Real Joint Research Articles

Influences of Weld Nugget Shape and Material Gradient on the Shear Strength of Resistance Spot‐Welded Joints

Resistance spot‐welded joints containing press‐hardened steels are seen to exhibit a fracture mode called total dome failure, where the weld nugget completely separates from one steel sheet along the weld nugget edge. The effect of weld nugget shape and material property gradients is studied based on damage mechanics modeling and experimental validation to shed light on the underlying influencing factors. For a three‐steel‐sheet spot‐welded joint combining DP600 (1.5 mm)–CR1900T (1.0 mm)–CR1900T (1.0 mm), experiments under shear loading reveal that fracture occurs in the DP600 sheet along the weld nugget edge. In subsequent numerical simulation studies with damage mechanics models whose parameters are independently calibrated for every involved material configuration, three variations of the geometrical joint configuration are considered—an approximation of the real joint, one variation with a steeper weld nugget shape, and one variation with a less pronounced gradient between weld nugget material and heat‐affected zone material properties. The results of the finite‐element simulations show that a shallower weld nugget and a more pronounced material gradient lead to a faster increase of plastic strain at the edge of the weld nugget and promote the occurrence of total dome failure.

Computer-Assisted Modeling of Greater Tubercle Transposition Effect on Stress Distribution in Shoulder

Background. The aim of the work was to investigate the influence of the position of a fractured greater tubercle of the humerus on stress distribution in the glenohumeral joint (GHJ) at shoulder abduction by performing stress-strain analysis (SSA). Material and methods. A simulated 3D model of the shoulder was constructed on the basis of anatomical and anthropometric data as close as possible to real ones using the SolidWorks software package.Results. A finite-element model (FEM) was generated in a semi-automatic mode composed mostly of tetrahedral and hexagonal elements < 1 mm in dimensions.Conclusion. The simulated 3D model of the shoulder, based on anatomical and anthropometric data as close as possible to the real ones, makes possible highly accurate determination of the optimal mutual position of the movable elements of the real joint individually for each specific patient, and makes it possible to accurately perform a minimally invasive surgical operation.

Thread-Embedded-in-PDMS Wearable Strain Sensor for Real-Time Monitoring of Human Joint Motion.

Real-time monitoring of human joint motion holds paramount importance in assessing joint health status, preventing and treating joint diseases, and evaluating physical flexibility and coordination. However, traditional strain sensors face limitations in meeting the substantial strain requirements associated with human joint motion. Recently, there has been considerable attention directed towards flexible strain sensors prepared using pliable substrates combined with silk and cotton fabrics. Nonetheless, these sensors exhibit insufficient linearity across the entire measurement range, thereby compromising the predictability of real joint motion based on the output signal. This paper introduced a flexible strain sensor designed to address this issue by offering an enhanced range and high linearity. Specifically, the core wire of the strain sensor was produced by coating a polybutylene terephthalate thread with conductive carbon ink integrated with carbon nanotubes, encapsulated in a thin layer of polydimethylsiloxane in an "S" configuration. The proposed strain sensor maintained excellent linearity within its strain range of 60%, along with advantages such as rapid response speed and robust durability. On-trial tests further affirmed the sensor's capability to effectively monitor the motion of human joints.

Nonparametric Multivariate Probability Density Forecast in Smart Grids With Deep Learning

This paper proposes a nonparametric multivariate density forecast model based on deep learning. It not only offers the whole marginal distribution of each random variable in forecasting targets, but also reveals the future correlation between them. Differing from existing multivariate density forecast models, the proposed method requires no a priori hypotheses on the forecasted joint probability distribution of forecasting targets. In addition, based on the universal approximation capability of neural networks, the real joint cumulative distribution functions of forecasting targets are well-approximated by a special positive-weighted deep neural network in the proposed method. Numerical tests from different scenarios were implemented under a comprehensive verification framework for evaluation, including the very short-term forecast of the wind speed, wind power, and the day-ahead forecast of the aggregated electricity load. Testing results corroborate the superiority of the proposed method over current multivariate density forecast models considering the accordance with reality, prediction interval width, and correlations between different random variables.

