Components Of Large Complexes Research Articles

Ultrasonic TFM imaging inspection of large complex rings using defect quantitative evaluation mappings

ABSTRACT Large complex rings are widely used in wind power energy, aerospace, large construction machinery. There are different scales of defects in the manufacturing process for large complex rings. Because of the complex cross-section and large thickness, it is difficult to quantitative evaluation of defects by conventional ultrasonic technology. Therefore, the ultrasonic total focusing method (TFM) defect quantitative inspection for large complex rings is proposed in this paper. First, the TFM inspection technology of large complex rings for simultaneous scanning of the end-face and side-face is designed. Then, the maximum amplitudes of defects are collected at each grid point of the imaging area by the TFM inspection of calibration specimens. The Φ1.5mm defect quantitative evaluation mappings are obtained by the interpolation fitting algorithm. Finally, the ultrasonic TFM and B-scan inspection experiments of the Φ3440mm large ring are carried out. The results show that the TFM quantitative evaluation mapping has higher accuracy compared to the conventional B-scan method. Especially for the Φ1.5mm defects, the average error of TFM quantitative evaluation is 2.92%. The proposed method can effectively identify defects of other sizes that exceed the calibration mapping. This work has industrial application value for developing ultrasonic TFM inspection of large complex components.

Planarian LDB and SSDP proteins scaffold transcriptional complexes for regeneration and patterning

Sequence-specific transcription factors often function as components of large regulatory complexes. LIM-domain binding protein (LDB) and single-stranded DNA-binding protein (SSDP) function as core scaffolds of transcriptional complexes in animals and plants. Little is known about potential partners and functions for LDB/SSDP complexes in the context of tissue regeneration. In this work, we find that planarian LDB1 and SSDP2 promote tissue regeneration, with a particular function in anterior regeneration and mediolateral polarity reestablishment. We find that LDB1 and SSDP2 interact with one another and with characterized planarian LIM-HD proteins Arrowhead, Islet1, and Lhx1/5–1. We also show that SSDP2 and LDB1 function with islet1 in polarity reestablishment and with lhx1/5–1 in serotonergic neuron maturation. Finally, we find new roles for LDB1 and SSDP2 in regulating gene expression in the planarian intestine and parenchyma; these functions are likely LIM-HD-independent. Together, our work provides insight into LDB/SSDP complexes in a highly regenerative organism. Further, our work provides a strong starting point for identifying and characterizing potential binding partners of LDB1 and SSDP2 and for exploring roles for these proteins in diverse aspects of planarian physiology.

A dual-robot cooperative arc welding path planning algorithm based on multi-objective cross-entropy optimization

In this paper a novel discrete multi-objective cross-entropy optimization (CrMOCEO) algorithm is proposed to solve the path planning problem of dual-robot cooperative arc welding. We strive to find a low-cost, fast and more efficient solution for robotic welding of large complex components. Firstly, an optimization model of dual-robot welding path planning is established by considering various variables and constraints in the actual welding process. Then, three strategies are introduced to improve the multi-objective cross-entropy optimization (MOCEO) algorithm to better solve the discrete path planning problem. Finally, in order to verify feasibility and effectiveness of the proposed algorithm, it is used to solve the 2-, 3-, 5- and 7-objective WFG2–9 problems and plan some typical welding seams of a large complex component, the MOCEO, NSGA-Ⅱ, MOPSO and MOGWO are used for comparison. The simulation demonstrates that the CrMOCEO can obtain better solutions for multiple objectives than the other four algorithms, and the path solved by the CrMOCEO is tested in the Gazebo physical model and workshop site, the results further verified the effectiveness of the CrMOCEO algorithm. Particularly, a series of experiments provide more solutions for actual production.

Clay Sculpture-Inspired 3D Printed Microcage Module Using Bioadhesion Assembly for Specific-Shaped Tissue Vascularization and Regeneration.

