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This paper aims to explore the influence of corrosion-deformation interactions (CDI) on the corrosion behavior and mechanisms of 316LN under applied tensile stresses.

Corrosion of metals would be aggravated by CDI under applied stress. Notably, the presence of nitrogen in 316LN austenitic stainless steel (SS) would enhance the corrosion resistance compared to the nitrogen-absent 316L SS. To clarify the CDI behaviors, electrochemical corrosion experiments were performed on 316LN specimens under different applied stress levels. Complementary analyses, including three-dimensional morphological examinations by KH-7700 digital microscope and scanning electron microscopy coupled with energy dispersive spectroscopy, were conducted to investigate the macroscopic and microscopic corrosion morphology and to characterize the composition of corrosion products within pits. Furthermore, ion chromatography was used to analyze the solution composition variations after immersion corrosion tests of 316LN in a 6 wt.% FeCl₃ solution compared to original FeCl₃ solution. Electrochemical experiment results revealed the linear decrease in free corrosion potential with increasing applied stress. Electrochemical impedance spectroscopy results indicated that high tensile stress level damaged the integrity of passivation film, as evidenced by the remarkable reduction in electrochemical impedance. Ion chromatography analyses proved the concentrations increase of NO₃⁻ and NH₄⁺ ion concentrations in the corrosion media after corrosion tests.

The enhanced corrosion resistance of 316LN SS is attributable to the presence of nitrogen.

The scope of this study is confined to the influence of tensile stress on the electrochemical corrosion of 316LN at ambient temperatures; it does not encompass the potential effects of elevated temperatures or compressive stress.

The resistance to stress electrochemical corrosion in SS may be enhanced through nitrogen alloying.

This paper presents a systematic investigation into the stress electrochemical corrosion of 316LN, marking the inaugural study of its impact on corrosion behaviors and underlying mechanisms.

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.

In this paper, a three-dimensional size-dependent constitutive model of SMP Timoshenko micro-beam is developed to describe the micromechanical properties.

According to the Hamilton's principle, the equilibrium equations and boundary conditions of the model are established and according to the modified couple stress theory, the model is available to capturing the size effect because of the material length scale parameter. Based on the model, the simply supported beam was taken for example to be solved and simulated.

Results show that the size effect of SMP micro-beam is more obvious when the dimensionless beam height is similar or the larger of the value of loading time. The rigidity and strength of the SMP beam decrease with the increasing of the dimensionless beam height or the loading time. The viscous property of SMP micro-beam plays a more important role with the larger dimensionless beam height. And the smaller the dimensionless beam height is, the more obvious the shape memory effect of the SMP micro-beam is.

This work implies prediction of size-dependent thermo-mechanical behaviors of the SMP micro-beam and will provide a theoretical basis for design SMP microstructures in the field of micro/nanomechanics.

There have been limited investigations on the mechanical characteristics of tunnels supported by corrugated plate structures during fault dislocation. The authors obtained circumferential and axial deformations of the spiral corrugated pipe at various fault displacements. Lastly, the authors examined the impact of reinforced spiral stiffness and soil constraints on the support performance of corrugated plate tunnels under fault displacement.

By employing the theory of similarity ratios, the authors conducted model tests on spiral corrugated plate support using loose sand and PVC (polyvinyl chloride) spiral corrugated PE pipes for cross-fault tunnels. Subsequently, the soil spring coefficient for tunnel–soil interaction was determined in accordance with ASCE (American Society of Civil Engineers) specifications. Numerical simulations were performed on spiral corrugated pipes with fault dislocation, and the results were compared with the experimental data, enabling the determination of the variation pattern of the soil spring coefficient.

The findings indicate that the maximum axial tensile and compressive strains occur on both sides of the fault. As the reinforced spiral stiffness reaches a certain threshold, the deformation of the corrugated plate tunnel and the maximum fault displacement stabilize. Furthermore, a stronger soil constraint leads to a lower maximum fault displacement that the tunnel can withstand.

In this study, the calculation formula for density similarity ratio cannot be taken into account due to the limitations of the helical corrugated tube process and the focus on the deformation pattern of helical corrugated tubes under fault action.

This study provides a basis for the mechanical properties of helical corrugated tube tunnels under fault misalignment and offers optimization solutions.

This paper aims to realize the automatic assembly process for multiple rigid peg-in-hole components.

This paper develops fuzzy force control strategies for the rigid dual peg-in-hole assembly. Firstly the fuzzy force control strategies are presented. Secondly the contact states and contact forces are analyzed to prove the availability of the force control strategies.

The rigid dual peg-in-hole assembly experimental results show the effectiveness of the control strategies.

This paper proposes fuzzy force control strategies for a rigid dual peg-in-hole assembly task.

The purpose of this paper is to describe a calibration method developed to improve the accuracy of a six degrees-of-freedom medical robot. The proposed calibration approach aims to enhance the robot’s accuracy in a specific target workspace. A comparison of five observability indices is also done to choose the most appropriate calibration robot configurations.

The calibration method is based on the forward kinematic approach, which uses a nonlinear optimization model. The used experimental data are 84 end-effector positions, which are measured using a laser tracker. The calibration configurations are chosen through an observability analysis, while the validation after calibration is carried out in 336 positions within the target workspace.

Simulations allowed finding the most appropriate observability index for choosing the optimal calibration configurations. They also showed the ability of our calibration model to identify most of the considered robot’s parameters, despite measurement errors. Experimental tests confirmed the simulation findings and showed that the robot’s mean position error is reduced from 3.992 mm before calibration to 0.387 mm after, and the maximum error is reduced from 5.957 to 0.851 mm.