Development of productive curing processes for the manufacturing of adhesively bonded milling tools

ABSTRACT The use of adhesive bonding in the milling tool industry has been reported as advantageous, when compared with the industry’s standard, i.e. brazed joints. This work focuses on improving a previously developed jigless manufacturing process – i.e. induction pre-curing – used to produce woodworking tools. To reduce production times, two tactics were employed to accelerate the induction process. Different coil geometries, changing the magnetic field intensity, and a ferromagnetic filler, promoting internal heat generation. It was found that these methods do not improve the heating process in a significant way. Therefore, the standard alternative, i.e. full oven curing, was also tested. Using small-scale real joint specimens, the shear resistance of both curing procedures was compared. This revealed that oven curing provides two times more strength. As such, a new joint geometry was developed, to facilitate the process of oven curing full milling tools, now fabricated with fixing jigs. In conclusion, the induction heating process was deemed unfeasible, and, as such, oven curing became the recommended method. Several milling tool prototypes were manufactured and validated both in laboratory and real-world conditions, through costumer focused testing. These tests showed good tool performance and workpiece surface quality.

Eğitim Yöneticilerinin Performans Değerleme Sürecinin Değerlendirilmesi

The aim of this study is to evaluate the performance evaluation process of educational managers. Performance is defined as the fulfillment of a work according to the determined conditions and the way of behavior of employees. The concept of performance, which comes across as the efforts of employees to achieve the organization's goals, is an issue that requires systemic integrity within the organization. It is a very important situation that the operations and activities in the systems to be carried out in organizations in order to increase performance have positive consequences. The concept of performance evaluation is the indication of the importance of personnel for the organization in certain periods of time with quantitative and qualitative aspects. Valuations are the process of making a judgment about people's performance, achievements or failures during the study. Valuations are an active system that provides an opportunity for real joint work, information exchange, sharing of tasks, authority and responsibility in terms of mistakes and achievements, and educational development. Performance evaluation, also called as success evaluation; it can be defined as a vetire that provides information about the effectiveness and competence of an employer in the task he is obliged to perform, and provides the opportunity to measure and benchmark the performances he shows in this regard. Performance evaluation is to systematically analyze the strengths and weaknesses of individuals or groups related to business and direct them in the direction of the goals determined by the organization. Performance evaluation is the ability of managers to evaluate the business success of employees by making comparisons and measurements with the standards they have set before. Key Words: Education Manager, Performance, Performance Evaluation

Analysis of the Mechanical Performance and Durability of Adhesively Bonded Joints Used in the Milling Tool Industry

Epoxy adhesives, widely used in multiple structural applications, are used in the milling tool industry to replace brazing and mechanical fastening when joining the cutting bits to the tool body; though their durability is still a concern. This work aims to evaluate and characterise the effect of environmental factors associated with a tool’s life cycle on the performance of these bonded joints. A gravimetric analysis was conducted on bulk adhesive plates for water, cutting emulsion and dielectric fluid to obtain diffusion and relaxation rates. Novel real joint shear specimens were developed to enable strength testing on joints which are comparable with the final application. These specimens were immersed in fluids and subjected to thermal cycles or a corrosive finishing surface treatment to simulate the tool’s life cycle. The joint’s resistance was then benchmarked. Lastly, a dimensional variation test was carried out on tool prototypes before and after ageing, showing no significant dimensional variation which could compromise the cutting performance of the tool. Overall, though it was possible to identify a decrease in strength of around 20% in most tests, joint strength was still within the values necessary for safe operation, with a large safety factor still being retained.