3D bioprinting techniques have enabled the fabrication of irregular large-sized tissue engineering scaffolds. However, complicated customized designs increase the medical burden. Meanwhile, the integrated printing process hinders the cellular uniform distribution and local angiogenesis. A novel approach is introduced to the construction of sizable tissue engineering grafts by employing hydrogel 3D printing for modular bioadhesion assembly, and a poly (ethylene glycol) diacrylate (PEGDA)-gelatin-dopamine (PGD) hydrogel, photosensitive and adhesive, enabling fine microcage module fabrication via DLP 3D printing is developed. The PGD hydrogel printed micocages are flexible, allowing various shapes and cell/tissue fillings for repairing diverse irregular tissue defects. In vivo experiments demonstrate robust vascularization and superior graft survival in nude mice. This assembly strategy based on scalable 3D printed hydrogel microcage module could simplify the construction of tissue with large volume and complex components, offering promise for diverse large tissue defect repairs.

A genetic algorithm with critical path-based variable neighborhood search for distributed assembly job shop scheduling problem

Production scheduling in distributed manufacturing systems has become an active research field, where large-sized complicated products, such as airplanes and ships, are taken as the primary focus. This paper investigates a distributed assembly job shop scheduling problem (DAJSP) which consists of two production phases. The first stage processes components in several job shops, and the second stage assembles the processed parts into final products. First, a mixed integer linear programming (MILP) model is established to describe the problem with minimizing maximum completion time and find optimal schedules for small-scale scenarios. Afterwards, a genetic algorithm with variable neighborhood search (GA-VNS) is proposed to address more complex instances, which adopts the genetic algorithm as the main framework and employs the variable neighborhood search for exploration. A problem-specific three-vector encoding scheme is designed to represent three decision-making processes of the DAJSP accordingly. To improve candidate solutions, a disjunctive graph model for DAJSP is formulated and three critical path-based neighborhood structures which directly perform on encoding vectors are designed. Numerical experiments are conducted on four groups of instances with different scales and the experimental results demonstrate the effectiveness of the proposed MILP model and GA-VNS. To sum up, the proposed GA-VNS shows the best performance on 30 instances out of 40 instances, while the superior stability has also been proved by statistical tests. In addition, two complicated DAJSP cases are abstracted from an enterprise for fabricating large complex components to further validate the GA-VNS.

Collaborative Effect of In-Plasma Catalysis with Sequential Na2SO3 Wet Scrubbing on Co-Elimination of NOx and VOCs from Simulated Sinter Flue Gas

Sinter flue gas produced by the iron-ore sinter process in steel plants is characterized by a large gas volume and complex components. Among the major air pollutants, preliminary emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx) exhibit an inevitable contribution to secondary aerosol and ozone formation. Herein, oxidation–absorption collaborative technology for in-plasma catalysis with sequential Na2SO3 wet scrubbing, aiming at co-elimination of NOx and VOCs from sinter flue gas, is proposed. Experimental parameters, including plasma discharge status, NO initial concentration, gas feed flux, Na2SO3 concentration, pH value, and absorption ions, were systematically investigated. The VOC and NOx removal performance of the integrated system was further investigated by taking simulated sinter flue gas as model pollutants. The results showed that the collaborative system has satisfactory performance for TVOC and NO removal rates for the effective oxidation of in-plasma catalysis and Na2SO3 absorption. The integration of plasma catalysis with Na2SO3 scrubbing could be an alternative technology for the co-elimination of sinter flue gas multi-compounds.

Local-to-global registration method of large complex components based on a de-pseudo-weighted variance minimization algorithm

Local-to-global registration method of large complex components based on a de-pseudo-weighted variance minimization algorithm

Spotlight on Plant Bromodomain Proteins.

Bromodomain-containing proteins (BRD-proteins) are the "readers" of histone lysine acetylation, translating chromatin state into gene expression. They act alone or as components of larger complexes and exhibit diverse functions to regulate gene expression; they participate in chromatin remodeling complexes, mediate histone modifications, serve as scaffolds to recruit transcriptional regulators or act themselves as transcriptional co-activators or repressors. Human BRD-proteins have been extensively studied and have gained interest as potential drug targets for various diseases, whereas in plants, this group of proteins is still not well investigated. In this review, we aimed to concentrate scientific knowledge on these chromatin "readers" with a focus on Arabidopsis. We organized plant BRD-proteins into groups based on their functions and domain architecture and summarized the published work regarding their interactions, activity and diverse functions. Overall, it seems that plant BRD-proteins are indispensable components and fine-tuners of the complex network plants have built to regulate development, flowering, hormone signaling and response to various biotic or abiotic stresses. This work will facilitate the understanding of their roles in plants and highlight BRD-proteins with yet undiscovered functions.

