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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.

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.

We propose a trust and self-confidence-based autonomy allocation strategy to automatically choose between manual and autonomous control of (semi)autonomous mobile robots in guidance and navigation tasks. We utilize a performance-centric, computational trust and self-confidence model and automated autonomy allocation strategy, developed in our earlier work (H. Saeidi and Y. Wang, “Trust and self-confidence based autonomy allocation for robotic systems,” in Proc. 54th IEEE Conf. Decis. Control , 2015, pp. 6052–6057.), based on objective and unbiased performance measures for the human and the robot. A set of robot simulations with a human-in-the-loop is conducted for a teleoperated unmanned aerial vehicle tracking task. The results demonstrate that our allocation strategy can capture human autonomy allocation pattern with an accuracy of 64.05%. We also show that the strategy can improve the overall robot performance by 11.76% and reduce operator's workload by 10.07% compared to a manual allocation. Moreover, compared to a performance maximization strategy, our strategy is 23.42% more likely to be accepted and generally preferred and trusted by the participants. Furthermore, we design a decision pattern correction algorithm based on nonlinear model predictive control to help a human operator gradually adapt to a modified allocation pattern for improved overall performance.

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.

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.

Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.

INTRODUCTION AND OBJECTIVE:The inconsistency and difficulty of suturing in minimally invasive surgeries stem from the limitations in tool motion and visualization. In pelvic surgery, difficulty is ...

Unmanned aerial vehicles (UAVs) can be challenging to operate due to remote control environments and unstable system dynamics. A haptic control strategy is introduced to improve the UAV’s stability...

Magneto-rheological elastomers (MRE), which undergo upon the smart materials, are one of the very common products frequently used in modern vehicle production nowadays. For their visco-hyper properties, elastomers find a prevalent use as an energy absorber. Inducing a magnetic field would make their energy absorbing characteristics vary upon the desired ones by adjusting the applied potential field. A precise calculation of the amount of their absorption with respect to the potential field has a key role in the prediction of MREs’ responses. Therefore, in this study, a hyper-visco-magnetic constitutive model is utilized in COMSOL commercial software for the energy damping estimation in magneto-rheological elastomers. A representative volume element has been considered for the calculation of hysteresis loop areas as a characteristic of energy damping behaviour in MREs. Finally, the effects of magnetic flux intensity and mechanical load frequency in the energy damping behaviour of automotive magneto-rheological elastomers are evaluated.

In recent years, increasing utilize of the adhesively bonded joints due to its prominent features in distribution of the stress in bonded area and bonding dissimilar material has led to developing its computational aspects to provide more reliable response. In this regard, cohesive zone model (CZM) as an effective method to simulate bondline is introduced. The crucial aspect of this method is the determination of the relation between traction and separation in fracture process zone (FPZ). In fact, the traction-separation law (TSL) is a material model which must be properly obtained and applied to the adhesive bondline. According to the literature, mechanical response of the adhesive joints in most cases (especially in ductile and semi-brittle adhesives) is depended on the TSL curve shape. In this study, a novel CZM is developed to simulate double cantilever beam (DCB) adhesive joint. The main advantageous this new model is considering non-linear behavior of ductile adhesives in elastic region. DCB coupons fabricated by means of Al 6061 adherends and Araldite 2015 adhesive. After direct extraction of the TSL and obtaining cohesive parameters of the new model, numerical simulation of the DCB is conducted. Finally, sensitivity analysis of cohesive parameters and effect of initial crack length on the DCB response is investigated.

The goal of this paper is to improve the performance of joint human–robot systems while balancing human experience through computational trust analysis in telerobotics applications. A mixed-initiative approach is enabled by scaling the manual and autonomous controls using a function of computational human-to-robot trust. A dynamic haptic force feedback scaling strategy is performed via a function of computational robot-to-human trust to adjust the assistive force and, hence, physical workload of the operator. Passivity-based methods are used to guarantee the stability of the overall framework. Moreover, guidelines are provided to adjust the transparency of force feedback and velocity signals while guaranteeing passivity. An experimental study with 30 human subjects demonstrates a 12.8% increase in task performance and a 10.7% decrease in operator workload when the proposed strategy is used as compared to a manual autonomy allocation approach. The results also indicate that the proposed method yields higher operator satisfaction compared to manual and optimal autonomy allocation methods and is 10.1% more trusted by the operators than the optimal allocation method.