Mirror-Descent Inverse Kinematics with Box-constrained Joint Space⋆

To control humanoid robots, the reference pose of end effector(s) is planned in task space, then mapped into the reference joints by IK. By viewing that problem as approximate quadratic programming (QP), recent QP solvers can be applied to solve it precisely, but iterative numerical IK solvers based on Jacobian are still in high demand due to their low computational cost. However, the conventional Jacobian-based IK usually clamps the obtained joints during iteration according to the constraints in practice, causing numerical instability due to non-smoothed objective function. To alleviate the clamping problem, this study explicitly considers the joint constraints, especially the box constraints in this paper, inside the new IK solver. Specifically, instead of clamping, a mirror descent (MD) method with box-constrained real joint space and no-constrained mirror space is integrated with the Jacobian-based IK, so-called MD-IK. In addition, to escape local optima nearly on the boundaries of constraints, a heuristic technique, called ϵ-clamping, is implemented as margin in software level. Finally, to increase convergence speed, the acceleration method for MD is integrated assuming continuity of solutions at each time. As a result, the accelerated MD-IK achieved more stable and enough fast tracking performance compared to the conventional IK solvers. The low computational cost of the proposed method mitigated the time delay until the solution is obtained in real-time humanoid gait control, achieving a more stable gait.

Influence analysis on the shear behaviour and failure mode of grout-filled jointed rock using 3D DEM coupled with the cohesive zone model

Grouting is one of the primary methods used to reinforce the strength of fractured rock masses. In this study, a three-dimensional discrete element method (3D Co-DEM) grouted joint shear model, which consists of upper and lower intact rock blocks, 3D real joint surfaces and a grout-filled layer, was developed with the cohesive zone model. The 3D real joint surface was imported into the model using 3D scanning point cloud data, and the grout-filled layer was described by a cohesive zone model. Then, a numerical simulation algorithm was developed to implement the numerical direct shear test and grout-filled layer cracking simulation. Also, the parameters of the proposed method were calibrated, and the effectiveness of the cohesive zone model and direct shear numerical test were verified by comparison with analytical and experimental results. Finally, grouted jointed specimens with regular sawtooth were used to analyse the influencing factors of shear characteristics. Numerical tests showed that shear peak strength and residual strength decrease with increasing grout water-cement ratio but increase with increasing JRC. Specifically, with increasing sawtooth inclination angle, the shear peak strength first decreases and then increases, while the peak shear strength increases as the sawtooth height increases.

CyberNSOF – A CRUCIAL FORCE MULTIPLIER IN MODERN WARFARE

Cyber security and special operations (CyberSOF) in the 21st century are constantly evolving and changing to meet today's threats. CyberSOF are constantly evolving as allied countries, strategic partners and key players in the Black Sea discover new tactics to achieve strategic objectives. So far, the one that has remained below the threshold of armed conflict by operating in the grey zone is the Russian Federation. The annexation of Crimea by the Russian Federation is the first strong indicator that CyberSOF binomial operations have been executed. The Romanian Naval Special Operations Forces community is still developing specific guidelines or responses to deter or prevent a major cyber attack on Romania and its NATO partners. This research addresses an aspect of special operations and cyber community that has yet to be explained adequately. To achieve this goal, we will describe how the symbiotic relationship between Naval Special Operations Forces and Cyber Defense Command is crucial within the national military instrument of power at the strategic level and the impact of this binomial on the operational and tactical levels of hybrid conflict can be treated as both a force multiplier and force protection generator for Naval Forces and beyond. According to the specified causes to achieve our objectives, we will present the concept of Cyber Operations and Naval Forces for Special Operations (CyberNSOF), a novel concept that can produce strategic-level effects with minimal forces. Although the two entities presented above are services in the Romanian Military, used as a binomial (CyberNSOF) in support of the supported element, will be able to be used both as force multiplier, force protection element and last but not least as forces executing pre-emptive actions to deter the enemy. Taking these recommendations into account will increase the effectiveness of SOF maritime operations with the support of cyberoperations while ensuring the transition to a robust/ real joint capability in response to any emerging existing threats.

