Sudden concrete failure is due to inelastic deformations of concrete subjected to tension. However, synthesizing nanomaterials reinforcements has significant impact on cement-based composites failure mechanism. Nanomaterials morphology bridges cement crystals as homogeneous and ductile matrix. In this experiment, cement matrix with water to cement ratio of 0.5 reinforced by 0.2–0.6 wt% of functionalized (COOH group) multi-walled and single-walled carbon nanotubes were used. After sonication of carbon nanotubes in water solution for an hour, the cementitious nanocomposites were casted in cylindrical molds (25 mm diameter and 50 mm height). Failure mechanism of cementitious nanocomposite showed considerable ductility throughout splitting tensile test compared to cement mortar. Additionally, the failure pattern after developing the initial crack provided additional time before ultimate failure occurred in cement-based nanocomposites. The evolution of crack propagation was assessed until ultimate specimen failure during splitting-tensile test on cementitious nanocomposite surface. The deformation of cross section from circle to oval shape augmented tensile strength by 50% in cementitious nanocomposite compared to conventional cement mortar.

The aim of this study is mainly about preventing crack initiation and propagation in rolling contact under moderate and extreme loading through coating technology using finite element simulation and design of experiment (DOE) optimization techniques. Several applications of rolling contact were conducted and the parameters related to rollers’ materials, coating, temperature, and loads were investigated. M50 steels (0.8C-4.2Cr-4.3Mo-1V wt.%) and 100CrMnMo8 steel (1.0C-2.0Cr-0.5Mo-1.0Mn-0.5Si wt.%) were analyzed with and without titanium nitride (TiN), zirconium nitride (ZrN) and tungsten carbide (WC) coatings under different temperature and loading conditions. Results showed that cracks propagation were limited to extreme load when using coating technology. A fully three-dimensional finite element model showed the Von Mises stresses and displacement under different temperatures. Findings confirmed that coating will enhance the lifetime of rollers and inhibit cracks and plastic deformation with better contribution from TiN under extreme pressure if compared to WC. DOE optimization of the parameter used in this study correlate closely with previous experiments and provided a solid conclusion of the best combination in rolling contact applications.

Thin walled members such as square tubes are commonly used in vehicle’s frontal chassis to provide protection and damage attenuation to the passenger cabin in the case of impact loading. These structural members undergo progressive deformation under axial loading. The type of deformation mode is critical as it defines the overall configuration of force-displacement curve. There are different types of deformation modes for square tube under axial loading. Likewise, cellular structure exhibit distinct deformation modes under in-plane loading. The work presented here investigates the effects of partial or discrete bonding of cellular core structure on deformation modes of square tubes under axial loading. The results show that discrete bonding of cellular core with the tube has significant effect on progressive deformation of tubes and therefore, presents an opportunity to re-configure force-displacement curve for improved protection of automobile structures under impact loading.

We investigate the relationship between the average profile height and the average plastic strain of a grain in a polycrystalline material under plastic tensile strain using Crystal Plasticity Finite Element Method (CPFEM). The simulation consists of using an anisotropic grain embedded in an isotropic sample undergoing tensile plastic deformation. 150 different lattice orientations for the embedded anisotropic grain are used to represent all possible grain orientations. We found that plastic strain in the loading direction is not related to the surface profile height. However, the plastic strains in the direction normal to the surface and the transverse direction are linearly proportional to the average profile heights, irrespective of the grain orientation. The magnitude of the plastic strain in the direction normal to the surface decreases with increasing surface profile height. It is vice versa for plastic strains in the transverse direction. These results establish a possibility of determining a grain’s plastic strains from the profile height.

This study compares the deformation characteristics of steel and carbon fiber composite (CFC) front bumper crush can (FBCC) assemblies when subjected to a full-overlap frontal impact into a rigid wall. Both the steel and composite bumper tests were conducted using a sled-on-sled testing method. Several high-speed cameras (HSCs) and accelerometers were used to gather kinematics data. The applied forces were measured using a load cell wall. For each test, the collective set of data was filtered, sorted, and analyzed to compare the performance of the steel and CFC bumpers. Similarities in Acceleration-Time plots suggested resemblance in the deformation patterns for both types of bumper systems. The difference observed in the velocity and displacement time-histories was because of the brittle nature of the composite material. The velocity-time history of the CFC FBCC had two distinct patterns, events suggesting adhesive bond failure between the bumper beam and the crush cans, which was validated through video tracking. Post-impact photographs showed a clear difference between the material behavior of composite and steel bumpers when subjected to high-velocity impact. The steel bumper beam was bent uniformly with intact, equally crushed crush cans. The composite beam was cracked in the middle and was detached from the crush cans.