For the first time in this paper, free vibration and thermal buckling of micro temperature-dependent FG porous circular plate subjected to a nonlinear thermal load are numerically studied. The governing equations are derived based on Hamilton's principal and using both classical and the first-order shear deformation theories in conjunction with the modified couple stress theory. Generalized Differential Quadrature method is applied to solve the equations with associated boundary conditions. The results reveal that the increase of size dependency and the temperature-change would lead to the increase of differences between the first natural frequencies predicted based on the two theories. In contrast, the porosity and the FG power index do have not any effect on that. While the effect of porosity on free vibration of clamped and free plates are negligible, but the effect of porosity for hinged ones is considerable as the temperature-change increase. Moreover, the critical conditions of the plates which are expressed by porosity, FG power index, size dependency, temperature-change and geometrical dimensions are presented, as well. Numerical results are in good agreement with those available in literature in some special cases.

Autonomous robotic assisted surgery (RAS) systems aim to reduce human errors and improve patient outcomes leveraging robotic accuracy and repeatability during surgical procedures. However, full automation of RAS in complex surgical environments is still not feasible and collaboration with the surgeon is required for safe and effective use. In this work, we utilize our Smart Tissue Autonomous Robot (STAR) to develop and evaluate a shared control strategy for the collaboration of the robot with a human operator in surgical scenarios. We consider 2D pattern cutting tasks with partial blood occlusion of the cutting pattern using a robotic electrocautery tool. For this surgical task and RAS system, we i) develop a confidence-based shared control strategy, ii) assess the pattern tracking performances of manual and autonomous controls and identify the confidence models for human and robot as well as a confidence-based control allocation function, and iii) experimentally evaluate the accuracy of our proposed shared control strategy. In our experiments on porcine fat samples, by combining the best elements of autonomous robot controller with complementary skills of a human operator, our proposed control strategy improved the cutting accuracy by 6.4%, while reducing the operator work time to 44 % compared to a pure manual control.

Autonomous robotic anastomosis has the potential to improve surgical outcomes by performing more consistent suture spacing and bite size compared to manual anastomosis. However, due to soft tissue’s irregular shape and unpredictable deformation, performing autonomous robotic anastomosis without continuous tissue detection and three-dimensional path planning strategies remains a challenging task. In this paper, we present a novel three-dimensional path planning algorithm for Smart Tissue Autonomous Robot (STAR) to enable semi-autonomous robotic anastomosis on deformable tissue. The algorithm incorporates (i) continuous detection of 3D near infrared (NIR) markers manually placed on deformable tissue before the procedure, (ii) generating a uniform and consistent suture placement plan using 3D path planning methods based on the locations of the NIR markers, and (iii) updating the remaining suture plan after each completed stitch using a non-rigid registration technique to account for tissue deformation during anastomosis. We evaluate the path planning algorithm for accuracy and consistency by comparing the anastomosis of synthetic vaginal cuff tissue completed by STAR and a surgeon. Our test results indicate that STAR using the proposed method achieves 2.6 times better consistency in suture spacing and 2.4 times better consistency in suture bite sizes than the manual anastomosis.

Fatigue life is one of the most important characteristics of materials. Predicting fatigue life in magnetorheological elastomer (MRE) under combined and repetitive loads is an unavoidable step to increase the safety coefficient of MREs. In this study, high-temperature vulcanization silicon rubber (HTVSR) based MREs were fabricated by incorporating the different soft carbonyl iron particles (CIP) that samples with 10%, 20%, and 30% of CIP volume were made. Fatigue behavior of MRE under the combination of compression-tension and torsion loading in the presence and absence of magnetic fields was studied by using the multiaxial fatigue testing machine. The relationship between maximum energy density function (W max) and fatigue life (N) was achieved that it can predict fatigue life in MREs. The results showed that the dissipation energy was smaller in the presence of a magnetic field at the same CIP volume percentage and increased as the CIP volume percentages grew, because the agglomeration in the samples became more. And also with a magnetic field, at the same CIP volume percentages, the strength of the MRE increased that led to the fatigue life of MRE increasing.