Sim2real kinematics modeling of industrial robots based on FPGA-acceleration

It is challenging to apply robotic inverse kinematics directly in simulation to real robot motion due to the multi-configuration problem, robot end deviation, and delay. To this end, this paper proposes a industrial robot modeling method for “Simulation to Real” to obtain the real joint angle vector given real end-effector target pose . In the first stage, the joint angle in simulation corresponding to the real end-effector pose, is calculated by improved Newton–Raphson method. In the second stage, a data-driven ResNet model, which is trained on enough simulated joint angles and end-effector pose obtained in the first stage, is used to acquire the end-effector pose in simulation. The joint angles in real environment can be obtained by the simulated end-effector pose in execution stage. The experiment takes a six-axis industrial robot as a case study. The results verify the feasibility and real-time performance of the inverse kinematics method in robotic motion from simulation to real environment. • A sim2real modeling method for the kinematics of industrial robots is proposed. • An FPGA-accelerated inverse kinematics model based on iteration is built. • An FPGA-accelerated forward kinematics model in simulation based on ResNet is built.

Triaxial compression behavior of large-scale jointed coal: a numerical study

Accurate estimation of the triaxial compression behavior of jointed coal is essential for coal mining. Few studies addressed the triaxial compression behavior of large-scale rock mass, especially with real joint geometry. We employed a numerical synthetic rock mass (SRM) method to study the triaxial compression behavior of jointed coal. Jointed-coal specimens were constructed based on in-situ joint measurements and microparameter calibration against laboratory experiments. A series of triaxial compression tests under different loading orientations and confining pressures were numerically performed to obtain joint and confining-pressure effects on the triaxial compression behavior and reveal the failure mechanism of jointed coal. Results suggest that the triaxial compression behavior of the jointed coal has strong joint and confining-pressure effects. Joints weaken the strength and elastic modulus, reduce the lateral deformation, and affect the geometries of the shear-rupture surface. An increase in the confining pressure causes the peak and residual strength increase significantly. With an increase in the confining pressure, the elastic modulus increases sharply at low confining pressure, the mechanical behavior transitions from brittleness to ductility, the failure mode transitions from shear-rupture surface to plastic flow, and the joint effect diminishes and even disappears. The jointed coal fails by means of a shear-rupture surface under triaxial compression loading with a confining pressure (which is not too high), and the geometries of the shear-rupture surface vary with the distribution of joints.

You Must Have a Preference: The Impact of No-Preference Communication on Joint Decision Making

In many joint consumption decisions, such as choosing a restaurant or a movie to watch together, one party often communicates to the other that they do not have a particular preference among the options (e.g., “I have no preference,” “I’m fine with any option”). Despite their prevalence, little is known about how communications of no preference impact joint decision making and the consumption experience. Do consumers take the other party's indifference at face value? Does the decision become easier to make without one party's preference to incorporate? How will such communications ultimately impact consumption and social utility? In a series of six studies using both hypothetical and real joint consumption decisions, the authors find that recipients of no-preference communication infer that the co-consumer (i.e., the person communicating having no preferences) actually does have preferences but is not disclosing them. These perceptions of undisclosed preferences increase the decision makers’ decision difficulty and cause them to like the co-consumer less. Further, the authors find that the decision maker intuits that the co-consumer's (undisclosed) preferences are probably dissimilar to their own, which leads them to choose an option they like less and ultimately decreases their enjoyment. Interestingly, these negative effects are not anticipated by the party who communicates having no preference.

Modified power rate sliding mode control for robot manipulator based on particle swarm optimization

This work suggests an optimized improved power rate sliding mode control (PRSMC) to control a 4-degrees of freedom (DOF) manipulator in joint space as well as workspace. The proposed sliding mode control (SMC) aims to improve the reaching mode and to employ an optimization method to tune the control parameters that operate the robotic manipulator adaptively. Inverse kinematics is used to obtain the joint desired angles from the end effector desired position, while forward kinematics is used to obtain the real Cartesian position and orientation of the end effector from the real joint angles. The proposed enhancements to the SMC involve the use of the hyperbolic tangent function in the control law to improve the reaching mode. Added to that, particle swarm optimization (PSO) is used to tune the parameters of the improved SMC. Furthermore, the Lyapunov function is utilized to analyze the stability of the closed-loop system. The proposed enhanced sliding mode combined with the optimization method is applied experimentally on a 4-DOF manipulator to prove the feasibility and efficiency of the proposed controller. Finally, the performance of the suggested control scheme is compared with the conventional power rate SMC in order to demonstrate the enhanced performance of the suggested method.

