Polyethylene Acetabular Cups Using Micro X-ray Computed Tomography.

Wear is currently quantified as mass loss of the bearing materials measured using gravimetric methods. However, this method does not provide other information, such as volumetric loss or surface deviation. In this work, we validated a technique to quantify polyethylene wear in three different batches of ultrahigh-molecular-polyethylene acetabular cups used for hip implants using nondestructive microcomputed tomography. Three different configurations of polyethylene acetabular cups, previously tested under the ISO 14242 parameters, were tested on a hip simulator for an additional 2 million cycles using a modified ISO 14242 load waveform. In this context, a new approach was proposed in order to simulate, on a hip joint simulator, high-demand activities. In addition, the effects of these activities were analyzed in terms of wear and deformations of those polyethylenes by means of gravimetric method and micro X-ray computed tomography. In particular, while the gravimetric method was used for weight loss assessment, microcomputed tomography allowed for acquisition of additional quantitative information about the evolution of local wear and deformation through three-dimensional surface deviation maps for the entire cups' surface. Experimental results showed that the wear and deformation behavior of these materials change according to different mechanical simulations.

Micro X-Ray Computed Tomography Mass Loss Assessment of Different UHMWPE: A Hip Joint Simulator Study on Standard vs. Cross-Linked Polyethylene.

More than 60.000 hip arthroplasty are performed every year in Italy. Although Ultra-High-Molecular-Weight-Polyethylene remains the most used material as acetabular cup, wear of this material induces over time in vivo a foreign-body response and consequently osteolysis, pain, and the need of implant revision. Furthermore, oxidative wear of the polyethylene provoke several and severe failures. To solve these problems, highly cross-linked polyethylene and Vitamin-E-stabilized polyethylene were introduced in the last years. In in vitro experiments, various efforts have been made to compare the wear behavior of standard PE and vitamin-E infused liners. In this study we compared the in vitro wear behavior of two different configurations of cross-linked polyethylene (with and without the add of Vitamin E) vs. the standard polyethylene acetabular cups. The aim of the present study was to validate a micro X-ray computed tomography technique to assess the wear of different commercially available, polyethylene's acetabular cups after wear simulation; in particular, the gravimetric method was used to provide reference wear values. The agreement between the two methods is documented in this paper.