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Predicting fatigue life of magnetorheological elastomers (MREs) containing, different volumes of carbonyl iron particles (CIPs) with various external magnetic fields has been investigated. Unlike many studies on fatigue behavior of MREs, representing experimental models, a novel three-dimensional constitutive magneto-hyper-viscoelastic semi-coupling model based on strain energy density function (3DSED) is derived, analyzing the fatigue of structures enhanced by MRE experimentally and numerically. In this 3DSED model, to obtain the best predicting MREs’ fatigue life, three different hyper-elastic functions, including Neo-Hookean, Mooney-Rivlin, and Yeoh are utilized. Using some uniaxial compression, such as loading phase, relaxation, and loading/unloading phases tests, hyper-elastic, magneto-elastic, and viscoelastic constants are determined. In addition, multi-axial fatigue tests are performed to define the number of cycles to failure. These tests have been induced by the magnetic fields of 0, 0.27, and 0.4 T. The fatigue tests re-performed with the magnetic field of 0.3 T to compare the predicted results using the proposed fatigue models. The results show that the 3DSED model can be used for the prediction of MREs fatigue life when subjected to complex and repetitive loading. For all CIP contents, the Mooney-Rivlin fatigue predictor has more accurate results. The Yeoh fatigue predictor indicates better results for MREs with higher CIP contents, while the Neo-Hookean fatigue predictor doesn’t show acceptable results for any CIP contents.

Prediction of fatigue life is particularly crucial in magnetorheological elastomer (MRE) based rubber components, especially when are exposed to repetitive magnetic and cyclic loading. MREs are smart composites that contain soft elastomer matrix and carbonyl iron particles (CIPs). In this research, silicon rubber was mixed with 20% of CIPs in the absence of an external magnetic field to produce MREs. Firstly, for the determination of material constants (including hyper elastic, magnetic, and viscoelastic), two types of tests such as uniaxial compression and relaxation, were performed on the samples. Then, fatigue tests were performed by a servo-hydraulic fatigue testing machine with cyclic loading in a repetitive magnetic field. Fatigue equations were obtained based on the number of fatigue life and maximum stress. The results confirmed that maximum stress could be used as a trustworthy fatigue life predictor for MREs when they are subjected to a combination of repetitive magnetic and cyclic loading. Scanning electron microscopy images from fatigue crack showed that the internal structure of MREs became stronger in the direction of the magnetic field. The maximum stress of the MRE was smaller in the absence of a magnetic field and decreased as the number of fatigue cycles increased with and without the magnetic field.

In this paper, the crashworthiness characteristics of tapered structures with the uniform cells in cross-section subjected to oblique impacts are theoretically and numerically investigated. Benefit...

The application of piezoelectric materials in energy harvesting devices has become an interesting topic for designers in recent years. Most of the reported works consider electrical power as a major parameter throughout the design procedure. What is less discussed is considering other design factors like the fatigue life of the harvester as well as the financial costs of the device. In this research, a methodology is introduced to design an optimum harvester, taking into account the aforementioned design factors. The finite element model of a piezoelectric harvester used in roadways is developed and validated. The fatigue test constants of the piezoelectric material are extracted via a novel approach. A parametric study is conducted on the model to generate a dataset containing electrical and mechanical characteristics, where it is used as an input for training an artificial neural network to model the behavior of the harvester. In order to evaluate the level of importance of the optimization objectives, two methods are employed: the Shannon entropy method and equal weighting factors. Results show the effectiveness of the model, where considering the electromechanical characteristics of the module is important in terms of overall performance, efficiency, durability, and financial costs.

In this paper, transient coupled thermo-mechanical finite element analysis of a three-dimensional model of braking pairs (brake disk and brake pads) is accomplished in order to estimate temperatures and stresses in brake disk during a braking cycle, including braking and cooling phases, and calculate fatigue life. A nonuniform distribution of temperatures is revealed on the surface of the brake disk, gradually generating surface hot spots and hot bands with temperatures up to 800 °C that lead to an uneven distribution of thermal stresses on the frictional surfaces. According to the simulations, variations in the circumferential stress, which is mainly responsible for the cracking of the brake disk, can reach up to 400 MPa in the hot spot areas, depending on the braking configurations. The numerical results are also used to estimate the fatigue life of brake disk using the Smith–Watson–Topper model. The numerical model demonstrates a high accuracy of fatigue life estimation when evaluated by prior experimental studies, signifying the effects of hot spots in reducing the service life of brake disk. Results of the fatigue life estimation show superiority to the analytical method both in the accuracy of calculation and detection of the failure location.