While single network hydrogels show limited extensibility and low strength, double-network hydrogels benefit from significantly high stretchability and toughness due to their reinforcing mechanism of combining two soft and rigid networks. Here, a micro-mechanical model is developed to characterize the constitutive behavior of DN hydrogels in quasi-static large deformation. In particular, we focused on describing the permanent damage in DN gels under large deformations. Irreversible chain detachment and decomposition of the first network are explored as the underlying reasons for the nonlinear inelastic phenomenon. The proposed model enables us to describe the damage and the way it influences the micro-structure of the gel. The model is validated with uni-axial loading and unloading experiments of DN gels. The proposed model contains a few numbers of material constants and shows a good agreement with cyclic uni-axial test data.

Multi-level helical twisted structures represent an example of how natural design achieved an optimized approach for creating a tough and strong fiber from often weak and soft microscale yarns through a hierarchical architecture. In this work, a constitutive model is presented to describe the load transfer within a double twisted helical structures in large deformation regime. The model aims to establish the torsion-tensile properties of fibers as an assembly of twisted yarns and filaments. The model associates the fiber response to the mechanics and the geometry of yarns in the deformed state. In this work, we mainly focus on elastic response of the material and thus inelastic damages were not considered. We modeled the inter-yarn forces that can cause friction. By considering the deformation induced changes in the geometry of constituents, the model describes the influence of the fiber composition parameters such as helical angel of the filaments, prestretch, pretwist of the yarns and the inter-yarn frictions, on the mechanical response of fibers. The model provides a detailed outlook into load transfer within fibers which helps us understand how to design fibers with certain performance.

The bottom hole assembly (BHA) of a modern drill string for directional drilling mainly comprises a drill bit, a rotary steerable system, and a measurement while drilling tool. The tools and subs used on a BHA are screwed together through rotary shouldered threaded connections. Each connection is made up with a pin and a box. These connections are the weakest links when the BHA undergoes a large number of revolutions in a curved well section. When the fatigue life of a connection is consumed during a drilling job, a twist-off would occur, which could result in an enormous amount of non-productive time and possibly loss of the bottom BHA section in the hole. Cold rolling has proven to be able to improve fatigue resistance of a threaded connection by pressing a rolling wheel against the thread root and generating a layer of compressive residual stress at the root. Understanding how cold rolling improves fatigue resistance of a threaded connection is important for optimization of the rolling parameters and prediction of the BHA service life in a given drilling condition. In this paper, a predictive method is presented for fatigue life of a cold rolled threaded connection. A finite element model was developed to simulate the cold rolling process. The resulting deformation and stress states at the root were carried over through makeup of the pin and the box as well as through cyclic bending of the connection. The fatigue life predictions were found to be in favorable agreement with the experimental measurements from full-scale fatigue tests at different bending moment levels applied.

Unit-cell modelling is one of the useful methods to analyze deformation in periodic structures like honeycombs, perforated boards, and woven fabrics. The initial state of the structures is considered to be stress-free in ordinal deformation analysis, but in actual practice, the analysis is difficult, because initial stresses like assembly stress and residual stress need to be considered, as they are known to affect the results. In this study, a technique of taking into account the initial-stress state in woven fabrics is discussed, which has resulted in the establishment of a precise design method for textiles. LS-DYNA, which is a general-purpose finite element (FE) software, has been utilized to simulate the complex deformations in woven fabrics. In this software, a function of the global constraint on boundary conditions facilitates the analysis of periodic structures, but causes difficulties in computing the initial stress states in woven fabrics, as the conditions of mechanical equilibrium have to be satisfied in the governing equations. In particular, duplicated definitions of forced displacement and periodic deformation make the computation impossible, hence, a phantom-element has been introduced to ease the FE analysis by defining these quantities. A unit-cell of the woven fabric is identified and the initial states in stressed conditions can be estimated for periodic structures of plain-woven fabrics by a periodic-analysis technique of LS-DYNA coupled with the phantom-element, which yields a weaving motion of the yarn in plain-woven fabrics.

