Adaptive Edge Attention for Graph Matching with Outliers

Graph matching aims at establishing correspondence between node sets of given graphs while keeping the consistency between their edge sets. However, outliers in practical scenarios and equivalent learning of edge representations in deep learning methods are still challenging. To address these issues, we present an Edge Attention-adaptive Graph Matching (EAGM) network and a novel description of edge features. EAGM transforms the matching relation between two graphs into a node and edge classification problem over their assignment graph. To explore the potential of edges, EAGM learns edge attention on the assignment graph to 1) reveal the impact of each edge on graph matching, as well as 2) adjust the learning of edge representations adaptively. To alleviate issues caused by the outliers, we describe an edge by aggregating the semantic information over the space spanned by the edge. Such rich information provides clear distinctions between different edges (e.g., inlier-inlier edges vs. inlier-outlier edges), which further distinguishes outliers in the view of their associated edges. Extensive experiments demonstrate that EAGM achieves promising matching quality compared with state-of-the-arts, on cases both with and without outliers. Our source code along with the experiments is available at https://github.com/bestwei/EAGM.

Investigation of the Matching Relation Between Impeller and Flow Channel of Regenerative Flow Pumps

As a specific radial flow pump, the regenerative flow pump (RFP) usually has a low efficiency. In this study, in order to explore the matching mechanism, three cases with various matching relations were investigated by the methods of theoretical calculation, computational fluids dynamics (CFD) simulation, and experiment test. The results illustrate that the theoretical prediction, numerical simulation and experimental data are in good agreement. Furthermore, when the matching relation expressed by a ratio of the channel's and blade's radial length is equal to 1, the geometrical profiles of RFP can well guide the circulation flow into the channel at large radii and into the impeller at small radii, forming intense longitudinal vortex. The steady, strong exchange flow is characterized by the inflow and outflow regions approximately half of the iso-surface. The axial vortex motion without apparent flow separation and irregular flow is observed in the impeller, a low velocity annulus exists in the medium radii of the impeller without other distinct velocity clouds, and a low velocity strip and a high velocity annulus in the channel are respectively performed along the blade's pressure surface and the channel's outer radii. All of this corresponds to the best pump's performance and the largest efficiency of the impeller and channel. This work promotes a systematical understanding of the matching mechanism between impeller and flow channel in the RFP and could provide some reference for the design and performance optimization for RFP.

Deformable Microgel for Enhanced Oil Recovery in High-Temperature and Ultrahigh-Salinity Reservoirs: How to Design the Particle Size of Microgel to Achieve Its Optimal Match with Pore Throat of Porous Media

Summary Conformance control treatment in high-temperature and ultrahigh-salinity reservoirs for easing water/gas channeling through high-permeability zones has been a great challenge. In this work, we propose a deformable microgel that can be used at more than 373.15 K and ultrahigh-salinity conditions (total dissolved solids > 200 kg/m3, Ca2+ + Mg2+ > 10 kg/m3) and present a method for choosing the suitable particle size of the microgel to achieve an optimal match with the pore throat of the core. First, the particle size distribution of the microgel was analyzed to decide d50, d10, and d90 (diameter when cumulative frequency is 50, 10, and 90%, respectively). Coreflooding experiments were conducted under different permeability conditions from 20 to 900 md to investigate the migration and plugging patterns of the microgel by analyzing and fitting injection pressure curves together with the change in the morphology of the produced microgel analyzed by a microscope. The migration and plugging patterns were divided into three patterns: complete plugging; plugging—passing through in a deformation or broken state—deep migration; and inefficient plugging—smoothly passing through—stable flow. The second pattern can be further divided into three subpatterns as strong plugging, general plugging, and weak plugging. Finally, on the basis of five patterns, we build a quantitative matching relation between the particle size distribution of microgel and the pore-throat size of cores by defining three matching coefficients a = d10/d, ß = d50/d, γ = d90/d (d is the average pore-throat diameter). The effectiveness of this quantitative matching relation was verified by evaluating the plugging ability (residual resistance factor) in a post-waterflooding process after the injection of 1.5 pore volume (PV) of microgel. For a strong permeability heterogeneity, the strong plugging is believed to be the expected pattern. The particles size and the pore-throat size should meet the following relationship: 1 < a < 2, 2 < ß < 4, 4 < γ < 6. In this scenario, the deformable microgel particles could achieve both an effective plugging and a deep migration. The quantitative matching relation with multiple matching coefficients determined based on the particle size distribution might help to choose suitable particles more precisely in comparison to the method based on one matching coefficient (mostly, the ratio of the average diameter of particles to the average pore-throat diameter). In addition, the method itself to build a quantitative matching relation according to particle size distribution can be used for designing different particle-type conformance control agents for profile control and water shutoff treatment in field applications.