A Dual-Robot Cooperative Arc Welding Path Planning Algorithm based on Multi-Objective Optimization

In this paper a novel improved multi-objective genetic algorithm (R-NSGA-Ⅱ) is proposed to solve the problem of dual-robot arc welding path planning. We strive to find a low-cost, fast and more efficient solution for large complex components. Firstly, a multi-objective optimization model of path planning is established by considering various variables and constraints in the actual welding process. Then, the R-NSGA-Ⅱ introduces a recombination mechanism to replace the mutation operation of NSGA-Ⅱ; this can increase the diversity of individuals and populations, and find the global optimal solution with greater probability. Finally, in order to verify feasibility and effectiveness of the proposed algorithm, it is used to plan some typical welding seams of a large complex component, the NSGA-Ⅱ and OMOPSO are used for comparison. The simulation demonstrates that R-NSGA-Ⅱ can obtain better Pareto front than the other two algorithms. Particularly, the R-NSGA-Ⅱ reduces the waiting time by 42.39% and the no-load distance by 10.50% compared with NSGA-Ⅱ.

Fast Global Collision Detection Method Based on Feature-Point-Set for Robotic Machining of Large Complex Components

This paper presents a fast global collision detection method for robotic machining of large complex components, aiming to quickly determine whether there is a collision between the robot and the surrounding environment during the whole machining process. Geometric analysis shows that there are always some trajectory points on the motion path of the manipulator that are more likely to collide than the surrounding points during machining. These trajectory points with the highest collision probability within a certain range are defined as the feature points of global collision detection, and are used to replace all trajectory points to perform global collision detection, thus greatly improving the efficiency of related operations while ensuring accuracy. Compare to the traditional discrete collision detection method with computational complexity O( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{n}^{2}$ </tex-math></inline-formula> ), the computational complexity of the proposed method is only O(n). Numerical analysis and application experiments verify the effectiveness of the proposed method. Note to Practitioners—Motion planning in robotic machining of large complex components usually needs to perform a lot of global collision detection. Existing methods generally have the problems of large calculation and low efficiency, which seriously affects the efficiency of motion planning. This is mainly because a single global collision detection usually includes no less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> times of static collision detection, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> is the number of trajectory points. In order to solve this problem, we present a new global collision detection method based on feature-point-set. It does not need to traverse all trajectory points for static collision detection, but only needs to detect a few feature points, that is, the trajectory points most likely to collide within a certain range. On the premise of ensuring the collision detection accuracy, the proposed method greatly reduces the execution times of static collision detection, and significantly improves the computational efficiency of global collision detection. Numerical analysis and experiments show that this method effectively improves the efficiency of motion planning in robotic machining of large complex components.

Coordinated motion planning of the mobile redundant manipulator for processing large complex components

Coordinated motion planning of the mobile redundant manipulator for processing large complex components

Eco-friendly utilization of oilfield fracturing flow-back fluid and coal pitch for preparing slurry: Experiments and extended DLVO study

The fracturing flow-back fluid (FF), as the primary pollutant in oilfield exploitation, is challenging to handle because of the large output and complex components. In addition, large amounts of coal pitch (CP) are insufficiently utilized. In this study, based on the principle of clean production, three dispersants were employed to prepare CP-water slurry (CPWS) and CP-FF slurry (CPFS), which had the characteristics of high efficiency and low pollution. The feasibility of CPWS and CPFS and the influences of dispersants on their performance were systematically studied by measuring the viscosity, rheology and stability. Furthermore, the dispersion mechanisms of dispersants were investigated via adsorption, Zeta potential, and extended DLVO (EDLVO) theory. Results showed that replacing water with FF reduced the slurryability, while the stability was improved. The CPFS exhibited the shear-thinning characteristics, and the components in FF strengthened the pseudoplastic of slurry. Among the three dispersants, the adsorption capacity of AC-1215 was higher than that of PS and MF. And the inorganic salts in FF promoted the adsorption of dispersants. The calculation of interaction energies demonstrated that for CPFS without dispersant, the polar interaction energy played a dominant role, resulting in the aggregation of CP particles. The addition of AC-1215 maximized the total interaction energies (greater than zero) by introducing the steric hindrance energy, which was 1–4 orders of magnitude higher than other interaction energies.