During the E5 engine durability test, the failure happens in cast iron cylinder head. This is characterized as low cycle fatigue. The macro-scale cracks initiate and propagate in valve bridge region. The present investigation focuses on simulating durability test and evaluating low cycle fatigue life of the failed part. The simulation includes one pre-step as a determination of material grid and three steps as fluid, structural and fatigue analyses. In order to cover the durability test, the analysis steps are repeated at five crack speeds, 750, 1650, 2075, 2350, and 2600 rpm. The cylinder head is subjected to cyclic multi-axial variable amplitude loads. In fatigue analysis, critical plane and cumulative damage theories are utilized in order to predict fatigue life. A general script is developed and validated so as to calculate fatigue life in the whole model. The numerical results also show that the failure of critical cylinder head can be characterized as low cycle fatigue. The valve bridge region, in which high temperature exists during engine operation, is the critical area in fatigue analysis approach. The simulation results are in a good agreement with the durability test observations.

Targeted investigation of the impact fracture performance of PVB laminated glass, which is a combined analytical and numerical method for impact dynamics prediction, is presented. In this method, the relationship between the impact force and the post-cracking response of laminated glass is developed in the framework of impact dynamics to present a prediction formulation. The formulation is utilized to be applied to predict vehicle impact speed based on the crack patterns propagated on the automotive laminated glass due to the pedestrian head impact. To prepare a numerical set-up, an automotive laminated glass finite element model is proposed by inserting cohesive elements on all common surfaces of glass layers and glass-PVB interfacial. The prediction model is validated well by comparison with numerical crash patterns and ten real vehicle–pedestrian accident cases.

This paper reports a robotic laparoscopic surgery system performing electro-surgery on porcine cadaver kidney, and evaluates its accuracy in an open loop control scheme to conduct targeting and cutting tasks guided by a novel 3D endoscope. We describe the design and integration of the novel laparoscopic imaging system that is capable of reconstructing the surgical field using structured light. A targeting task is first performed to determine the average positioning error of the system as guided by the laparoscopic camera. The imaging system is then used to reconstruct the surface of a porcine cadaver kidney, and generate a cutting trajectory with consistent depth. The paper concludes by using the robotic system in open loop control to cut this trajectory using a multi degree of freedom electro-surgical tool. It is demonstrated that for a cutting depth of 3 mm, the robotic surgical system follows the trajectory with an average depth of 2.44 mm and standard deviation of 0.34 mm. The average positional accuracy of the system was 2.74±0.99 mm.

General point load weight function for semi-elliptical crack in finite thickness plates is derived. It is used to calculate stress intensity factors for any point along the crack front with the crack faces under two dimensional stress distributions. The comparison between the results obtained from the derived weight function and those available in literature is presented, indicating a good accuracy. In order to determine the pattern of crack growth, and to estimate fatigue life, this weight function can be easily used in plates as applied in industry under complicated stress fields such as residual stress field due to welding.

This paper presents effects of boundary conditions and axial loading on frequency characteristics of rotating laminated conical shells with meridional and circumferential stiffeners, i.e., stringers and rings, using Generalized Differential Quadrature Method (GDQM). Hamilton's principle is applied when the stiffeners are treated as discrete elements. The conical shells are stiffened at uniform intervals and it is assumed that the stiffeners have similar material and geometric properties. Equations of motion as well as equations of the boundary condition are transformed into a set of algebraic equations by applying the GDQM. Obtained results discuss the effects of parameters such as rotating velocities, depth to width ratios of the stiffeners, number of stiffeners, cone angles, and boundary conditions on natural frequency of the shell. The results will then be compared with those of other published works particularly with a non-stiffened conical shell and a special case where angle of the stiffened conical shell approaches zero, i.e. a stiffened cylindrical shell. In addition, another comparison is made with present FE method for a non-rotating stiffened conical shell. These comparisons confirm reliability of the present work as a measure to approximate solutions to the problem of rotating stiffened conical shells.

The rapid and sway-less conveyance of crane loads has been an essential task and a field of research; considering the broad application of transportation of goods and materials by these systems. In this paper, a neural network self tuner (NNST) controller, which aims to move the load precisely as well as to eliminate its sway, is presented. This controller is capable of being trained flexibly for either increasing the speed of load transportation or decreasing its sway. The developed training algorithm, in this paper, is inspired by a sway elimination method of input shapers. The proposed training method provides the controller with the capability to remove the majority of load sway, at the outset of transportation, and transport it with a slight sway. The results show that the neural network controller with the proposed training method, in the same time, is capable of removing the sway of the load in a better way and be more appropriate for longer distances compared to a proportional-integral-derivative controller with constant gain. Besides, compared to standard input shapers, the NNST controller is more robust to cable length variations as well as length uncertainty by utilizing the feedback. Using a lab scale gantry crane model, the feasibility of empirical implementation is proved and results are verified.