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The aim of the paper is to propose a global, automated and continuous curvature calibration strategy for bending sensors, which is used for the angle feedback control of soft fingers.

In this work, the proposed curvature calibration strategy for bending sensors is based on the constant curvature bending properties of soft fingers. The strategy is to install the bending sensor on the soft finger and use the laser distance sensor to assist calibration, then calculate the relationship between the curvature and the voltage of the bending sensor through geometric conversion. In addition, this work also develops a full set of standard calibration systems and collection procedures for the bending sensor curvature calibration and uses machine learning algorithms to fit the collected data.

First, compared with the traditional calibration methods, the proposed curvature calibration strategy can achieve constant curvature measurement with the advantages of better continuity. Second, using the sensor data obtained by the proposed calibration method as the feedback signal for the soft finger bending angle control, the control effect is better than that of the traditional method.

This work proposes and verifies a global, automated and continuous curvature calibration strategy for bending sensors and is used for the angle feedback control of soft fingers. In addition, this work also develops a full set of standard calibration systems and collection procedures, which can be applied to a variety of flexible bending sensors with a good adaptability.

A numerical study on the stretching of a Newtonian fluid filament is analysed. Stretching is performed between two retracting plates, moving under constant extension rate. A semi‐implicit Taylor‐Galerkin/pressure‐correction finite element formulation is employed on variable‐structure triangular meshes. Stability and accuracy of the scheme is maintained up to large Hencky‐strain levels. A non‐uniform radius profile, minimum at the filament mid‐plane, is observed along the filament‐length at all times. We have found maintenance of a suitable mesh aspect‐ratio around the mid‐plane region (maximum stretch zone) to restrict early filament break‐up and consequently solution divergence. As such, true transient flow evolution is traced and the numerical results bear close agreement with the literature.

Describes the importance of plastic payment cards at the point of sale (POS) and the evolution of the credit card in general and affinity cards in particular. Suggests reasons for both the growth of plastic card payments (the cashless society) and the threats to affinity cards (the interchange fee). Places the affinity credit card within the paradigm of relationship marketing and emphasises the triadic nature of these relationships. Discusses the development of the research into affinity credit cards and the issues of branding and trust that impact upon the triadic relationships. Explores the potential for affinity marketing and reports on research into trust and ethics which is relevant to this concept. Places affinity marketing within the retail arena and finally draws conclusions on the future for payments at the POS, relationships operationalised via plastic cards and triadic affinities.

In any machining process, the surface profile of the workpiece is continuously changing with respect to time and input parameters. In a conventional machining process, input parameters are feed and depth of cut whilst other parameters are considered to be constant throughout the process.

The direct and indirect participation of this instantaneous curvature can be used to optimize the strategy of cutting operation in terms of different parameters like heat generation-induced stresses, etc. The concepts of the metric tensor and Riemannian curvature tensor are made use in this study as a representation of curvature itself. The objective of this study is to create a mathematical methodology that can be implemented on a highly flexible machining process to find an optimum cutting strategy for a particular output parameter.

The study also includes different case studies for the validation of this newly introduced mathematical methodology.

The study will also find its position in other mechanical processes like forging and casting where instantaneous curvature affects various mechanical properties.

Laser powder bed fusion (LPBF) provides the means to produce unique components with almost no restriction on geometry in an extremely short time. However, the high-temperature gradient and high cooling rate produced during the fabrication process result in residual stress, which may prompt part warpage, cracks or even baseplate separation. Accordingly, an appropriate selection of the LPBF processing parameters is essential to ensure the quality of the built part. This study, thus, aims to develop an integrated simulation framework consisting of a single-track heat transfer model and a modified inherent shrinkage method model for predicting the curvature of an Inconel 718 cantilever beam produced using the LPBF process.

The simulation results for the curvature of the cantilever beam are calibrated via a comparison with the experimental observations. It is shown that the calibration factor required to drive the simulation results toward the experimental measurements has the same value for all settings of the laser power and scanning speed. Representative combinations of the laser power and scanning speed are, thus, chosen using the circle packing design method and supplied as inputs to the validated simulation framework to predict the corresponding cantilever beam curvature and density. The simulation results are then used to train artificial neural network models to predict the curvature and solid cooling rate of the cantilever beam for any combination of the laser power and scanning speed within the input design space. The resulting processing maps are screened in accordance with three quality criteria, namely, the part density, the radius of curvature and the solid cooling rate, to determine the optimal processing parameters for the LPBF process.