Matching Design of Active Magnetic Bearing and Elastic Support Vibration Isolator

In modern industries, high-speed machinery occupies a fundamental place. However, rotating machinery will inevitably produce a variety of structural noise and vibration. Generally, vibration isolation means can be divided into active vibration isolation and passive vibration isolation, among which the most representative are active magnetic bearings (AMBs) and vibration isolators, respectively. The combination of active magnetic bearings and vibration isolators is widely used in rotating machinery because of its excellent effect in vibration and noise reduction. This paper concentrates on the analysis of the vibration transmission mechanism of the active magnetic bearings coupled with the vibration isolators. A 30 kW prototype pump is taken as an example to help describe the research method. The model of the pump is first established. The stationary pump components and the rotor are respectively modeled through the finite element method and converted to substructure modal expression after low-order modal extraction. The bearing force is simplified to spring-dampers with equivalent stiffness and equivalent damping relating to the exciting frequency. The vibration isolators are simplified as three-dimensional spring-dampers. Based on the model, this paper then investigates the matching relation of the AMBs and the vibration isolators and proposes a dynamic vibration isolation design method for the rotor-AMBs-flexible support system. On the basis of the frequency-domain response of the original design, this design method gives the frequency-domain curves of the desired stiffness and damping of the suitable active vibration isolation, which can be used to guide the controller design of the AMBs and isolators selection. According to the design, we have done laboratory experiments on the prototype pump. The results show that the design method based on matching relation has good performance in vibration isolation.

Equivalence principle for antiparticles and its limitations

We investigate the particle–antiparticle symmetry of the gravitationally coupled Dirac equation, both on the basis of the gravitational central-field problem and in general curved space–time backgrounds. First, we investigate the central-field problem with the help of a Foldy–Wouthuysen transformation. This disentangles the particle from the antiparticle solutions, and leads to a “matching relation” of the inertial and the gravitational mass, which is valid for both particles as well as antiparticles. Second, we supplement this derivation by a general investigation of the behavior of the gravitationally coupled Dirac equation under the discrete symmetry of charge conjugation, which is tantamount to a particle[Formula: see text]antiparticle transformation. Limitations of the Einstein equivalence principle due to quantum fluctuations are discussed. In quantum mechanics, the question of where and when in the Universe an experiment is being performed can only be answered up to the limitations implied by Heisenberg’s Uncertainty Principle, questioning an assumption made in the original formulation of the Einstein equivalence principle. Furthermore, at some level of accuracy, it becomes impossible to separate nongravitational from gravitational experiments, leading to further limitations.

A Multi-Objective and Multi-Dimensional Optimization Scheduling Method Using a Hybrid Evolutionary Algorithms with a Sectional Encoding Mode

Aimed at the problem of the green scheduling problem with automated guided vehicles (AGVs) in flexible manufacturing systems (FMS), the multi-objective and multi-dimensional optimal scheduling process is defined while considering energy consumption and multi-function of machines. The process is a complex and combinational process, considering this characteristic, a mathematical model was developed and integrated with evolutionary algorithms (EAs), which includes a sectional encoding genetic algorithm (SE-GA), sectional encoding discrete particle swarm optimization (SE-DPSO) and hybrid sectional encoding genetic algorithm and discrete particle swarm optimization (H-SE-GA-DPSO). In the model, the encoding of the algorithms was divided into three segments for different optimization dimensions with the objective of minimizing the makespan and energy consumption of machines and the number of AGVs. The sectional encoding described the sequence of operations of related jobs, the matching relation between transfer tasks and AGVs (AGV-task), and the matching relation between operations and machines (operation-machine) respectively for multi-dimensional optimization scheduling. The effectiveness of the proposed three EAs was verified by a typical experiment. Besides, in the experiment, a comparison among SE-GA, SE-DPSO, H-SE-GA-DPSO, hybrid genetic algorithm and particle swarm optimization (H-GA-PSO) and a tabu search algorithm (TSA) was performed. In H-GA-PSO and TSA, the former just takes the sequence of operations into account, and the latter takes both the sequence of operations and the AGV-task into account. According to the result of the comparison, the superiority of H-SE-GA-DPSO over the other algorithms was proved.

Formation and improvement of surface waviness for additive manufacturing 5A06 aluminium alloy component with GTAW system

Purpose As known, the wire and arc additive manufacture technique can achieve stable process control, which is represented with periodic surface waviness, when using empirical methods or feedback control system. But it is usually a tedious work to further reduce it using trial and error method. The purpose of this paper is to unveil the formation mechanism of surface waviness and develop a method to diminish it. Design/methodology/approach Two forming mechanisms, wetting and spreading and remelting, are unveiled by cross-section observation. A discriminant is established to differentiate which mechanism is valid to dominate the forming process under the given process parameters. Findings Finally, a theoretical method is developed to optimize surface waviness, even forming a smooth surface by establishing a matching relation between heat input (line energy) and materials input (the ratio of wire feed speed to travel speed). Originality/value Formation mechanisms are revealed by observing cross-section morphology. A discriminant is established to differentiate which mechanism is valid to dominate the forming process under the given process parameters. A mathematical model is developed to optimize surface waviness, even forming a smooth surface through establishing a matching relation between heat input (line energy) and materials input (the ratio of wire feed speed to travel speed).

Diagnosis of supervision patterns on bounded labeled Petri nets by Model Checking

This paper investigates the problem of pattern diagnosis of systems modeled as bounded labeled Petri nets that extends the diagnosis problem on single fault events to more complex behaviors. An effective method to solve the diagnosis problem is proposed. Itrelies on a matching relation between the system and the pattern that turns the pattern diagnosis problem into a model-checking problem.