Unsupervised discriminative feature learning via finding a clustering-friendly embedding space

In this paper, we propose an enhanced deep clustering network (EDCN), which is composed of a Feature Extractor, a Conditional Generator, a Discriminator and a Siamese Network. Specifically, we will utilize two kinds of generated data based on adversarial training, as well as the original data, to train the Feature Extractor for learning effective latent representations. In addition, we adopt the Siamese network to find an embedding space, where a better affinity similarity matrix is obtained as the key to success of spectral clustering in providing reliable pseudo-labels. Particularly, the obtained pseudo-labels will be used to generate realistic data by the Generator. Finally, the discriminator is used to model the real joint distribution of data and corresponding latent representations for Feature Extractor enhancement. To evaluate our proposed EDCN, we conduct extensive experiments on multiple data sets including MNIST, USPS, FRGC, CIFAR-10, STL-10, and Fashion-MNIST by comparing our method with a number of state-of-the-art deep clustering methods, and experimental results demonstrate its effectiveness and superiority.

Fabricación de modelos anatómicos articulares para formación en intervencionismo ecoguiado

IntroductionEco-guided interventionism has changed the way Physical Medicine and Rehabilitation specialists deal with musculoskeletal pain and other problems such as spasticity. The implementation of the Eco-Guided Intervention Units improves the results of the usual minimally invasive treatments in our speciality's clinical practice. The biggest drawback of this practice is the long learning curve and the difficulty of practice during training courses. ObjectiveTo develop a system of phantoms that allow the practice of interventionism in anatomical models by shortening learning times and improving certainty by achieving the objective of interventionist practice. MethodsDescribes the method of manufacturing three-dimensional models of joints with images obtained from computerized axial tomography, and their subsequent inclusion in gelatin's made molds, which allow to obtain phantoms, similar to real joint models, that allow to study using ultrasound techniques, and the practice of eco-guided interventionism. ConclusionThree-dimensional joint models made with gelatin are useful in the practice and learning of joint eco-guided interventionism techniques.

Nonlinear Stiffness of Semi-Fixed Dowel Joints in Semi-Integral Bridges

The semi-fixed dowel joint studied in this paper consists of a steel dowel with rubber sleeves and a rubber pad to connect the superstructure and the substructure and to support the main beam. This type of joint is suitably used in retrofitting a jointed bridge with high-stiffness substructure into a semi-integral bridge. This study aimed to investigate the nonlinear stiffness of the joint, which is the key parameter in the retrofitting design. Taking the real joint in a retrofitted semi-integral bridge as a prototype, tests on full-scale models were carried out, in which the wall thickness of the rubber sleeve and the thickness of the rubber pad were taken as parameters. The test results show that the wall thickness of the rubber sleeve is the main factor affecting the radial stiffness and the flexural stiffness of the semi-fixed dowel joint. With the decrease of the wall thickness of the rubber sleeve, the radial stiffness decreases while the flexural stiffness increases. However, the thickness of the rubber pad has little influence on both the radial and flexural stiffness of the joint, and its main role is only vertical loading-bearing. If the longitudinal deformation of the main beam of a bridge under maximum temperature variation is 10 mm as the allowance value of engineering design, the wall thickness of the rubber sleeve for this joint should not be less than 40 mm. At last, on the basis of experimental research and theoretical analysis, the formulas of radial stiffness and flexural stiffness are fitted; it can be used as reference for practical engineering application, or for formulation of relevant specifications.