A Dual-Robot Cooperative Welding Path Planning Algorithm Based on Improved Ant Colony Optimization

In this paper a novel path planning algorithm based on improved ant colony optimization is proposed for dual-robot cooperative welding. We seek to provide a low-cost, fast and effective solution for such problems. The optimization model of dual-robot collaborative welding is established based on actual welding process constraints and shortest welding path target. Then, a dynamic transfer strategy and information update strategy are proposed to improve the ant colony algorithm (ACO+) based on this model. Finally, the proposed ACO+ algorithm is implemented to solve the dual-robot path planning problem in the welding task of a large complex component. The simulation demonstrates that the proposed method has faster convergence rate and shorter welding path compared with the unmodified ant colony algorithm. Particularly, this algorithm is suitable for path planning of dual-robot cooperative welding for symmetrical complex component.

CAD-BASED PATH PLANNING FOR LINE LASER SCANNING OF CURVED SURFACE

On-machine measurement by a line laser scanner has a great potential in machining large complex components in aerospace and automation applications. This paper proposes a novel approach for path planning of measuring curved surfaces in a 5-axis machine tool, which takes scanning overlap, visual angle, and working distance into consideration. A conformal mapping algorithm is employed to transform a three-dimensional (3D) mesh surface to a 2D parametric plane. The shortest equidistant paths calculated in the 2D plane are transformed into smooth collision-free scanning paths in the 3D surface. The experiments verify that this method can improve the efficiency by 21.4% and the accuracy by 24.9%.

A Review on Additive Manufacturing of Titanium Alloys for Aerospace Applications: Directed Energy Deposition and Beyond Ti-6Al-4V

Titanium alloys are expensive and difficult to process into large complex components for aerospace applications. Directed energy deposition (DED), one of the additive manufacturing (AM) technologies, offers a high deposition rate, being suitable for fabricating large metallic components. So far, most review articles on the AM of titanium discuss the popular powder bed fusion method with the emphasis on the “workhorse” titanium alloy—Ti-6Al-4V. There have been few review articles on the DED process of a broad range of titanium alloys—near-α, β, and other α + β alloys beyond Ti-6Al-4V. This article focuses on the processing–microstructure–property relationships in the DED-processed titanium alloys (Ti-6Al-4V and beyond) with the following aspects: (1) microstructure evolution induced by solidification, thermal cycles, and post-processing heat treatment; (2) tensile properties of as-deposited and heat-treated titanium alloys; (3) defects, residual stresses, and fatigue properties; and (4) micro/nanomechanical properties. The article concludes with perspectives about future directions in this field.

Base position optimization of mobile manipulators for machining large complex components

• A BP optimization method for mobile manipulator considering both kinematics and stiffness performance is proposed. • A performance index MSPI is proposed to evaluate the robot's global stiffness performance. • A multi-constrained BP optimization model with maximum MSPI is established. • A sparse uniform grid decomposition + SQP solution method that can accurately obtain the optimal BP is designed. • Simulation and experiment verify the effectiveness of the BP optimization method. With good mobility and high flexibility, the mobile manipulator shows a broad application prospect in the machining of large complex components. In these applications, in order to fully utilize the capabilities of the robot, it is usually necessary to design a series of suitable working positions (i.e. robot's base position) for the mobile manipulator. However, the performance distribution of the robot in the task space is highly nonlinear, which makes it difficult to determine the optimal base positions. Therefore, this paper proposes a new base position optimization method, which can accurately find the optimal base position that takes into account both kinematics and stiffness performance. First, a task-oriented performance index MSPI (mean stiffness performance index) is proposed to evaluate the global stiffness performance of the robot. Based on MSPI, an optimization model considering multiple constraints such as joint range, joint speed, singular avoidance and collision avoidance is established. The optimization model is solved by sparse uniform grid decomposition and Sequential Quadratic Programming (SQP) method, the former is used to find a suitable initial value, the latter is used to determine the optimal base position. Finally, simulation analysis and experiments confirmed the effectiveness of the optimization method and the correctness of the performance index MSPI.

