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Gas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.

In this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.

This paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.

The analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

A free trade area (FTA) is the designated economic area where bilateral trades between membership nations are tax-free. An FTA provides an important knowledge-sharing platform across cultures. Most studies discuss FTA issues from the perspectives of economics and international law. However, this study aims to analyse the challenges and opportunities relating to FTAs from a novel, integrative perspective of culture and knowledge management.

This study used a single-case study design to investigate the Sino-Vietnam bilateral trade conditions in the FTA of the Regional Economic Comprehensive Partnership. Semi-structured interviews were conducted in Yunnan province, China, with government officials and firm managers involved in Sino-Vietnam trade.

This study identifies three major challenges in the China-Vietnam case: the existence of a knowledge iceberg, the lack of deep mutual trust and the inconsistency of bilateral port policies. This study identifies three possible solutions to these challenges: creating different communication channels for knowledge sharing, building mutual trust and respect for knowledge sharing and reducing inconsistencies in the two border gate management systems.

Considering cross-cultural knowledge sharing, this study provides new insight and feasible guidance for better cooperation of member countries of FTAs all over the world.

This research is novel because it considers the FTA as a knowledge-sharing platform where the intersection of diverse cultural values and judgement may result in a variety of knowledge icebergs. Thus, this study enriches the FTA research by focussing on the intersection of culture and knowledge management.

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique. Based on the unique functions of TMS, it has been widely used in clinical, scientific research and other fields. Nowadays, the robot-assisted automatic TMS has become the trend. In order to simplify the operation procedures of robotic TMS and reduce the costs, the purpose of this paper is to apply the marker-based augmented-reality technology to robotic TMS system.

By using the marker of ARToolKitPlus library and monocular camera, the patient’s head is positioned in real time. Furthermore, the force control is applied to keep contact between the coil and subject’s head.

The authors fuse with visual positioning which is based on augmented-reality and force-control technologies to track the movements of the patient’s head, bring the coil closer to the stimulation site and increase treatment effects. Experimental results indicate that the trajectory tracking control of robotic TMS system designed in this paper is practical and flexible.

This paper provides a trajectory tracking control method for the robotic TMS. The marker-based augmented-reality technology is implemented which simplifies the operation procedures of robotic TMS as well as reduce the costs. During the treatment process, the patients would wear an AR glasses, which can help patients relax through virtual scenes and reduce the uncomfortableness produce by treatment.

Multiple-source disturbances exist in the polarization sensor, which severely affect the sensor accuracy and stability. Hence, the disturbance analysis plays a vital role in improving the sensor orientation performance. This paper aims to present a novel sensor error model, a disturbances quantitative analysis, a calibration and performance test of polarization sensor based on a polarizing beam splitter.

By combining with the sensor coefficient errors, the Azimuth of Polarization (AoP) error model and the Degree of Polarization (DoP) error model are established, respectively. In addition, the multiple-source disturbances are classified, while the influence on the orientation accuracy is quantitative analyzed. Moreover, the least square optimization algorithm is employed to calibrate the sensor coefficients. Finally, an outdoor test is carried out to test the sensor long-term accuracy.

The theoretical analysis and numerical simulations illustrate that the sensor accuracy is closely related to the disturbances. To eliminate the influence of the disturbances, the least square optimization algorithm, which can minimize the sum of squares of the residual difference of AoP and DoP, is used to calibrate the sensor coefficients. The outdoor test indicates that the sensor can maintain long-term accuracy and stability.

The main contribution of this paper is to establish a novel sensor error model, where the sensor coefficient errors are introduced. In addition, the disturbances are classified and analyzed to evaluate the orientation accuracy of the sensor.

The purpose of this paper is to investigate the effect of pulsed magnetic field (PMF) with different duty cycles on the melt flow and heat transfer behaviors during direct-chill (DC) casting of large-size magnesium alloy billet and find the appropriate range of duty cycle.

A transient two-dimensional mathematical model coupled electromagnetic field, flow field and thermal field, is conducted to study the melt flow and temperature field under PMF and compared with that under the harmonic magnetic field.

The results reveal that melt vibration and fluctuation are generated due to the instantaneous impact of repeated thrust and pull effects of Lorentz force under PMF. The peak of Lorentz force decreases greatly with the increasing duty cycle, but the melt fluctuation region is expanded with higher duty cycle, which accelerates the interior melt velocity and reduces the temperature gradient at the liquid-solid interface. However, PMF with overly high duty cycle has adverse effect on the melt convection and limited influence on the interior melt. A duty cycle of 20% to 50% is a reasonable range.

