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Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control algorithms to surmount an obstacle. Therefore, this paper aims to propose a new simple configuration of an all-terrain robotic vehicle with eight wheels including four-swing arms.

This vehicle is driven by distributed hydraulic motors which provide high mobility. It possesses the ability to change the posture by means of cooperation of the four-swing arms. This ensures that the vehicle can adapt to complex terrain. In this paper, the bionic mechanism, control design and steering method of the vehicle are introduced. Then, the kinematic model of the center of gravity is studied. Afterward, the obstacle surmounting performance based on a static model is analyzed. Finally, the simulation based on ADAMS and the prototype experiment is carried out.

The experiment results demonstrate that the robotic vehicle can surmount an obstacle 2.29 times the height of the wheel radius, which verifies the feasibility of this new configuration. Therefore, this vehicle has excellent uneven terrain adaptability.

This paper proposes a new configuration of an all-terrain robotic vehicle with four-swing arms. With simple mechanism and control algorithms, the vehicle has a high efficiency of surmounting an obstacle. It can surmount a vertical obstacle 2.29 times the height of the wheel radius.

The chapter summarizes key literature, including emerging ideas, that is pertinent to the question of how organizations and their leadership deal with and are resilient through crises – highlighting what works in surviving unexpected crises. The chapter presents an illustration of organizational response; it concludes with an analysis of what is missing from the literature and recommends a path forward to expanding actionable knowledge in this area. Multiple, interdependent factors that foster resilience are identified including (1) being sensitive to possible threats – even seemingly small failures, (2) not relying on simple interpretations of events but rather seeking diversity to create a complete view of the environment, (3) leadership that embraces communication, transparency, and continuous learning, (4) valuing expertise and allowing expert staff to make decisions during a crisis, and (5) a cultural commitment to a resiliency mindset that accepts failures as opportunities to learn and improve. Emerging concepts that may foster resilience but require more research include managing paradox, emotional ambivalence and diversity. Additional areas for fruitful research include: the impact of short-term versus long-term, or successive, crises; external versus internal shocks and the framing of the source of shocks; how crisis affect the pace of innovation and change; the role of diversity in organizational responses to crises; and a set of methodological opportunities to leverage natural experiments or simulations in ways that allow for longitudinal data illuminating the full cycle of crises across organizations from anticipation, to response, to longer-term adaptation to the new normal.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

The purpose of this study is to investigate structure parameters that influence the mixing process of droplets-gas in underwater depth-adjustable launcher cooling chamber and help engineers who design the launcher to distinguish the most important factor that impacts mixing performance in the cooling chamber.

Euler–Lagrangian droplet tracking method was used to simulate droplets-gas mixing process in the cooling chamber. The SST k-w model was adopted to simulate turbulence. Droplet breakup was described by KHRT hybrid model using modified contains which are more fit to the supersonic main flow condition.

The results show the counter-rotating vortex pairs which caused by injected liquid accelerate the mixing process. High-pressure supersonic freestream makes the liquid jet break into more small droplets due to the high momentum of the main stream. Axial injection angle has the greatest influence on Sauter mean diameter (SMD). Penetration height, SMD and total pressure loss slightly change in different tangential injection conditions. However, mixedness decreases with reduction of tangential injection angle due to a more limited space for spray developing. Enlarging orifice diameter raises penetration and mixedness greatly, while SMD and total pressure loss increase slightly.

The findings of this study confirm the key structure parameter to improve mixing performance in the cooling chamber. Engineers who design the underwater depth-adjustable launcher can refer the findings in this study to make control of launching power more accurate.

This paper aims to propose a framework for optimizing the pose in the assembly process of the non-ideal parts considering the manufacturing deviations and contact deformations. Furthermore, the accuracy of the method would be verified by comparing it with the other conventional methods for calculating the optimal assembly pose.

First, the surface morphology of the parts with manufacturing deviations would be modeled to obtain the skin model shapes that can characterize the specific geometric features of the part. The model can provide the basis for the subsequent contact deformation analysis. Second, the simulated non-nominal components are discretized into point cloud data, and the spatial position of the feature points is corrected. Furthermore, the evaluation index to measure the assembly quality has been established, which integrates the contact deformations and the spatial relationship of the non-nominal parts’ key feature points. Third, the improved particle swarm optimization (PSO) algorithm combined with the finite element method is applied to the process of solving the optimal pose of the assembly, and further deformation calculations are conducted based on interference detection. Finally, the feasibility of the optimal pose prediction method is verified by a case.

The proposed method has been well suited to solve the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the effectiveness of the method with an example of the shaft-hole assembly.

The method proposed in this paper has been well suited to the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the method with an example of the shaft-hole assembly.

The different surface morphology influenced by manufacturing deviations will lead to the various contact behaviors of the mating surfaces. The assembly problem for the components with complex geometry is usually accompanied by deformation due to the loading during the contact process, which may further affect the accuracy of the assembly. Traditional approaches often use worst-case methods such as tolerance offsets to analyze and optimize the assembly pose. In this paper, it is able to characterize the specific parts in detail by introducing the skin model shapes represented with the point cloud data. The dynamic changes in the parts' contact during the fitting process are also considered. Using the PSO method that takes into account the contact deformations improve the accuracy by 60.7% over the original method that uses geometric alignment alone. Moreover, it can optimize the range control of the contact to the maximum extent to prevent excessive deformations.