Piezoelectric energy harvesting is an efficient technique among energy scavenging methods employed in asphalt pavements. Several designs are reported in the literature; however, what is less discussed is how to design the harvester. In this paper, a fixed volume of piezoelectric material is considered, and various design parameters are discussed in order to achieve an improved design. The main objective is to enhance the harvester performance, considering electrical and mechanical aspects, simultaneously. The output power, the level of induced stress on the piezoelectric material, the endurance limit, and the coupling effect of the device with the pavement are considered. As a case study, the finite element model of a piezoelectric harvester is developed and validated with the experimental results. A parametric study is then carried out in order to improve both the electrical and mechanical characteristics of the device. Various parameters, such as piezoelectric disks cross-section, piezoelectric material, as well as the disks aspect ratio are considered. The proposed structures are compared with similar ones reported in the literature and show higher output powers of 3 − 5.8 times. A case study is presented to show the signal conditioning process of the harvested power for practical applications. Improvements in various aspects of the device performance, while considering the economic aspects, i.e., the amount of consumed piezoelectric material, show the effectiveness of the proposed method.

The most important purpose of the present work is to propose an analytical approach for solving the governing characteristic equations of the free vibrations problem of an orthotropic cylindrical shell with its length much greater than its other dimensions half way along which exist a semi-elliptical surface crack. Governing equations of motion of the problem have been derived using classical shell theories and simplified with regard to the Donell–Mushtari–Vlasov (DMV) theory. In comparison to shell dimensions, crack size is considered to be very small, which would minimize effects of the curvature in this study. Equations have been extracted for two different types of cracks: circumferential and axial cracks. In both cases, effects of the presence of crack on overall stiffness of the structure have been included in governing motion equations utilizing some crack compliance coefficients which have been calculated through Line Spring Model (LSM). A closed form solution for the characteristic equations of the problem has been introduced using Hamilton's principle and separation of variables for the simply supported shells. A comparison has been made between obtaining results through the proposed model and those from previous studies and Finite Element model. Last but not least, effects of the various shells, materials and the crack parameters on the fundamental natural frequency of the shell have been investigated.

In this paper, environmental strength degradation of 180 different adhesive single lap joints (SLJ), including mono-adhesive Araldite 2015, mono-adhesive Araldite AV138, and a mixed-adhesive of Araldite 2015 and Araldite AV138 subjected to moist conditions are experimentally studied. Four different moist conditions, i.e. dry, 75.3, 84.2 RH% and immersion in tap water, have been taken into consideration and the specimens are tested after exposing to these environments at room temperature for 0, 35, 80 and 270 days. The specimens have been tested in two different strain rate, i.e. 1 mm/min and 100 mm/min. The results reveal that although, in a dry environment, mixed-adhesive joints have higher failure loads in comparison to mono-adhesive SLJs, in a moist environment, they have the highest reduction in static failure load with regard to the mono-adhesive ones. Moreover, despite the finally brittle trend in failure load, mixed-adhesives manifest a behavior very similar to ductile mono-adhesives regarding elongation. Analytical predictions of failure load are also consistent with the experimental observations in dry condition.

Autonomous robotic suturing has the potential to improve surgery outcomes by leveraging accuracy, repeatability, and consistency compared to manual operations. However, achieving full autonomy in complex surgical environments is not practical and human supervision is required to guarantee safety. In this paper, we develop a confidence-based supervised autonomous suturing method to perform robotic suturing tasks via both Smart Tissue Autonomous Robot (STAR) and surgeon collaboratively with the highest possible degree of autonomy. Via the proposed method, STAR performs autonomous suturing when highly confident and otherwise asks the operator for possible assistance in suture positioning adjustments. We evaluate the accuracy of our proposed control method via robotic suturing tests on synthetic vaginal cuff tissues and compare them to the results of vaginal cuff closures performed by an experienced surgeon. Our test results indicate that by using the proposed confidence-based method, STAR can predict the success of pure autonomous suture placement with an accuracy of 94.74%. Moreover, via an additional 25% human intervention, STAR can achieve a 98.1% suture placement accuracy compared to an 85.4% accuracy of completely autonomous robotic suturing. Finally, our experiment results indicate that STAR using the proposed method achieves 1.6 times better consistency in suture spacing and 1.8 times better consistency in suture bite sizes than the manual results.