It is shown that the parameters lying within the optimal region of the processing map reduce the curvature of the cantilever beam by 17.9% and improve the density by as much as 99.97%.

The present study proposes a computational framework, which could find the parameters that not only yield the lowest distortion but also produce fully dense components in the LPBF process.

When manufacturing an arc-shaped tube product using push bending process, the transition zone and outfeed zone will inevitably occur. Transition zone and outfeed zone are caused by the kinematical motion of mobile tools. The existence of transition zone and outfeed zone will lead to a big deviation between the forming product and desired shape. To improve the forming quality of arc-shaped products in push bending, the transition zone and outfeed zone are investigated in this paper.

A piecewise function is used to describe the bending characteristics along bending line, in which a series of vibration parameters are extracted and considered as control values.

The new strategy is helpful for finding the relationship between tools motion and curvature distribution and improving the bending lines design procedure in flexible push bending.

The new strategy is helpful for finding the relationship between tools motion and curvature distribution and improving the bending lines design procedure in flexible push bending.

When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise, into idealized geometrical entities. As an engineering application, wheel-rail contact interactions are fundamental in the dynamic modeling of railway vehicles. Many approaches used to solve the contact problem require a continuous parametric description of the geometries involved. However, measured wheel and rail profiles are often available as sets of discrete points. A reconstruction method is needed to transform discrete data into a continuous geometry.

The authors present an approximation method based on optimization to solve the problem of fitting a set of points with an arc spline. It consists of an initial guess based on a curvature function estimated from the data, followed by a least-squares optimization to improve the approximation. The authors also present a segmentation scheme that allows the method to increment the number of segments of the spline, trying to keep it at a minimal value, to satisfy a given error tolerance.

The paper provides a better understanding of arc splines and how they can be deformed. Examples with parametric curves and slightly noisy data from realistic wheel and rail profiles show that the approach is successful.

The developed methods have theoretical value. Furthermore, they have practical value since the approximation approach is better suited to deal with the reconstruction of wheel/rail profiles than interpolation, which most methods use to some degree.

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

This paper aims to present a shape sensing method and feedback control strategy based on fiber Bragg grating (FBG) sensor to improve the control accuracy of the robot and ensure the safety of the cardiac interventional surgery.

To theoretically describe the shape of the catheter robot, the kinematic model is established by the geometric analysis method. And to obtain the actual shape, a large curvature assemble sensor based on FBG is adopted and a novel simple shape reconstruction model is proposed, which can provide the shape curve and distal position. In addition, the influence of external load on the bending deformation is investigated by experiments. To improve the shape accuracy of the robot, a shape feedback control method is presented to control the catheter robot, which can control the robot to bend into the pre-given desired shape.

Experiment results verify the effectiveness of the shape sensing method and the reconstruction model, and the correlation coefficients of three sets of curve in different coordinate directions are 0.9986, 0.9992 and 0.9999. Results of the shape feedback experiment show that the curvature error and direction angle error are 1.42% and 10.3%, respectively. The continuum catheter robot can be controlled to achieve the desired bending shape.

The shape reconstruction method and feedback control strategy proposed in this paper can improve the control accuracy of the robot to avoid the risk of the collision with the surrounding blood vessels, the tissues and organs.

This study investigates a forecasting power of volatility curvatures and risk neutral densities implicit in KOSPI 200 option prices by analyzing minute by minute historical index option intraday trading data from January of 2007 to January of 2011. We begin by estimating implied volatility functions and risk neutral price densities based on non-parametric method every minute and by calculating volatility curvature and skewness premium. We then compare the daily rate of return of the signal following trading strategy that we buy (sell) a stock index when the volatility curvature or skewness premium increases (decreases) with that of an intraday buy-and-hold strategy that we buy a stock index on 9:05AM and sell it on 2:50PM. We found that the rate of return of the signal following trading strategy was significantly higher than that of the intraday buy-and-hold strategy, which implies that the option prices have a strong forecasting power on the direction of stock market. Another finding is that the information contents of option prices disappear after three or four minutes.