This paper aims to propose an optimization method to automatically adjust the spatial route of multibend pipes to meet the assembly demands in constrained space.

The compact geometric parameters that uniquely determine the pipe route are analyzed. Besides, the relationship between these parameters and the end pose is revealed based on the exponential product formula. Mathematical representations for the engineering constraints, including the end pose restriction, collision interference, manufacture ability and geometric limitations, are further established. On this basis, the adjustment of the spatial route is formulated as a multiconstraint optimization problem. A modified particle swarm optimization method based on the combination of gradient projection and swarm intelligence is designed to find the near-optimal pipe that meets the required assembly demands.

The experimental results show that the proposed method can effectively find the feasible pipe route that satisfies the engineering constraints and the end pose requirement is highly guaranteed.

The proposed method can automate the geometric adjustment of multi-bend pipes to meet the actual assembly demands, which significantly reduces manual efforts and guarantees high accuracy. The results demonstrate the possibility of further applications in the pipe assembly or design process, especially in ships, aerospace products or pressure vessels.

The purpose of this paper is to study the variations of composition and properties of the passive film on 316 L stainless steel surface in 80°C, 0.5 mol L-1 H2SO4 + 2 mg L-1 NaF solution, is helpful to understand the mechanisms of corrosion resistancethe of plated Pd on 316 L ss.

The variations of composition and properties of the passive film on 316 L stainless steel surface in 80°C, 0.5 mol L-1 H2SO4 + 2 mg L-1 NaF solution after connected to Pd electrode were studied with methods of potential monitor, X-ray photoelectron spectroscopy analysis and electrochemical impedance spectrum (EIS) measurement.

By connecting to a Pd electrode, the potential of the SS sample increased from the active region to the passive region. By connecting to the Pd electrode, the contents of Cr, Cr(OH)3 and Fe3O4 in passive film increased obviously. With increased Pd/SS area ratio, the Cr(OH)3 content in passive film increased but the Fe3O4 content changed little. The results show that after connecting to Pd the corrosion resistance of the passive film on 316 L stainless steel increases obviously, which may be attributed to the more compact passive film because of higher Cr, Cr(OH)3 and Fe3O4 contents and less point defects in the film.

The effects and mechanism of Pd on passivation of SS was studied.

The purpose of this study is to investigate the effect of the injection angle α on the spray structures of an air-blast atomizer and help enhance the understanding of droplet-gas mixing process in such atomizers in the engineering domain.

The phenomena in the air-blast atomizer were numerically modelled using the computational fluid dynamics software Fluent 17.2. The Euler-Lagrange approach was applied to model the droplet tracking and droplet-gas interaction in studied cases. The standard k-ε model was used to simulate the turbulent flow. A model with a modified drag coefficient was used to consider the effects of the bending of the liquid column and its penetration in the primary breakup region. The Kelvin-Helmholtz, Rayleigh-Taylor model was applied to consider the secondary breakup of the droplets.

The basic spatial distribution and spray structures of the droplets corresponding to the angled liquid jet (α = 60°) were similar to those reported in liquid jets injected transversely into a gaseous crossflow studies. The injection angle α did not considerably influence the averaged Sauter to mean diameter (SMD) of the cross-sections. However, the spray structures pertaining to α = 30°, α = 60° and α = 90° were considerably different. In the case of the atomizer with multiple injections, a “collision region” was observed at α = 60° and characterized by a higher ci and larger averaged SMD in the central parts of the cross-sections.

The injection angle α is a key design parameter for air-blast atomizers. The findings of this study can help enhance the understanding of the droplet-gas mixing process in air-blast atomizers. Engineers who design air-blast atomizers and face new challenges in the process can refer to the presented findings to obtain the desired atomization performance. The code has been validated and can be used in the engineering design process of the gas-liquid jet atomizer.

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

It is aiming at finding tribology performance laws and mechanism of sintering materials, including new materials, which are popular or potential materials of mechanical seals working under water condition with different working parameters, involving load and sliding speed.

Falex-1506 tribo-machine has been used. The upper sample is rotated against the stationary sample below. They are all rings. The samples are WNV2, sintered pressureless bonded; CHV1, graphite-added PLSiC; R, sintered reaction bonded; R2, graphite-added RBSiC, cemented carbide YN6 and graphite MSMG. Twenty kinds of hard/hard and soft/hard pairs were tested under water condition. Then, SEM was used to observe the sliding surface to explain their rubbing mechanism.

Friction coefficients decrease with the load increasing under water lubrication due to water holding by small holes on their surface. But the friction coefficients have no change with the varying of velocity. The hard alloy/sintered silicon carbon pairs may be better choice, where the lowest friction coefficient is only about 0.02, than soft/hard or silicon carbon/silicon carbon pairs under water lubrication, especially under heavy load.

The test was carried under load from 89 N (0.7 MPa) to 356 N (2.80 MPa) and sliding velocity from 0.746 to 5.074 m/s where the lubrication is in mixed.

The detailed values of frictional coefficients of popular and potential sintered material of mechanical seals working under water lubrication were given by the experimental research which may be helpful for the choice of mechanical seal materials.