The COVID-19 pandemic has emerged as a serious global health crisis, with the predominant morbidity and mortality linked to pulmonary involvement. Point-of-Care ultrasound (POCUS) scanning, becoming one of the primary determinative methods for its diagnosis and staging, requires, however, close contact of healthcare workers with patients, therefore increasing the risk of infection. This work thus proposes an autonomous robotic solution that enables POCUS scanning of COVID-19 patients’ lungs for diagnosis and staging. An algorithm was developed for approximating the optimal position of an ultrasound probe on a patient from prior CT scans to reach predefined lung infiltrates. In the absence of prior CT scans, a deep learning method was developed for predicting 3D landmark positions of a human ribcage given a torso surface model. The landmarks, combined with the surface model, are subsequently used for estimating optimal ultrasound probe position on the patient for imaging infiltrates. These algorithms, combined with a force–displacement profile collection methodology, enabled the system to successfully image all points of interest in a simulated experimental setup with an average accuracy of 20.6 ± 14.7 mm using prior CT scans, and 19.8 ± 16.9 mm using only ribcage landmark estimation. A study on a full torso ultrasound phantom showed that autonomously acquired ultrasound images were 100% interpretable when using force feedback with prior CT and 88% with landmark estimation, compared to 75 and 58% without force feedback, respectively. This demonstrates the preliminary feasibility of the system, and its potential for offering a solution to help mitigate the spread of COVID-19 in vulnerable environments.

Surgical tumor resection is a common approach to cancer treatment. India Ink tattoos are widely used to aid tumor resection by localizing and mapping the tumor edge at the surface. However, India Ink tattoos are easily obscured during electrosurgical resection, and fade in intensity over time. In this work, a novel near-infrared (NIR) fluorescent marker is introduced as an alternative. The NIR marker was made by mixing indocyanine green (ICG), biocompatible cyanoacrylate, and acetone. The marking strategy was evaluated in a chronic ex vivo feasibility study using porcine tissues, followed by a chronic in vivo mouse study while compared with India Ink. In both studies, signal-to-noise (SNR) ratios and dimensions of the NIR markers and/or India Ink over the study period were calculated and reported. Electrocautery was performed on the last day of the mouse study after mice were euthanized, and SNR ratios and dimensions were quantified and compared. Biopsy was performed at all injection sites and slides were examined by a pathologist. The proposed NIR marker achieved (i) consistent visibility in the 26-day feasibility study and (ii) improved durability, visibility, and biocompatibility when compared to traditional India Ink over the six-week period in an in vivo mouse model. These effects persist after electrocautery whereas the India Ink markers were obscured. The use of a NIR fluorescent presurgical marking strategy has the potential for intraoperative tracking during long-term treatment protocols.

Compared to open surgical techniques, laparoscopic surgical methods aim to reduce the collateral tissue damage and hence decrease the patient recovery time. However, constraints imposed by the laparoscopic surgery, i.e. the operation of surgical tools in limited spaces, turn simple surgical tasks such as suturing into time-consuming and inconsistent tasks for surgeons. In this paper, we develop an autonomous laparoscopic robotic suturing system. More specific, we expand our smart tissue anastomosis robot (STAR) by developing i) a new 3D imaging endoscope, ii) a novel actuated laparoscopic suturing tool, and iii) a suture planning strategy for the autonomous suturing. We experimentally test the accuracy and consistency of our developed system and compare it to sutures performed manually by surgeons. Our test results on suture pads indicate that STAR can reach 2.9 times better consistency in suture spacing compared to manual method and also eliminate suture repositioning and adjustments. Moreover, the consistency of suture bite sizes obtained by STAR matches with those obtained by manual suturing.