Functional metamaterials are gradually becoming the frontier of scientific research and industrial applications. Among them, reconfigurable mechanical metamaterial with inbuilt motion capability could result in unusual physical properties such as shape tunability and programmable density and stiffness. Inspired by the transformable cuboid structure that was first investigated by Ron Resch, we proposed a tilted cuboid structure that can fold into a 3D configuration. By designing the individual building units, face angles and tessellation pattern, we are able to construct a series of reconfigurable structures with various shape, twist and permeability feature. Based on our approach, a configuration method to build multi-layer metamaterial is proposed, and it can be generalized to other tilted structures with different building units. The volumetric strains of different models are analyzed, and the result shows the metamaterial has a massive deformation ability as the maximum volume can be four times of the packaged volume. The tilted cuboid structure is highly flexible with variable stiffness and permeability, and can be used to develop metamaterials, large deformation devices and kinetic architectures.

A composite material (CM) of periodic structure with the peristatic properties of constituents (see Silling, J. Mech. Phys. Solids 2000; 48:175–209) is analyzed by a generalization of the classical locally elastic computational homogenization to its peristatic counterpart. One introduces new volumetric periodic boundary conditions (PBC) at the interaction boundary of a representative unit cell (UC). A generalization of the Hill’s equality to peristatic composites is proved. The general results establishing the links between the effective moduli and the corresponding mechanical influence functions are obtained. The discretization of the equilibrium equation acts as a macro-to-micro transition of the deformation-driven type, where the overall deformation is controlled. Determination of the microstructural displacements allows one to estimate the peristatic traction at the geometrical UC’s boundary which is exploited for estimation of the macroscopic stresses and the effective moduli. One demonstrates computationally, through one-dimensional examples, the approach proposed.

Recently there has been a growing interest to develop innovative surgical needles for percutaneous interventional procedures. Needles are commonly used to reach target locations inside of the body for various medical interventions. The effectiveness of these procedures depends on the accuracy with which the needle tips reach the targets, such as a biopsy procedure to assess cancerous cells and tumors. One of the major issues in needle steering is the force during insertion, also known as the insertion (penetration) force. The insertion force causes tissue damage as well as tissue deformation. It has been well studied that tissue deformation causes the needle to deviate from its target thus causing an ineffective procedure. Simulation of surgical procedures provides an effective method for a robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the mechanical behavior on the interface of surgical needles and organs, specifically the insertion force, has been well recognized as a major challenge. Overcoming such obstacle by development of robust numerical models will enable realistic force feedback to the user during surgical simulation. This study investigates feasibility of predicting the insertion force of bevel-tip needles based on experimental data using neural network modeling. Simulation of the proposed neural network model is performed using Kera’s Python Deep Learning Library with TensorFlow as a backend. The insertion forces of needles with different bevel-tip angles in gel tissue phantom are measured using a specially designed automated needle insertion test setup. Input-output datasets are generated where the inputs are defined as bevel-tip angles and gel tissue phantom stiffness, and the output is defined as the insertion force. A properly trained neural network then maps the input data to the output data and the input-output dataset is supplied to train a neural network. Its performance is then evaluated using different and unseen input-output dataset. This paper shows that the proposed neural network model accurately predicts the insertion force.

This study tests a custom-designed knee implant made of an FDA approved biomaterial, Chronoflex AR. The implant is designed to cushion the damaged cartilage at the distal end of the femur to reduce knee pain without the removal of cartilage and bone. A patient’s MRI scan was used to render a 3D computer graphic design of the knee. The manufacturing of the implant is conducted by 3D printing the shape of the distal end of the femur and coating it with the biomaterial. This is a preliminary fabrication method. Ultimately, the implant material will be 3D printed or cast in 3D printed molds. A successful implementation of this sort of custom-designed implant would reduce the invasiveness of knee correcting procedures, enable the patient to retain the shape of his or her femoral and tibial anatomy, and reduce the possibility of revision surgeries. A custom knee implant testing machine was designed and fabricated to measure the force, elastic deformation, plastic deformation, wear and fatigue of the component after performing lab tests simulating a normal walking pattern while adhering to ISO standards.

