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The purpose of this paper devoted to the application of modal analysis to analyze the flow structure of trailing edge cutback film cooling and the effects of vortex structure on the film cooling effectiveness of the cutback surface.

Large eddy simulation (LES) is used to simulate the trailing edge cutback film cooling. The results of LES are analyzed by proper orthogonal decomposition (POD) method and dynamic mode decomposition (DMD) method. The POD method is used to determine the dominated vortex structure and the energy level of these structures. The DMD method is used to analyze the relationship between vortex structures and wall temperature.

The POD method shows that the flow field consists of three main vortices – streamwise vortex, lip vortex and coolant vortex. The DMD results show that the lip vortex mainly acts on the middle section of the cutback surface, while the streamwise vortex mainly acts on the back section of the cutback surface.

The modal analysis is only based on numerical simulation but the modal analysis of experimental results will be further studied in the future.

This paper presents the powerful ability of the modal analysis method to study complex flows in trailing edge cutback film cooling. Establishing the relationship between vortex and wall temperature by modal analysis method can provide a new idea for studying convective heat transfer problems.

The role of streamwise vortex in the flow of the trailing edge cutback cooling and its effect on the cooling effectiveness of the cutback surface is found.

This paper aims to propose a novel method to identify the parameters of robotic manipulators using the torque exerted by the robot joint motors (measured by current sensors).

Previous studies used additional sensors like force sensor and inertia measurement unit, or additional payload mounted on the end-effector to perform parameter identification. The settings of these previous works were complicated. They could only identify part of the parameters. This paper uses the torque exerted by each joint while performing Fourier periodic excited trajectories. It divides the parameters into a linear part and a non-linear part, and uses linear least square (LLS) parameter estimation and dual-swarm-based particle swarm optimization (DPso) to compute the linear and non-linear parts, respectively.

The settings are simpler and can identify the dynamic parameters, the viscous friction coefficients and the Coulomb friction coefficients of two joints at the same time. A SIASUN 7-Axis Flexible Robot is used to experimentally validate the proposal. Comparison between the predicted torque values and ground-truth values of the joints confirms the effectiveness of the method.

The proposed method identifies two joints at the same time with satisfying precision and high efficiency. The identification errors of joints do not accumulate.

The cost-oriented robotic assembly line balancing problem (cRALBP) has practical importance in real-life manufacturing scenarios. However, only a few studies tackle the cRALBP using exact methods or metaheuristics. This paper aims to propose a hybrid particle swarm optimization (PSO) combined with dynamic programming (DPPSO) to solve cRALBP type-I.

Two different encoding schemes are presented for comparison. In the frequently used Scheme 1, a full encoding of task permutations and robot allocations is adopted, and a relatively large search space is generated. DPSO1 and DPSO2 with the full encoding scheme are developed. To reduce the search space and concern promising solution regions, in Scheme 2, only task permutations are encoded, and DP is used to obtain the optimal robot sequence for a given task permutation in a polynomial time. DPPSO is proposed.

A set of instances is generated, and the numerical experiments indicate that DPPSO achieves a tradeoff between solution quality and computation time and outperforms existing algorithms in solution quality.

The contributions of this paper are three aspects. First, two different schemes of encoding are presented, and three PSO algorithms are developed for the purpose of comparison. Second, a novel updating mechanism of discrete PSO is adjusted to generate feasible task permutations for cRALBP. Finally, a set of instances is generated based on two cost parameters, then the performances of algorithms are systematically compared.

A distributed piezoelectric actuator (DPA) improving the deformation performance of wing is proposed. As the power source of morphing wing, the factors affecting the driving performance of DPA were studied.

The DPA is composed of a substrate beam and a certain number of piezoelectric patches pasted on its upper and lower ends. Utilizing the inverse piezoelectric effect of piezoelectric material, the DPA transfers displacement to the wing skin to change its shape. According to the finite element method and piezoelectric constitutive equation, the structure model of DPA was established, and its deformation behavior was analyzed. The accuracy of algorithm was verified by comparison with previous studies.

The results show that the arrangement way, length and thickness of piezoelectric patches, the substrate beam thickness and the applied voltage are the important factors to determine the driving performance of DPA.

This paper can provide theoretical basis and calculation method for the design and application of distributed piezoelectric actuator and morphing wing.

A novel morphing wing drove by DPA is proposed to improve environmental adaptability of aircraft. As the power source achieving wing deformation, the DPA model is established by FEM. Then the factors affecting the driving performance are analyzed. The authors find the centrosymmetric arrangement way of piezoelectric patches is superior to the axisymmetric arrangement, and distribution center of the piezoelectric patches determines the driving performance.

The light detection and ranging sensor has been widely deployed in the area of simultaneous localization and mapping (SLAM) for its remarkable accuracy, but obvious drift phenomenon and large accumulated error are inevitable when using SLAM. The purpose of this study is to alleviate the accumulated error and drift phenomenon in the process of mapping.

A novel light detection and ranging SLAM system is introduced based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies conditions of loop-closed.

The proposed algorithm exhibits competitiveness compared with current approaches in terms of the accumulated error and drift distance. Further, supplementary to the place recognition process that is usually performed for loop detection, the authors introduce a novel dynamic constraint that takes into account the change in the direction of the robot throughout the total path trajectory between corresponding frames, which contributes to avoiding potential misidentifications and improving the efficiency.