This paper presents a calibration method which makes it possible to accurately identify the kinematic errors for a novel medical robot. In addition, this paper presents a comparison between the five observability indices proposed in the literature. The proposed method might be applied to any industrial or medical robot similar to the robot studied in this paper.

Installing a tight tolerant stepped shaft is not a trivial task for an industrial robot. If all peg-hole constraints are complete, the cascaded peg-in-hole task can be simplified into several independent stages and accomplished one by one. However, if some of the constraints are incomplete, the cross stage interference will bring additional difficulties. This paper aims to discuss the cascaded peg-in-hole problem with incomplete constraints.

In this paper, the problem is formulated according to geometric parameters of the stepped shaft and completeness of the corresponding hole. The possible jamming type is modeled and analyzed. A contact modeling and control strategy is proposed to compensate the peg postures under incomplete constraints.

The above methods are implemented on an experiment platform and the results verify the effectiveness of the proposed robotic assembly strategy.

Based on force/torque sensor, a hybrid control strategy for incomplete constraints cascaded peg-in-hole assembly problem is proposed.

The purpose of this paper is to develop a dual peg-in-hole insertion strategy. Dual peg-in-hole insertion is the most common task in manufacturing. Most of the previous work develop the insertion strategy in a two- or three-dimensional space, in which they suppose the initial yaw angle is zero and only concern the roll and pitch angles. However, in some case, the yaw angle could not be ignored due to the pose uncertainty of the peg on the gripper. Therefore, there is a need to design the insertion strategy in a higher-dimensional configuration space.

In this paper, the authors handle the insertion problem by converting it into several sub-problems based on the attractive region formed by the constraints. The existence of the attractive region in the high-dimensional configuration space is first discussed. Then, the construction of the high-dimensional attractive region with its sub-attractive region in the low-dimensional space is proposed. Therefore, the robotic insertion strategy can be designed in the subspace to eliminate some uncertainties between the dual pegs and dual holes.

Dual peg-in-hole insertion is realized without using of force sensors. The proposed strategy is also used to demonstrate the precision dual peg-in-hole insertion, where the clearance between the dual-peg and dual-hole is about 0.02 mm.

The sensor-less insertion strategy will not increase the cost of the assembly system and also can be used in the dual peg-in-hole insertion.

The theoretical and experimental analyses for dual peg-in-hole insertion are proposed without using of force sensor.

This study aims to fabricate a cool phthalocyanine green/TiO₂ composite pigment (PGT) with high near-infrared (NIR) reflectance, good color performance and good heat-shielding performance under sunlight and infrared irradiation.

With the help of anionic and cationic polyelectrolytes, the PGT composite pigment was prepared using a layer-by-layer assembly method under wet ball milling. Based on the light reflectance properties and color performance tested by ultraviolet-visible-NIR spectrophotometer and colorimeter, the preparation conditions were optimized and the properties of PGT pigment with different assembly layers (PGT-1, PGT-3, PGT-5 and PGT-7) were compared. In addition, their heat-shielding performance was evaluated and compared by temperature rise value for their coating under sunlight and infrared irradiation.

The PGT pigment had a core/shell structure, and the PG thickness increased with the self-assembly layers, which made the PGT-3 and PGT-7 pigment show higher color purity and saturation than PGT-1 pigment. In addition, the PGT-3 and PGT-7 pigment showed 11%–16% lower light reflectance in the visible region. However, their light reflectance in the NIR region was similar. Under infrared irradiation the PGT-5 and PGT-7 pigment coating showed 1.1°C–3.4°C and 1.3°C–4.7°C lower temperature rise value than PGT-1 pigment coating and physical mixture pigment coating, respectively. And under sunlight the PGT-3 pigment coating showed 1.5–2.6°C lower temperature rise value than the physical mixture pigment coating.

The layer-by-layer assembling makes the core/shell PGT composite pigment possess low visible light reflectance, high NIR reflectance and good heat-shielding performance.

In this paper, the authors aim to propose a method for learning robotic assembly sequences, where precedence constraints and object relative size and location constraints can be learned by demonstration and autonomous robot exploration.

To successfully plan the operations involved in assembly tasks, the planner needs to know the constraints of the desired task. In this paper, the authors propose a methodology for learning such constraints by demonstration and autonomous exploration. The learning of precedence constraints and object relative size and location constraints, which are needed to construct a planner for automated assembly, were investigated. In the developed system, the learning of symbolic constraints is integrated with low-level control algorithms, which is essential to enable active robot learning.

The authors demonstrated that the proposed reasoning algorithms can be used to learn previously unknown assembly constraints that are needed to implement a planner for automated assembly. Cranfield benchmark, which is a standardized benchmark for testing algorithms for robot assembly, was used to evaluate the proposed approaches. The authors evaluated the learning performance both in simulation and on a real robot.

The authors' approach reduces the amount of programming that is needed to set up new assembly cells and consequently the overall set up time when new products are introduced into the workcell.

In this paper, the authors propose a new approach for learning assembly constraints based on programming by demonstration and active robot exploration to reduce the computational complexity of the underlying search problems. The authors developed algorithms for success/failure detection of assembly operations based on the comparison of expected signals (forces and torques, positions and orientations of the assembly parts) with the actual signals sensed by a robot. In this manner, all precedence and object size and location constraints can be learned, thereby providing the necessary input for the optimal planning of the entire assembly process.