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Conventional crimp joints show high sensitivity to process conditions which makes it difficult to ensure joint quality. Low sensitivity of a joint to process conditions increases the structural integrity and performance of the product, yielding a more reliable structure. In this work, we address this problem and propose a new type of crimp joint. First the sensitivity of the joint to the crimping process parameters is investigated numerically, i.e. the crimping tool stroke, friction conditions, and the range of tolerances. The results provide a mechanical interpretation for the scatter of burst pressure at conventional crimp joints and that the sensitivity of the proposed joint to process parameters is practically negligible. The numerical model of the proposed joint is validated experimentally and good agreement between the numerical and experimental measurements is observed.

We present a novel constitutive model capable of describing non-linear anisotropic fibre-reinforced materials with different responses in tension and compression under a general stress state. The model is based on the original one-dimensional Ramberg–Osgood model, which is generalized to a multiaxial stress state and anisotropic material behaviour under thermodynamic requirements. To account for tension–compression asymmetry under a multiaxial stress state, the model is extended by the use of the stress triaxiality invariant as an indicator of stress state type, e.g. shear, uniaxial or biaxial tension, compression, etc. The model is implemented in ABAQUS/Explicit via the VUMAT subroutine and verified on two material datasets, which are an S2-glass/E773-epoxy and a reinforced polyester composite material. In comparison with other models, the proposed model provides an elegant formulation for the description of all the aforementioned phenomena, resulting in a simple calibration procedure based on uniaxial tensile and compressive tests.

In the paper, an alignment methodology of finite element and full-field measurement data of planar specimens is presented. The alignment procedure represents an essential part of modern material response characterisation using heterogeneous strain-field specimens. The methodology addresses both the specimen recognition from a measurement’s image and the alignment procedure and is designed to be applied on a single measurement system. This is essential for its practical application because both processes, shape recognition and alignment, must be performed only after the specimen is fully prepared for the digital image correlation (DIC) measurements (white background and black speckles) and placed into a testing machine. The specimen can be observed with a single camera or with a multi-camera system. The robustness of the alignment method is presented on a treatment of a specimen with a metamaterial-like structure and compared with the well-known iterative closest point (ICP) algorithm. The performance of the methodology is also demonstrated on a real DIC application.

In this work, a novel class of collocation methods for numerical integration of ODEs is presented. Methods are derived from the weighted integral form of ODEs by assuming that a polynomial function at individual time increment approximates the solution of the ODE. A distinct feature of the approach, which we demonstrated in this work, is that it allows the increase of accuracy of a method while retaining the number of method coefficients. This is achieved by applying different quadrature rule to the approximation function and the ODE, resulting in different behaviour of a method. Quadrature rules that we examined in this work are the Gauss–Legendre and Lobatto quadrature where several other quadrature rules could further be explored. The approach has also the potential for enhancing the accuracy of the established Runge–Kutta-type methods. We formulated the methods in the form of Butcher tables for convenient implementation. The performance of the new methods is investigated on some well-known stiff, oscillatory and non-linear ODEs from the literature.

During winter conditions, water intake structures represent one of many critical parts of hydraulic structures. Frazil ice deposits, accumulates and adhere to trash racks that can, in severe circumstances, completely prevent the water from entering the intake structure. One of the possible ways to cope with frazil ice blockage is by using waste heat of the discharge water, where a portion of the pumped water is recirculated back via a feedback loop to the intake structure. The recirculated water, serving as a heat source, can then somewhat warm the intake water and indirectly the air in the intake structure. In this work, an equation is derived that predicts the temperature of pumped water as a function of the recirculated-to-pumped water ratio and a case study on treating a water intake structure in a nuclear power plant is presented. The example demonstrates that, with a proper ratio between the pumped and recirculated flow rate, the formation of frazil ice and atmospheric icing could both be prevented.

This paper aims to compare different heterogeneous test designs from the perspective of the confidence interval quantification of inversely identified parameters, where the influence of a DIC optical system systematic and random error are taken into account. Because the errors in optical measurement can arise from many reasons and sources, our methodology relies on the system's errors determined from initial sets of pictures acquired at the load-free state for hundreds of specimens (over 850 tests over the past three years). In this way, a prior probability distribution of systematic and random error, arisen from the system initial settings and testing procedures are determined. Further, by conducting an inverse identification procedure of linear orthotropic elastic material parameters, the influence of the error distributions is studied for different types of heterogeneous specimens. The presented methodology determines the DIC bias and random error propagation through the inverse identification procedure to individual parameters. For each specimen design, confidence intervals of identified material parameters were determined. The results show the appropriateness of a specimen design for the identification of particular material parameters.

The purpose of this work is to predict the effect of impaired red blood cells (RBCs) deformability on blood flow conditions in human carotid artery bifurcation. First, a blood viscosity model is developed that predicts the steady-state blood viscosity as a function of shear rate, plasma viscosity, and mechanical (and geometrical) properties of RBC's. Viscosity model is developed by modifying the well-known Krieger and Dougherty equation for monodisperse suspensions by using the dimensional analysis approach. With the approach, we manage to account for the microscopic properties of RBC's, such as their deformability, in the macroscopic behavior of blood via blood viscosity. In the second part of the paper, the deduced viscosity model is used to numerically predict blood flow conditions in human carotid artery bifurcation. Simulations are performed for different values of RBC's deformability and analyzed by investigating parameters, such as the temporal mean wall shear stress (WSS), oscillatory shear index (OSI), and mean temporal gradient of WSS. The analyses show that the decrease of RBC's deformability decrease the regions of low WSS (i.e., sites known to be prevalent at atherosclerosis-prone regions); increase, in average, the value of WSS along the artery; and decrease the areas of high OSI. These observations provide an insight into the influence of blood's microscopic properties, such as the deformability of RBC's, on hemodynamics in larger arteries and their influence on parameters that are known to play a role in the initiation and progression of atherosclerosis.