This paper can provide guiding significance for the setting of duty cycle parameters on DC casting under PMF.

There are few reports on the effect of PMF parameters during DC casting with applying PMF, especially for duty cycle, a parameter unique to PMF. The findings will be helpful for applying the external field of PMF on DC casting.

Assessing the failure probability of engineering structures is still a challenging task in the presence of various uncertainties due to the involvement of expensive-to-evaluate computational models. The traditional simulation-based approaches require tremendous computational effort, especially when the failure probability is small. Thus, the use of more efficient surrogate modeling techniques to emulate the true performance function has gained increasingly more attention and application in recent years. In this paper, an active learning method based on a Kriging model is proposed to estimate the failure probability with high efficiency and accuracy.

To effectively identify informative samples for the enrichment of the design of experiments, a set of new learning functions is proposed. These learning functions are successfully incorporated into a sampling scheme, where the candidate samples for the enrichment are uniformly distributed in the n-dimensional hypersphere with an iteratively updated radius. To further improve the computational efficiency, a parallelization strategy that enables the proposed algorithm to select multiple sample points in each iteration is presented by introducing the K-means clustering algorithm. Hence, the proposed method is referred to as the adaptive Kriging method based on K-means clustering and sampling in n-Ball (AK-KBⁿ).

The performance of AK-KBⁿ is evaluated through several numerical examples. According to the generated results, all the proposed learning functions are capable of guiding the search toward sample points close to the LSS in the critical region and result in a converged Kriging model that perfectly matches the true one in the regions of interest. The AK-KBⁿ method is demonstrated to be well suited for structural reliability analysis and a very good performance is observed in the investigated examples.

In this study, the statistical information of Kriging prediction, the relative contribution of the sample points to the failure probability and the distances between the candidate samples and the existing ones are all integrated into the proposed learning functions, which enables effective selection of informative samples for updating the Kriging model. Moreover, the number of required iterations is reduced by introducing the parallel computing strategy, which can dramatically alleviate the computation cost when time demanding numerical models are involved in the analysis.

This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment.

First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems.

The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller.

A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.

This paper aims to search the optimum content of Ni on the microstructure, phase and electrochemical behavior of high-strength low alloy (HSLA) steel in the 3.5 wt.% NaCl solution.

The microstructure and corrosion resistance of Ni-containing HSLA steel in the simulated marine environment was studied by optical microscopy, scanning electron microscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and electrochemical techniques.

The sample containing 3.55 wt.% of nickel exhibited a finer grain size of 10 μm and a lower i_corr of 2.169 µA cm⁻². The XRD patterns showed that the Fe-Cr-Ni solid solution, FeC and Cr₃C₂ were observed in samples when Ni was added. Besides, the 3.55 wt.% of nickel addition enhanced the charge transfer resistance of the low alloy steel which suggested the sample possessed excellent inhibition of electrochemical reaction and corrosion resistance. The XPS spectrum suggested that nickel was beneficial to improve the corrosion resistance of steel by forming protective oxides, and the ratio of Fe²⁺/Fe³⁺ in protective oxides was increased.

Finding the comprehensive performance of HSLA steel which can be applied to unmanned surface vehicles in marine operations.

This study has a guiding significance for optimizing the composition of HSLA steel in a Cl- containing environment.

The purpose of this paper is to provide additive manufacturing-based solutions for preparation of elastomeric foam with broaden compressive stress plateau.

Mechanic models are developed for obtaining designs of foam cell units with enhanced elastic buckling. An experimental approach is taken to fabricate the foams based on direct ink writing technique. Experimental and simulation data are collected to assist understanding of our proposals and solutions.

A simple tetragonal structured elastomeric foam is proposed and fabricated by direct ink writing, in which its cell unit is theoretically designed by repeating every four filament layers. The foam exhibits a broader stress plateau, because of the pronounced elastic buckling under compressive loading as predicted by the authors’ mechanic modeling. A two-stage stress plateaus as observed in the foam, being attributed to the dual elastic buckling of the cell units along two lateral directions of the XY plane during compression.

Future work should incorporate more microscopic parameters to tune the elastomeric foam for mechanic performance testing on linear elastic deformation and densification of polymer matrix.

Additive manufacturing offers an alternative to fabricate elastomeric foam with controlled cell unit design and therefore mechanics. Our results comment on its broad space for development such superior cushioning or damping material in the fields of vibration and energy absorption.

This work has contributed to new knowledge on preparation of high performance elastomeric foam by providing a better understanding on its cell structure, being printed using direct ink writing machines.