The paper proposes a numerical approach for the analysis of the blood flow in human aorta under real operating conditions. An ad-hoc procedure is developed for importing the aorta geometry from magnetic resonance imaging in order to have a patient based analysis. The aortic flow is simulated accounting for the dynamic behavior of the flow resulting from the heart pulse and for the non-Newtonian properties of blood. Fluid – structure analysis is carried out to address the mutual influence of the flow transient nature and the aorta walls’ deformation on the pressure flow field and tissue’s stresses. Finite element method approach is used for the structural analysis of the aorta walls which are assumed as a linear elastic isotropic material; nevertheless, different regions are introduced to account for the Young modulus variation from the ascending aorta to the common iliac arteries. Mesh morphing techniques are adopted to simulate the wall deformation and a two equation turbulence model is adopted to include the turbulence effects. The proposed numerical approach is validated against the measurements carried out on magnetic resonance imaging scanner and a good agreement is found in terms of aorta wall maximum and minimum deformation during the cardiac cycle. Therefore, the fluid-structure analysis can provide an important tool to extend the insight of the aortic system from magnetic resonance imaging techniques and improve the understanding of arteriosclerosis and the related phenomena as well as their dependence on flow structure and tissue stresses.

Mild traumatic brain injury (TBI) is a very common injury to service members in recent conflicts. Computational models can offer insights in understanding the underlying mechanism of brain injury, which can aid in the development of effective personal protective equipment. This paper attempts to correlate simulation results with clinical data from advanced techniques such as magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), MR spectroscopy and susceptibility weighted imaging (SWI), to identify TBI related subtle alterations in brain morphology, function and metabolism. High-resolution image data were obtained from the MRI scan of a young adult male, from a concussive head injury caused by a road traffic accident. The falling accident of human was modeled by combing high-resolution human head model with an articulated human body model. This mixed, multi-fidelity computational modeling approach can efficiently investigate such accident-related TBI. A high-fidelity computational head model was used to accurately reproduce the complex structures of the head. For most soft materials, the hyper-viscoelastic model was used to captures the strain rate dependence and finite strain nonlinearity. Stiffer materials, such as bony structure were simulated using an elasto-plastic material model to capture the permanent deformation. We used the enhanced linear tetrahedral elements to remove the parasitic locking problem in modeling such incompressible biological tissues. The bio-fidelity of human head model was validated from human cadaver tests. The accidental fall was reconstructed using such multi-fidelity models. The localized large deformation in the head was simulated and compared with the MRI images. The shear stress and shear strain were used to correlate with the post-accident medical images with respect to the injury location and severity in the brain. The correspondence between model results and MRI findings further validates the human head models and enhances our understanding of the mechanism, extent and impact of TBI.

In the United States, Alzheimer’s disease (AD) affects one in ten people ages 65 and older. In most patients, the first indication of AD is the inability to remember new information, and symptoms grow to include behavior changes and increasing confusion and suspicions surrounding loved ones and daily events. As the disease progresses, the cortex and hippocampus regions of the brain decrease in size, allowing the fluid-filled ventricles within the brain to increase. New and innovative therapies to delay the onset of the disease and progression of the symptoms are being discovered. For example, the antibody solanezumab is undergoing clinical trials to determine its ability to reduce the levels of beta-amyloid in the brain, a known risk factor of AD. Consequently, the ability to identify patients who could benefit from the therapies will be invaluable. The purpose of this study is to determine if the digital volume correlation (DVC) algorithm can detect and track the onset and progression of AD using magnetic resonance imaging (MRI) scans of the head. DVC measures the deformation and strain of the volumetric MRI dataset by tracking the changes in its grey value pattern. A collection of MRI datasets of a patient’s head, which include scans from a baseline visit and visits at 6 months, 12 months, and every 12 months thereafter, is used in our analysis. A strain is applied to each set of MRI scans prior to implementation of the digital volume correlation algorithm. The DVC algorithm is then applied to the dataset and the resulting error between the expected and calculated strain is computed. A decrease in the contrast of the MRI dataset will correlate to additional error by the algorithm. As a result, an increase in the calculated strain error is anticipated to correlate with an increase in the ventricles in the brain, or progression of the disease, over the time period of interest.