Variational Bayesian Based IMM Robust GPS Navigation Filter

This paper investigates the navigational performance of Global Positioning System (GPS) using the variational Bayesian (VB) based robust filter with interacting multiple model (IMM) adaptation as the navigation processor. The performance of the state estimation for GPS navigation processing using the family of Kalman filter (KF) may be degraded due to the fact that in practical situations the statistics of measurement noise might change. In the proposed algorithm, the adaptivity is achieved by estimating the time-varying noise covariance matrices based on VB learning using the probabilistic approach, where in each update step, both the system state and time-varying measurement noise were recognized as random variables to be estimated. The estimation is iterated recursively at each time to approximate the real joint posterior distribution of state using the VB learning. One of the two major classical adaptive Kalman filter (AKF) approaches that have been proposed for tuning the noise covariance matrices is the multiple model adaptive estimate (MMAE). The IMM algorithm uses two or more filters to process in parallel, where each filter corresponds to a different dynamic or measurement model. The robust Huber's M-estimation-based extended Kalman filter (HEKF) algorithm integrates both merits of the Huber M-estimation methodology and EKF. The robustness is enhanced by modifying the filter update based on Huber's M-estimation method in the filtering framework. The proposed algorithm, referred to as the interactive multi-model based variational Bayesian HEKF (IMM-VBHEKF), provides an effective way for effectively handling the errors with time-varying and outlying property of non-Gaussian interference errors, such as the multipath effect. Illustrative examples are given to demonstrate the navigation performance enhancement in terms of adaptivity and robustness at the expense of acceptable additional execution time.

Study of Structural Characteristics of Asphalt Overlays on Airport Pavement with Damaged Load Transfer Efficiency of Joints

In this paper, the real joint load transfer efficiency of airport pavement is calculated by combining the results of airport pavement deflection detection and ground-penetrating radar detection. Spring elements are used to simulate the actual load transfer efficiency of joints in ABAQUS. The impact of different asphalt overlays on the stress state of the critical point in the pavement is analyzed by the airport cement concrete pavement model. The result shows that adding a thin stress-absorbing layer with fine-graded and low modulus can effectively disperse the load transferred from the asphalt pavement to the cement pavement and the stress concentration at the joint under the asphalt overlay. Compared with airport pavement without a stress-absorbing layer, the tensile stress and shear stress at the critical point in the airport pavement asphalt overlay decreased by 24.62% and 22.49%, respectively. Therefore, the combination of the high-modulus upper layer and low-modulus lower layer can effectively reduce the tensile stress and shear stress at the critical point. In addition, increases in the thickness of the asphalt overlay can effectively improve the stress state at the critical point. When the thickness of the asphalt overlay changed from 13 cm to 21 cm, the maximum tensile and shear stress decreased by 8.82% and 8.92%, respectively. Finally, based on the analysis of the numerical simulation and field test verification, the optimal airport pavement asphalt overlay scheme is proposed.

The development of artificial intelligence in Brazil: emphasis on the military sphere and the questions of intellectual property

The subject of this research is the development of artificial intelligence in Brazil based on the recently adopted act “National Strategy for the Development of Artificial Intelligence” of April 2021 with an emphasis on the military sphere through the prism of legislative provisions on intellectual property, potential and needs of the country, as well as real joint projects with its foreign partner Israel in the sphere of procurement and engineering of unmanned aerial vehicles (Harpia, Elbit Hermes 900 and 450, IAI Heron). The relevance of this article is substantiated by timely consideration of the legal perspective of the approaches of Brazil towards the implementation of artificial intelligence, as multiple foreign states aim to implement the adopted strategies in this sphere. The scientific novelty consists in the following positions: artificial intelligence can be implemented in production, public safety and public authority, through ensuring the due level of the development of such crucial components as education and human resources, scientific and technology infrastructure, and business foundation, legal regulation and management, as well as taking into account international experience. At the same time, the technologies underlying artificial intelligence and machine learning – computational models, algorithms of classification, clusterization, educational, and others are not subject to patenting in Brazil (same as in the European Union), although are regarded as inventions for solution of technical issues – as the engineering applications of artificial intelligence.