Off-line programming of robot on laser cleaning for large complex components

Laser cleaning path planning is great for significance to the cleaning effect of component surface. In view of the fact that the cleaning head must keep a fixed focal length with the workpiece surface and keep a vertical angle with the workpiece surface at all times in the laser cleaning process, this paper introduces the numerical model of large components into the general off-line programming software, and according to the relevant laser cleaning process and setting specific parameters in the software, obtains the automatically planned machine. The human trajectory program is introduced into the robot to realize the surface cleaning of large and complex components. Finally, according to the actual cleaning effect in the field, the laser focal length deviation is controlled within ± 2mm, and the application of off-line programming of industrial robots in complex surfaces is summarized and prospected.

Mechanical properties and microstructure of 316L stainless steel produced by hybrid manufacturing

Hybrid manufacturing is a combination of additive (deposition) and subtractive (machining) manufacturing in a single machine tool. Such a system can be used for near net shape manufacturing and component repair using either similar or dissimilar materials. Integrated into a single system, transition between additive and subtractive manufacturing can occur immediately and be leveraged to generate large components by alternating between the processes. This investigation shows how the interleaved capabilities can reduce overall cycle time by up to 68 %, improve average relative elongation to failure by 71 %, and reduce the average relative porosity fraction by 83 % when compared to traditional additive manufactured components. Results from this investigation builds the foundation needed for hybrid manufacturing to be applicable towards the manufacture of large complex components such as nosecones and marine propulsors.

An Alternative Casting Technique to Improve the Creep Resistance of Cast INCONEL Alloy 740H

The increasing performance requirements of power plant designs, such as advanced-ultra supercritical (A-USC), require the use of Ni-based superalloys to replace high-strength, ferritic-martensitic steels for components subjected to temperatures above 898 K (625 °C) and for austenitic stainless steels components at temperatures above 973 K (700 °C). To date, commercial Ni-based superalloy INCONEL 740H has been shown to be appropriate for use in A-USC power plants as boiler components in a wrought product. However, large complex components in boilers as well as other casings in the turbine and valve chest require castings of a thick-wall nature. Using the alloy in its cast form would be significantly valuable in terms of range of component size, geometry and complexity. Previous investigations revealed short creep lives from cast INCONEL alloy 740H. In this investigation, an alternative casting route that utilized a melt procedure resulting in a fine-grain casting, and in conjunction with a computationally optimized homogenization heat treatment, not only controlled the grain size and grain boundary structure but minimized chemistry variability and segregation. A primarily equiaxed and homogenous grain size distribution was obtained from this approach with better repartition of M23C6 carbides along the grain boundaries. Furthermore, better than 38 pct increase was obtained for this material in comparison to the creep life obtained from the best performing conventionally cast material. More importantly, the fine-grain homogenized (FGH) casting route resulted in the Larson–Miller plot for this material that coincided with that of wrought alloy 740. At low creep stresses (with a test still in progress), the FGH casting is resulting in higher values of the LMP than the wrought alloy.

Influence of Rare Earth Elements in Magnesium Alloy - A Mini Review

In recent days, the use of Magnesium and its alloys is preferred in defence, automotive and aerospace industries where large size and complex components are required in light weight. Besides, magnesium alloys are used in computers, electronic devices and biomedical applications. Alloying magnesium with rare earth elements (RE) is used to develop the light alloys for the stated applications at elevated temperature. Rare earth magnesium alloys are having unique properties over other metals, including a high specific strength, low thermal conductivity, good damping capacity and good castability. In this review article, the recent development of rare earth magnesium alloys will be reviewed from the view point of novel alloying designs. It has been revealed that in ternary alloy system Mg-ZN-RE alloy exhibited high strength and ductility. This leads the researchers to investigate Mg-ZN-RE alloy recently.