Breastfeeding provides both nutrients and immunities necessary for infant growth. Understanding the biomechanics of breastfeeding requires capturing both positive and negative pressures exerted by infants on the breast. This clinical experimental work utilizes thin, flexible pressure sensors to capture the positive oral pressures of 7 mother-infant dyads during breastfeeding while simultaneously measuring vacuum pressures and imaging of the infants oral cavity movement via ultrasound. Methods for denoising signals and evaluating ultrasound images are discussed. Changes and deformations on the nipple are evaluated. The results reveal that pressure from the infant’s maxilla and mandible are evenly distributed in an oscillatory pattern corresponding to the vacuum pressure patterns. Variations in nipple dimensions are considerably smaller than variations in either pressure but the ultrasound shows positive pressure dominates structural changes during breastfeeding. Clinical implications for infant-led milk expression and data processing are discussed.

The aim of this study was to develop a test method to characterize the material behavior of bovine brain samples in large shear deformations and high strain rates relevant to blast-induced neurotrauma (BINT) and evaluate tissue damage. A novel shear test setup was designed and built capable of applying strain rates ranging from 300 to 1000 s −1 . Based on the shear force time history and propagation of shear waves, it was found that the instantaneous shear modulus (about 6 kPa) was more than 3 times higher than the values previously reported in the literature. The shear wave velocity was found to be strain path dependent which is an indication of tissue damage at strains greater than 10%. The results of this study can help in improving finite element models of the brain for simulating tissue injury during BINT.

Because the fracture behaviors of soft materials are complex, high-precision technology is needed to perform the detailed analysis necessary to produce more effective materials. Indentation methods exist to characterize the fracture behavior of soft materials, with fractures varying in accordance with the shape of the indenter. Thus, it is important to clarify the relationship between indenter shape and the fracture behaviors of soft materials, and necessary to consider the complicated deformation patterns induced by the mechanical nonlinearity of the materials. To this end, various needle-like indenter shapes are modeled via a finite element method (FEM). In this study, we employ a cone-shaped reference needle. Then, the shape is changed to have the tip form a curvilinear indentation, resembling a steep mountain ridgeline. In addition, shear strain is set as the fracture criterion for soft material in the FE analysis since the shear force resulting from penetration primarily damages the soft materials. Regarding the force applied to the needle, there is a tendency for the force to become smaller as it more resembles a cone shape. There are three fracture types: holing, opening, and slitting. Holing is generated by the cone needle, and the fracture of soft material appears along the shape of the needle. Opening fractures are generated by the needle with a curvilinearly spreading tip, forming a small slit on the surface of the soft material. Lastly, slitting fractures are also generated by the needle with a curvilinearly spreading tip, but the resulting slit is deepened without damaging the tissue surrounding the needling. These fracture types can also be classified according to the fracture area of the soft material surface, with slitting resulting in the smallest fracture area.

External mechanical forces can reach the cell nucleus causing changes in nuclear morphology, size and motility. A common explanation is that these forces are transmitted by surrounding cytoskeleton network through its linkage to nuclear envelope; shear stress causes reorganization of cytoskeleton, thus, the changes in nuclear shape. In this study, we measured nuclear shape and intracellular Ca 2+ under fluid shear stress in MDCK cells using a parallel plate microfluidic chip. We show that fluid shear stress (1.1 dyn/cm 2 , 3 hrs) causes significant changes in nuclear shape in cells, from a flat disk shape having larger area to a thicker disk having smaller area. An increase in intracellular Ca 2+ is required for shear induced nucleus deformation. Inhibiting Ca 2+ influx with GsMTx4 and Gd 3+ eliminated Ca 2+ influx and abolished the nuclear deformation. The cytoskeleton reorganization occurred in parallel with Ca 2+ rise in the cells. Increasing intracellular Ca 2+ with thapsigargin that depletes the Ca 2+ stores resumed the nuclear deformation. This suggests that shear induced nuclear deformation is a Ca 2+ dependent process.