The proposed system is based on Normal Distributions Transform and dynamic Scan Context with switch. The pose-graph optimization is used as back-end optimization module. The loop closure detection is only operated in the scenario, while the path satisfies condition of loop-closed.

The purpose of this paper is to investigate the effect of perceived fit on thriving and reveal the potential moderator and mediator of this effect by drawing on self-determination theory. Moreover, to adapt the research to Chinese contexts, a four-factor conceptualization of perceived fit is suggested.

The paper includes two studies. Study 1 involved a survey that collected data from 531 employees to investigate the relationship between perceived fit and thriving and the moderating role of personal goal commitment. Study 2 consisted of a scenario-based experiment in which 240 university students were recruited to strengthen the main findings of Study 1 and test the underlying mechanisms of the effect of perceived fit on thriving.

Study 1 shows that perceived fit positively relates to thriving, and personal goal commitment plays a moderating role in this effect. In addition, it demonstrates the validity of the proposed four-factor conceptualization of perceived fit in Chinese contexts. Study 2 strengthens the proposition of the positive effect of perceived fit on thriving and identifies the mediating roles of self-determination in this effect.

This paper contributes to the literature on thriving and fit by exploring new antecedents of thriving and extending the dimensions of perceived fit.

The purpose of this paper deals with a capacitated multi-item dynamic lot-sizing problem with the simultaneous sequence-dependent setup scheduling of the parallel resource under complex uncertainty.

An improved chance-constrained method is developed, in which confidence level of uncertain parameters is used to process uncertainty, and based on this, the reliability of the constraints is measured. Then, this study proposes a robust reconstruction method to transform the chance-constrained model into a deterministic model that is easy to solve, in which the robust transformation methods are used to deal with constraints with uncertainty on the right/left. Then, experimental studies using a real-world production data set provided by a gearbox synchronizer factory of an automobile supplier is carried out.

This study has demonstrated the merits of the proposed approach where the inventory of products tends to increase with the increase of confidence level. Due to a larger confidence level may result in a more strict constraint, which means that the decision-maker becomes more conservative, and thus tends to satisfy more external demands at the cost of an increase of production and stocks.

Joint decisions of production lot-sizing and scheduling widely applied in industries can effectively avert the infeasibility of lot-size decisions, caused by capacity of lot-sing alone decision and complex uncertainty such as product demand and production cost. is also challenging.

This study provides more choices for the decision-makers and can also help production planners find bottleneck resources in the production system, thus developing a more feasible and reasonable production plan in a complex uncertain environment.

The aim of this paper is to implement direct teaching of industrial manipulators using current sensors. The traditional way to implement teaching is either to use a teaching pedant, which is time consuming, or use force sensors, which increases system cost. To overcome these disadvantages, a novel method is explored in the paper by using current sensors installed at joints as torque observers.

The method uses current sensors installed at each joint of a manipulator as torque observers and estimates external forces from differences between joint-driven torque computed based on the values of current sensors and commanded values of motor-driven torque. The joint-driven torque is computed by cancelling out both pre-calibrated gravity and friction resistance (compensation). Also, to make the method robust, the paper presents a strategy to detect unexpected slowly drifts and zero external forces and stop the robot in those situations.

Experimental results demonstrated that compensating the joint torques using both pre-calibrated gravity and friction resistance has performance comparable to a force sensor installed on the end effector of a manipulator. It is possible to implement satisfying direct teaching without using force sensors on 7 degree of freedom manipulators with large mass and friction resistance.

The main contribution of the paper is that the authors cancel out both pre-calibrated gravity and friction resistance to improve the direct teaching using only current sensors; they develop methods to avoid unsafe situations like slow drifts. The method will benefit industrial manipulators, especially those with large mass and friction resistance, to realize flexible and reliable direct teaching.

The purpose of this paper is to improve the tracking performance of the tracking loops under high dynamic and severe jamming conditions.

First, as the two dominant measurement error sources of the tracking loops, the thermal noise jitter and the dynamic stress error are thoroughly analyzed. Second, a scheme of adaptive tracking loops, which could adaptively adjust the order and the bandwidth of tracking loops, is proposed. Third, real-time detections of the vehicle dynamics and the carrier-to-noise density ratio, and the adaptive bandwidth of the carrier loop are presented, respectively. Finally, simulations are operated to validate the excellent tracking performance of the adaptive tracking loops.

Based on the principle of minimizing the measurement errors, the loop order and bandwidth are adaptively adjusted in the proposed scheme. Thus, the anti-jamming capability and dynamic tracking performance of the tracking loops could be effectively enhanced.

This paper provides further study on the method of improving the tracking capability under complexly applied conditions of high dynamics and severe jamming.

The detections of carrier-to-noise density ratio and vehicle dynamics are used to adaptively adjusting the loop order and bandwidth, which could not only improve the measurement accuracy but also ensure the stable operation of tracking loops.

Recently, filling mining is becoming more and more important in the mining industry and has been used widely. In order to better control the process of paste filling mining and acquire the accurate amount of filling material used, and to reduce the waste of paste filling material, we should detect in real time the paste flow in the pipe during the process of filling. This paper introduces in detail the basic principle of ultrasonic detection technology and the hardware composition and working principle of the on-line detection system. The author uses the theory of unascertained error analysis of detecting data and implements ultrasonic detection technology to realize on-line detection of paste filling pipe flow.